Cancer Systems Biology Consortium

Arizona Cancer and Evolution Center


Center Title

Arizona Cancer and Evolution Center

Center Website

Center Summary

Cancer is an evolutionary and ecological phenomenon driven by the fundamental forces of evolution: mutations, natural selection and genetic drift. It provides a classic example of multi-level selection. At the level of individual cancer cells, selection favors neoplastic proliferation; at the level of the host organism, selection favors cancer suppression. A full understanding of cancer hinges on an appreciation of this fundamental tension. Regulatory mechanisms at the organismal level determine evolutionary parameters at the cell level such as the somatic mutation rate and response to DNA damage. Cancer circumvents those constraints and changes the parameters of cell-level evolution, leading to malignancy and eventual host death. Thus, organismal and cell-level evolution feed back upon each other. To paraphrase Dobzhansky, nothing in cancer biology makes sense except in the light of evolution. This opens an opportunity. We may apply evolutionary and ecological theory to neoplastic progression and response to therapy.

The mission of the Arizona Cancer and Evolution Center (ACE) is to advance our fundamental understanding of cancer and its clinical management through the development and application of evolutionary and ecological models to cancer biology. This mission spans scales from the evolution of cancer suppression mechanisms and cancer susceptibility across species (Project 1) down to the evolution of normal somatic cells (Project 2) and populations of cancer cells (Project 3).

Project 1 will develop models of organismal evolution to predict cancer rates and cancer defenses across species. We will test those predictions using veterinary databases of cancer incidence in over 1,900 animal species, and examine the genomes of 57 mammalian species for evidence of adaptations to the selective pressure of cancer. In addition, Project 2 will test Project 1’s model predictions of cancer defenses in primary cells from those same 57 mammalian species.

Project 2 will also measure the fundamental forces of evolution in normal colonic and small intestine tissue from humans, mice and elephants to address a basic but poorly understood property of cancer: tissue-level differences in cancer susceptibility. Project 3 will develop novel evolutionary and ecological indices, based on models of cell-level evolution in neoplasms from Project 1, to predict long term therapeutic response and patient survival in stage 2&3, chemo-naïve colorectal cancers. These indices will provide, for the first time, a classification system that the community can use to draw distinctions between tumors with different evolutionary dynamics, and thereby provide a foundation for the clinical management of this evolving disease. ACE will support the Cancer Systems Biology Consortium and the growing field of evolution and cancer by providing data, analytical tools, models, workshops, and tutorials to facilitate the use of those resources.


Principal Investigators

Carlo Maley

Associate Professor, Arizona State University

Prof. Maley is a cancer biologist, evolutionary biologist and computational biologist, working at the intersection of those fields. His team applies evolutionary and ecological theory to three problems in cancer: (1) Neoplastic progression: The evolutionary dynamics among cells of a tumor that drive progression from normal tissue to malignant cancers, (2) Acquired therapeutic resistance: the evolutionary dynamics by which our therapies select for resistance and how we may be able to prevent or control resistant cancer cells, and (3) the evolution of cancer suppression mechanisms in large, long-lived animals like elephants and whales (a problem called Peto’s Paradox). They use genomic data mining, phylogenetics, computational modeling, as well as wet lab techniques to solve these problems. In all of this work, their goals are to develop better methods to prevent cancer and improve cancer management.

Darryl Shibata

Professor, University of Southern California

After attending UCLA for his undergraduate degree, Dr. Shibata obtained his medical degree from the Keck School of Medicine of USC. After completing his internship training in pediatrics from UC San Diego, Dr. Shibata returned to USC for his residency and fellowship at LAC+USC Medical Center. Currently, Dr. Shibata has clinical appointments at both LAC+USC Medical Center and USC/Norris Comprehensive Cancer Center. In addition to his wide array of responsibilities in the research, education and practitioner capacities, Dr. Shibata sits on the editorial board of the BMC Cancer Journal and the American Journal of Pathology.

Participating Investigators

Athena Aktipis

Assistant Professor, Arizona State University

Athena Aktipis is an Assistant Professor in the Psychology Department at Arizona State University, co-Director of the Human Generosity Project and Director of Human and Social Evolution and co-founder of the Center for Evolution and Cancer at the University of California, San Francisco.  Dr. Aktipis completed her BA at Reed College (Psychology), her PhD at University of Pennsylvania (Psychology) and post-doctoral work at University of Arizona (Ecology and Evolutionary Biology). She is a cooperation theorist, theoretical evolutionary biologist, and cancer biologist who now works at the intersection of these fields.  Dr. Aktipis is the author of the forthcoming book from Princeton University Press “Evolution in the flesh: Cancer and the transformation of life.”

Amy Boddy

Assistant Professor, University of California, Santa Barbara

Amy Boddy is an Assistant Professor in the Integrative Anthropological Sciences Unit at the University of California, Santa Barbara (UCSB) and a Research Associate in the Broom Center for Demography at the University of California, Santa Barbara. Dr. Boddy is a human biologist and evolutionary theorist. Her work uses applications from evolution and ecology to understand human health and disease. She uses a combination of genomics, computational biology and evolutionary theory to understand life history trade-offs between survival and reproduction across different levels of biological organization. One component of her research program examines how environmental cues, such as high extrinsic mortality, may guide resource allocations to cancer defenses and reproduction. Current cancer research topics include comparative oncology, intragenomic conflict, cellular life history trade-offs, and early life adversity and cancer outcomes later in life. In addition to her cancer research, she studies maternal/fetal conflict theory and the consequences of fetal microchimeric cells in maternal health and disease.

Christina Curtis

Assistant Professor, Stanford University

Christina Curtis, PhD, MSc is an Assistant Professor in the Departments of Medicine (Oncology) and Genetics in the School of Medicine at Stanford University where she leads the Cancer Systems Biology Group and serves as Co-Director of the Molecular Tumor Board at the Stanford Cancer Institute. Trained in molecular and computational biology, she received her doctorate from the University of Southern California in 2007 advised by Simon Tavaré, and holds Masters degrees in Bioinformatics and Computational Biology from the University of Southern California and in Molecular and Cellular Biology from the University of Heidelberg, Germany. She has been the recipient of several young investigator awards, including the 2012 V Foundation for Cancer V Scholar Award, the 2012 STOP Cancer Research Career Development Award, a 2016 AACR Career Development Award and was named a Kavli Fellow of the National Academy of Sciences in 2016. Dr. Curtis is the principal investigator on grants from the NIH/NCI, Department of Defense, American Association for Cancer Research, Breast Cancer Research Foundation, Susan G. Komen Foundation, V Foundation for Cancer Research and Emerson Collective. She also serves on the Editorial Boards of Breast Cancer Research, Carcinogenesis: Integrative Biology, the Journal of Computational Biology and JCO Precision Oncology.

Paul Davies

Regents Professor, Arizona State University

Paul Davies is a theoretical physicist, cosmologist, astrobiologist and best-selling science author. He has published about 30 books and hundreds of research papers and review articles across a range of scientific fields. He is also well-known as a media personality and science popularizer in several countries. His research interests have focused mainly on quantum gravity, early universe cosmology, the theory of quantum black holes and the nature of time. He has also made important contributions to the field of astrobiology, and was an early advocate of the theory that life on Earth may have originated on Mars. For several years he has also been running a major cancer research project, and developed a new theory of cancer based on tracing its deep evolutionary origins. Among his many awards are the 1995 Templeton Prize, the Faraday Prize from The Royal Society, the Kelvin Medal and Prize from the Institute of Physics, the Robinson Cosmology Prize and the Bicentenary Medal of Chile. He was made a member of the Order of Australia in the 2007 Queen’s birthday honours list and the asteroid 6870 Pauldavies is named after him. His more recent books include About Time, The Origin of Life, The Goldilocks Enigma: Why Is the Universe Just Right for Life?, How to Build a Time Machine and The Eerie Silence: Are We Alone in the Universe?

Pauline Davies

Professor of Practice, Arizona State University

Pauline Davies is an award winning radio science and health broadcaster with an extensive international career.  She spent many years with the BBC’s World Service where her programs reached audiences of tens of millions worldwide.  Her topics ranged from fundamental physics to human origins and she has reported from conflict zones on maternal health and combatant injuries. She continues to make documentaries from across the sciences for public broadcasters worldwide.  Now she collaborates with the Mayo Clinic on a project to help prevent physician burnout, but her main specialization is the dissemination of cancer research. She led the outreach and education component of an NCI Physical Sciences and Oncology Center for 5 years and is excited to work with her talented ACE colleagues in finding new ways to bring fundamental research findings to the science community and the public.

Trevor Graham

Professor, Barts Cancer Institute, QMUL

Professor Trevor Graham leads the Evolution and Cancer laboratory at the Barts Cancer Institute, QMUL in London, UK.  The lab focuses on measuring the dynamics and drivers of somatic evolution in human tissues, particular in the gastrointestinal tract, and tries to use these measures to better predict cancer development risk in premalignant disease, and determine prognosis and optimise treatment regimes in established cancers. His multidisciplinary lab combines expertise in both theory (maths, physics, computer science, evolutionary biology) together with empirical measurement (molecular genetics, histopathology, bioinformatics).

Tara Harrison

Assistant Professor, North Carolina State University

Dr. Tara Harrison is a veterinarian who specializes in zoo animal medicine and the epidemiology of cancer across zoo animal species. She became interested in cancer in zoo animals after diagnosing a lion with T-cell lymphoma and not being able to find information on how to treat it, or what the survival would be for him after treatment. She has since worked on treating numerous zoo and exotic animal species diagnosed with cancer. She, along with Dr. Zehnder, have created to better discover what types of cancers, their risk factors, and treatments exist in zoo and exotic animals. She has joined up with the ACE colleagues as we are all interested in the prevalence of cancer across zoo and exotic animal species.

Hanna Kokko

Professor, University of Zurich

Hanna Kokko is an evolutionary ecologist and mathematical modeller. Her stay at the Wissenschaftskolleg zu Berlin in 2014 sparked her interest in cancer as a life history problem. She currently runs a research group that focuses on life history questions – such as scheduling of reproduction, reproductive modes (e.g. sex or asex? with or without a male-female dimorphism?), ageing, and dispersal – with the aim of theory building being informed by all life, rather than constrained by the necessarily narrow view offered by a few model species.

Li Liu

Assistant Professor, Arizona State University

Dr. Liu is an assistant professor of Biomedical Informatics and the director of the Bioinformatics Core Facility at Arizona State University. She holds an M.D. degree in Medicine and an M.S. degree in Information System. As a trained clinician and a bioinformatics researcher, she fully appreciates the critical roles genomic medicine and bioinformatics play in advancing precision medicine. By integrating genomic, phylogenetic, population genetic, statistical and machine-learning techniques, Dr. Liu and her research team investigate clinical and molecular signatures of human diseases, and develop novel computational methods to discover biomarkers for early diagnosis and accurate prediction of therapeutic responses for individual patients. Before joining ASU, Dr. Liu helped build and directed the bioinformatics core facility at University of Florida.

Joshua Schiffman

Professor, University of Utah

Dr. Schiffman is a pediatric hematologist-oncologist at Primary Children’s Hospital (PCH) and Huntsman Cancer Institute (HCI) at the University of Utah.  He serves as the Medical Director for the Family Cancer Assessment Clinic, where he cares for children and families with inherited risk for cancer. Dr. Schiffman’s research focuses on the development of pediatric cancer and he runs a translational genomics laboratory to identify which children are at risk for cancer and why.  Dr. Schiffman works closely with epidemiologists, population scientists, and molecular biologists to try to answer this question. Most recently, Dr. Schiffman recognized the power of comparative oncology to advance the field of cancer research. Teaming up with collaborators from across the country, the Schiffman Lab is now actively involved in comparing the genomics and functional biology of different species across the animal kingdom and using this information to generate hypotheses to guide experimental design in cancer research.  Dr. Schiffman holds the inaugural Edward B. Clark, MD Endowed Chair in Pediatric Research.

Andrea Sottoriva

Team Leader, The Institute of Cancer Research, London

Dr Andrea Sottoriva obtained his BSc in computer science from the University of Bologna in 2006 and his MSc in computational modelling from the University of Amsterdam in 2008. While attending his BSc and master’s he worked in neutrino physics at the Department of Physics of the University of Bologna and at the Institute for Nuclear and High Energy Physics (NIKHEF) in the Netherlands as a research assistant. During his master’s he specialised in computational biology and bioinformatics and became interested in mathematical modelling of cancer. This emerging field employs rigorous mechanistic modelling and simulations to understand complex biological systems such as cancer.

In 2012 he completed his PhD in cancer genomics and modelling at the University of Cambridge within the CRUK Cambridge Research Institute, focusing on the integration of computational models with cancer genomic data. After his PhD he conducted postdoctoral research at the University of Southern California within the Norris Comprehensive Cancer Centre, investigating the use of multiple sampling genomic data from human malignancies to understand tumour evolution.

Dr Sottoriva joined the Centre for Evolution and Cancer at The Institute of Cancer Research, London, in 2013, where his research focuses on using multi-disciplinary approaches based on high-throughput genomics and mathematical modelling to understand cancer as a complex system driven by evolutionary principles. The goal of his group is to identify those patient-specific rules that regulate the development and progression of the disease, to inform prognosis and novel therapeutic options that are tailored to the need of the individual cancer patient. He is currently the Chris Rokos Fellow in Evolution and Cancer at the ICR.

Yinyin Yuan

Team Leader, The Institute of Cancer Research, London

Yinyin Yuan is the leader of the Computational Pathology and Integrative Genomics team at the ICR. Her team develops computational approaches to study tumours as evolving ecosystems by fusing digital pathology, bioinformatics and ecological statistics. The research focuses on the emerging concept that tumours are complex, evolving ecosystems with dynamic crosstalk among cancer, immune and normal cells. Studying the complex relationships between cancer cells and their natural habitats allows for development of new and effective therapeutic interventions, analogous to draining the swamps to help eradicate malaria. By combining large-scale digital pathology, machine learning and spatial statistics, her team studies how genetically different cancers grow and spread under selective pressures from the tumour microenvironment.

Ashley Zehnder

Research Scientist/Postdoctoral Fellow, Stanford University

Ashley Zehnder graduated from the University of Florida College of Veterinary Medicine in 2005, completed a small animal medicine and surgery internship at the Animal Medical Center in New York City in 2006 and a 3-year residency in Companion Avian and Pet Exotic Medicine at the University of California-Davis, becoming boarded in Avian Medicine in 2009.  She completed her Cancer Biology PhD in the Khavari Lab at Stanford in 2016, working on novel therapeutic strategies to target altered signaling pathways in epithelial cancers. Since beginning her research training at Stanford, she has pursued interests in cancer biology as well as comparative medicine by maintaining active research interests in both fields.  She spearheaded the Zoobiquity Research Symposium held at Stanford in April 2014 and Stanford One Health symposium in 2016, which brought together veterinarians and human medical researchers to discuss research efforts in infectious diseases, cancer as well as novel animal models of disease. She is also on the Board of Advisors for Stanford One Health. More recently, she has founded a research alliance to bring together medical professionals to pursue research interests relating to cancer in non-domestic species, shedding light on the biology of tumors in these potentially valuable animal models (  Her current research focuses on building resources and methods to improve sharing of veterinary clinical data across the US as well as developing a tumor database focused on non-domestic species, thereby helping to identify potential novel models of cancer for human and animal research.


Project 1: Organismal Evolution and Cancer Defenses

PIs: Maley, Kokko, Boddy; Co-Is: Aktipis, Harrison, Zehnder

Cancer has been an important selective pressure for organisms and a great deal of variation in cancer rates exist across species. Why do species vary in their susceptibility to cancer and what mechanisms are responsible for this variation? Life history theory (LHT) may provide an explanation for these differences. LHT is an evolutionary and ecological approach that focuses on organism-level tradeoffs between growth, maintenance and reproduction. Organisms can either live fast and die young, or live slowly and die old, or anywhere in between. Cancer suppression is an important component of building a robust body that can live into old age. Our previous models show that lower levels of cancer defense can be favored by natural selection when there are tradeoffs with traits such as reproductive competitiveness, body size, and longevity. Here we use real life history parameters to predict cancer rates across animals and test the predictions with a highly curated comparative oncology dataset, including animals from major orders of reptiles, birds, fish, amphibians and mammals. Additionally, we will analyze the genomes of mammalian species to identify patterns of selection and mutation in tumor suppressor genes. Our approach combines mathematical modeling, comparative techniques, evolutionary theory, genomic sequencing, molecular evolution, and phylogenetics to study cancer suppression. We are particularly interested in identifying cancer resistant species, discovering how they prevent cancer, and translating that into better cancer prevention for humans.

Life history strategies fall on a continuum from fast to slow, and organisms with a fast life history strategy allocate less energy to somatic maintenance (i.e. cancer defense), while slow life history organism have higher investment in cancer defenses, such as DNA damage sensitivity

Impact: More cancers could be prevented if we better understand the evolution of cancer defense mechanisms and other biological parameters that make humans more susceptible to cancer than other species. We can leverage these findings to develop novel tools for prevention and clinical management of human cancers. Comparative oncology offers a unique opportunity to see how evolution has, over millions of years, led to both cancer defense mechanisms and why certain forms of susceptibility remain.

Project 2: Somatic Cell Evolution in Small Human Replicative Units

PI: Shibata; Co-Is: Graham, Schiffman

This Project will study somatic cell evolution in distinct, small human replicative units (intestinal crypts and tumor glands). The compartmentalization of cells into small replicative units can modify evolution because selection and drift (random cell turnover) is limited to immediately adjacent cells. The advantages of analyzing small replicative units are that experimentally they large enough to measure with conventional methods yet small enough to simulate in detail. Characterizing somatic cell evolution in replicative units can lead to better understanding of tumor evolution because selection or drift first occurs at the cell-cell level.

We will sample multiple colon crypts from different aged individuals and multiple tumor glands from opposite sides of 20 colorectal tumors (adenomas and CRCs). Crypts from different species will also be compared with the human data. For each crypt or gland we will document genetic alterations (whole genome sequencing), epigenetic alterations (ATAC-seq), and expression. Combining epigenetic and genetic evolution is important because phenotypic plasticity can mimic clonal evolution when epigenetic modulation allows a single genome to express multiple phenotypes. This data will be modeled through simulations to better understand somatic cell proliferation (division and death) within small replicative units, specifically to determine whether selection or neutral drift are more common during normal human aging and tumor progression.

This Project will also compare the evolutionary biology of fibroblasts. We will test the predictions of Project 1 for the mutation rates, proliferation rates, apoptosis rates, DNA damage response, and stress responses of early passage, primary fibroblasts from species with a wide variety of life history traits. We will also test for functional differences in cancer associated pathways that have evidence of selection in specific species identified by Project 1.

Project 3: Neoplastic Cell Evolution

PIs: Graham, Yuan; Co-Is: Sottoriva, Liu, Curtis

Cancer is an evolutionary process where a single cell grows into a visible tumor after it has acquired multiple driver alterations. In this Project, we will develop predictive biomarkers for colorectal cancer (CRC) outcomes. The innovation is that the biomarkers will be direct measures of evolution. Such evolution-based biomarkers also provide mechanistic understanding for what aspects of evolution most impact survival. To fully characterize tumor evolution, it is necessary to measure both how tumor cells evolve and the host ecology.

In Aim 1, mutations detected by whole exome sequencing of CRC cohorts with long-term follow-up will be classified as public (clonal) and private (subclonal). CRCs will then be subclassified with a newly developed algorithm that can infer selection (positive, neutral, negative) based on private mutation frequencies, where selection preferentially increases (positive) or decreases (negative) subclone subsets. In Aim 2, we will scan microscope sections from the above tumors, using a unique automated platform that can identify cells and quantify tumor microenvironments with respect to lymphocytes and stromal cells. To determine if host ecological heterogeneity reflects responses to specific tumor subclones, we will overlay private mutation distributions on the same microscope slides.
We will combine tumor evolution and the host reaction into a single evolution-ecology (Evo-Eco) index that summarizes the underlying evolutionary struggle. For example, patients with aggressive tumors (positive selection) and supportive environments are likely to have poorer outcomes relative to patients with tumors under negative selection and repressive environments. We will validate our Evo-Eco index on another cohort of CRCs. If successful, these studies will yield improved CRC predictive biomarkers.


PI: Pauline Davies; Co-Is: Aktipis, Paul Davies

The Outreach Unit of the Arizona Cancer and Evolution (ACE) Center will bring together students, researchers, and the general public to consider the evolutionary pathways and ecology of cancer. We have three aims within our Outreach Unit: (1) to integrate and synergize our interdisciplinary team to produce real innovation and ultimately impact the field of cancer research; (2) to connect the Center with the wider Cancer Systems Biology Consortium, other scientists and the public to promote collaboration; (3) to educate the next generation of scientists and communicators in cancer research methods and encourage them to work in integrative teams in order to stimulate new ideas.  We will achieve these aims through a comprehensive program that includes educational courses, online tutorial videos with accompanying monitored discussion boards, seminars, internships and public lectures and also an innovative creative activity – a unique, immersive new media exhibit, based on the work of ACE Center researchers, that visualizes the fundamental forces of evolution: mutation, selection and drift in relation to the ecology of cancer cells. This project will explore the intersection of science, art and technology to promote new ways of imagining scientific concepts. It will be displayed in major public galleries and conferences.

IMPACT: We will stimulate public interest in cancer theory research and educate students, scientists and the public about ACE advances and our drive to understand the nature of cancer and its evolutionary origins.  We will foster research and academic excellence and advance the goals of the National Cancer Institute.


Measuring, Modeling and Controlling Heterogeneity (M2CH)


Center Title

M2CH Center for Cancer Systems Biology (M2CH-CCSB)

Overall Project Title

Measuring, Modeling and Controlling Heterogeneity (M2CH)

Participating Sites

Oregon Health & Science University
University of California, Berkeley

Center Website

Center Summary

The overall goal of our M2CH Center for Cancer Systems Biology (M2CH-CCSB) is to improve management of triple negative breast cancer (TNBC) by developing systems level strategies to prevent the emergence of cancer subpopulations that are resistant to treatment. We postulate that heterogeneity arising from epigenomic instability intrinsic to cancer cells and diverse signals from extrinsic microenvironments in which cancer cells reside are root causes of resistance.

We learn how intrinsic and extrinsic factors influence differentiation state, proliferation and therapeutic response in TNBC through experimental manipulation and computational modeling of cancer cell lines, 3D engineered multicellular systems, xenografts and clinical specimens. We deploy single cell ‘omic and imaging technologies that allow quantitative assessment of molecular, cellular, and structural heterogeneity. We interpret these data using computational models that define control networks and structures in heterogeneous systems as well as transitions between states of therapeutic resistance and sensitivity.

This is accomplished in three related Projects and three Cores. Project 1 focuses on measuring and managing resistance-associated heterogeneity intrinsic to cancer cells. Project 2 focuses on identifying resistance-associated signals from the microenvironment and on mitigating effects from these signals on therapeutic response. Project 3 applies spatial systems biology approaches to TNBC specimens and multicell type models thereof to discover molecular control networks that influence how cell intrinsic plasticity and microenvironment signaling alter therapeutic responses in complex tissues. All Projects analyze core cell lines, patient derived cultures, and FDA approved, pathway-targeted drugs (afatinib, ruxolotinib, trametinib, BYL719, cabozantinib, and everolimus).

An Imaging Management and Analysis Core provides infrastructure and image analytics that enables efficient image data management, quantitative analysis of image features, and visualization of images and metadata generated using multiscale light and electron microscopy. An Outreach Core makes available educational materials, experimental and computational tools and data to the scientific community.


Principal Investigators

Joe W. Gray, Ph.D.

Joe W. Gray, Ph.D., a physicist and an engineer by training, is the Gordon Moore Endowed Chair in the Department of Biomedical Engineering and serves as Director for the Center for Spatial Systems Biomedicine and Associate Director for Biophysical Oncology at the Knight Cancer Institute at Oregon Health & Science University. He also serves as co-PI of an NIH LINCS project on effects of the microenvironment on cell phenotypes and a clinical trial aimed at understanding cancer evolution under treatment through Serial Measurements of Molecular and Architectural Responses to Therapy with which the M2CH-CCSB interacts. Dr. Gray’s research program applies experimental and mathematical tools to elucidate mechanisms by which genomic, transcriptional and proteomic abnormalities occur in selected cancers including how these abnormalities alter the multiscale architecture of cancers and their microenvironments cancer pathophysiology and how these changes contribute to cancer progression and response to therapy. He brings substantial experience in development and application of advanced measurement technologies. He has contributed to development of cytometric techniques for cell and genome analysis including high speed chromosome sorting, BrdUrd/DNA analysis of cell proliferation, Fluorescence In Situ Hybridization, Comparative Genomic Hybridization and End Sequence Profiling. More recently, Dr. Gray has elucidated mechanisms of cancer progression and developed systems biology approaches for identification of molecular markers that predict and determine response to therapeutic treatment. Currently, he is applying multiscale image analysis approaches to identify multiscale (Ängstroms to millimeters) structures that lead to therapeutic resistance.

Rosalie Sears, Ph.D.

Rosalie Sears, Ph.D. is a Professor in the Department of Molecular and Medical Genetics and a senior member of the Knight Cancer Institute and the Center for Spatial Systems Biomedicine at Oregon Health & Science University. She is also Co-Director of the Brenden-Colson Center for Pancreatic Care at OHSU, where she has built the infrastructure for deep omic analysis of longitudinally collected patient samples as well as propagation of primary patient tumor cells. This infrastructure is contributing to a multi-organ site clinical trial at OHSU aimed at understanding cancer evolution under treatment through the M2CH-CCSB. The Sears Lab studies cellular signaling pathways that control tumor cell behavior, with an emphasis on the management of tumor phenotypic heterogeneity and cell plasticity contributing to therapeutic resistance. Her research focuses on the convergence of signaling pathways on the c-Myc oncoprotein and how this impacts Myc’s expression, activity, and its regulation of cell fate. Myc is constitutively overexpressed in the majority of human tumors and studies have demonstrated that this affects both tumor cell state (proliferation, differentiation, metabolism) as well as cross-talk with the tumor microenvironment affecting immune surveillance and vasculature. Dr. Sears’ work reveals new ways to target post-translational activation of Myc that suppress tumor cell plasticity and phenotypic heterogeneity.

Claire Tomlin, Ph.D.

Claire Tomlin, Ph.D. is the Charles A. Desoer Professor of Engineering in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. Dr. Tomlin works in the area of dynamics, control and learning for hybrid systems, with applications to biology and engineering. She and her group have designed mechanistic and data-driven ODE models of the HER2+ signaling network in breast cancer, which led to design and test a pre-treatment scheme for steering the signaling network, and she has worked on understanding and developing models of phenotypic heterogeneity in breast cancer. In addition, she has developed high fidelity and deep mechanistic models of embryonic development, through a coupled process of biological experiments and mathematical modeling and analysis tasks in Drosophila, as well as models to understand the spatio-temporal architecture and molecular details of Planar Cell Polarity signaling. Her group develops tools for control system analysis and design using reachability and machine learning.

Emek Demir, Ph.D.

Emek Demir, Ph.D. is an Associate Professor of Molecular & Medical Genetics at Oregon Health & Science University. Dr. Demir’s overall research integrates multi modal profiles and pathway information to provide mechanistic explanations with a specific focus on cancer. His work on pathway informatics led to the development of the largest human pathway database, Pathway Commons and numerous tools and algorithms.

Center Administrator

Heidi Feiler, Ph.D.

Heidi Feiler, Ph.D. is a Research Associate Professor and the Deputy Director, Center for Spatial System Biomedicine at OHSU. She serves as Center Administrator for the M2CH-CCSB and is the primary contact for the logistical and organization aspects of the center to ensure that the goals are achieved. She works with the Center leadership to establish program governance, and communications strategies within the Center, with the External Advisory Committee, the CSB Consortium, the CSBC/PS-ON Coordinating Center (Sage Bionetworks), NCI, and other NCI large data initiatives. She oversees the center’s resources and budgets, compliance and reporting activities, the intra-center pilot project proposal process, and provides logistics support to the Outreach Core, to coordinate the Center SAGE-Synapse website and DREAM Challenge events, workshops and symposia. She also coordinates personnel exchanges and ensures that resources available through the M2CH-CCSB are available to the researchers in the CSBC and the broader research community.

Participating Investigators

Ellen Langer, Ph.D.

Ellen Langer, Ph.D. is a Postdoctoral Researcher in Rosalie Sears’ laboratory in the Department of Molecular and Medical Genetics at Oregon Health & Science University. Her current work focuses on mechanisms of cellular plasticity in cancer cells as well as in stromal cells within the tumor microenvironment.

Andrew Adey, Ph.D.

Andrew Adey, Ph.D. is an Assistant Professor in the Department of Molecular and Medical Genetics at Oregon Health & Science University. His past work has involved the development of numerous genome sequencing technologies for the acquisition of sequence contiguity information and for the interrogation of a variety of epigenomic properties. His current work involves the development of single cell genome and epigenome technology platforms to profile thousands of single cells in parallel.

James Korkola, Ph.D.

James Korkola, Ph.D. is an Assistant Professor in the Department of Biomedical Engineering and member of the Knight Cancer Institute and OHSU Center for Spatial Systems Biomedicine. Dr. Korkola’s laboratory focuses on how the microenvironment alters the phenotype of cancer cells, including their proliferative potential, differentiation state, and response to targeted therapeutics. He has developed and implemented MicroEnvironment MicroArray technology at OHSU to study simple combinatorial microenvironment factors for their effects on cancer cell phenotypes. His laboratory has applied MEMA technology to the study of HER2+ breast cancer, where it was found that different factors within the microenvironment can confer resistance to lapatinib, but in tumor subtype specific manner. Currently, Dr. Korkola is applying MEMA technology to other subtypes of breast cancer to identify microenvironment modifiers of drug response.

Laura Heiser, Ph.D.

Laura Heiser, Ph.D. is an Assistant Professor in the Department of Biomedical Engineering and member of the Knight Cancer Institute and OHSU Center for Spatial Systems Biomedicine. Her laboratory is focused on understanding mechanisms of therapeutic response and resistance, using novel imaging and omic analysis techniques to identify phenotypic changes associated with molecular aberrations and therapeutic response, and studying the influence of the microenvironment on cancer cells.

Xiaolin Nan, PhD

Xiaolin Nan, PhD is an Assistant Professor in the Department of Biomedical Engineering, and a member of the Knight Cancer Institute and the OHSU Center for Spatial Systems Biomedicine. Dr. Nan’s biophysics laboratory develops quantitative single-molecule and superresolution microscopy techniques for high resolution imaging of cells and tissue sections in up to tens of colors. The Nan Lab is also applying these powerful imaging tools to investigate the spatiotemporal regulation of the HER family receptors and the Ras GTPases at the nanometer and single-molecule scales.

Young Hwan Chang, Ph.D.

Young Hwan Chang, Ph.D. is an Assistant Professor of Biomedical Engineering and Computational Biology and a member of the OHSU Center for Spatial Systems Biomedicine. His current work focuses on developing image analysis tools for multiplexed imaging data to characterize subtypes and understand spatial distribution of cancer cells and their interactions with components of the microenvironment.

Damir Sudar, M.S.

Damir Sudar, M.S. is a Staff Scientist at Quantitative Imaging Systems, LLC (Qi), a member of OHSU Center for Spatial Systems Biomedicine, and a Visiting Scientist at Lawrence Berkeley National Laboratory. He develops automated microscopy techniques, image data processing and analysis software, and image data management systems. He is interested in integrating imaging modalities over multiple spatial, temporal, and functional/structural scales. He co-manages the Imaging Core, developing and optimizing image data management and image analysis software capabilities, overseeing microscopic imaging and data analysis, and work to enable image data sharing.

Michel Nederlof, Ph.D.

Michel Nederlof, Ph.D. is President and Chief Technology Officer at Quantitative Imaging Systems (Qi) and a member of the OHSU Center for Spatial Systems Biomedicine. He has 30 years of experience in digital imaging microscopy for life sciences, ranging from basic technological developments, to advanced image analysis, High Content Screening and clinical applications. He founded six biotechnology companies that have created pioneering products in the areas of microscopy research, pharmaceutical drug discovery, and clinical diagnostics. As CTO of Qi, he oversees all technical development on software and analytics integration and is responsible for the imaging workflow of many projects and involved in most aspects from microscopy image acquisition, to analysis, and visualization. Qi co-manages the Imaging Core for the M2CH-CCSB and provides image analytics.


Schematic illustration of the interplay between cancer cell intrinsic networks and extrinsic signals that influence aspects of cancer biology and response to therapy.

Overview of the Measuring, Modeling and Controlling Heterogeneity Center for Cancer Systems Biology.

Project 1 focuses on measuring and managing resistance-associated heterogeneity intrinsic to cancer cells. Project 2 focuses on identifying resistance-associated signals from the microenvironment and on mitigating effects from these signals on therapeutic response. Project 3 applies spatial systems biology approaches to TNBC specimens and multicell type models thereof to discover molecular control networks that influence how cell intrinsic plasticity and microenvironment signaling alter therapeutic responses in complex tissues.

Project 1: Therapeutic Management of Lineage- and Differentiation-state Plasticity

PIs: Sears, Demir; co-Is: Tomlin, Demir, Adey, Langer

Heterogeneity in differentiation state in a TNBC tumor and cell line demonstrated by immunofluorescence staining for differentiation-associated proteins.

TNBC is an aggressive disease characterized by high intratumor heterogeneity and poor patient outcome. In preliminary experiments, we identified subpopulations of tumor cells in primary TNBC as well as in basal-like TNBC cell lines that are characterized by differential expression of luminal, basal, and mesenchymal differentiation-state markers. We have observed that distinct classes of targeted therapeutics have the capacity to eliminate or enrich specific differentiation-state subpopulations within these lines, steering heterogeneous cancer cell populations toward increased homogeneity. Importantly, we identified synergistic combinatorial treatments that targeted either pathway dependencies predicted by master regulator analysis of residual cells or epigenetic regulators found to contribute to a cell’s transition to a resistant state. The overall goal of this project, therefore, is to understand cell intrinsic regulation of therapeutic response in phenotypically heterogeneous TNBC in order to develop targeting strategies to kill all co-existing subpopulations. We focus on phenotypic heterogeneity, as this can represent the combination of genetic and epigenetic factors, and we take advantage of clinically relevant therapeutics that drive heterogeneous populations toward homogeneity. We hypothesize that a systems biology approach of measuring and computationally modeling the functional pathways underlying phenotypic state changes in response to state-aggregating therapeutics will reveal common escape routes and regulators of cell plasticity, which allow us to predict effective combinatorial therapeutic strategies that eliminate all cancer subpopulations. We address this hypothesis by (1) examining and computationally modeling phenotype state changes in multiple genetically diverse, heterogeneous TNBC cell lines in response to targeted therapeutics that induce homogeneity using high-content imaging and single cell expression analysis, (2) determining whether clonal expansion or differentiation state plasticity drives the dynamic phenotype changes following targeted therapy and modeling the molecular network changes that underlie these transitions, and (3) determining epigenetic regulation underlying state transitions and developing combinatorial strategies that overcome therapeutic resistance in heterogeneous TNBC cells in vitro and in vivo. Together, these aims support our goal to measure and model cell intrinsic responses to clinically relevant targeted therapeutics and to predict synergistic drug combinations that more effectively control heterogeneous TNBC. Integration of this work with Projects 2 and 3 allows us to incorporate extrinsic regulators of these intrinsic mechanisms and to iteratively refine control strategies for this devastating disease.

Project 2: Managing Microenvironment-mediated Heterogeneity and Resistance

PIs: Heiser, Korkola; co-Is: Demir

Schematic illustration of the process used to use microenvironment microarrays to interrogate the effects of microenvironmental proteins on therapeutic responses.

The inability to effectively treat TNBC is thought to be in part due to its heterogeneity, as cells are highly plastic and able to respond rapidly to therapeutic insults to steer into drug resistant states. One aspect that is likely to strongly influence TNBC plasticity, heterogeneity, and response to therapy is the microenvironment (ME) in which cells reside. Interactions with extracellular matrix proteins or soluble factors like growth factors and cytokines can profoundly change phenotypic properties of TNBC cells, and mounting evidence suggests that such ME factors also influence response to therapy. We hypothesize that the ME impacts therapeutic response of TNBC, and that consideration of signals from the ME in treatment decisions are likely to lead to improved therapeutic control and patient outcomes. We couple experimental assessment of TNBC response to targeted therapeutics in the presence of defined combinatorial ME perturbations (MEPs) with concomitant expression profiling and computational approaches to define underlying pathway signatures to identify vulnerabilities in residual cancer cells that could be exploited for therapeutic benefit. This is accomplished using microenvironment microarrays to identify MEPs that confer resistance to six targeted therapeutics in TNBC cell lines and primary patient-derived xenograft (PDX) samples. We perform expression profiling by RNA-Seq at fixed time points on TNBC cells grown in the presence of resistance conferring MEPs plus therapeutic and use computational approaches to identify underlying reduced dimensionality network signatures (PREdictors of CEllular Phenotypes to guide Therapeutic Strategies, PRECEPTS) that are altered as a result of interactions of cells with MEP and drug. These altered PRECEPTS signatures represent candidates for therapeutic intervention, and are tested using drug combinations in an attempt to overcome ME-mediated resistance. We perform dynamic imaging and expression profiling of the response of TNBC cells to resistance conferring MEPs plus drug and identify PRECEPTS signatures that are dynamically altered. Such PRECEPTS signatures represent potential transition vulnerabilities that could be targeted for therapeutic intervention, which we test experimentally using drug combination treatments of TNBC cells. These approaches are closely coordinated with those of Projects 1 and 3 in the use of common cell lines, drugs, and reagents and to maximize the information that we derive from the experiments. This approach enables the discovery of new drug combinations that could be deployed clinically to improve outcome in TNBC patients with primary and disseminated disease.

Project 3: Understanding the Impact of Microscale and Nanoscale Heterogeneity and Resistance

PIs: Gray, Tomlin; co-Is: Nan, Demir, Chang

Integration of omic and spatial features to identify molecular networks that control molecular heterogeneity.

We use a spatial systems approach to identify molecular networks that control development of resistance-associated heterogeneity in TNBCs and to use this information to devise multidrug treatments that are effective in heterogeneous TNBCs. Our focus is on heterogeneity that arises from epigenomic plasticity intrinsic to cancer cells and from extrinsic signals from the diverse microenvironments into which TNBC cells disperse. Individual cells within a TNBC exhibit variable phenotypes and respond variably to treatment so that establishing durable control of TNBCs is notoriously difficult. We explore the mechanisms by which individual cells in TNBC tissues respond to perturbations induced by microenvironment interactions and/or drugs. Our approach is based on the concept that the phenotype and response to therapy of every cell in a heterogeneous TNBC tissue is influenced by its intrinsic epigenomic status and by the microenvironmental signals it receives. In short, every cancer cell-microenvironment-drug interaction in a heterogeneous experimental tissue or clinical specimen is an independent experiment of nature. We analyze ensembles of such interactions in TNBC tissues before and after treatment to determine the impact of local environmental signals on cancer cell phenotype and therapeutic response.

We accomplish this using cyclic multiplex immunofluorescence to stain cancer cells for quantitative analysis of proliferative status, differentiation state, and expression levels of proteins that report on control network activity. We quantify cancer cell-microenvironment interactions at the microscale using multicolor fluorescence microscopy and at the nanoscale using multispectral super resolution fluorescence microscopy and 3D scanning electron microscopy. We use custom image analysis techniques developed in the Imaging Core to quantify cell and microenvironment components and machine/deep learning strategies to identify microenvironment-cancer cell interactions that influence phenotype. This work guides development of dynamic models of spatially dependent control network-microenvironment interactions that can be used to devise therapeutic strategies to control TNBCs. The approach is statistically powerful since every tissue section contains details about tens of thousands of cell-microenvironment interactions. We accomplish this by; (1) developing cyclic multiplex immunofluorescence, multiscale image analysis, and machine learning procedures needed to identify molecular control networks in individual cells in TNBC tissues that respond to signals from microenvironmental cells and proteins (MEPs) and that influence phenotype and/or therapeutic response, (2) elucidating the effects of microenvironmental cells and high impact proteins on TNBC control network activity, phenotype, and therapeutic response in bioprinted tissues. (3) assessing the effects of microenvironmental cells and high impact proteins on TNBC control network activity, phenotype, and therapeutic response in TNBC xenografts and clinical TNBC specimens.


Imaging Management and Analysis Core

(Gray, Nederlof, Sudar)
The Imaging Management and Analysis Core (Imaging Core) provides a common infrastructure for image acquisition, efficient image data management, and quantitative analysis for all projects. It deploys and integrates images from multiple platforms including multiwell high content imaging, microenvironment microarrays, cyclic immunofluorescence workflows and correlative light/electron microscopy. This includes: (1) developing customized workflows for the three high-content microscope systems to acquire and store images and metadata and all derived and associated measurement data, using an open source OMERO image database and our Annot experiment tracking database, (b) providing automated scene segmentation and feature extraction solutions, and (c) developing novel visualization methods to interactively analyze quantitative imaging data, metadata, and externally linked data. These tools and methods are integrated into a highly efficient workflow for acquiring, managing, analyzing, and visualizing the types of high-content imaging data that are generated in Project 1 for assessing phenotypic state changes from drug therapy, and in Project 2 for analyzing the effects of the microenvironment, alone and in combination with drugs, on differentiation state. These data and visualization tools are made available to the community through the Outreach Core in close collaboration with Sage Synapse. The Imaging Core supports Project 3 and image analysis and visualization requirements in all projects by further developing our Dynamic Visualization Engine framework for visualization methods that integrate image data at the level of individual cells, images, and assays; experimental metadata and external annotations; image analysis features such as segmentation results; and interactive quantitative graphs that allow drilling down to all levels of underlying data.

Outreach Core

(Heiser, Feiler, Sudar)
The Outreach Core disseminates results, methods and tools from the Center to the broader research community. It accomplishes this by; (a) hosting symposia, workshops, and think tanks that present, train, and extend the state of the art in techniques useful for understanding heterogeneity in cancer, (b) providing access to the bioimaging and genomic data using a custom portal for access, visualization, and interactive analysis based on OMERO (Open Microscopy Environment image database) and Sage Synapse; and (c) conducting DREAM crowd-sourcing activities to seek analytical solutions to spatial systems biology questions, and to identify new methods and approaches for analyzing these data.

Administrative Core

(Gray, Tomin, Demir, Sears, Feiler)
The Administrative Core provides leadership and supports and coordinates: (a) communications and interactions within the Center and across the CSBC, (b) proposal preparation, management, reporting, and compliance activities, (c) oversight of budgetary and intellectual property issues, (d) oversight of the M2CH-CCSB computational infrastructure and the Resource Sharing Plan, (e) project integration and evaluation (including pilot projects), and (f) external review of the Center, including assembly of an External Advisory Committee (EAC).

Modeling the Role of Lymph Node Metastases in Tumor-Mediated Immunosuppression


Center Title

Stanford University Center for Cancer Systems Biology

Overall Project Title

Modeling the role of lymph node metastases in tumor-mediated immune suppression

Center Website

Center Summary

Our Research Center aims to identify the mechanisms in which tumor cells instruct the immune system to tolerant them by focusing on the understudied role of lymph node invasion in tumor-mediated immunosuppression.

Overall Distant metastasis is the primary cause of cancer-related death. To colonize distant tissues, cancer cells must migrate while evading elimination by the immune system. Evidence suggests that key steps in the induction process of immune tolerance occur early in the metastatic cascade, located at regional lymph nodes. However, the nature of the interactions between tumors and immune cells remains poorly understood, particularly for those occurring within the lymph nodes. Even though lymph nodes are in fact commonly assessed in cancer patients to determine disease stage and treatment plan, they are understudied in the context of metastatic progression.

We hypothesize that lymph node metastasis constitutes an essential, first step in the metastatic cascade of cancer progression. Based on our preliminary findings, we speculate that such metastases act locally upon the adaptive immune system within the nodes to begin to induce systemic tolerance of the tumor. We will explore, compare and test this hypothesis in two malignancies: (i) melanoma and (ii) head and neck squamous cell carcinoma. We have assembled a multidisciplinary team whose coordinated efforts will involve the application of genomic and single-cell in-situ imaging technologies on preclinical and human samples to explore the evidence and mechanisms of the induction of immunosuppression in the lymph nodes. We propose three inter-connected Research Projects that focus our scientific theme on different platforms: murine models (Project 1), high-dimensional in-situ imaging (Project 2), and integrative computational analysis (Project 3). All three projects will utilize a shared resource core dedicated to the acquisition of patient samples and associated clinical annotation and data management (Biospecimen and Data Management Core. These efforts will yield highly multiplexed, multi-scale datasets which will be analyzed by novel bio-computational methods to reconstruct intracellular and intercellular molecular interaction networks in order to identify, then functionally validate, critical mediators of tumor immunosuppression.

Our ultimate objective is to advance our understanding of the systemic consequences of lymph node metastases and identify new therapeutic approaches to cancer immunotherapy. Our findings promise to provide critical insights into blocking metastatic progression and thereby preventing cancer-related deaths.


Principal Investigators

Sylvia Plevritis, Ph.D.

Sylvia Plevritis, Ph.D. is a Professor in the Department of Radiology in the Stanford School of Medicine. Dr. Plevritis holds a PhD in Electrical Engineering (Stanford, 1992) with concentration on MRI spectroscopic imaging of tumors. She also holds an MS in Health Services Research (Stanford, 1996), with concentration on the evaluation of cancer screening programs on reducing cancer mortality. Dr. Plevritis is the Director of the Stanford Center for Cancer Systems Biology (CCSB), Director of the Cancer Systems Biology Scholars (CSBS) Program, and the co-Section Chief of the Integrative Biomedical Imaging Informatics at Stanford (IBIIS). She has developed integrative cancer research programs that bridge genomics, imaging and population sciences to understand cancer progression and treatment response. She served as PI in the NCI Integrative Cancer Biology Program for the past 10 years, currently as the Director of the Stanford Center in Cancer Systems Biology (CCSB).

Dr. Plevritis is also Director of the Stanford Postdoctoral Scholars Program in Cancer Systems Biology which aims to train the next generation of scholars at the interface of molecular cancer biology and biocomputation. She serves as the coDirector of Integrative Biomedical Imaging Informatics at Stanford (IBIIS,, a section in the Department of Radiology that promotes the development and application of novel biocomputational tools to integrate imaging, molecular and clinical data. She has been a Principal Investigator with the NCI Cancer Intervention Surveillance Network (CISNET, for over fifteen years and currently serves on the Executive Committee of Stanford Biomedical Data Sciences Initiative which promotes interdisciplinary research opportunities for “big data” sciences in precision medicine at Stanford University. Having pursued a career path that spans multiple disciplines, she was drawn to cancer systems biology research as it propels the intersection of diverse scientific concepts with the goal of unraveling the complexity of cancer and ultimately defeating this disease through improvements in early detection and treatment strategies.

Garry Nolan, Ph.D.

Garry Nolan, Ph.D. is the Rachford and Carlota A. Harris Professor in the Department of Microbiology and Immunology at Stanford University School of Medicine. He trained with Leonard Herzenberg (for his Ph.D.) and Nobelist Dr. David Baltimore (for postdoctoral work for the first cloning/characterization of NF-kB p65/ RelA and the development of rapid retroviral production systems). He has published over 180 research articles and is the holder of 20 US patents, and has been honored as one of the top 25 inventors at Stanford University. Dr. Nolan is the first recipient of the Teal Innovator Award (2012) from the Department of Defense (a $3.3 million grant for advanced studies in ovarian cancer), the first recipient of an FDA BAAA, for “Bio-agent protection” grant, $3million, from the FDA for a “Cross-Species Immune System Reference”, and received the award for “Outstanding Research Achievement in 2011” from the Nature Publishing Group for his development of CyTOF applications in the immune system. Dr. Nolan has new efforts in the study of Ebola, having developed instrument platforms to deploy in the field in Africa to study Ebola samples safely with the need to transport them to overseas labs (funded by a new $3.5 million grant from the FDA).

Dr. Nolan is an outspoken proponent of translating public investment in basic research to serve public welfare. Dr. Nolan was the founder of Rigel Inc. (NASDAQ: RIGL), and Nodality, Inc. (a diagnostics development company), BINA (a genomics computational infrastructure company sold to Roche Diagnostics), and serves on the Boards of Directors of several companies as well as consults for other biotechnology companies. DVS Sciences, on which he was Chair of the Scientific Advisory Board, recently sold to Fluidigm for $207 million dollars (2014) on an investment of $14 million.
His areas of research include hematopoiesis, cancer and leukemia, autoimmunity and inflammation, and computational approaches for network and systems immunology. Dr. Nolan’s recent efforts are focused on a single cell analysis advance using a mass spectrometry-flow cytometry hybrid device, the socall “CyTOF” and the “Multiparameter Ion Beam Imager” (MIBI) developed by Dr. Mike Angelo in his lab (Dr. Angelo is now an Assistant Professor in the Dept of Pathology at Stanford). The approaches uses an advanced ion plasma source to determine the levels of tagged reagents bound to cells enabling a vast increase in the number of parameters that can be measured per cell either as flow cytometry devices (CyTOF) or imaging platforms for cancer (MIBI).Further efforts are being develop with another imaging platform termed CODEX that inexpensively converts fluorescence scopes to high dimensional imaging platforms.Dr. Nolan’s efforts are to enable a deeper understanding not only of normal immune function, trauma, pathogen infection, and other inflammatory events but also detailed substructures of leukemias and solid cancers which will enable wholly new understandings that will enable better management of disease and clinical outcomes.

Ed Engleman, M.D., Ph.D.

Ed Engleman, M.D., Ph.D. is Professor of Pathology and of Medicine Immunology and Rheumatology). His laboratory studies the biology of immune cells and their roles in the pathogenesis of cancers and other life-threatening diseases. By applying new and more precise analytical tools for assessing this system in mice and humans, they have been successful at identifying disease-promoting immune abnormalities. By targeting the cells responsible for or affected by these abnormalities, they have succeeded in reversing the abnormalities and ameliorating the diseases they cause.
Dr Engleman’s lab has been particularly interested in the biology and functions of dendritic cells (DC), which are potent antigen presenting cells that can either induce or suppress immunity. Their first generation methods for isolating and arming human DC with tumor antigens provided the basis for the Sipuleucel-T vaccine that was approved by the FDA in 2010 for the treatment of metastatic prostate cancer. More recently, the lab developed a novel immunotherapeutic strategy that targets tumoral DC in vivo. In addition, they have been using newer technologies, including high dimensional single cell proteomic technology (CyTOF) and deep gene sequencing to investigate the immune system in cancer. A key goal is to identify and understand the key cellular and molecular mechanisms required for tumor elimination. The lab makes extensive use of mouse models for in depth mechanistic studies in addition to studying human samples.

In addition to cancer, the Engleman lab have been studying the role of immune cells in autoimmune diseases, metabolic diseases, graft versus host disease and transplantation tolerance. Recently, the group has developed novel tools for studying microglia in the brain and has begun to use these tools to analyze the role of these rare immune cells in chronic neurodegenerative disorders such as Alzheimer’s Disease, Parkinson’s Disease and amyotrophic lateral sclerosis (ALS). Preliminary findings in mouse models suggest that abnormal metabolism affecting these cells may contribute to the development of these disorders.

John Sunwoo M.D., Ph.D.

John Sunwoo M.D., Ph.D. is Professor of Otolaryngology (Head and Neck Surgery). Dr Sunwoo received his undergraduate degree from Brown University in Providence, Rhode Island and his medical degree from Washington University in St. Louis, Missouri. He completed his training in Otolaryngology – Head and Neck Surgery at Washington University. Dr. Sunwoo has been at Stanford University since 2008, and his clinical focus is on the surgical management of head and neck cancer, specifically focusing on melanoma and neoplasms of the thyroid and parathyroid glands. He is a member of the Pigmented Lesions and Melanoma Clinic and the Melanoma Working Group at Stanford. He is also the co-founder of the Stanford Thyroid and Parathyroid Tumor Board.
In addition to his clinical work, Dr. Sunwoo is the Director of Head and Neck Cancer Research at Stanford University and the principal investigator of an NIH-funded laboratory in the Stanford Cancer Institute. His research is focused on three primary areas: (1) the immune response to cancer, particularly a tumorigenic population of cells within malignancies called cancer stem cells; (2) the biology and developmental programs of a special lymphocyte population involved in innate immunity called natural killer (NK) cells; and (3) intra-tumor and inter-tumor heterogeneity in head and neck cancer. A major focus of the Sunwoo lab is the study of natural killer (NK) cells, a special lymphocyte population critically involved in the innate immune response to viral infections and malignancy. They are interested in understanding the regulation of NK cell development, homeostasis, and effector functions. One such regulator of these processes is the aryl hydrocarbon receptor (AhR), a cytoplasmic receptor that binds numerous endogenous and exogenous ligands. They recently showed that these small molecule ligands can modulate NK cell homeostasis and anti-tumor functions.

An overarching goal of the lab is to understand how the immune system interfaces with and protects against developing and metastasizing tumor cells, especially a rare population of tumor-initiating cells called cancer stem cells. In these studies, they utilize human and mouse models of head and neck squamous cell carcinoma (HNSCC) and melanoma. The lab is investigating novel mechanisms by which malignant cells can alert the immune system at the earliest stages of transformation. The lab also studies how regulators of genetic networks control the behavioral features of a subset of cells with stem cell–like properties. These cells are more resilient and have the ability to metastasize and are more resistant to chemotherapy and radiation therapy. A particularl interest is identifying mechanisms by which these tumor-initiating cells can selectively suppress the host immune response and understanding how to overcome these immunosuppressive properties.

Participating Investigators

Christina Kong, M.D.

Christina Kong, M.D. is Professor of Pathology. Her group is interested in improving the accuracy of cytologic diagnosis through refining diagnostic criteria and the use of ancillary techniques (e.g. immunoperoxidase stains, flow cytometry, in situ hybridization, PCR) on specimens obtained by the minimally invasive technique of fine needle aspiration biopsy. They are also working on identifying potential indicators of prognosis in head and neck squamous cell carcinomas. Additional interests include evaluating the utility of immunohistochemical stains in refining the diagnosis of squamous dysplasia of the cervix, vulva, and head and neck.

Robert Tibshirani, Ph.D.

Robert Tibshirani, Ph.D. is Professor of Statistics and of Biomedical Data Sciences. His main interests are in applied statistics, biostatistics, and data mining. He is co-author of the books Generalized Additive Models (with T. Hastie), An Introduction to the Bootstrap (with B. Efron), and Elements of Statistical Learning (with T. Hastie and J. Friedman). His current research focuses on problems in biology and genomics, medicine, and industry. With collaborator Balasubramanian Narasimhan, he also develops software packages for genomics and proteomics.

Jinah Kim, M.D., Ph.D.

Jinah Kim, M.D., Ph.D. is Assistant Professor, Pathology, and Dermatology, Stanford University Medical Center; Medical Director, Dermatopathology Service, Stanford Hospital and Clinics. Dr. Kim is a clinical pathologist in melanoma. She brings to the CCSB her considerable expertise to provide a pathological interpretation of the ABSeq (CODEX) imaging analysis of the melanoma samples. Research: Melanocytic lesions, fibrohistiocytic neoplasms, and genodermatoses.

Andrew Gentles, Ph.D.

Andrew Gentles, Ph.D. is Assistant Professor of Medicine (Biomedical Informatics Research) Dr. Gentles has been part of the Stanford ICBP for the past 8 years serving as Scientific Program Manager for the past 5 years. He lead the CCSB Data Integration and Analytics Core, creating a focal point for sharing data and facilitating collaborations between the different groups in the previous CCSB center and he co-leads the Data Core for the new center. Dr. Gentles developed prognostic signatures based on genomic data for AML, specifically the influence of leukemic stem cells, lung cancer, and large cell lymphoma. His research interests are in systems biology of cancer, integration/analysis of proteomic and genomic data to computationally infer biological insights about molecular pathways, analysis of next-generation sequencing data.


Project 1: Murine modeling of tumor-mediated immunosuppression

We hypothesize that lymph node (LN) metastasis constitutes an essential step in the metastatic cascade of melanomas and head and neck tumors in that such metastases act locally upon the adaptive immune system within the nodes to induce tolerance to the tumor and that leukocytes recirculating from these nodes carry the tolerance to distant sites. Our objectives are to establish whether LN metastases induce perturbations in anti-tumor immunity and to identify the mechanisms of these perturbations. We will a) characterize differences in local and systemic immune responses to metastatic tumors; b) identify differential regulators of tolerance induction by metastatic cells through the use of genomic profiling; and c) identify the molecular mediators of metastatic tolerance induction in mice and humans. Through the use of serial in vivo passaging, we have developed a panel of syngeneic melanoma cell lines that exhibit enhanced LN metastatic potential. We will compare the activation states of these immune cells, cytokine profiles, T cell polarization, and cytolytic activity toward tumor cells using single cell proteomic methods (Project 2). Using cytokine profiling and RNA sequencing on the lines, we will apply computational systems biology approaches (Project 3) to identify the molecules relevant for induction of tolerance. If our hypothesis is proven correct that LN metastasis is an obligate step in the generation of systemic disease due to tolerance induction, targeting the molecules responsible for LN metastasis induced tolerance could prevent and treat metastatic disease.

Project 2: Spatial architecture of tumor-mediated immunosuppression

Beyond the internal genomic and epigenetic events that occur to drive a cell towards outright carcinogenesis and then metastasis, there co-exist the ordered events a cancer imposes on immune cells it encounters on its progression towards advanced disease. Induction of tolerance, avoidance of apoptosis, and even recruitment of the immune system to aid a tumor’s growth are all poorly understood processes. We propose to undertake deep phenotyping of the 2D and 3D architecture of tumour-lymph node micro-environment—wherein it is expected some of the initial phases of the tumor’s avoidance and recruitment mechanisms are implemented. How is the architecture of the immune environment disrupted in the face of tumor metastasis? Are their micro-communities (as defined by particular cell-cell interactions) whose presence or absence defines an outcome in progression of the tumor? To this end we have developed a technology (ABSeq) that enables us to sensitively and quantitatively image tumors with 60 markers per 3 hours (scalable to 480 in a time-dependent manner) with markers selected from a range of intracellular or surface epitopes (recognized by antibodies) or RNAs. The hypothesis is that an orchestrated corruption of immune surveillance is initiated by cancers as they progress, and that the micro-scale architecture of the lymph node (by way of which cells are talking to whom and what broader effects occur across the lymph node and beyond) is disrupted in a defined manner. A major aim of the research is to, with ABSeq, define the 2D and 3D architecture and communities of immune and cancer cells in draining lymph nodes from 2 cancers (melanoma and head and neck cancer) in murine models and with human samples. Databases of 2D and 3D microenvironments will be publicly created and mined for associations that define the architectural changes that occur as tumors progress and initiate tolerance.

Project 3: Integrative computational modeling of tumor-mediated immunosuppression

We will develop and apply computational tools to integrate the complex datasets generated by our Center in order to identify candidate mediators of tumor-immune interactions that induce immunosuppression for functional validation. To enrich our ability for interpretation, we will explore signatures of the immune system in a pan-cancer analysis using the TCGA datasets annotated with time to distant metastasis, in the context of node-negative and nodepositive patients. We hypothesize that pan-cancer genes whose expression is strongly associated with time to distant metastasis are more likely to be associated with tumor-intrinsic or microenvironmental processes driving metastasis progression, thus we will prioritize these genes in our integrative computational analysis of our melanoma and head and neck squamous cell carcinoma datasets. Using the RNAseq data generated by our study, we will develop and apply novel network-based computational methods for reconstructing the interactions between malignant and immune subpopulations. Moreover, we will develop and apply new approaches to integrate the spatial information from high dimensional single cell in situ images from Project 2 with the gene expression datasets to further refine our inferences of candidate mediators of immunosuppression. The datasets and computational resources developed by our Project, and Center at large, will not only enable use to deeply explore the role of lymph nodes in tumor-mediated immunosuppression, but will also provide the community with powerful resources for understanding systemic influences on the forces governing metastatic dissemination.


Core 1: Biospecimen and Data Management Core

Our Biospecimen and Data Management Core will be utilized by all the Research Projects in our Center. All three Research Projects aim to identify mechanisms by which tumor cells, metastatic to regional lymph nodes, interface with the host immune system to perturb systemic immunity to induce global immune tolerance. While we will methodically study this process in murine models (Project 1), analysis of human tumor and lymph node specimens is paramount for two primary reasons. The first reason is to ensure the translation of the murine discovery approach to human disease. The second reason is to facilitate the discovery of critical mediators of tumor-induced immunosuppression directly from the human samples, then follow with functional validation in our murine models. Hence it is critical that we establish the necessary infrastructure to procure viable human tumor specimens and autologous immune tumorinfiltrating immune cells. Importantly, matched sets of fresh primary tumor cells, metastatic tumor cells, tumor-infiltrating immune cells (from the primary tumor and the lymph nodes) and circulating immune cells will be collected to address the hypotheses and goals of the Research Projects. Furthermore, in this shared core, a database of clinical annotation (aka clinical metadata) for these matched samples will be created and maintained. This clinical metadata is critical for interpretation of our molecular and imaging data given tumor and patient heterogeneity and will likely provide important insight into how the data generated by the proposed projects may be used to guide treatment and predict outcome. Our proposed Biospecimen and Data Management Core that will focus on collecting tissue and collating all the molecular data on our two index cancer models: melanoma and head and neck squamous cell carcinoma (HNSCC).

Core 2: Outreach Core

Stanford University has a diverse range of faculty in biostatistics, computer science, applied mathematics, cancer biology, immunology, biomedical engineering and many other disciplines. A number of transformative technologies such as DNA microarrays, flow cytometry, single cell transcriptomics, and applications of next generation sequencing had their genesis in labs here. We are therefore in a unique environment for promoting cancer systems biology to a wide audience of researchers, the relevance of whose expertise to the field may not be obvious a priori. We envisage that our efforts to promote our research and those of others to the Stanford community will seed new collaborations across disciplines. We will conduct outreach through regular seminar series and meetings, an annual symposium, funding for pilot projects, as well as participation in the CSBC Postdoctoral Exchange Program that will place researchers at reciprocal institutions to have short-term dense exposure to relevant research objectives and expertise at other institutions. And finally, important collaborative possibilities with the other CSBC Research Centers will be facilitated by their updates provided at annual meetings, as well as in our newsletter. The great value of this new NCI Consortium will be harnessed by ongoing building of an expansive investigator network across universities and research centers.

Complexity, Cooperation and Community in Cancer ([email protected])


Center Title

Complexity, Cooperation and Community in Cancer ([email protected])

Center Website

Center Summary

The overall goal for the UCI Center for Cancer Systems Biology ([email protected]), also known as the Center for Complexity, Cooperation and Community in Cancer, is to understand the principles that underlie why cancers are organized as they are. Our approaches stem from the idea that cancer cells proliferate and evolve in complex environments that have been highly selected for the robust control of growth and differentiation, and thus the behaviors of cancer cells can only be fully understood in the context of the design principles underlying such control. [email protected] is a joint effort by the systems biology and cancer biology communities at the University of California Irvine (UCI), as represented by two campus-wide research organizations, the Center for Complex Biological Systems and the Cancer Research Institute of the UCI Chao Family Comprehensive Cancer Center.

[email protected] is carrying out three coordinated, team-oriented research projects on the role of context, cooperation and community in the initiation and progression of cancer. All three projects seek to understand how the in vivo behaviors of transformed cells are constrained by rules inherited from the communities of diverse, interacting cell types and lineage hierarchies within which those cells arise. Project 1 leverages new observations from xenograft models of colon cancer to investigate non-genetic heterogeneity in solid tumors, both its origins and its relevance to tumor growth and response to therapy. Project 2 investigates the cellular origins of melanoma, seeking to clarify the relationship between melanoma and the benign lesions (melanocytic nevi) that are driven by a common oncogenic event. This work focuses on interactions among melanocyte precursors, within the skin environment, and under conditions that promote progression from benign to malignant. Project 3 focuses on improving models of chronic myeloid leukemia (CML) and its treatment, taking into account interactions between hierarchical lineages, intercellular feedback, and dynamics.

All three projects combine mathematical modeling, genomics, and experimental manipulation of animal models. Mathematical modeling is central to all three projects, not just as a means to analyze large data sets, but as a way of identifying, with the most generality, the architectures of cell interaction and feedback that can explain generic features of cancer cell behavior. All three projects develop models with design principles built on similar concepts: cell state transitions, proliferation and quiescence, positive and negative feedback, but in different contexts that derive from the different cancer types (spatial vs. non-spatial; focus on self-organizing pattern vs. focus on control; emphasis on model and parameter identification vs. emphasis on replicating qualitative behaviors). A common theme is the idea that bi- and multistability that arises as a result of feedback can potentially explain bifurcating system behaviors, such as nevi and melanoma in the same mouse, spatial patterns of heterogeneity, or resistance to cancer therapy, without having to attribute such events to new mutational “hits.”

All three projects are served by a core facility for investigating tumor cells at the single cell level, providing access to the latest in single-cell genomic, transcriptomic and other technologies, which are needed to provide the kind of data that can adequately constrain models.

An Administrative Core provides the organizational framework and logistic support for the center. The Administrative Core also solicits, reviews and administers pilot project grants initiated both by faculty and by trainees (graduate students and postdoctoral fellows). An Outreach Core promotes cancer systems biology to the research community, targeting researchers and trainees at all career stages through a wide variety of educational and professional development activities.


Principal Investigators

John Lowengrub, Ph.D.

John Lowengrub, Ph.D., Chancellor’s Professor of Mathematics and Biomedical Engineering, is a systems biologist and mathematician whose research efforts focus on developing mathematically rigorous and biologically-justified models of solid tumors. His research is highly interdisciplinary and has involved collaborations with many of the faculty participating in this center. In general, Dr. Lowengrub’s research aims to use mathematical modeling to understand how misregulated feedback signaling, metabolic reprogramming and interactions between a vascularized tumor and its microenvironment can drive tumor progression and dictate the optimal course of treatment. Recently, Dr. Lowengrub’s research group has provided an explanation of how cancer stem cells drive the development of invasive fingers (joint work with MPI Lander) and crosstalk with the stroma and vascular network. In addition, Dr. Lowengrub’s research group has developed models that explain how Wnt-driven spatiotemporal patterns of different metabolic states can emerge in vascularized tumor xenografts with genetically identical cells (joint work with MPI Waterman). Dr. Lowengrub currently serves as a co-leader of the Systems, Pathways and Targets (SPT) program of the Chao Family Comprehensive Cancer Center, a program that brings together cell biologists, immunologists, geneticists, developmental biologists, systems biologists, computational scientists, and clinicians. He is deeply committed to education in mathematical biology, cancer biology and systems biology, and spearheaded the development of an interdisciplinary M.S./Ph.D. graduate program at UCI that spans 10 departments and 5 schools; he now serves as Director of that program.

Arthur Lander, M.D., Ph.D.

Arthur Lander, M.D., Ph.D., Bren Professor of Developmental and Cell Biology and Professor of Biomedical Engineering and Logic & Philosophy of Science, originally trained in biochemistry, medicine, neurobiology and developmental biology, but his research over the last 15 years has focused primarily on the systems biology of morphogenesis and growth. His interests in the feedback control of growth, as well as his early clinical training, led him to an interest in cancer biology that ultimately resulted in several collaborative papers with the Lowengrub group, and his service as an MPI on a multi-investigator RC2 grant from the NCI. He has 18 years of experience as director of T32 training grants (three different ones), 8 years of service as the Chair of Developmental and Cell Biology, 10 years of experience as founding director of the UCI transgenic mouse core facility, and 16 years of experience as the founding director of the Center for Complex Biological Systems, UCI’s NIGMS-designated National Center for Systems Biology, which supports the research and educational activities of over 100 Systems Biology-affiliated faculty. Dr. Lander has served as chair of an NIH Developmental Biology study section and, from 2013 to 2017, as a member and Chair of the MABS (modeling and analysis of biological systems) NIH study section.

Marian Waterman, Ph.D.

Marian Waterman, Ph.D., Professor of Microbiology and Molecular Genetics, is the Director of the UCI Cancer Research Institute and Deputy Director of the Chao Family Comprehensive Cancer Center. She focuses her research on mechanisms of Wnt signaling that direct cellular phenotypes in cancer and stem cells. Dr. Waterman discovered one of the first members of the LEF/TCF transcription factor family and since then has focused on how these factors function in normal and diseased tissue. Dr. Waterman collaborates with physician scientists, mass spectroscopists, biomedical engineers, biophysicists at the Laboratory for Fluorescence Dynamics (Gratton, Digman), and mathematicians (including MPI Lowengrub). The overarching goal of her research is to understand how gene expression, metabolism, development, carcinogenesis and Wnt signaling are connected. As Director of the Cancer Research Institute, she also coordinates member leadership for a T32 training grant in Cancer Biology and Therapeutics; an American Cancer Society seed grant mechanism for junior faculty; the Cancer Biology track for the Molecular and Cellular Biology cross-campus graduate program; and a popular and competitive summer internship program for high school students. As Deputy Director of the Chao Family Comprehensive Cancer Center, Dr. Waterman coordinates the basic science programs and Shared Resources and works with the Director Richard Van Etten to advance strategic initiatives of the center and aims of the NCI cancer center support grant. At the national level, Dr. Waterman has served as chair of an NIH cancer biology study section (CAMP; 2010-2016), as chair of an American Cancer Society review panel (DMC; 2003-2007), and a member of ACS council for extramural grants (2010-2014).

Participating Investigators

Steven D. Allison, Ph.D.

Steven D. Allison, Ph.D., is an Associate Professor in the Departments of Ecology and Evolutionary Biology and Earth System Science. He is broadly trained as a biologist but with a focus on the role of micro-organisms in ecosystem scale processes, such as carbon cycling. His research spans scales from genomes to the globe, and he applies both experimental and theoretical approaches to analyze microbial functioning. Most of his experimental work has focused on the regulation, environmental responses, and ecosystem consequences of extracellular enzymes in environmental systems. More recently, his research has increasingly focused on theory and models. There is a clear need for new models that scale up microbial processes, and he brings a unique experimental perspective to the models he has developed. One set of individual-based models he created has potential applications to human health. These models are spatially-explicit and represent interactions among different cell types. The variation across cell types is flexible and informed by empirical data. One of the main results from this set of models is that emergent properties at the ecosystem scale are dependent on microbial interactions involving metabolite production. In some cases, evolutionary processes that optimize individual cell performance serve to undermine system-level functioning. This type of prediction is relevant in cancer treatments where targeting particular cellular interactions might provide a means of arresting tumor development and other system-scale symptoms.

Michelle Digman, Ph.D.

Michelle Digman, Ph.D., is an Assistant Professor in the Department of Biomedical Engineering. Her research focuses on developing fluctuation imaging techniques to study protein dynamics in real time and space inside live cells and tissues. In addition, her lab is developing a metabolic index for organs, tissue sections, tumors, embryos and single cells using the FLIM/Phasor method. This fast computational approach allows for the detection of metabolic states at the single cell level will help create a reference for metabolically active or non-active cells under specific conditions. She is also working on characterizing the competitive recruitment and binding activity of DNA repair proteins upon DNA single strand and double strand laser induced DNA damage using high spatiotemporal resolution scanning correlation spectroscopies. She has extensive expertise in measuring protein dynamics in both nuclear and cytosolic compartments in living cells as her background is multidisciplinary in the areas in biochemistry and biophysics. She has coauthored over 80 peer reviewed manuscripts including PNAS, Biophysical Journal, EMBO, and Nature Communication. She set up her lab as Assistant Professor in July 2013 and is focused in the quantitative understanding of cell function including cell invasion, proliferation, differentiation and apoptosis. She has several peer reviewed papers on using the pair correlation method to calculate the diffusive rout of proteins in the nucleus to understand nuclear epigenetic regulation in cancer cells. She is developing imaging methods with high spatial-temporal resolution in correlation analysis to elucidate signaling protein network interactions in the 2D and 3D microenvironment. Using a bioengineering approach, she can mimic the tissue microenvironment and quantitatively measure changes in matrix reorganization to dissect key molecular mechanisms that govern tumor cell invasion. She also developed the phasor/FLIM method for mapping and identifying intrinsic autofluorescence markers in tissues and for fluorescent FRET biosensors (Rho, Rac and CDC42) to measure signaling and activation. She has extensive expertise in measuring protein dynamics in live cells. Among these techniques, which she co-developed, the raster image correlation spectroscopy (RICS) method, the Number and Molecular Brightness (N&B) technique, the Phasor/FLIM and the pair correlation spectroscopy (pCF) method, are now being used by researchers in Biology.

Robert A. Edwards, M.D., Ph.D.

Robert A. Edwards, M.D., Ph.D., is an Associate Professor in the Department of Pathology & Laboratory Medicine. Dr. Edwards is the Director of the Experimental Tissue Resource (ETR) within the Chao Family Comprehensive Cancer Center. Research in his laboratory is focused on understanding how chronic inflammatory signals in the intestine promote colorectal cancer (CRC). As a Pathology resident and post-doctoral fellow, he studied a new mouse tumor model that links inflammation and colon cancer, via knockout of the G-protein subunit Gi2. Upon establishing his laboratory at UC Irvine, he developed collaborations with Dr. Steve Lipkin and MPI Waterman to study how this mouse model connects to human colon cancer. For the past 10 years, his work has highlighted network links between inflammation, hypoxia, Wnt and Notch signals in the tumor microenvironment, both in animal models and in clinical isolates of human CRC.

Anand K. Ganesan, M.D., Ph.D.

Anand K. Ganesan, M.D., Ph.D., is an Associate Professor of Dermatology and Biological Chemistry. His research focuses on understanding how the melanocyte interacts with the environment and other cells within the skin during the process of normal tanning and transformation. He has recently published studies identifying novel pathways that drive the early steps in melanoma progression, studies identifying novel pathways that regulate melanogenesis in vivo, and studies characterizing how melanoma tumors modulates the immune response during progression. His published work has used in vitro cell based approaches to understand the cell biology of melanocytes, in vivo approaches to understand how melanocytes interact with other skin and immune cells in mouse models, and studies with human tissue to ensure that the findings in these models are relevant to human disease. His clinical practice focuses on caring for patients with atypical moles and determining whether these lesions have malignant potential or not. He has recently redirected his research efforts to answer this important question and developed models to study nevus development, regression, and progression non-invasively. The eventual goal of this line of investigation is to develop better algorithms to identify and remove nevi evolving to melanoma at an early stage before they become a problem.

Christopher C.W. Hughes, Ph.D.

Christopher C.W. Hughes, Ph.D., is the Francisco J. Ayala Chair of the Department of Molecular Biology & Biochemistry and a Professor in the Department of Biomedical Engineering, where he serves as Director of the Edwards Lifesciences Center for Advanced Cardiovascular Technology. Dr. Hughes is also co-Leader of the Onco-Imaging and Biotechnology (OIB) Program, part of the Chao Family Comprehensive Cancer Center at UCI, and in 2014 was elected a Fellow of the American Association for the Advancement of Science (AAAS). His research focuses on the development and growth of blood vessels. The work in his lab spans multiple scales – from understanding the basic molecular mechanisms of angiogenesis (the growth of new blood vessels), to engineering of artificial tissues. Recently his lab has been pioneering “Body-on-Chip” technology, which allows for micro-organs – heart, pancreas, tumor, etc. – to be grown in the lab, each with its own blood vessel network. In addition to his research, Dr. Hughes works extensively with the non-profit organization, cureHHT, which provides patient support and research advocacy on behalf of those suffering from the rare vascular disorder Hereditary Hemorrhagic Telangiectasia. Professor Hughes serves as Chair of the foundation’s Global Research and Medical Advisory Board. He has worked with Marian Waterman on several projects related to tumor angiogenesis and wnt signaling, and has co-mentored a student with John Lowengrub

Kai Kessenbrock, Ph.D.

Kai Kessenbrock, Ph.D., is an Assistant Professor in the Department of Biological Chemistry. His research experiences include: a) 5 years of working on inflammatory diseases using mouse models and human samples during his PhD thesis; and b) 6 years of postdoctoral training studying the role of microenvironmental factors in the regulation of breast epithelial stem cell function and breast cancer in single cell resolution. His lab at UC Irvine is focusing on single cell analyses of the epigenetic landscapes and the transcriptional signatures in individual cancer cells in order to ultimately understand how one may therapeutically tackle the clinical problem of tumor heterogeneity. Dr. Kessenbrock is highly experienced in tissue dissociation, cell preparation, cell screening and analysis using the C1 Fluidigm and 10X Chromium platforms. The goals of his research are to use enhanced understanding of tumor initiation to improve methods for early detection of cancer in order to treat cancer patients before it turns into a life-threatening condition.

Natalia Komarova, Ph.D.

Natalia Komarova, Ph.D., is a Professor in the Departments of Mathematics and Ecology and Evolutionary Biology. She has extensive experience with mathematical models that describe the in vivo dynamics of human diseases, most notably cancer. In particular, she is very familiar with stochastic modeling approaches to describe cancer and with the types of approaches required to predict age-incidence patterns from mathematical models of in vivo biological processes. She has a strong background in applied mathematics, the area in which I performed my doctoral studies at the University of Arizona. She has been working extensively in various fields of mathematical biology since her postdoctoral position at the Institute for Advanced Study in Princeton, including biomedical fields, as well as general evolutionary dynamics and problems in social and behavioral sciences. She has been PI and investigator on a number of NIH and NSF grants, has collaborated with a variety of experimental groups, and has successfully led and coordinated scientific work in the context of larger projects.

Tatiana B. Krasieva, Ph.D.

Tatiana B. Krasieva, Ph.D., is a Project Scientist at the Beckman Laser Institute and the Department of Surgery. She has been involved with the development of optical microscopy methods and its applications through Laser Microbeam and Medical Program (LAMMP) since 1991. She has extensive expertise in developing in-vitro, ex-vivo, and in-vivo microscopy applications, experimental design and data interpretation in the field of optical microscopy, including conventional techniques, multiphoton excited fluorescence, second harmonic generation, fluorescence life-time imaging, optical coherence microscopy and spectroscopy. She has developed an optical method based on fluorescence spectroscopy and fluorescence lifetime imaging for identification and separation of two pigments – eumelanin and pheomelanin, two major constituents of human skin. She also has expertise in development of novel murine model imaging in vivo microscopy applications (skin, brain) and in laser ablation of tissue in the laboratory setting and experience in imaging regeneration after laser injury.

Devon A. Lawson, Ph.D.

Devon A. Lawson, Ph.D., is an Assistant Professor, Department of Physiology and Biophysics. The goal of her research program is to understand the cellular and molecular basis of breast cancer metastasis, with an emphasis on using new single-cell genomics technologies to investigate the role of genetic and phenotypic diversity in different phases of the metastatic process. Her research takes an interdisciplinary approach, combining recent advances in human in mouse modeling, sequencing technology, bioinformatics and computational biology, systems biology, and mathematical modeling to investigate the metastasis problem at an integrated level. Since metastasis remains the cause of most cancer-related mortality, enhanced understanding of the metastatic process is needed to effectively treat and prevent metastatic progression. The ultimate goal of her research is to utilize new insights to develop biomarkers for early detection of metastatic cells, and identify new therapeutic strategies to prevent and treat metastatic disease.

Harry Mangalam, Ph.D.

Harry Mangalam, Ph.D., is a research computing specialist in the Office of Information Technology. He is deeply familiar with a wide range of research computing domains and works with researchers to help them accelerate their work in large scale visualization, bioinformatics, evolutionary biology, high-throughput sequencing, large scale data processing, compute cluster planning & implementation, system administration, data center planning, and grant preparation. He is experienced at integrating multiple pieces of software into a pipeline or complex script, usually addressed with Perl, Python, and R/Bioconductor. He is an expert in C and is familiar with the GNU build toolchain. Dr. Mangalam has performed bioinformatics contract work for the Epidemic Outbreak Surveillance taskforce (now part of the Homeland Security Department), GeneCodes, the CDC, Allergan, Accelerys, and startups. He has also worked in the Science group on their Genomics Knowledge Platform (GKP), which provided both syntactic and semantic integration of biological information from a number of sources through their “Biological Object Model”. In addition, Dr. Mangalam has significant experience in storing and analyzing results from large scale gene expression through projects involving the GeneX gene expression database project, an Open Source Gene Expression database. He has created the sequence analysis application tacg and it’s CGI Web interface tacgi to make a small, fast (~30X faster than GCG or EMBOSS), free, and capable molecular biology tool available for Linux/Unix. Dr. Mangalam has taught introductory linux classes, written online documents on various subjects in scientific computing, and written useful Open Source applications, including the clusterfork, a cluster administration tool, parsyncfp, a parallel, load-balancing wrapper for rsync, and scut, a regular-expression-aware data slicer.

Edwin S. Monuki, M.D., Ph.D.

Edwin S. Monuki, M.D., Ph.D., is the Warren L. Bostick Professor and Chair of the Department of Pathology & Laboratory Medicine. His laboratory investigates basic forebrain development to inform human disorders and stem cell culture strategies with clinical potential. The two forebrain structures of particular interest to his group are the cerebral cortex, the seat of higher cognitive functions, and the choroid plexus, the source of cerebrospinal fluid (CSF) that bathes and nourishes the brain and spinal cord. Over the past several years, the experimental work in his lab has benefitted tremendously from collaborations with systems biologists. Dr. Monuki is working closely with systems biologists to develop an educational program in systems pathology in the School of Medicine at UC Irvine.

Ali Mortazavi, Ph.D.

Ali Mortazavi, Ph.D., is an Assistant Professor of Developmental and Cell Biology. His research interests are in the application of genomic methods to answer fundamental questions in the transcriptional regulation of development using a combination of functional sequencing assays and computational methods. He is particularly interested in understanding how homologous gene regulatory networks are encoded in the human and mouse genomes. He also has a separate interest in comparative genomics and development of nematode parasites with a particular focus on the genus Steinernema. His lab combines experimental work and computational analysis primarily in hematopoietic, skeletal muscle, and embryonic stem cells in human, mouse, and other mammals to understand which regulatory elements are conserved, which elements are not conserved but functional, and which elements regulates what genes. His laboratory has focused over the last five years on doing comparative analyses of regulatory elements and their long-range interactions in human and mouse using a combination of ChIP-seq, ChIA-PET, DNase-seq, ATAC-seq and RNA-seq using ever lower amounts of starting material down to single cells when practical. His long term goals are (a) to develop models that take into account the complex interplay of promoters and enhancers in controlling gene expression and (b) to understand the common and species specific parts of the human and mouse Gene Regulatory Networks for homologous cell types and tissues in order to translate seamlessly results between human and mouse models of disease.

Qing Nie, Ph.D.

Qing Nie, Ph.D., is a Professor of Mathematics, Biomedical Engineering, and Developmental and Cell Biology. He is a fellow of the American Association for the Advancement of Science (AAAS) and American Physical Society (APS). Dr. Nie is also the Director of the Mathematical and Computational Biology Graduate Gateway Program and an Associate Director of the Mathematical, Computational and Systems Biology interdisciplinary graduate program. Originally trained in scientific computing and mechanics during my Ph.D. study and as a postdoctoral fellow working on fluids and materials, during the past 15 years Dr. Nie has devoted his research effort to systems biology of morphogenesis, regulatory networks, cell signaling, and stem cells with emphasis on addressing challenging and complex biological questions in close collaboration with experimentalists. One of his major research aims is to develop predictive models and powerful computational tools that target specific and important questions including developmental patterning, stem cells, spatial dynamics, and stochastic dynamics in cell signaling. Dr. Nie is a leader in interdisciplinary training at the interface between mathematics and biology and is a MPI of a NIH T32 pre-doctoral training grant on Mathematical, Computational, and Systems Biology.

Nilamani Jena, Ph.D.

Nilamani Jena, Ph.D., is a Senior Project Scientist in the Department of Hematology and Oncology. His graduate and postdoctoral studies focused on the molecular pathogenesis of human hematologic malignancies. As a graduate student with Dr. Carlo Croce, he identified a novel pathway of regulation of the BCL-2 antiapoptotic protein via phosphorylation. As a postdoctoral fellow with Dr. George Daley, he demonstrated a specific role for Cyclin D2 in transformation and proliferation of BCR-ABL1-transformed B lymphoid cells. In his subsequent work as a postdoctoral fellow and now as a Senior Project Scientist in the research group of Dr. Rick Van Etten at UC Irvine, he has gained expertise on study of lymphoid development, hematopoietic stem cell isolation, retrovirus mediated gene transfer, bone marrow transplantation, analysis of development of leukemia in mice, and treatment of mice with leukemia with experimental therapy. He also has extensive experience in recombinant DNA techniques, in vitro cell culture, production of recombinant retrovirus, analysis of cells using FACS, analysis of proteins by immunoblotting.

Melanie L. Oakes, Ph.D.

Melanie L. Oakes, Ph.D., is a Project Scientist in the Department of Biological Chemistry and the Facilities Manager of the UCI Genomics High Throughput Facility (GHTF). As manager of the UCI Genomics High Throughput Facility, she brings the latest technologies to the UCI campus research community. She supervises a staff of five research associates in applications including current Affymetrix microarrays, next generation sequencing using the Illumina HiSeq 2500 and 4000 and Pacific Biosciences Sequel sequencers, Nanostring RNA analysis and BioNano Irys genome mapping system. Additionally, her team at the GHTF supports single cell gene expression with the Fluidigm C1 single cell auto prep system and the 10x Genomics Chromium platform. Her team tests and develops custom approaches to assist users in optimal applications of emergent technologies. Her research focused on using yeast as a model system to explore regulation of cellular growth with a specific focus on the regulation of transcription of ribosomal RNA. During the course of the work, she identified and characterized polymerase I transcription factors and took advantage of yeast genetics to create mutants and subsequently analyze ribosomal RNA synthesis, nucleolar structure and cell growth.

Bruce J. Tromberg, Ph.D.

Bruce J. Tromberg, Ph.D., is a Professor of Biomedical Engineering and Surgery. Dr. Tromberg is also the Director of the Beckman Laser Institute and Medical Clinic (BLI) and is the Director of the Laser Microbeam and Medical Program (LAMMP), an NIH P41 National Biomedical Technology Center. His lab has been involved in the development of biophotonic technologies for cancer detection, diagnosis, and treatment for more than 25 years. A major emphasis has been on the clinical translation of in vivo imaging technologies based on nonlinear optical microscopy (NLOM) and diffuse optical spectroscopic imaging (DOSI). He has extensive experience in building and supporting optical imaging technologies, including leading an ECOG-ACRIN national clinical trial of DOSI in breast cancer imaging and a UCI trial of NLOM in melanoma.

Richard Van Etten, M.D., Ph.D.

Richard Van Etten, M.D., Ph.D., is a Professor of Medicine and Biological Chemistry and the Director of the Chao Family Comprehensive Cancer Center at UCI. Dr. Van Etten has been involved in basic and translational cancer research for over 25 years as a faculty member at academic medical centers, initially at the Dana-Farber/Harvard Cancer Center and subsequently at Tufts University. He currently serves as a regular member of NCI Cancer Centers Subcommittee A. He is also a member of the Leukemia Committee of the Eastern Cooperative Oncology Group/ACRIN. His lab studies the molecular pathogenesis of human leukemia with a heavy emphasis on modeling these diseases in laboratory mice using retroviral/lentiviral gene transfer and bone marrow transplantation, and using conditional transgenic mouse technology. He has extensive experience in murine hematopoietic stem cell transplantation and in the analysis of healthy and diseased BM chimeric mice. Dr. Van Etten’s group has modeled adoptive immunotherapy of chronic myeloid leukemia (CML) and B-cell acute lymphoblastic leukemia (B-ALL), discovered novel signaling pathways in CML and B-ALL, and tested new approaches to targeted therapy of myeloid and lymphoid leukemia. Dr. Van Etten also a clinician specializing in hematologic malignancies, currently caring for many CML patients in various phases of the disease, and serving as institutional co-investigator on multiple clinical trials in blood cancer.

Dominik Wodarz, D. Phil.

Dominik Wodarz, D. Phil., is a Professor in the Department of Ecology and Evolutionary Biology. He has a broad background in mathematical models that describe biological processes, especially in the context of diseases and biomedical questions. He has extensive experience with modeling the in vivo dynamics of carcinogenesis, as well as with modeling the in vivo dynamics of viral infections and immune responses. He works with a variety of modeling approaches, including ordinary differential equations, stochastic models, as well as a variety of spatial modeling approaches including agent based models. He began this work as a D. Phil. student at the University of Oxford, expanded on it as a postdoctoral researcher at the Institute for Advanced Study in Princeton. Dr. Wodarz has been working in this area of research as a faculty member both at the Fred Hutchinson Cancer Research Center, and at the University of California Irvine. He has worked successfully with a number of experimental laboratories, and have previously led dual PI projects that involved combinations of mathematics and experiments.

Jie (Jenny) Wu, Ph.D.

Jie (Jenny) Wu, Ph.D., is a Project Scientist in the Department of Biological Chemistry and the UCI Genomics High Throughput Facility. She has a broad background in computational biology, with specific training and expertise in key research areas such as sequence analysis, network analysis, statistical analysis and software development. As a postdoctoral researcher at Boston University, she carried out whole genome sequence data analysis to automatically annotate newly sequenced genomes and developed software for visualization and exploration of functional association networks. At Delta Search Labs, she focused on integrating heterogeneous data types such as microarray data, genomics data, proteomics and metabolomics data from toxicological treatments, using pathway and network analysis with GeneGO metacore and IPA. As a Sr. Scientist at CODA and Verdezyne, she designed pipelines for whole genome sequencing data analysis to optimize protein expression using MATLAB, R and Perl. At UC Irvine, she has performed next generation sequencing data analysis including exome-sequencing, WGS and RNA-seq data, pathway and network analysis with WGCNA and IPA. Working with huge data sets on a daily basis, she has experience with Unix environment scripting, high performance computing and parallel programing. She is also familiar with popular NGS tools such as Bowtie, Samtools, IGV etc.

Xiaohui Xie, Ph.D.

Xiaohui Xie, Ph.D., is a Professor of Computer Science. His main research and teaching interests are in computational biology, bioinformatics and machine learning. He has extensive experience in sequence analysis, genomics, statistics including 1) large-scale genome analysis; 2) development of deep learning methods; 3) development of machine learning algorithms for probabilistic models; 4) data structures and algorithms for sequence alignment; 5) genome-wide regulatory element discovery; and 6) development of analysis tools for CLIP-seq, ChIP-seq, RNA-seq, epigenomics, and genetic variation detection. His group has developed popular tools for cancer genome analysis, including TEMT, a software package for analyzing RNA-seq in heterogeneous cancer tissues, and PyLOH and MixClone, two packages for analyzing cancer genome heterogeneity. Xie has also pioneered in the application of deep learning to genomic analysis. Dr. Xie also been actively involved in teaching machine learning, computational and systems biology to both undergraduate and graduate students.

Core Director

Suzanne B. Sandmeyer, Ph.D.

Suzanne B. Sandmeyer, Ph.D., is the Grace Beekhuis Bell Chair of Biological Chemistry and a Professor of Microbiology & Molecular Genetics and Chemical Engineering & Materials Science. She is the Director of the UCI Genomics and High-Throughput Facility (GHTF), the Associate Director of the UCI Institute for Genomics and Bioinformatics and the Vice Dean for Research in the School of Medicine. As Director of the UCI Genomics High-Throughput Facility, Dr. Sandmeyer strives to make emerging technologies available to investigators at UCI, and where possible beyond, and to facilitate development of such technologies. The GHTF currently provides Affymetrix microarray, Illumina HiSeq 4000 and PacBio Sequel sequencing, Nanostring RNA analysis, BioNano Long Range mapping, and 10X Genomics Chromium single-cell DNA sequencing to the UCI campus and outside clients. The GHTF also provides workshops for users in wet bench techniques and bioinformatics. Dr. Sandmeyer discovered the Ty3 retrotransposon in budding yeast which became a molecular model for Ty3/gypsy elements, one of the largest families of retrotransposons. Using this system and the power of yeast genetics and biochemistry she described the essential features of the Ty3 genome and encoded proteins, Ty3 host factors, virus-like particle assembly in association with RNA processing bodies, and integration targeting by transcription factors. She has expanded her research interests to development of the oleaginous yeast model, for metabolism, Yarrowia lipolytica. She recently published an annotated version of the genome for this organism and a study using transposon mutagenesis to identify essential genes of Yarrowia and test the requirements for growth under different conditions.

Project Manager

Sohail Jahid, Ph.D.

Sohail Jahid, Ph.D., is an Academic Coordinator at the Center for Complex Biological Systems. Her research experiences have included studying the role of microRNAs in the development of colon cancer. She identified a recurrent amplicon on mouse chromosome 8 that encodes microRNAs (miRs) 23a and 27a. miRs-23a and 27a levels are upregulated in mouse intestinal adenocarcinomas, primary tumors from stage I/II CRC patients, as well as in human CRC cell lines and cancer stem cells. She also studied the role of DNA mismatch repair proteins in genomic recombination. Mammalian mismatch repair (MMR) complexes include MLH/PMS proteins, which heterodimerize to form three distinct complexes: MLH1/PMS1, MLH1/PMS2, and MLH1/MLH3. MMR suppresses tumor formation via three mechanisms: repair of base substitution, repair of frameshift, and repair of small insertion-deletion mutation. She became interested in next generation cancer imaging, and joined Dr. Enrico Gratton’s laboratory to develop novel techniques to image cancer cell metastasis in vivo. While in his laboratory, she gained expertise in advanced imaging techniques and how they can be utilized to image the extravasation of cancer cells from the bloodstream. She has also studied RhoJ (a Cdc42 homologue), as a novel regulator of melanoma chemoresistance, and has investigated whether Pak inhibitors are useful agents to treat metastatic melanomas through both transgenic mouse and translational human biomarker studies.


Project 1: Patterned Heterogeneity in Colon Cancer

PIs: Christopher C.W. Hughes, Marian Waterman
Key Personnel: Steven D. Allison, Michelle Digman, Robert A. Edwards, Kai Kessenbrock, Arthur Lander, John Lowengrub, Qing Nie

Solid tumors are complex masses of cancer cells with a multitude of genetic, epigenetic, morphologic and metabolic phenotypes. This heterogeneous condition is a formidable barrier to treating cancer as it underlies the ability of tumors to adapt to nutrient starvation, immune challenges and to develop resistance to cancer treatments – the most common cause of mortality. Non-genetic heterogeneity in gene expression, signaling and metabolism are considered to be some of the most dynamic forms of heterogeneity and the most responsive to the tumor microenvironment. But we currently understand little about such heterogeneity, both mechanistically (what drives it) and functionally (how it helps the tumor). Non-genetic heterogeneity is very challenging to study, partly because of a limited toolbox and partly for lack of tractable model systems. Consequently, there are fundamental unknowns about how such heterogeneity arises and what its role in tumor growth and drug resistance really is.
In preliminary and published work, we observed heterogeneity in a xenograft model of colon cancer where the heterogeneity is patterned in a manner suggestive of a spatially self-organizing process (such as Turing-patterning). What is heterogeneous in these tumors is both Wnt signaling (thought to be the essential driver of proliferation in these cells), and metabolism (the balance between glycolysis and oxidative phosphorylation). In particular, the pattern consists of cell clusters, or spots, in which biomarkers of Wnt signaling are higher than in surrounding regions. These spots also mark regions of glycolytic metabolism. These patterns are likely connected through Wnt regulation of the expression of genes that control metabolism, as identified in our earlier work, and possibly through Wnt-Turing patterning of cancer cell subpopulations. Interestingly, glycolytic heterogeneity has recently been proposed to serve as the basis for resistance to anti-angiogenic therapy, one of the most important clinical problems in colorectal cancer. The short time scale of the xenografting (14-21 days), the reproducibility of the heterogeneity across genetically identical cell lines, and sites of injection, all suggest that this heterogeneity is not genetic.

In this project, Hughes, Waterman and their team seek to understand the causes of the observed heterogeneity in colon cancer, the reason why spatial patterns of heterogeneity develop spontaneously, the consequences of such heterogeneity for the growth of tumor cells, and whether this, or possibly other, forms of heterogeneity indeed drive resistance to therapy (and if so, why). They are addressing these questions by 1) explaining the relationships between heterogeneity, patterning and growth of colon tumors; 2) defining the general principles linking heterogeneity, patterning and growth in colon tumors; and 3) defining the link between heterogeneity and drug resistance.

Figure 1. Xenograft colon tumors reveal a spotted pattern of metabolic (A) and Wnt signaling (B) heterogeneity; concordant heterogeneity in metabolism and Wnt signaling is present in primary patient tumors (C). (D) shows a new vascularized microtumor (VMT) platform that supports human vessels (red) and colon tumors (green), NADH-fluorescence lifetime imaging (FLIM) of colon tumors in the VMT shows metabolic heterogeneity (D: lower right). (E) Single Cell Sequence analysis using Seurat/tSNE clustering reveals that SW480 xenograft tumors are strikingly heterogeneous with a cancer stem cell-like cluster (0: top left) that is missing in tumors expressing dominant negative LEF1 (dnLEF: bottom left). In (E/Middle Panel) Ligand and receptor pairs among several cell clusters of the human and mouse (right panels in E) cells are shown. (F) Candidate mathematical model for simulating SW480 tumors.

The foundation of the project is multi-scale modeling of stochastic and self-organizing processes that potentially explains overt differences in tumor growth, patterning of heterogeneity and metabolism, and the most likely mechanisms for drug resistance. The experimental tools pair xenograft studies with a novel platform for generating fully vascularized micro-tumors in vitro; the use of fluorescence lifetime imaging to read out the metabolic states of unlabeled, living cells, and the use of single cell transcriptomics to identify cell states, the gene expression signatures that define them and signaling and adhesion molecules that mediate communication among the cells. Modeling predictions of strategies that re-establish drug sensitivity will be tested via genetic engineering (CRISPR/Cas9) or small molecule drug therapies. The overarching goal of the work is to discover deep insights into the origins and consequences of tumor heterogeneity in an especially manipulable, and clinically relevant tumor system. The integration of this work with Projects 2 and 3, which focus on different cancer types (melanoma and chronic myeloid leukemia, respectively), enables us to identify general principles that underlie how the in vivo behaviors of transformed cells are constrained by rules inherited from the communities of diverse, interacting cell types and lineage hierarchies within which those cells arise.

Project 2: Understanding the Cellular Origins of Melanoma

PIs: Anand Ganesan, Arthur Lander
Key Personnel: Devon A. Lawson, John Lowengrub, Bruce Tromberg, Tatiana Krasieva

Melanoma, a tumor resistant to therapy in late stages, is curable by excision when caught early. Early melanomas can be difficult to distinguish from benign, pigmented “moles”, i.e. melanocytic nevi; this leads to unnecessary excision of many normal nevi while early melanomas are often missed. Nevi and melanomas share more than morphological features: Clinical and experimental data show that ~90% of nevi are initiated when melanocytes acquire an activating mutation in the BRAF oncogene, the same oncogenic mutation observed in >60% of melanomas. Yet nevi spontaneously stop growing. This is usually attributed to “oncogene-induced senescence,” but the fact that nevi readily re-grow after incomplete excision, or in response to UV-irradiation, and can sometimes evolve to melanoma, suggest nevi are not “senescent” but reversibly growth-arrested. Nevi also spontaneously regress, a process that appears to involve the immune system.

In preliminary work, we investigated nevus dynamics in a mouse model of inducible Braf activation, which mimics human nevus formation and also produces melanomas either at low frequency or when additional oncogenic mutations are added (e.g., in Pten). We found that as we activate Braf in more melanocytes, such that nevi become more numerous and closely-spaced, the smaller individual nevi become—as if nevi, when close together enough, inhibit each other’s growth. Such behavior is predicted by mathematical models of growth control based on feedback through diffusible signaling molecules. Such models achieve robust control when feedback regulates decisions between self-renewal and progression to alternate cell states or fates. Interestingly, when we look closely at the nevi in this model, we see that there are, in fact, two distinct cell types: highly pigmented nevus body cells and a scattered, lightly pigmented melanocyte population that forms a “veil” around the pigmented cells that had not been observed before. These veil cells are usually not seen unless the melanocyte lineage is fluorescently-labeled with GFP. Single cell RNA-sequencing suggests that these cells likely communicate through ligands and receptors they differentially express.

In this project, Ganesan, Lander and their team seek to understand the role of the nevus body and veil cell types in mouse models that produce both nevi and melanoma, and to identify both the nature of how growth is controlled in nevi and the means by which melanoma cells escape from it. The goal of the work is to build a solid molecular and cellular framework on which to base clinical decisions about melanoma prevention, detection and treatment. They are addressing these issues by 1) Explaining feedback growth dynamics in melanocytic nevi; 2) Elucidating how melanomas escape growth control mechanisms that arrest nevi; and 3) Revealing how the immune system targets nevi, and how this affects melanoma development.

Figure 2. (A) BRAF-mutant (Tyrosinase::CreERT2; BraffloxV600E/+) mice are crossed with ROSAmT/mG mice (TCBR) to GFP-label BRAF-mutant melanocytes. (B) Fluorescence emission (confocal and MPM) 3-D imaging of skin of live mice (as in Fig. 1; total depth = 90, 115 and 190μm for 1x, 2x, and 3x representative stacks, respectively). Green = GFP; red = td Tomato. (C,D). Continuum modeling, in which cells at an arrested (quiescent) lineage stage feedback on the self-renewal probability of dividing cells. Model snapshots (D) show cell density (see heatmap) as a function of time (T= cell cycles) and location. Top and bottom rows are for low and high seeding densities, respectively, that represent different levels of nevi induction. (E) Single Cell RNA-seq of melanocytic nevi. Control mice (Tyrosinase::CreERT2; ROSAmTmG; TCR) and TCBR mice, as labeled. Left: tSNE clustering of gene expression for individual cells. Right: A portion of the tSNE map, showing contributions of TCR and TCBR mice as well as expression of selected marker genes.


This project integrates multiscale mathematical modeling with experiments in mice using a nevus-forming inducible activated Braf model, and a version of the same model that combines Braf activation with inducible loss of one allele of Pten, leading to the reliable production of both nevi and melanoma tumors. We are developing hypotheses that can explain the spatiotemporal dynamics and spatial statistics of nevus and melanoma development in these models, including potential bifurcations that account for the development of both nevi and melanoma in the same mouse. We are investigating the reasons why some cells escape from growth control, while others do not. We anticipate that this is unlikely to be due to a requirement for inactivation of the other Pten allele, and instead believe that escape may more likely be due to the spatial dynamics of collective feedback. The results are expected to shed light on signaling pathways that could be manipulated to prevent or treat melanoma. Live cell imaging, focused laser ablation, immunohistochemistry, and time-course single cell RNA-sequencing are used to identify potential positive and negative feedback regulators that drive the mathematical models, and experiments are used to test model-based predictions concerning the roles that such molecules play. Finally, an investigation of spontaneous regression, which occurs with both mouse and human nevi, provides clues into how the immune system efficiently recognizes melanocyte overgrowth. Since immunotherapy has recently emerged as a promising therapy for melanoma, this study is expected to reveal whether immunotherapy leverages an existing immune program for eliminating nevi, and if so, how that program is carried out, and how melanomas typically escape from it. Such information should aid in developing new prevention and therapeutic strategies for this devastating disease. The integration of this work with Projects 1 and 3 occurs through the use of scRNA-seq as a tool for hypothesis generation and development and through the application of mathematical models that have similar underlying structures (cell state transitions, proliferation and quiescence, positive and negative feedback), but differ in their context (e.g., spatial in Projects 1 and 2 vs. non-spatial in Project 3).

Project 3: Modeling malignant myelopoiesis to increase efficacy of targeted leukemia therapy

PIs: Richard Van Etten

Key Personnel: Kai Kessenbrock, Natalia Komarova, John S. Lowengrub, Qing Nie, Dominik Wodarz, Xiaohui Xie, Nilamani Jena
Chronic myeloid leukemia (CML), one of the most prevalent of human leukemias, is a natural model of dysregulated granulopoiesis driven by a single genetic abnormality in a hematopoietic stem cell, the BCR-ABL1 gene fusion. Although therapy with tyrosine kinase inhibitors (TKIs) such as imatinib mesylate has dramatically lowered the death rate in CML, lifelong treatment is needed and the associated economic costs are significant. Two major unaddressed questions are to understand the mechanism of primary resistance to TKI therapy (affecting ~10-15% of newly diagnosed CML patients), and to identify strategies to increase the frequency of complete molecular remission (CMR) in patients treated with TKIs and subsequently the rate of treatment-free remission (TFR), which may represent a surrogate for permanent cure of the disease. The scientific premise of this project is that new and clinically relevant insights into the biology of CML and its response to therapy can be gained by a more physiologically accurate mathematical model of the disease.

While mathematical models of CML have been developed by several groups, these models tend to be highly simplified and largely omit feedback interactions among the different hematopoietic components. These models are designed to fit clinical data sets of the response of patient populations to TKI therapy but unfortunately, they have not proven useful for understanding primary TKI resistance or for predicting TFR. In preliminary work, we found that nonlinear models that incorporate feedback are more robust, have a better fit to alternative patterns of patient response than simple linear models used previously, and allow predictions about the effects of interventions affecting parameters (such as cell cycle status) subject to feedback mechanisms on the response to TKI therapy. Preliminary analyses from prototype feedback models have already raised two provocative hypotheses about CML. The first is that the initial response to TKI therapy may depend on the relative size of the leukemic stem cell clone, which will be analyzed by TKI treatment of mice engrafted with different levels of BCR-ABL1+ stem cells. The second is that interventions that increase leukemic stem cell cycling may sensitize this population to killing by TKIs.

In this project, Van Etten and his team seek to develop improved mathematical models of chronic phase CML and the response to TKI therapy, to validate these models using data from a binary transgenic mouse model of CML and from human CML patients, and to utilize the models to test several hypotheses about the response of CML to therapy and to predict strategies for improving the treatment-free remission rate in CML. We address these issues by 1) Developing data-driven, dynamic models of CML hematopoiesis incorporating feedback control; 2) Measuring granulocytopoiesis parameters in a CML mouse model and in human CML patients; 3) Testing model-driven hypotheses about the response of CML to therapy and informing strategies for improving the treatment-free remission rate in CML.

Figure 3. (A) Illustrative nonlinear feedback models of hematopoiesis. The red box indicates the model used in (B). (B) Increased leukemic stem cell (LSC) cycling predicts faster LSC decline on TKI therapy. The results correspond to different LSC cycling parameters applied (expressed as ratio of LSC to multipotential progenitor (MPP) cycling rate). Note the increasing negative slope of the second linear phase with increased cycling. (C,D) Selective decrement of HSC compartment increases MPP proliferation. Mice were irradiated (50 cGy), injected 24h post-radiation with BrdU and analyzed 12h later. (C) 50 cGy irradiation significantly (P=0.018) decreased the size (%LSK) of the HSC compartment (right panel) at 36h without a significant effect on the MPP compartment (left panel). (D) Reduction in HSC pool by low-dose radiation dramatically increases proliferation of the MPP compartment, supporting the existence of a negative feedback loop in the model above. (E) t-SNE analysis of scRNA-seq data from the MPP population isolated from mice with BCR-ABL1-induced CML shows eight separate subpopulations. (F) Expression of sorted lineage markers mapped on the t-SNE plot from (E). (G) Expression of GFP (marking leukemic MPP) and MPP/HSC markers mapped onto the t-SNE plot from (E).

Machine-based automated model selection methods are being utilized to arrive at a mathematical model that maintains appropriate stability and homeostasis, responds physiologically to stress and depletion of different cell compartments, and conforms to the limited existing qualitative data on CML hematopoiesis derived from mouse models and patient studies. To validate and inform potential models, binary/conditional BCR-ABL1 transgenic donor mice are being used to generate mixed BM chimeras via transplantation of high doses of unfractionated marrow cells without use of conditioning radiation. Recipients bearing a clone of BCR-ABL1+ cells have leukemia induced by withdrawal of doxycycline, leukemic mice are treated with BrdU or subjected to short-term stable isotope labeling with D2-glucose, marrow and spleen stem and progenitor compartments isolated by flow cytometry, and cell cycle and kinetic parameters estimated to inform the mathematical models. Single cell transcriptome profiling is used to investigate the heterogeneity of the MPP compartment and to discover potential regulatory mechanisms mediated by cytokine/receptor interactions. Feedback relationships are tested via direct in vivo manipulation using depleting monoclonal antibodies and through a novel mouse that targets metronidazole cytotoxicity to specific cell compartments. Parallel studies of human CML progenitor flux will be carried out through a clinical protocol of short-term D2-glucose labeling in patients presenting with suspected CML prior to diagnostic BM biopsy. The response to TKI therapy is also being analyzed. The integration of this work with

Projects 1 and 2 occurs through the use of scRNA-seq as a tool for hypothesis generation and development and through the application of nonlinear mathematical models that have similar underlying structures (cell state transitions, proliferation and quiescence, positive and negative feedback), although the models in Project 3 are non-spatial.


Single Cell Analysis Core

Core Director: Suzanne Sandmeyer
Key personnel: Kai Kessenbrock, Devon A. Lawson, Melanie Oakes, Ali Mortazavi, Jie (Jenny) Wu

This core provides technical, bioinformatic, and training support for the Center. The goal of the Single Cell Analysis Core technical support is to make cost-effective high-throughput analysis of single cells optimal for and accessible to each of the three Projects. Technical support consists of providing staff and instrument infrastructure, as well as advising on design of experimental strategies, facilitating sharing of protocols for process development; providing single-cell services including microscopy, protein localization, cell sorting, library production, and sequencing; and working with investigators to innovate in these technologies

Administrative Core

Core Director: John S. Lowengrub

Key personnel: Arthur Lander, Ed Monuki, Marian Waterman
The Administrative Core (AC) provides the administrative, communication and oversight needs for the three projects and the single cell analysis and outreach cores. The AC defines, approves and reviews membership in the Center and provides logistical support for Center members, including assisting investigators with meeting regulatory hurdles associated with research. In addition, the AC solicits, reviews and administers two types of pilot project grants: one directed at graduate students and postdocs and the other directed at faculty. The AC guides the integration of the Center into the Cancer Systems Biology Consortium by facilitating the sharing of Center resources and member expertise across the Consortium, by participating in the Annual Consortium meeting and by matching Center members with counterparts in the Consortium to foster new collaborations.

Outreach Core

Core Director: Arthur Lander
Key personnel: Ed Monuki; Sohail Jahid

The Outreach Core of the UCI cancer systems biology center promotes cancer systems biology to the research community, targeting researchers and trainees at all career stages, and disseminates advances and capabilities of cancer systems biology to the cancer research and broader communities. These goals are accomplished through a variety of activities including symposia, seminars, “short courses”, interest groups, “bootcamps”, a visiting scientist program, and an annual retreat. Included among the activities of the core are programs aimed at mentoring junior faculty, programs to provide undergraduate and pre-college students with exposure to cancer systems biology research, and activities to increase public awareness of the advances and capabilities of cancer systems biology. The core monitors its effectiveness through periodic evaluation, and coordinates and integrates with activities of the larger NCI Cancer Systems Biology consortium

Systems Analysis of Epigenomic Architecture in Cancer Progression


Center Title

Systems Analysis of Epigenomic Architecture in Cancer Progression

Center Website

Center Summary

Despite anti-hormone therapies in patients, the cognate receptors ERα and AR can remain functional to support oncogenic signaling for advanced progression of breast and prostate cancers. Intensive studies have uncovered cellular and biochemical changes underlying the development of hormone resistance. However, epigenetic mechanisms for establishing and maintaining a hormone-resistant phenotype remain to be explored. Our recent studies have found remarkably similar epigenetic machineries that regulate hormone-independent gene transcription in both breast and prostate cancers. This process has multifaceted components, involving trans- and cis-acting elements, nucleosome reorganization, and chromatin interactions. To understand this complex mechanism, the San Antonio-Duke University Research Center for Cancer Systems Biology (SA-Duke RCCSB) has assembled a team of 21 experimental and computational investigators, and oncologists who plan to study a three-tiered epigenetic framework for gene regulation.

Our U54 Research Center studies a three-tiered epigenetic framework of ER and AR-mediated gene transcription in cancer.

First, microenvironmental cues initiate the recruitment of a specific combination of trans-bound transcription factors (TFs), called MegaTrans TFs, to ERα or AR-bound enhancers (Project 1). MegaTrans TFs are composed of diverse signaling-dependent transcription factors that activate these enhancers through receiving other signal cues without hormone stimulation. Second, this hormone-independent action requires well-orchestrated repositioning of nucleosomes, enabling maximal MegaTrans-DNA contact in target chromatin regions (Project 2). Pioneer factor FOXA1 and chromatin remodelers are also critical regulators of repositioned nucleosomes during the transition of a hormone-sensitive to -resistant phenotype. Third, this concerted action triggers chromatin movement, remotely bringing the MegaTrans/enhancer complexes in close proximity to target promoters (Project 3). Intra- and inter-chromatin interactions facilitate the formation of transcriptional architectures that efficiently and autonomously regulate ERα/AR-mediated gene expression even in the absence of agonists or in the presence of antagonists. Experimental investigators plan to use omics-seq platforms to map combinatorial MegaTrans complexes, repositioned nucleosomes, and topologically associated domains (TADs) that spatiotemporally regulate hormone-independent transcription. Computational scientists then use omics data to derive 3D models of DNA-eRNA-protein interacting units in subnuclear compartments of cancer cells. Back to the bench, experimental scientists will use in silico findings to validate enhancer/gene markers that predict a hormone-resistant phenotype in patient-derived xenografts (PDXs) and clinical samples. To ensure seamless data integration of the three projects, a Data Analysis and Management Core will implement customized toolkits to manage computational infrastructure and store omics-seq metadata for heuristic queries by community systems biologists. An Outreach Core will facilitate training of new-generation systems biologists and enhance collaborative efforts within the NCI’s consortium and in the 4D nucleome community. An Administrative Core will provide governance and oversee rigorous evaluations of Intra-center Pilot Projects (IPPs), ensure cross-pollination between bench and in silico scientists in the SA-Duke RCCSB, and reinforce national guidelines of data sharing.


Principal Investigators

Tim Huang, Ph.D.

Tim Huang, Ph.D., is Professor and Chair in the Department of Molecular Medicine at the University of Texas Health Science Center – San Antonio (UTHSCSA) and Deputy Director of the NCI-designated Cancer Therapy and Research Center. He is also the holder of Alice P. McDermott Distinguished University Chair. He has been conducting studies on cancer epigenetics for the last 25 years and has pioneered the development of microarray technologies for the detection of promoter DNA methylation in solid tumors. Dr. Huang serves as the Contact Principal Investigator (PI) of our Center. Dr. Huang oversees all aspects of the center’s activities. He has been conducting studies on cancer epigenetics for the last 27 years. The projects of the CSBC are focused on dissecting the roles of three layers of epigenomic architectures in cancer progression specifically focusing on prostate and breast cancers. The goals of the studies to enhance our understanding of genomic regulations in cancer cells that will lead improved individualized therapies that combat drug resistance.

Victor Jin, Ph.D.

Victor Jin, Ph.D., is an Associate Professor in the Department of Molecular Medicine at UTHSCSA. He also has a joint appointment in the Department of Epidemiology and Biostatistics. Dr. Jin has more than 15 years of experience in developing statistical methods, machine learning algorithms, and software tools for analyzing omics-seq data, including those derived from ChIP-exo, ChIP-seq, MBDCap-seq, Hi-C, RNA-seq and miRNA-seq. Dr. Jin serves as a PI along with Drs. Tim Huang and Qianben Wang in our Center, oversees all aspects of computation modeling and data management and facilitates intra- and inter-center communication between computational and experimental scientists. In particular, he and Dr. Huang co-leads Project 3 about three-dimensional transcriptional regulation as well as leads computational modeling in nucleosome regulation in cancer progression. He is also responsible for managing the core of data analyses and management.

Qianben Wang, Ph.D.

Qianben Wang, Ph.D., is a Professor in the Department of Pathology at Duke University School of Medicine. Dr. Wang’s research focuses on studying multi-layer transcription regulatory networks of nuclear receptors (e.g., androgen receptor and glucocorticoid receptor), pioneer transcription factors (e.g., FOXA1), transcription coactivators (e.g., Mediator and histone acetyltransferases), and epigenetic regulators (e.g., histone modifications and chromatin looping) in hormone-related cancers. Dr. Wang has made high impact contributions to this field, particularly in understanding genome-wide transcriptional regulation by nuclear receptors. Dr. Wang serves as a PI to provide oversight for Project 2 tasks and outreach and administrative activities performed at Duke. Dr. Wang is also Experimental Leader of Project 2.

Project Leaders and Co-Investigators

Zhijie (Jason) Liu, Ph.D.

Zhijie (Jason) Liu, Ph.D., is an Assistant Professor in the Department of Molecular Medicine at UTHSCSA. Dr. Liu is the experimental Project Leader in Project 1. He studies the changes of DNA regulatory elements that are controlled by sex hormones in either breast or prostate cancer as a molecular biologist. Dr. Liu is an expert on various genomics high throughput assays, and he will use these cutting-edge technologies to characterize the dynamic assembly of enhancer activation machinery during cancer hormone resistance progression.

Jianhua Ruan, Ph.D.

Jianhua Ruan, Ph.D., is an Associate Professor in the Department of Computer Science at The University of Texas at San Antonio. Dr. Ruan will work closely with Dr. Zhijie (Jason) Liu on computational modeling of mega genomic assemblies composed of regulatory proteins and DNA and function during cancer progression. He will build efficient and effective computational tools to analyze and model the vast amount of data generated in this project; with these tools, Drs. Ruan and Liu plan to characterize and compare regulatory networks between hormone-resistant and hormone-sensitive cancers, and develop machine learning algorithms that can utilize the derived network features to predict patient response to endocrine therapies.

Chun-Liang Chen, Ph.D

Chun-Liang Chen, Ph.D., is an Assistant Professor in the Department of Molecular Medicine at UTHSCSA. Dr. Chen is involved in developing methods for isolation and ex vivo expansion of circulating tumor cells (CTCs) for single-cell epigenome analysis. During metastasis that leads to cancer fatality, tumor cells are shed into blood stream and colonized in distant organs. The expanded CTCs open an important window to understanding the metastatic epigenetic mechanism of cancer and facilitate high throughput drug susceptibility screening for precision personalized medicine.

Wei Li, Ph.D.

Wei Li, Ph.D., is a Professor in the Department of Molecular and Cellular Biology at Baylor College of Medicine. Dr. Li is a computational Project 2 Leader and develops a computational model to determine AR/ERα or FOXA1-mediated nucleosome positioning and spacing, and be responsible for interactions with other investigators in the U54 project. He has collaborated with Dr. Wang since 2005 and they have published many collaborative papers in high impact journals.

Seth Frietze, Ph.D.

Seth Frietze, Ph.D., is an Assistant Professor in the Department of Medical Laboratory and Radiation Sciences at University of Vermont. Dr. Frietze is a Co-Investigator in Project 3. He has been collaborating with Dr. Victor Jin for more than eight years, and both investigators have joint publication is genomics studies. Specifically, he works with Dr. Jin’s team member, Dr. Yufan Zhou to set up TCC and ChIP-seq protocols for the experiments.

Nameer Kirma, Ph.D

Nameer Kirma, Ph.D., is an Associate Professor in the Department of Molecular Medicine at UTHSCSA. Dr. Kirma leads the outreach core of the U54 Center at the San Antonio site. The goals of the core are to enhance the awareness and knowledge of cancer systems biology, recruit next-generation trainees interested in genomics studies, and expand the scope of early-stage and established investigators to engage in whole-genome scale studies as part of their research portfolio. This includes seminar series, annual symposia, workshops and summer research programs that provide didactic and practical training of novel technologies and advances in genomic interactions in cancer.

Pearlly Yan, Ph.D.

Pearlly Yan, Ph.D., is a Research Assistant Professor in the Department of Internal Medicine at the OSU. Dr. Yan is a Co-Leader in the outreach core, and leads the outreach effort in the OSU site. Dr. Yan has worked closely with Dr. Huang (Contact-PI) and Dr. Wang (PI at OSU) in research projects, publications and trainee mentoring.

Virginia Kaklamani, M.D

Virginia Kaklamani, M.D., is a Professor of Medicine in the Division of Hematology/Oncology at UTHSCSA. Dr. Kaklamani is a leader of the Breast Cancer Program.

Michael Liss, M.D.

Michael Liss, M.D., is an Assistant Professor in the Department of Urology at UTHSCSA. Drs. Kaklamani and Liss are Co-Investigators in Projects 1 and 3. As clinical investigators, both will closely work with the basic scientists within the Center and provide a resource of cancer patient samples for the targets validations and for facilitating the translational studies.

Steven K. Clinton, M.D.

Steven K. Clinton, M.D., Ph.D., is a Professor in the Department of Internal Medicine at OSU. Dr. Clinton is a Co-Investigator in Project 2. He is responsible for the human tissue procurement, processing, storage, allocating to investigators, and parallel evaluation of tissue by immunohistochemical and histopathologic evaluation, including digital image analysis as appropriate. Dr. Clinton has collaborated with Dr. Wang since 2008.

Jiaoti Huang, M.D., Ph.D.

Jiaoti Huang, M.D., Ph.D., is Professor and Chairman of Department of Pathology at Duke University School of Medicine. Dr. Huang is a Co-Investigator in Project 2 and provides pathological support for PDX samples and patient samples. Dr. Huang has collaborated with Dr. Wang since 2012.


Project 1: High-order assembly of MegaTrans complexes for hormone-independent enhancer activation

Cis- and trans-binding transcription factors

Endocrine therapy is commonly used in hormone-driven breast and prostate cancers. A persistent challenge is disease progression caused by hormone resistance during the treatment. Studies for the past 25 years have revealed an essential role of hormones (i.e., estrogen and androgen) and their receptors, ERα and AR, in cancer progression. Increased evidence indicates that epigenetic deregulation of ERα/AR-bound enhancers profoundly alters hormone-mediated transcription machineries, leading to the development of hormone resistance. However, the molecular mechanisms underlying this hormone-resistance transition of enhancer function are largely unknown. We have recently discovered that the most active and functionally important ERα-bound enhancers can recruit a large number of DNA-binding transcription factors through protein-protein interactions. These newly identified ERα ‘co-activators’, termed MegaTrans transcription factors (TFs), are required to activate ERα-bound enhancers and also serve as a signature of functional enhancers. Our preliminary data additionally show the presence of MegaTrans TFs in AR-bound enhancers. Because most MegaTrans TFs are signaling-dependent molecules, they may receive other signals from tumor microenvironments to alter enhancer functions. Thus, combinatorial interactions between ERα/AR and MegaTrans TFs make their enhancers respond not only to estrogen or androgen, but also to other microenvironmental signals. The composition and interaction of MegaTrans TFs undergo dynamic changes during cancer progression, resulting in alterations of ERα/AR enhancer functions that promote hormone-resistance in breast and prostate cancer cells.

Project 2: Fine-scale nucleosome repositioning of enhancers for hormone-independent genomic function

Pre-existing nucleosome phasing (N2) promotes androgen-independent AR transcription in cancer cells treated with antagonist ENZ, compared to those stimulated with agonist DHT

The cognate receptors AR and ERα can remain active for tumor progression after anti-hormone treatment for patients with prostate and breast cancers. Despite intensive efforts to elucidate the underlying mechanisms, little information is available concerning AR/ERα genomic function for promoting hormone resistance at the nucleosome level. In recent studies, we observed this genomic function is well orchestrated, relying on precise nucleosome organization within cis-bound enhancers for hormone-dependent transcription. Interestingly, we also found that this epigenetic mechanism can be hijacked by hormone-resistant cells to gain their growth and invasion advantages. Therefore, we hypothesize that altered nucleosome positions, or nucleosome repositioning, in and near AR/ERα-bound enhancers is being exploited for hormone-independent genomic function in advanced cancers. In Aim 1, we will conduct ChIP-ePENS and MNase-seq to comprehensively map nucleosome boundaries of AR/ERα-bound enhancers in a panel of hormone-sensitive and -resistant cancer cells. RNA-seq will be conducted to determine differential expression patterns of corresponding genes in these cell lines. The NucPat computational pipeline will be deployed to seamlessly process complex omics-seq data (Aim 2). We will use a Kernel Density Estimation algorithm to determine nucleosome positioning and spacing when AR or ERα establishes direct contact with its binding motif. Using a Hidden Markov model, we will identify active nucleosome states that maximize DNA-protein contact for AR/ERα genomic functions. In addition, pioneer factor FOXA1 and chromatin remodelers participate in this nucleosome repositioning even in the absence of agonists or in the presence of antagonists. To confirm this computational modeling in vivo, ChIP-ePENS and MNase-seq will be conducted in patient-derived xenograft (PDX) lines carrying hormone-sensitive and -resistant tumors (Aim 3). A nucleosome-phasing index (NPI) will be established to quantitatively assess the nucleosome states of AR/ERα redeployment in different PDX lines. This integrative omics analysis will be extended to a cohort of primary tumors, categorized into high- and low-risk groups. Again, we will calculate individual NPIs and correlate the data with clinicopathological features of patients. This translational study is intended to determine whether nucleosome phasing for AR/ERα redeployment is already present in high-risk primary tumors. Patients with this intrinsic phenotype are expected to have an adverse clinical outcome, irrespective of their anti-hormone treatments. Therefore, our study will address a previously uncharacterized mechanism of hormone resistance and provide experimental evidence that nucleosome repositioning plays an integral role in redefining AR/ERα genomic function for advanced development of prostate and breast cancers.

Project 3: Topological mapping of chromatin architectures for hormone-independent gene transcription

ERα-mediated transcription of a TAD located on 17q23 in breast cancer cells

Long-range chromatin interactions between ERα/AR-bound enhancers and promoters are necessary for coordinated gene regulation in breast and prostate cancer cells. These interactions occur via the formation of 3D chromatin architecture that brings enhancers and transcription factor complexes into close contact with target genes. To decode this complex regulation, we and other investigators have previously used Hi-C to map topologically associated domains (TADs) in different cell types. In a further study, we have identified a cancer-specific TAD on chromosome 17q23 that can be partitioned into an ERα-regulated transcription hub. Concordant up-regulation of its target genes is found to be associated with short disease-free survival in a subgroup of ERα-positive breast cancer patients, irrespective of their anti-hormone treatments. Emerging evidence has also shown AR-specific TADs are present in the prostate cancer cell genome. Therefore, we hypothesize that 1) frequent hormone (i.e., estrogen or androgen) stimulation leads to the formation of ERα/AR-related TADs that dynamically regulate transcription of multiple genes for aberrant proliferation of breast and prostate cancer cells and 2) in the presence of antagonists, a subset of these chromatin domains, herein termed transition TADs, continue to be exploited through chromatin redeployment for hormone-independent transcription. Whereas the majority of ERα/AR-related TADs are functionally suppressed by antagonists, transition TADs may partially escape this blockade for constitutive regulation of gene transcription. To test these hypotheses, we will use a modified Hi-C method, called tethered conformation capture (TCC), to investigate dynamic changes of TAD structures in hormone-sensitive and -resistant cancer cell lines exposed to agonists or antagonists (Aim 1). ChIP-seq of repressive, active, and gene-body histone marks and CTCF insulator will also be conducted in this cell line panel. MNase-seq and MBDCap-seq datasets will be acquired to map euchromatinized and heterochromatinized TADs. To integrate omics-seq data, we will develop a computational model, PRAM3D, which applies a Poisson Random effect Architecture Model (PRAM) to recapitulate 3D chromatin architectures (Aim 2). A Bayesian hierarchical model will predict putative transition TADs that concordantly regulate hormone-independent transcription of target genes. Furthermore, we will use a nucleosome density method to classify transition TAD subdomains into different regulatory categories, i.e., active, repressive, or bivalent transcription hubs. CRISPR/Cas9 genome-editing of critical chromatin regions may functionally disassemble spatiotemporal organization of these TAD-associated hubs (Aim 3). Proliferation and invasion/migration assays will determine whether this genome editing partially re-sensitizes cancer cells to anti-hormone treatments. We will also interrogate mechanistic contribution of histone modifications and other epigenetic modulators for the establishment of transition TAD structures. In silico expression profiling and single-cell RNA seq will be conducted in primary tumors of TCGA cohorts and in cancer cell subpopulations, respectively, and determine whether concordant regulation of TAD-associated target genes is intrinsic predictors of hormone resistance in breast or prostate cancer.


Data Analysis and Management Core

A huge amount of high-throughput sequencing data is expected to be generated from TCC, ChIP-ePENS, BirA-BLRP-seq, ChIP-seq, MBDCap-seq, CLIP-seq, GRO-seq, and population-cell or single-cell RNA-seq assays and proteomic analysis in the three projects of the SA-OSU Research Center for Cancer Systems Biology (SA-OSU RCCSB). Thus, it is critical to establishing a central data process hub in order to meet the scientific missions and goals of our center. The Data Analysis and Management Core (DAMC) will ensure a unified approach to data analysis and management for all three projects, including the following tasks: 1) implementing and maintaining new software tools for computational models developed in the three projects and intra-center pilot projects; 2) designing and supporting the data analysis flow using existing public or our own software tools; 3) managing data submission to public archives, maintaining data repository and exploring data visualization; and 4) coordinating with the Data Coordination Center (DCC) within the Research Centers for Cancer Systems Biology (RCCSB) Consortium. To accomplish these tasks, the DAMC will leverage existing infrastructure and computational expertise at University of Texas at San Antonio of both Health Science Center (UTHSCSA) and Academics (UTSA), the Ohio State University, and Baylor College of Medicine. We will establish a leadership team to develop and coordinate ongoing support of cancer omics research and to communicate monthly with the Executive Committee in the Administrative Core. Members of the DAMC leadership team include the leader of the DAMC and senior investigators of the three projects – Drs. Jin (Chair), Ruan, Weintraub, and Li who have extensive experience in large-scale data management, computational, statistical, genomic and proteomic analyses, and coordination of data analytic efforts within multi-project centers. Members of the DAMC will also be involved in all phases of project planning, from design to execution, to ensure that the flow of data from projects to the relevant cores and is well-coordinated.

Outreach Core

The goals of the Core are to enhance the awareness and knowledge of cancer systems biology, recruit next- generation trainees interested in epigenomics, and expand the scope of early-stage and established investigators to engage in omics analysis as part of their research portfolio. Two experienced Core leaders, Dr. Nameer Kirma (UTHSCSA) and Dr. Pearlly Yan (OSU), will coordinate outreach/training activities within the two center sites. In Aim 1, knowledge of advances in cancer systems biology will be disseminated through seminar series and annual symposium. Workshops will provide practical training of novel omics technologies. To maximize exposure and capitalize on our existing expertise, these symposia and workshops will be held every year alternating between the two center sites. In Aim 2, we plan to train new scientists and retool established investigators in systems epigenomics. Postdoctoral fellows and early-stage investigators will have the opportunity to participate in cross-pollination training beyond their current expertise, facilitating a more rounded understanding of systems biology. Early-stage and established investigators will have the opportunity to re-sharpen their research skills in omics analyses through the three projects in our center and the release of annual RFA for supporting two Intra-center Pilot Projects (IPPs). In addition, the Core will organize summer programs for at least six undergraduate students and visiting scientists who will have the opportunity to engage in short-term research projects using omics approaches. Given that both sites have access to a great pool of minority and underserved students in South Texas and Appalachia, we will encourage them to apply for these programs. In Aim 3, we plan to interact with investigators in the RCCSB Consortium and other genomics communities. Working with the leaders of our Administrative Core, we will send a delegation consisting of 10 senior and early-stage investigators and IPP awardees to participate in the annual RCCSB Consortium Steering Committee meeting. Through platform and poster presentations and face-to-face meetings, our investigators will find opportunities and niches for collaboration and data sharing with scientists in the Consortium. Furthermore, we will make contact with members of the NIH-funded 4D nucleome programs and other genomics forums, such as the Cold Spring Harbor Nuclear Organization and Function Symposium, to share our epigenomic findings. To disseminate knowledge on epigenomic advances, we will work with the staff in the Data Analysis and Management Core to set up searchable databases. Ongoing and to-be-developed toolkits will be made available to researchers through our website portal. Collectively, these integrative efforts are expected to nurture next-generation trainees in the area of systems biology and to foster a collaborative spirit with investigators in the RCCSB Consortium and other genomics communities.

Systems Analysis of Phenotypic Switch in Control of Cancer Invasion


Center Title

Systems Analysis of Phenotypic Switch in Control of Cancer Invasion

Center Website

Center Summary

Aerial view of Yale’s West Campus, which is where the Yale Systems Biology and Yale Cancer Institutes are located.

Over 90% of cancer related mortality is linked to invasive and metastatic spread of cancer cells from the primary tumor. In spite of the crucial importance of invasive cancer phenotype, we still have only fragmentary knowledge and understanding of the mechanisms leading to transition from proliferative to aggressive, migratory behavior of cancer cells, which we refer to as Proliferative-to-Aggressive phenotype switching. Increasing evidence suggests that this switch is a reflection of the inherent capacity of cancer cells to adopt both proliferative and migratory phenotypes, with the probability and rate of switching between these two phenotypes controlled by the cell genome, environmental conditions, and cell-cell interactions. The Cancer Systems Biology at Yale ([email protected]) will address the problem of regulation of invasive cancer spread and, more specifically, the Proliferative-to-Aggressive phenotypic switch. A combination of diverse expertise and innovative methods, ranging from synthetic biology, micro- and nano-fabrication technology, evolutionary biology, and mathematical analysis of intracellular molecular networks to the creation of novel CRISPR-based animal models and the design of novel kinase inhibitors that can lay the basis for novel therapeutic compounds will be used.

The Yale Systems Biology Institute features open laboratories (depicted here), dedicated support rooms, shared equipment rooms, and interactive office and community space.

[email protected] brings together researchers from seven Yale departments based at Yale schools of Arts and Sciences, Engineering and Applied Science, and Medicine and at Emory University, in close collaboration with Yale Cancer Institute, Yale Cancer Center, Yale skin cancer SPORE, and Yale Neurosurgery department. The work at [email protected] will be initially based on the tightly knit two Research Projects and two support shared resource Cores, first focused on the analysis of glioblastoma and melanoma cells, and normal cells of various species modeling invasive growth behavior and phenotypic switching. The work will be supported by the Administrative Core and the results disseminated through various mechanisms mediated by the Outreach and Education Core. The orthogonal and unconventional approaches, characteristic of the highly collaborative use of cutting edge, innovative approaches, will provide an opportunity to advance our understanding of the molecular networks controlling invasive, aggressive cancer spread and lead to new approaches to controlling and treating highly invasive and metastatic malignancies.


Andre Levchenko, Ph.D.

Dr. Andre Levchenko is the Principal Investigator of [email protected] He is John C. Malone Professor of Biomedical Engineering at Yale and is also the Founding Director of Yale Systems Biology Institute (YSBI), whose major unifying activity will be centered on this Project. Dr. Levchenko has been the director of YSBI since Fall 2013, guiding it through a 2-fold expansion, consolidation in a new space, and establishment of vigorous research experience on a new campus. Dr. Levchenko is a systems biologist, bio-engineer, and biophysicist who has been among the active developers of Systems Biology as a discipline since its most recent emergence, and has made considerable impact on the integrative computational/experimental analysis of cellular signaling and cell-cell communication. His more recent efforts are in development of novel micro- and nano-fabricated devices for enhanced control of cellular micro-environments. His work on understanding of the innate immune response and mechanisms of cell migration has received wide acclaim (with the latter leading to his election as a Fellow of the American Physical Society earlier this year). His current focus is on understanding of the mechanisms of aggressive cell migration in diverse settings and in response to different cues. This research emphasis created the platform for unifying the efforts of multiple Yale researchers.

Mark Lemmon, Ph.D.

Dr. Mark Lemmon is a cellular and molecular biologist and pharmacologist, is Co-Director of the Yale Cancer Biology Institute, and David A. Sackler Professor of Pharmacology. The Lemmon laboratory has made significant contributions to understanding molecular mechanisms of cellular signaling by growth factor receptor tyrosine kinases – notably the EGF receptor – and through lipid second messengers, notably the phosphoinositides and other anionic lipids that bind pleckstrin homology (PH), FYVE, KA1, and other domains. The Lemmon lab made highly significant and high impact contributions to the structural understanding of both of these phenomena, and to understanding these signaling axes from structural/mechanistic perspectives – combining cellular, biochemical, structural, and (increasingly) organismal studies. Recently, a key goal of the laboratory has been to understand how mutational alterations of receptor tyrosine kinases, in particular the therapeutic targets EGFR and ALK, lead to aberrant signaling and cancer – and how this information can be used to impact clinical approaches (through direct collaboration with clinicians). The goal is to bring more biochemistry to personalized medicine in oncology. Another key aim of work of the Lemmon laboratory is to understand signaling systems and networks more broadly by studying the signaling consequences of molecular perturbations that are well defined (through the lab’s in vitro and structural work). This has been applied to studies of the role of the EGF receptor in Drosophila development, and is now being pursued in several cancer cell contexts.

Günter Wagner, Ph.D.

Dr. Günter Wagner is an evolutionary biologist studying the evolution of the mammalian female reproductive tract, and other aspects of the evolution of development. He is Alison Richard Professor of Ecology and Evolutionary Biology and a core faculty member in the Yale Systems Biology Institute. His laboratory focuses on the evolution of gene regulation and the evolutionary origin of the uterine decidual cell, a cell type critical for the implantation of the fetus and the maintenance of pregnancy. One of the main functions of the decidual cell is to regulate the invasion of the fetal trophoblast and thus the regulation of invasive behavior. Last year Dr. Wagner, together with a student Alaric D’Souza, published a paper that documented a correlation between the (secondary) evolution of non-invasive placentation and a lower rate of malignancy in certain forms of cancer. This observation motivates his participation [email protected], where he will investigate the mechanisms by which endometrial stromal cells oppose the invasion of the fetus and how, in bovines and related species, this may also have conveyed resistance to melanoma malignancy.

Murat Acar, Ph.D.

Dr. Murat Acar is an Assistant Professor in Molecular, Cellular and Developmental Biology and in Physics, and is a core faculty member of the Yale Systems Biology Institute. He is a systems biologist who combines experimental and computational tools in his research by using the budding yeast as a model organism. Trained as a physicist, Dr. Acar is interested in understanding and solving the complexity in the organization of natural gene networks by using a reductionist approach. Since even the most complex gene networks can be broken down to modular pieces operating as locally-embedded network motifs in the larger gene networks, Dr. Acar’s research aims to characterize the function and evolution of these frequently-occurring modular network motifs. He has many years of hands-on experience in yeast genetics, cell biology, and computational modeling. Dr. Acar will lead the research efforts aiming at characterizing the evolution of phenotypic switching rates in the yeast galactose network during cellular adaptation to fluctuating environments.

Jesse Rinehart, Ph.D.

Dr. Jesse Rinehart is an Assistant Professor in the Department of Cellular & Molecular Physiology at the Yale University School of Medicine and also a core faculty member in the Yale Systems Biology Institute. He is a physiologist and proteomics expert. Dr. Rinehart studied protein synthesis and the evolution of the genetic code during his graduate work and completed his postdoctoral training focused on protein phosphorylation in physiological systems. Dr. Rinehart’s research aims to understand and “decode” complex signaling networks in physiological systems. Researchers in the Rinehart laboratory use an innovative combination of quantitative phosphoproteomics and synthetic biology to achieve their aims. They are now applying this technology to understand the properties of phosphoserine in human kinases and singling networks. Dr. Rinehart’s team will deploy these enabling technologies to advance our understanding of how kinases control aggressive cancers and specifically to identify small molecule kinase inhibitors to target human cancers.

Farren Isaacs, Ph.D.

Dr. Isaacs is an Associate Professor in the Department of Molecular, Cellular and Developmental Biology and a core faculty member in the Systems Biology Institute at Yale. He is a synthetic biologist focused on developing foundational genomic and cellular engineering technologies to understand and engineer biological systems. His lab integrates engineering and evolution through the construction of genes, networks and genomes alongside quantitative models to gain a better understanding of biological systems. In turn, they utilize these insights to program and evolve organisms with new biological function. A particular emphasis is the development of genome engineering technologies to construct ‘Genomically Recoded Organisms’ that possess an alternate genetic code. In the context of [email protected], re-coded organisms improve properties for incorporating nonstandard amino acids into proteins, including the site-specific incorporation of phosphoserine to activate human kinases in engineered bacteria. Dr. Isaacs’ work focuses on incorporating phosphorylated amino acids to enable the production of active kinases implicated in the tumorigenesis of glioblastomas. These efforts will be extended in three key areas: (1) to recapitulate phosphorylation-based mammalian signaling in recoded bacteria, (2) to elucidate biomolecular interactions of kinase functions, and (3) will be leveraged to identify novel inhibitors of kinase activity.

Michael Murrell, Ph.D.

Dr. Michael Murrell, an Assistant Professor in the Department of Biomedical Engineering and a core faculty member in the Systems Biology Institute at Yale, is a biophysicist whose primary expertise is in mechanical force production in cell biology. His laboratory develops approaches to understanding mechanical force generation by two distinct but complementary approaches. First, he measures the mechanical stresses produced by living cells subject to genetic and pharmacological perturbation. In doing so, he identifies how the dynamics and composition of the cell cytoskeleton and cell membrane influence the generation and transmission of mechanical stresses to the extracellular matrix. In parallel, he designs and engineers artificial cells in vitro, using purified proteins and lipids to reconstruct the cell cytoskeleton and membrane, for the goal of reproducing force production in a simplified system. As there are few components, and no biochemical regulation, this allows him to isolate the role of individual components, whose abundance and activity can be easily manipulated. To this end, Dr. Murrell has developed precise control of physical variables that can influence the generation and transmission of mechanical stresses, including cell volume, F-actin organization, membrane tension, fluid pressure and adhesion. From this, his lab learns basic physical principles regarding how cells produce mechanical force, which may otherwise be obfuscated by the overlapping biochemical and genetic regulation that exits in living cells. Thus, their simplified systems can inform us as to the basic physical relationships that underlie mechanical force production in cells, as well as provide potential targets for genetic and pharmacological perturbations. Dr. Murrell will seek to identify the role of NKCC1 in mediating mechanical force production in invasive glioblastoma and melanoma cells, by exploring its role in coupling to the cytoskeleton, as well as modulating fluid flow, hydrostatic pressure, and the volume of the cell.

Rong Fan, Ph.D.

Dr. Rong Fan is an Associate Professor of Biomedical Engineering and a microfabrication and microfluidics expert at Yale University. He was trained as an analytical and materials chemist before becoming a trainee of the NCI-founded Nano Systems Biology Cancer Center at Caltech, where he developed a high-density antibody barcode chip for multiplexed protein biomarker detection in microliters of blood or even single cells. His research interest is focused on the development of microfluidic systems and bioMEMS technology for multiparameter analysis of single cells and cell-cell paracrine signaling. His laboratory developed a high-throughput microchip technology for single cell, 42-plex cytokine profiling that was utilized to quantify the deep functional heterogeneity in human immune cells in response to pathogenic stimulation and in hematologic cancer cells. It was also used to quantify paracrine communication between cancer and immune cells. His laboratory is also working on the development of other microfluidic devices for single-cell functional genomics analysis tools (e.g., methylomics, transcriptomics, etc). He is the recipient of the Howard Temin Pathway to Independence award (K99/R00) from the National Cancer Institute, the NSF Early Stage Faculty Career Development (CAREER) Award and the Packard Fellowship for Science and Engineering. In this project, Dr. Fan provides support in microdevice design and single-cell proteomic assay for investigating cell-cell interaction and offers training in microfluidics techniques to researchers in the Center and local community for outreach activities.

Sidi Chen, Ph.D.

Dr. Sidi Chen is a geneticist, who is an Assistant Professor of Genetics and a core faculty member of the Systems Biology at Yale. His current research focuses on cancer systems biology, in particular in vivo CRISPR/Cas9-mediated cancer modeling and genetic screening. He has led studies on the essential function of new genes in animal development and tumorigenesis, microRNA regulation of tumor hypoxia and angiogenesis, in vivo modeling of lung cancer and liver cancer using gene editing, and genome-wide screens for metastasis regulators. Dr. Chen will lead the studies aimed at validation of the role of molecular components predicted by Research Projects to play key roles in promoting or suppressing invasive cancer spread.

Lynne Regan, Ph.D.

Dr. Lynne Regan is a biophysicist and biochemist. She is Professor of Molecular Biophysics and Biochemistry and of Chemistry and is an active member of the Yale Cancer Center. Her research investigates novel strategies by which to inhibit Hsp90 as a route to a new class of anti-cancer agents. She is also studying the multifaceted roles of heat shock factor-1 (HSF1), the mechanisms of HSF1 activation, and the role of HSF1 in cancer. She is Director of the Raymond and Beverley Sackler Institute for Biological, Physical and Engineering Sciences (RBSI), Director of the Integrated Graduate Program in Physical and Engineering Biology (IGPPEB) and co-Director of the NSF REU Site: Convergence of Research at the Interface of the Biological, Physical, and Engineering Sciences. The IGPPEB brings students with backgrounds in the physical and biological sciences into educational and research programs that apply quantitative physical approaches to key questions in biology. Students entering through the IGPPEB program will be well prepared to perform research in any [email protected] laboratory. The RBSI supports multiple activities, for researchers at all levels, to enhance interdisciplinary research at Yale. Institute activities and events are synergistic with [email protected] plans and Dr. Regan’s involvement with both will enhance this connection. The NSF-REU site that Regan co-directs has proven to be an effective route by which to encourage undergraduates from under-represented and disadvantaged groups to embark upon STEM careers. 75% of students who have participated are now enrolled in Ph.D. or M.D./Ph.D. programs.

Adam Marcus, Ph.D.

Dr. Adam Marcus, an Associate Professor of Hematology and Medical Oncology at Emory University School of Medicine, is a cancer biologist who focuses on understanding how cancer cells invade using a combination of molecular and imaging-based approaches. He has numerous publications studying the mechanisms of cancer cell invasion and metastasis that incorporates clinical and pre-clinical studies. His laboratory has developed a new image-guided genomics approach to dissect tumor cell heterogeneity in the context of cancer cell invasion. This work has revealed a symbiotic mechanism for cancer cell invasion and has led to generation of novel cell lines to probe the biology of cell:cell communication. This work will be used to generate a portion of the data related [email protected] research. Dr. Marcus serves as the Director of the Emory Integrated Cellular Imaging Core, which houses 17 microscopes throughout Emory’s campus and is part of the NCI-Designated Winship Cancer Institute. Dr. Marcus also serves as the Director of Graduate Studies for the Cancer Biology Ph.D. program at Emory, and founded the K-12 STEM outreach organization Students for Science. Dr. Marcus will enable the development and use of the SAGA methodology to explore the homotypic cell-cell communication.

Kshitiz Gupta, Ph.D.

Dr. Kshitiz Gupta is a bioengineer who is an Associate Research Scientist in the Department of Biomedical Engineering at Yale University. Dr. Gupta has broad expertise in mechanobiology, and studying intercellular communication. He has a B.Tech. in Computer Science and a Ph.D. in Biomedical Engineering, and served as the founder and Chief Scientific Officer of CardiacMimetics, a startup company based on detecting cardiotoxic drugs during drug development. Dr. Gupta is developing techniques to study cell-cell interactions, including platforms to measure collective cell invasion, and cellular intercommunication.

Anatoly Kiyatkin, Ph.D.

Dr. Anatoly Kiyatkin is a Research Scientist in the Department of Pharmacology and Cancer Biology Institute at the Yale University School of Medicine. He is a systems biologist working in the Lemmon lab on the projects that are focused on the analysis of the dynamics of receptor tyrosine kinase-mediated cell signaling networks with a goal to understand design principles of regulatory network structures that are crucial for network function and cell fate decisions. To reconstruct signaling routes from receptors at the plasma membrane to the activation of MAPK and immediate early genes he uses systematic perturbations and measures activation patterns of signaling proteins. This analysis will help to determine network vulnerabilities in cancerous cells and target them with molecular therapeutics.

Maria Apostolidi, Ph.D.

Dr. Apostolidi is a postdoctoral fellows in the Rinehart lab. Her project will aim to decode the molecular mechanisms of a novel class of kinases thought to control the migration of aggressive cancer cells. She will utilize novel synthetic biology platform technologies developed in the Yale Center to develop new therapeutic strategies designed to arrest cancer cell migration. Dr. Apostolidi trained with Prof. Constantinos Stathopoulos at the University of Patras School of Medicine in the Department of Biochemistry. Her PhD studies focused on the role of aminoacyl-tRNA synthesis in the regulation of ribosomal and exo-ribosomal protein synthesis in pathogens.


Project 1: Analysis of Cell Autonomous Mechanisms of Phenotypic Plasticity in Invasive Cell Spread

The use of nano-fabricated patterns to mimic in vivo migration of glioblastoma and melanoma cells. Cell shapes and migration patterns on the “tissue-mimetic surfaces” is similar to that found in vivo and inside collagen/laminin gels for patient derived tumor cells (GBM612; MRI of tumor shown). This surface allows faster cells to separate from slower, more proliferative ones, in the process of directed cell migration (see RACE, Project 1). The cell population can be modified, for example by initial transfection with an shRNA library, such that sequential RACE assays can be performed to observe gradual enrichment of specific shRNAs in faster vs. slower cells, which can then be further analyzed biochemically.

The goal of this project is to obtain a better quantitative understanding of the complex regulation and characteristic of the invasive phenotypic state. The analysis in the project is aimed at the cell autonomous view of regulation, without explicit emphasis of cell-cell interactions. We will combine a variety of tools and approaches, including combining experimentation and mathematical modeling.

We are able to separate slow moving, proliferative cells from fast moving, migratory cells (and enrich each phenotype) using a “phenotypic filter” through an assay called Rapid Analysis of Cell migration Enhancement (RACE). This assay employs nano-fabricated surfaces that result in rapid and highly oriented cell migration. Preliminary results using RACE not only suggest that the assay can help identify molecular mechanisms of the Proliferative-to-Aggressive phenotypic switch but have also led us to develop a preliminary mathematical model describing how specific kinases, thought to be activated by the same growth factors, can be differentially active in different cell sub-populations. In addition, using synthetic biology techniques, we have created a new platform for generating novel kinase inhibitors that can be used to, for the first time, target kinases considered to be “difficult” to target due to their orphan status and unclear regulation mechanisms. When possible, the mechanistic significance in cancer invasion and spreading of newly identified and targeted kinases will be examined using biophysical approaches that can determine whether and how cytoskeletally-mediated processes leading to cell migration have been triggered.


Project 2: Analysis of Non-Cell-Autonomous (Cell Communication-Dependent) Mechanisms of Phenotypic Plasticity in Invasive Cell Spread

Non-cell autonomous interactions, including both those between cancer cells of different phenotypes (homotypic) and between cancer and stromal cells (heterotypic), will be studied in Project 2. Cancer cells are depicted in shades of red and purple, and stromal cells in shades of white.

Preliminary data from the RACE assay (see Project 1) combined with additional evidence suggests that both cancer cell-cancer cell and cancer cell-stroma interactions are critically important for controlling the Proliferative-to-Aggressive phenotypic switch and the ensuing invasive cancer spread. Therefore, in Project 2, our goal is to identify and analyze novel targets as possible regulators of invasive cancer phenotype, particularly ones involved in cell-cell interactions. The key novelty in this project is in the realization that invasive cancer migration has many similarities with normal, invasive processes occurring in developmental or physiological processes, such as wound healing or development of the placental tissue.

We will examine, in a species-dependent fashion, whether stromal cells exert differential resistance to or cooperation with the invasive cancer spread. A focus will be on the differential expression of specific chemo-attractants and chemo-repellents that are frequently associated with angigogenesis or neuronal migration. We will study the mechanisms regulating communication and putative interaction between cells adopting a more proliferative phenotype with cells adopting a more migratory phenotype. We will use novel techniques and approaches in Project 2 to perturb and validate possible novel targets as regulators of invasive cancer phenotype. Analysis of such targets will be conducted in collaboration with Project 1, since many of the techniques used in these projects are compatible and mutually enriching.


Core 1: Microfabrication Core

Core 1 will offer two key microfabricated platforms and assays to enable two different measurements. First, to measure at the scale of a single cancer cell, the migration and invasiveness of melanoma and glioblastoma cell populations in response to combinations of external cues. This will enable the RACE assay, analysis of the cell migration in different types of channels, and a new assay aimed at investigation of heterotypic cell communication. Second, to measure a panel of paracrine signals mediating heterotypic cell-cell communication that drive non-autonomous cancer progression.

Core 2: Animal Core

Core 2 will focus on the validation of the molecular targets and mechanisms involved in phenotypic switching between proliferative and invasive cancer phenotypes. This will be achieved using novel CRISPR-based models of cancer invasion and metastasis. This will allow us to explore the progression of disease following genetic perturbation of molecules of interest identified in the RACE assay, for example, in the analysis of homo- and hetero-typic cell interactions. Viral libraries generated by Core 2 will be used to perform in vivo high throughput analysis, aimed at assaying multiple genetic perturbations, ultimately mimicking the RACE assay in vivo. Both animal models and virus libraries will be of immense utility to researchers both at Yale and elsewhere, representing a valuable resource within the Consortium.

The CSBC Research Center for Cancer Systems Immunology at MSKCC


Center Title

The CSBC Research Center for Cancer Systems Immunology at MSKCC

Participating Institutions

Memorial Sloan-Kettering Cancer Center (MSKCC)
Dana Farber Cancer Center

Center Website

Center Summary

Exciting clinical breakthroughs with checkpoint blockade antibodies and adoptive T cell transfers demonstrate the power of harnessing the immune system to eliminate cancer. However, fundamental challenges remain. Only a subset of patients and cancer types—especially hematological malignancies and melanoma—show significant clinical responses. What properties of tumors determine clinical responses? How can we produce clinical responses in cancers currently unbeatable?

The CSBC Research Center for Cancer Systems Immunology at MSKCC addresses these challenges towards predictable and effective cancer immunotherapy. We assembled a multidisciplinary team of computational biologists, immunologists and cancer scientists; together we will deepen our fundamental understanding of cancer-immune system interactions at the molecular, cellular, and systems levels.
We investigate cancer-immune system interactions at three stages of disease progression: cancer initiation and early tumorigenesis (Project I); established and progressing tumors (Project II); and latent disease and metastasis (Project III). All projects will use cutting-edge single-cell droplet sequencing technologies and computational analyses (Shared Resource Core).


Principal Investigators

Dr. Christina Leslie, Ph.D.

Dr. Christina Leslie, Ph.D. is an Associate Member in the Computational Biology Program at MSKCC. She is an expert in using machine learning to study mechanisms of gene regulation and the epigenetics of cell fates in differentiation, and is widely known for introducing k-mer string kernels for support vector machines in diverse computational biology sequence classification problems. Dr. Leslie is the computational PI for this Research Center and will be the computational Co-Lead for Project I.

Dr. Alexander Rudensky, Ph.D.

Dr. Alexander Rudensky, Ph.D. is Chair of the Immunology Program and Director of the Ludwig Center for Cancer Immunotherapy at MSKCC and an HMMI Investigator. He studies the molecular mechanisms of function and differentiation of CD4 T cells and their role in immunity and tolerance, and he is one of the world’s foremost experts on regulatory T cells. Dr. Rudensky is a Member of the National Academy of Sciences, Member of the American Academy of Arts and Sciences, and Member of National Academy of Medicine, and a recipient of the Coley Award in Basic and Tumor Immunology and an American Association of Immunologists BD-Investigator Award among others. He is the experimental PI leading this Research Center as well as the experimental Lead on Project II.

Computational Investigators

Dr. Joao Xavier, Ph.D.,

Associate Member in the Computational Biology Program at MSKCC

Dr. Dana Pe’er, Ph.D.,

Program Chair and Member in the Computational Biology Program at MSKCC

Dr. Chris Sander, Ph.D.,

Director of the cBio Center at Dana Farber Cancer Institute

Experimental Investigators

Dr. Joan Massagué, Ph.D.,

Director of the Sloan Kettering Institute and Member of the Cancer Biology Genetics Program at MSKCC

Dr. Andrea Schietinger, Ph.D.,

Assistant Member in the Immunology Program at MSKCC.

Clinical collaborator

Dr. Jedd Wolchok, M.D., Ph.D.,

Chief of the Melanoma and Immunotherapeutics Service and Lloyd J. Old Chair for Clinical Investigation in the Department of Medicine at MSKCC


Project 1: Tumor-specific T Cell State Dynamics and Heterogeneity in Early Tumorigenesis

Project 1 aims to define the molecular and epigenetic characteristics and mechanisms that cause tumor-specific T cell to differente to a dysfunctional state during early tumorigenesis. In Aim 1 we will define the chromatin states and transcription factor networks that mediate the transition from plastic to fixed T cell dysfunction states. In Aim 2, we will elucidate the mutational landscape, stromal and immune population dynamics over the course of tumor development and assess how tumor-specific, dysfunctional T cell populations and cell states co-evolve with these changes; exploit single-cell technologies to dissect diversity of T cell states, and develop a novel single cell technology to capture TCR sequences together with gene expression profiles to connect tumor antigen specificity with cell states; ultimately, develop computational and mathematical models of T cell differentiation states to predict responsiveness to therapeutic interventions (e.g. checkpoint blockade). In Aim 3, we will define cell states and heterogeneity of tumor-specific T cells from human solid tumors, and predict and validate changes in their cell states in response to therapeutic interventions (e.g. checkpoint blockade) at a population and single-cell level. Identifying cell states and epigenetic programs of tumor-specific T cells that mediate plasticity or imprinting of cellular hyporesponsiveness will not only provide new insights into the genomic control circuitry of T cell differentiation and dysfunction but may point to novel strategies for cellular reprogramming of cancer-specific T cells for cancer therapy.

Project 2: The tumor ecosystem in cancer progression and immunotherapeutic response

The goal of this project is to identify the ecological interactions between cancer and immune cells that govern cancer dynamics and response to therapy. A tumor can be considered an ecosystem or organ, where multiple accessory cell types are interconnected and communicate with each other and with tumor cells, which serve as their clients. We seek to identify key cellular and molecular regulatory elements in the tumor microenvironment and potential means of their manipulation for therapeutic benefit through systems analysis and modeling of functional interactions in the tumor ecosystem on different scales including cellular, protein, metabolite, and gene expression dynamics at a population and single cell levels. In Aim 1, we will explore the multiple accessory cell types and their interactions with tumor cells using experimental models of skin and lung cancer in mice and in human cancer patients. The accessory cells include myeloid cells, dendritic cells, innate lymphoid cells (ILC), neutrophils, eosinophils, endothelial cells, fibroblasts, and regulatory T (Treg) cells. We will also investigate features of mediators of anti-tumor immunity including NK cells, CD4 and CD8 T cells and their specialized subsets. In Aim 2, we will use perturbation of the tumor ecology impacting its progression in mice and human patients by established and novel immunotherapeutic modalities including PD1 and CTLA4 blockade and Treg cell depletion. The impact of these perturbations will be assessed through comprehensive analysis of cellular dynamics and states in relation to biological and clinical outcomes to generate predictive models. In Aim 3, we will then validate key interaction components in the tumor ecosystem by modeling cell-cell interactions in vitro using tissue mimetic systems and in silico using agent-based models.

Project 3: Latent Metastasis: Immune Regulation of Disseminated Cancer Stem Cells

The goal of Project 3 is to discover mechanisms that critically regulate immune evasion by disseminated tumor cells (DTCs) and their evolution as latent metastatic entities. We will use an integrated approach that combines single-cell interrogation methods with unique biological models of latent metastasis from breast cancer and lung adenocarcinoma, and novel computational strategies. Distant metastasis underlies the overwhelming majority of cancer-related deaths and its inception is exceedingly variable. Residual DTCs may outgrow immediately or, more frequently, linger in a viable state of replicative quiescence or mass dormancy for months to years after infiltrating distant organs. This latency state of DTCs is accompanied with significant resistance to anti-neoplastic therapy, which typically targets actively dividing tumor cells. Moreover, latent DTCs somehow evade immune surveillance. The biology underlying these adaptive abilities remains poorly understood and factors governing DTC population dynamics, whether stochastic or deterministic, remain unknown. We aim to address this significant knowledge gap by combining massively parallel, single-cell RNA expression profiling using a bead-based molecular barcoding technology with unsupervised learning methods to identify stable/transitory cell states within latent, residual disease and their molecular control mechanisms. As a complementary approach, individual cell responses to molecular perturbations will be dynamically tracked by live cell imaging. In Aim 1 we propose to determine whether the latent state pre-exists in the primary tumor or is induced by the stress of immunosurveillance in a host tissue. In Aim 2 we will model the evolutionary dynamics of metastatic cells as they exit latency under growth permissive and immunoediting conditions. In Aim 3 we will identify key regulators of metastatic immune evasion by probing transcriptional heterogeneity in quiescent subpopulations differentially sensitive to NK-cell mediated elimination. The amalgamation of these approaches, combined with our deep understanding of the biology of cancer metastasis, will promote the discovery of therapeutic strategies to eradicate or control metastasis from its earliest stages of inception.


Shared Resource Core

Single-cell sequencing technology and computational analysis
The Research Center’s Shared Resource Core will provide a broadly applicable set of experimental technologies and computational tools for high-throughput single-cell RNA-seq (scRNA-seq) of heterogeneous populations. Single-cell resolution is crucial for elucidating the functional cell subpopulations in both the tumor and its immune microenvironment and can be harnessed to elucidate regulatory relationships within and between these cell subpopulations. To achieve our goals requires a technology that can collect many thousands of cells per tumor and computational methods to analyze and interpret the complex data collected. We will use an improved version of in-drop scRNA-seq, which provides an unprecedented increase in throughput for automated capture and library preparation for single cells in a cost effective manner. The technology will be used to interrogate cell populations for Projects I, II, and III. The Shared Resource will provide the computation, visualization and analysis methods needed to interpret the collected single cell data and integrate it with other data types.

Quantitative and functional characterization of therapeutic resistance in cancer


Center Title

Quantitative and functional characterization of therapeutic resistance in cancer

Center Website

In progress

Center Summary

Fig. 1. Overview of Center and integration of Projects and Cores.

Despite tremendous advances in understanding of cancer pathogenesis, the treatment of individual patients with either conventional chemotherapy or targeted agents remains highly empiric. Current efforts to predict drug efficacy are generally focused on genetic and transcriptional markers of pathway activation or drug binding, such as resistance mutations that sterically hinder small molecule binding or activate parallel or orthogonal signaling pathways. These markers exist in a very small fraction of all cancers, such that most patients are treated with little or no understanding of whether they will respond to an individual therapy. This results in many patients receiving ineffective and/or unnecessarily toxic therapies. There is a desperate need to change this paradigm. The ideal for characterizing therapeutic sensitivity would allow for: real-time decision making, identification of rare subpopulations with therapeutic resistance, analysis of very small samples (e.g. MRD), and maintenance of viable individual cells for downstream assays to characterize phenotypic, genotypic, transcriptional and other determinants of sensitivity.

As shown in Fig. 1, the overall goal of our center is to address this need using new strategies for predicting therapeutic response in which paired phenotypic and genomic properties are measured at the single-cell level. Phenotypic properties will include both physical parameters (e.g. mass, mass accumulation rate) and molecular markers (e.g. protein secretion, surface immunophenotype) that are rapidly affected by effective therapeutics and precede longer-term phenotypes (e.g. loss of viability). Because these properties are measured for each single cell, clonal architectures based on therapeutic response will be established across each tumor sample by incorporating molecular and physical parameter data from large numbers of cells. In settings of deep treatment response, pre-treatment and MRD samples will be compared to define the effects of therapy on clonal architecture. The cells that exhibit particular functional properties (e.g. phenotypic non-responders) will be isolated and analyzed for genomic determinants of these properties. These data will then be incorporated into mathematical models to design and optimize therapeutic approaches that overcome the heterogeneity within individual tumors responsible for treatment failure. By pursuing this approach, our center will establish a framework that enables an iterative cycle between novel single-cell measurements from clinically-relevant specimens and computational approaches that result in testable predictions.


Principal Investigators

Dr. Scott Manalis

Dr. Scott Manalis has an undergraduate and doctorate degree in physics and applied physics, respectively, and his faculty appointment is in the departments of biological and mechanical engineering and an intramural member of MIT’s cancer center (Koch Institute for Integrative Cancer Research). He was the PI of MIT’s PSOC for Single Cell Dynamics in Cancer from 2012-2016 and a leader of a project and core within the center since it started in 2009. His lab developed suspended microchannel resonators for measuring the mass and mass accumulation rate of single cells with unprecedented precision – a capability that is used extensively in this center for measuring ex vivo drug sensitivity of tumor cells.

Dr. Douglas Lauffenburger

Dr. Douglas Lauffenburger is a biological engineer, formally educated in chemical engineering but with research program focused on quantitative, multi-variate studies of cell biology since beginning his academic faculty career in 1979. He is an affiliate member of the Koch Institute for Integrative Cancer Research, and has served as PI of the NCI-funded MIT Integrative Cancer Biology Program for the period 2007-2014. His expertise is in integration of computational analysis and modeling with quantitative cell biology and biochemistry experiments, toward development and testing of mathematical models for how phenotypic cell functions depend on cellular and extracellular molecular properties. He has extensive experience in combined experimental/computational studies of relating molecular properties and phenotypic behaviors on a single-cell basis.

Dr. William Hahn

Dr. William Hahn is a medical oncologist and professor of medicine at Harvard Medical School who has extensive experience in the genomic characterization and functional genomic analysis of cancers in vitro and in vivo. He is currently the Chief of the Division of Molecular and Cellular Oncology and Chair of the Executive Committee for Research at DFCI. Dr. Hahn is also an Institute Member of the Cancer Program at the Broad Institute. His lab has developed new experimental models of human cancer of defined genetic composition, created methods to perform systematic interrogation of gene function in mammalian cells and tissues and helped optimize new approaches to integrate genome scale data. Using these approaches, they have identified and credentialed new oncogenes and tumor suppressor genes and have performed preclinical studies that will form the foundation necessary for translational studies in patients.

Dr. Alex K. Shalek

Dr. Alex K. Shalek received training in physics, mathematics and chemistry, and his faculty appointment is in the Institute for Medical Engineering and Science and the department of Chemistry. He is also an Associate Member of the Broad and Ragon Institutes, where he has additional labs and access to an array of cutting-edge equipment, platforms and approaches. His expertise relevant to this proposal is on developing and utilizing nanoscale manipulation and measurement technologies to understand how small components (molecules, cells) drive systems of vast complexity (cellular responses, population behaviors). As a postdoctoral fellow, he developed a strategy that uses single-cell RNA-Seq to identify distinct cell states and circuits from the natural variation that exists between seemingly identical cells. His lab is determining how cell-to-cell variability arises from intra- and inter-cellular regulatory circuits in healthy and diseased states, as well as to explore the causes and consequences of cellular heterogeneity. These approaches are used extensively in this center.

Dr. David Weinstock

Dr. David Weinstock is an oncologist at DFCI, Associate Professor at Harvard Medical School and Associate Member of the Broad Institute. His laboratory has made a series of high-impact discoveries in leukemias, including the identification of CRLF2 as a targetable oncoprotein in poor-risk B-cell acute lymphoblastic leukemia (B-ALL), the therapeutic targeting of CRLF2-dependent leukemias with inhibitors of JAK2, HSP90, MDM2 and BRD4, the role of the nucleosome remodeling protein HMGN1 in cases with Down Syndrome, and the identification of alterations in G protein subunits as a mechanism of targeted therapy resistance. The Weinstock lab leads the effort to establish leukemia and lymphoma PDX models at the DFCI, Brigham and Women’s Hospital, Boston Children’s Hospital and Massachusetts General Hospital. He has already established a repository of >300 models serially passaged through immunodeficient mice and characterized by exome and transcriptome sequencing, and made these available open-source ( as well as through the Jackson Laboratories. He currently leads a multi-institutional Specialized Center of Research that is supported by the Leukemia and Lymphoma Society and focuses on lymphoid cancer biology and targeting.

Dr. Christopher Love

Dr. Christopher Love has an undergraduate and doctoral degree in physical chemistry, and his faculty appointment is in the department of chemical engineering. He is an intramural member of the Koch Institute for Integrative Cancer Research and an associate member at both the Broad Institute and Ragon Institute. He has been part of a working group on systems biology and engineering solutions for sparse samples in mucosal immunology (DAIDS/HVTN MIG). He has served as the primary PhD thesis advisor of graduate students from the departments of chemical engineering and biological engineering. His lab developed the nanowell technology that is used in our center. It has been optimized in all aspects of the technology, including imaging of cells in nanowells, time-resolved, multiplexed analysis of cytokines, and software tools for data extraction. New advances in plate formats allow for 24-array processing in parallel, and up to 16-channel imaging cytometry on a microscope. These capabilities will be employed in both projects.

Ms. Kristen Stevenson

Ms. Kristen Stevenson is a biostatistician and has worked for the past 10 years at DFCI in research of hematologic malignancies primarily including myelodysplastic syndrome, chronic lymphocytic leukemia, and acute lymphoblastic leukemia. She also has undergraduate degrees in chemical engineering, computer science, and industrial mathematics and statistics. Her expertise is in statistical modeling and analysis, power and samples size calculation, and experimental and clinical trial design.


There are three novel single-cell analysis approaches that extensively utilized in our center:

[1] Suspended microchannel resonator. Our approach for measuring cell growth, or mass accumulation rate, is based on a sensing technology known as the suspended microchannel resonator (SMR). When an object that is denser than water passes through the SMR, the net increase in mass (i.e. the buoyant mass of the object) lowers the resonant frequency. By continually measuring buoyant mass when the cell travels back and forth through the sensor, growth of individual bacteria, yeast, and mammalian cells has been quantified with a precision that has not been achievable by conventional microscopy. In our center, we will use a novel SMR array-based technique for high-throughput mass accumulation rate measurements that increases throughput by 100-fold without sacrificing precision. This is accomplished by an array of SMRs microfluidically connected in series, with “delay” channels in between each cantilever (Fig. 2). These delay channels give the cell time to continue changing mass as it flows between cantilevers. After a cell exits a cantilever, other cells are free to enter it and be weighed. We are not limited to flowing only one cell through the array at a time, but can have many cells flowing through the array in a queue, enabling precision growth measurements with a throughput approaching 100 cells per hour per device. In a collaboration between MIT and DFCI researchers, the serial SMR device has been validated for ex vivo drug susceptibility testing in several cell lines, patient-derived cell lines and primary cells from mouse models.

Fig. 2: A) Micrograph of serial SMR device. Cantilever lengths range from 380 to 470 μm to provide unique resonant frequencies, which are readout with integrated piezoresistors. The MEMS foundry CEA-LETI recently fabricated several 8” wafers, each of which includes ~200 hundred devices. B) Buoyant mass data from mouse lymphoblast cells extracted from frequency shifts of cantilevers, color-coded by cantilever. 7 and 9 μm polystyrene particles are added as calibration and negative control, respectively. Each cell requires ~20 min to pass through the serial array, which is sufficient for measuring its mass accumulation rate with high precision. Over the course of incubation with a selected drug (2-24 hrs), the serial SMR can detect changes in the growth of single cells to predict therapeutic response without the need for extended culture. In some cases, measuring single cell growth can result in drug sensitivity test that is sufficient more rapid than viability. This is important since the properties of primary cells change quickly when moved to an ex vivo environment.

Through a seed grant from the MIT/DFCI Bridge program (co-Principal Investigators: Manalis, Weinstock), two serial SMR platforms are now being operated in CLIA-approved space at the DFCI/Brigham and Women’s Cancer Center by a dedicated technician in the Weinstock lab. This was an essential step toward translating the SMR into a clinical assay for predicting therapeutic response in heterogeneous tumor populations directly from primary specimens.

[2] Single-cell genomic profiling. scRNA-Seq, an approach co-developed by the Shalek Lab in both basic and clinical settings, is utilized throughout Projects 1 and 2. In previous work, we have established and validated robust experimental and computational pipelines for scRNA-Seq. This work has demonstrated that scRNA-Seq enables unbiased identification of the cell types, states, and circuits that drive complex biological systems, such as tumors, at the single-cell level. More specifically, in the context of human cancer biopsies, we have optimized strategies for the capture and lysis of individual cancer, stromal, and immune cells, and developed computational approaches to identify the cell states of each and their molecular underpinnings. Here, scRNA-Seq will enable not only the precise identification of malignant and non-malignant cells from the bone marrow microenvironment, but also the nomination of putative extracellular factors that influence malignant cell drug responses through the identification of co-expressed gene programs downstream of secreted molecules or receptor-ligand pairs. Recent work in the Shalek Lab, performed in collaboration with the Regev (Broad, MIT) and Garraway (DFCI) Labs, identified intratumor and intertumor heterogeneity in melanoma biopsies and discovered patient-specific immune and stromal cell populations that correlate with prognosis and potentially explain some instances of resistance (Fig. 3). Here we propose to specifically examine the phenotype of cells with unaffected MAR in the presence of drug using scRNA-Seq in order to define resistant cell states and intuit treatment strategies that target them.

Fig. 3: scRNA-Seq in human cancer. scRNA-Seq of primary human melanoma samples demonstrates (A) inter- and intratumor heterogeneity among malignant (left) and non-malignant (right) cells. Further, in the context of malignant cells, (B) substantial variability is observed in the fractional abundance of a drug-resistant cell state (AXL-high) across patient samples (labeled MelXX). Adapted from Tirosh et al, Science, 2016.


[3] Nanowells. We will utilize a nascent technology for single-cell analysis that relies on dense arrays of subnanoliter wells to profile the phenotypic and molecular properties of tumor cells and for precise control of a cell’s microenvironment (Project 2). The majority of examples, and the development of this technology to date, has emphasized the characterization of the diversity and functions of antigen-specific B- and T-cells of the immune system. The Love Lab has developed a strategy for bioanalytics that uses these arrays in defined processes comprising one or more modular unit operations—each one reporting on different characteristics of the cells analyzed, such as phenotypic lineages or functions (Fig. 4). Examples include on-chip cytometry (51), quantitative measures of secreted proteins by a printing method called microengraving, single-cell cytolysis assays and gene expression. To date, this nanowell-based platform has been used to characterize mouse hybridomas, mouse B and T cells, yeast cells, and human PBMCs.

Innovative aspects of the nanowell technology relevant to this proposal include:

  • Modular operations that link complex phenotypic traits like viability to genotypic features (clonal lineages determined by single-cell sequencing)
  • Resolution and recovery of extremely rare cells (~1 in 10,000 or fewer), including circulating tumor cells, for clonal expansion or single-cell sequencing
  • Deep immunophenotyping by multi-spectral imaging cytometry (MuSIC) for up to 16 channels of data (comparable to state-of-the-art flow cytometers)
  • Quantitative measures of secretion from one or a few cells with sensitivities 10-100x greater than conventional clinical assays like ELISpot
  • Discrete co-cultures of multiple cells to measure intercellular communication among tumor cells, or mixed populations.




Fig. 5. Functional characterization of therapeutic resistance in cancer.Cells are treated in vivo before target populations are extracted, purified and measured immediately upon removal from the mouse or patient. Alternatively, the target population is treated ex vivo prior to the measurement. Upon measurement of mass accumulation rate (MAR), each cell is sorted into a well and lysed within ~1 min, thereby allowing scRNA-seq of a given cell to be linked to its MAR. Cells that maintain MAR similar to vehicle-treated cells after sufficient drug exposure are considered to be non-responders. The overall goal of this proposal is to determine mechanisms of resistance and make testable predictions to overcome that resistance through transcriptome analysis of phenotypically-defined single cells.

As illustrated in Fig. 5, scRNA-Seq will be acquired from cells that are determined by the SMR growth assay to be non-responders to a particular treatment (i.e. phenotypically drug resistant). These data will provide unprecedented insight into: i) pathways that distinguish response after target inhibition compared to untreated cells, ii) whether these same pathways distinguish response upon relapse and thus could be predicted at the time of minimal residual disease, and iii) pathways that associate with differential response to targeted therapeutics between different compartments (e.g. bone marrow and peripheral blood leukemia cells at the untreated and relaps ed time points). Based on these findings, we expect to nominate combination strategies that target the phenotypically-resistant cells as well as come up with drugs that might be appropriate targets currently not appreciated as being relevant for a particular cancer. Project 1 will focus on cell-intrinsic properties of tumor cells while Project 2 will focus on cell-extrinsic effects through the use of nanowells to control paracrine and juxtacrine interactions that mimic the microenvironment.


Project 1. Systematic discovery of cell-intrinsic mechanisms of cancer drug resistance

PIs: Manalis (lead) and Lauffenburger (co-lead), Shalek, Weinstock and Hahn
We aim to utilize high precision single-cell growth measurements together with single-cell RNA-Seq (scRNA-Seq) to profile the intrinsic factors that inform the responses of individual cancer cells to therapeutic interventions. We will ask to what extent paired phenotypic and transcriptomic measurements can identify pathways that mediate cell autonomous resistance and highlight therapeutic approaches to overcome that resistance. Cancer cells will be isolated from primary tumors or from patient-derived cell lines/xenografts of both leukemias (as a liquid tumor model) and colon/pancreatic cancers (as a solid tumor model). In contrast to Project 2, cells will be measured in isolation without mimicking aspects of the microenvironment. Over a period of many hours, we will examine distinct phenotypic attributes of the cells (mass and mass accumulation rate) and link these attributes to the transcriptome at the single-cell level. We will then determine cell intrinsic mechanisms for resistance by analyzing transcriptomic features of responding and non-responding tumor cells.

Project 2. Systematic discovery of cell-extrinsic mechanisms of cancer drug resistance

PIs: Shalek (lead), Hahn and Love (co-leads), Weinstock, Lauffenburger and Manalis
We aim to utilize high precision single-cell growth measurements and single-cell RNA-Seq (scRNA-Seq) together with nanowells to systematically examine how the extracellular factors present in leukemias and colon and pancreatic cancers influence drug responses. First, we will identify the signals and non-malignant cells present in each tumor type by performing scRNA-Seq on primary biopsies. We will then generate an atlas of implicated cell types/states and putative signaling molecules that may influence cancer cell drug responses in vivo. Second, we will use high precision single-cell growth measurement and nanowells to systematically uncover how these soluble factors and tumor cells inform on cancer cell drug responses; we will similarly examine the impact of previously implicated environmental factors as well as other cancer cells (of the same and different intrinsic states; from Project 1). By analyzing and modeling our results, we will uncover previously unknown microenvironmental synergies (e.g., cytokines, receptor-ligand pairing) that may modulate cancer cell drug responses in vivo. Collectively, these aims will afford an unprecedented view of the tumor microenvironment and shed light on current therapeutic bottlenecks, while suggesting potential new and more effect therapeutic inroads for treating cancer.


Core 1: Biospecimens and Patient-derived xenografts

PIs: Hahn (lead) and Weinstock (co-lead)
The overarching goal of Core 1 is to provide the infrastructure and professional expertise needed to bank primary leukemia, colon, and pancreatic cancer specimens, establish patient-derived xenograft (PDX), organoid, and cell models, and make these patient-derived resources available to all Program investigators, thereby facilitating the translational and laboratory-based research performed by CSBC investigators in Projects 1 and 2. Both projects will require access to patient samples and cells derived from PDX and organoid models. The core supports 3 functions: (1) cryopreservation and distribution of primary cells from patients with leukemia, colon, and pancreatic cancer, (2) establishment, characterization, and distribution of xenograft, organoid, and cell culture models of these diseases, and (3) isolation of cell populations from primary tumor samples and tissue models for single cell analysis. The functions of the core include documentation and tracking of informed consent, isolation and cryopreservation of viable tissue, plasma or serum, and genomic DNA from patient samples and distribution of samples to CSBC investigators. A large number of primary leukemia, colon and pancreatic tumor samples are currently available in our existing repositories for use by Project Investigators. Additional samples will be acquired from patients routinely evaluated in our gastrointestinal oncologic and hematologic malignancies clinics. In addition to distributing primary cells to program investigators, Core 1 will also maintain and distribute a bank of well characterized PDXs selected for passage in immunocompromised mice. Methods for engrafting leukemia cells and primary epithelial tumor tissues in immunodeficient mice are now well established, and we and others have successfully used PDX models for drug testing. Organoid culture approaches will be used to complement the PDX effort, and will provide an additional way of propagating and segregating patient-derived epithelial tumor cells and stromal cells. Core 1 will maintain a bank of PDX models and organoids and distribute to program investigators as needed. Overall, Core 1 has extensive experience in the processing, cryopreservation, flow cytometric analysis, purification, propagation, banking, and genomic characterization of primary specimens and tumor models, as well as their use in preclinical drug evaluation.

Core 2: Computational Analysis Core

PIs: Lauffenburger (lead), Shalek and Stevenson
The Computational Analysis Core (Core 2) will support Projects 1 & 2 by bringing necessary bioinformatics and computational methods to bear on the questions addressed by each project. More specifically, we will apply established computational pipelines to perform quality control on, and extract maximal information (cell types, states, circuits, and drivers) from, our rich data sets. We will help our CSBC team identify the cell types, states, and circuits active in the Leukemia and Colon and Pancreatic tumor models of Core 1 from the single-cell RNA-Seq data collected in Projects 1 & 2, as well as the molecular drivers of interesting behaviors. We will deploy numerical algorithms to uncover the predictive power of phenotypic measurements, alone or in combination, made via our Nanowell (NW) and Suspended Microchannel Resonator (SMR) platforms to explain cancer cell drug responses. When necessary, we will identify and/or develop new algorithms, enhancing our CSBC’s quantitative and multivariate capabilities. Finally, we will work closely with our CSBC team members to help with experimental design, ensuring that an appropriate number of cells/samples are processed to test hypotheses of interest and that appropriate statistical testing is performed. By providing comprehensive analysis (QC, power, gene set enrichment) and modeling capabilities, we will dramatically enhance our ability to draw crucial insights from our data. This will lead to new hypotheses that can be tested by designing new experiments.

Education and Outreach Core

PI: Lauffenburger
The mentorship of current and future trainees who can tackle cancer-related problems with computational systems biology approaches is an integral part of fulfilling our commitment to catalyze and generate new bodies of knowledge and fields of cancer study. To achieve this goal, we will: 1) Establish graduate student fellowships for students jointly mentored in computational systems biology, precision measurement or oncology. 2) Provide undergraduate research opportunities for MIT students to work in laboratories at DFCI. 3) Provide outreach to the biotech/pharmaceutical industry. 4) Establish an NCI CSBC Junior Investigators program. 5) Facilitate monthly meetings and annual retreats that will be open to the MIT/DFCI community. 6) Offer mini-courses and training in experimental and computational methods. 8) Provide outreach to the community. and 7) Establish and maintain a website for disseminating research activities of our center as well as relevant techniques and applications.

Administrative Core

The overall mission of the Administrative Unit is to provide oversight and coordination on administrative and fiscal aspects of the MIT/DFCI CSBC.

Center for Cancer Systems Pharmacology (CCSP)


Center Title

Center for Cancer Systems Pharmacology (CCSP)

Center Website

Center Summary

The Center for Cancer Systems Pharmacology (CCSP) based at Harvard Medical School focuses on constructing and validating network-level models of responsiveness and resistance (innate and acquired) to immune checkpoint inhibitor (ICI) and small molecule (targeted) therapies in human cancer. The over-arching goal is to improve the treatment of disease and advance molecular understanding of oncogenic transformation and opposing immune surveillance on the initiation and progression of human cancer. Our Center also studies the adverse effects of targeted therapies, with an initial focus on ICI toxicity in the skin.
Our approach involves the use of systems pharmacology tools and concepts to address the most significant questions encountered in the use of ICIs and targeted therapies individually and in combination in melanoma, in which both classes of drug can be highly effective individually, and also in triple negative breast cancer (TNBC) and glioblastoma multiforme (GBM) in which clinical responses are sporadic. In the long-term, expected outcomes include (i) translating clinical problems in melanoma, TNBC and GBM from the bedside to bench and then back to the bedside via new drug-disease pairings, drug combinations and response biomarkers (ii) developing, validating and applying to clinical trials innovative pharmacological concepts that consider the impact of cell-to-cell variability, micro environment, and dose and drug sequencing on outcomes and (iii) reducing the burden of therapy through improved understanding of mechanism-based drug toxicities and ways of mitigating them.

Conceptual focus of the CCSP Center. We study mechanisms of therapeutic and adverse response and of drug resistance in melanoma, in which both ICIs and targeted therapy are effective, and triple negative breast cancer (TNBC) and brain cancers, in which they are sporadic and a significant unmet need exists. (+) signs denote responsiveness to therapy.


Principal Investigators

Peter Sorger (PI)

Peter Sorger (PI), Otto Krayer Professor of Systems Biology; Founding Director of the Laboratory of Systems Pharmacology and Head of the Harvard Program in Therapeutic Science in which the Center for Cancer Systems Pharmacology (CCSP) is based. Dr. Sorger’s research focuses on the systems biology of mammalian signal transduction and the drugs that target oncogenic signaling proteins. His group uses single-cell and multiplexed imaging and mass spectrometry methods to constrain and validate physico-chemical models of oncogenesis and drug action.

Sameer Chopra

Sameer Chopra, Instructor of Medicine, Harvard Medical School (HMS); Attending Physician, Dana-Farber Cancer Institute (DFCI); Research Associate, Harvard Program in Therapeutic Science. Dr. Chopra studies mechanisms of immune evasion in women’s cancers (breast, ovarian, endometrial) and their relationship to specific molecular and phenotypic aberrations commonly found in these tumors such as replication stress and genome instability. He aims to improve strategies for initiating and sustaining effective anti-tumor immune responses in patients using rational combinations of small molecule drugs, immunotherapy, and chemotherapy.

Conor Evans

Conor Evans, Assistant Professor at the Wellman Center for Photomedicine of Harvard Medical School at the Massachusetts General Hospital. Dr. Evans develops advanced imaging technologies for the direct visualization and quantification of pharmacokinetics and pharmacodynamics in situ. By leveraging tools such as coherent Raman imaging, image analysis, and machine learning, his group aims to improve our understanding of how cancer drugs reach and engage their targets.

Keith Flaherty

Keith Flaherty, Director of the Termeer Center for Targeted Therapies, Director of Clinical Research at the Massachusetts General Hospital; Professor of Medicine at Harvard Medical School. Dr. Flaherty focuses on understanding mechanisms of action and resistance to signal transduction targeted therapy and immunotherapy in melanoma, as well as the mechanistic interaction between the two modalities. Deep molecular analysis of serial tumor biopsies and rapid autopsy samples are used to motivate functional pre-clinical studies and to inform next generation clinical trials.

Jennifer Guerriero

Jennifer Guerriero, Director of the Breast Immunology Laboratory in the Women’s Cancer Program at Dana-Farber Cancer Institute; Instructor in Medicine at Harvard Medical School. Dr. Guerriero studies the role of tumor associated macrophages (TAMs) in promoting tumorigenesis and as a therapeutic target. Her research aims to understand the molecular and functional regulation of tumor macrophage phenotype and subsets, identify how tumor macrophages inhibit T cell function and limit the effectiveness of immunotherapy, and identify novel strategies to target macrophages therapeutically.

Marcia Haigis

Marcia Haigis, Associate Professor in the Department of Cell Biology at Harvard Medical School. Dr. Haigis studies the metabolic programs of mammalian cells and the pathways that regulate these programs. She focuses on metabolic reprogramming of tumor cells and immune cells within the tumor microenvironment to discover novel anti-tumor therapies.

Steve Hodi

Steve Hodi, Director of the Melanoma Center and the Center for Immuno-Oncology, and Institute Physician at the Dana Farber Cancer Institute; Sharon Crowley Martin Chair in Melanoma; Professor of Medicine at Harvard Medical School. Dr. Hodi studies mechanisms of immuno-therapy via clinical trials in multiple disease areas. He focuses on understanding determinants of response and the specific disease features that allow a subset of patients to experience extremely durable responses to immune checkpoint inhibition.

Benjamin Izar

Benjamin Izar, Medical Oncologist in the Department of Medical Oncology (Melanoma Disease Center) and Center for Immunology and Virology at the Dana-Farber Cancer Institute; Center for Cancer Precision Medicine at the Dana-Farber Cancer Institute; investigator at the Broad Institute of MIT and Harvard. Dr. Izar has pioneered the implementation of single-cell RNA-sequencing and single-cell protein imaging in clinical specimens and the development of patient-derived models to understand drug resistance to targeted therapies and immune checkpoint inhibitors. As a medical oncologist, he focuses on the treatment and understanding of drug resistance in melanoma.

Darrell Irvine

Darrell Irvine, Professor in the Departments of Biological Engineering and Materials Science & Engineering, Koch Institute for Integrative Cancer Research at the Massachusetts Institute of Technology, Ragon Institute of MGH, MIT, and Harvard; Howard Hughes Medical Institute Investigator. Dr. Irvine’s laboratory is focused on the development of combination immunotherapies leveraging innate and adaptive immune pathways as a means to eradicate established tumors. His group is particularly interested in combination therapies that trigger an “in situ” vaccination response.

Douglas Lauffenburger

Douglas Lauffenburger, Ford Professor of Biological Engineering, Chemical Engineering, and Biology Head, Department of Biological Engineering at the Massachusetts Institute of Technology. Dr. Lauffenburger studies cell dysregulation in complex pathophysiologies, emphasizing applications in cancer, inflammatory diseases, and vaccines. A central objective is gaining understanding of how multiple pathways and processes — both intracellular and intercellular – combine to govern cell functions and how they become dysregulated in disease.

Nicole Leboeuf

Nicole Leboeuf, Director, Center for Cutaneous Oncology at Dana-Farber/Brigham and Women’s Cancer Center, Director of Dermatologic Immunology; Clinic Director of Skin Toxicities from Anticancer Therapies Clinic; Assistant Professor at Harvard Medical School. Dr. Leboeuf provides urgent and ongoing expert dermatologic care for cancer patients with cutaneous adverse events from oncologic treatments. Her research focuses on profiling the immune infiltrate in the skin and blood of patients with cutaneous eruptions from immune checkpoint blockade.

Patrick Ott

Patrick Ott, Attending Physician in the Department of Medicine at Brigham and Women’s Hospital; Clinical Director of the Center for Immuno-Oncology and Melanoma Center at the Dana Farber Cancer Institute; and Assistant Professor at Harvard Medical School. Dr. Ott is interested in the development of new immunotherapeutic strategies for cancer patients. He is the principal investigator and site investigator of a large portfolio of clinical trials assessing novel agents and innovative combinatorial strategies for patients with melanoma and other cancers.

Sandro Santagata

Sandro Santagata, Associate Pathologist in Neuropathology at the Brigham and Women’s Hospital and the Dana Farber Cancer Institute; Assistant Professor in Pathology at Harvard Medical School. Dr. Santagata is interested in applying novel imaging methods, including tissue-based cyclic immunofluorescence (t-CyCIF) to brain tumor resection specimens from clinical trials in order to measure and model responses in tumors and their microenvironment before and after therapy.

Arlene Sharpe

Arlene Sharpe, George Fabyan Professor of Comparative Pathology, Head of the Division of Immunology; Co-Director of the Evergrande Center for Immunologic Diseases; Chair of the Department of Immunobiology at Harvard Medical School. Dr. Sharpe studies T-cell costimulation and its immunoregulatory functions in T cell tolerance and anti-tumor immunity. Her laboratory has been at the forefront of this field for over two decades, discovering T cell costimulatory pathways, and elucidated their functions, including the functions of B7-1 and B7-2, CTLA-4, ICOS, PD-1 and PD-1 ligands.


Project 1: Multi-scale modeling of adaptive drug resistance in BRAF-mutant melanoma

We are constructing families of computational models, at different levels of molecular detail, that capture and ultimately explain the diversity of phenomena associated with resistance to RAF/MEK inhibitors. This is accomplished by collecting time-series single-cell and population-level data from cells with diverse genotypes followed by time-resolved modeling using differential equations, logic-based models and supervised machine learning. These studies are performed initially in patient-derived cell lines and mouse models, but intended to provide hypotheses that can be tested in clinical trials.

Project 2: Measuring and modeling the tumor and immune microenvironment before and during therapy and at the time of drug resistance

We study changes in the tumor ecosystem induced by ICIs or targeted therapy and predictive of therapeutic response. The precise proportions and spatiotemporal arrangements of tumor, stromal and immune cells will be determined in tissue biopsies, and single-cell features will be extracted and associated with disease progression and therapeutic response using machine learning, deep learning and high-dimensional data analysis. Adverse responses in the skin and gut will also be investigated and compared to therapeutic responses at a mechanistic and clinical level.

Project 3: Mechanisms of immunotherapy action

We study ICIs alone or in combination in tumor-bearing mice to evaluate whether highly efficacious responses arise from co-targeting cells of single lineages (e.g. CD8+ effector T cells) or concurrent targeting of multiple cell lineages (e.g. CD8+ T cells, regulatory T cells), and to identify the tumor settings in which either strategy might prove more effective. Metabolic, signaling, and transcriptional changes associated with cellular responses to ICIs are assessed and modeled. Agent-based models are then used to study non-cell autonomous mechanisms that mediate therapeutic and adverse drug effects. We hope to thereby discover combinations of ICIs and specific patient populations in which therapeutic responses are high and toxicity is minimal.


Systems Pharmacology Core

The Systems Pharmacology Core provides all CCSP members, as well as individuals selected for funded internal research projects, access to a central, high quality resource for molecular profiling of cells and tissues and for data analysis. The core will join together four approaches based in the Laboratory of Systems Pharmacology (LSP) (i) deep, high throughput, and single cell RNA-Seq (ii) targeted and shotgun mass-spectrometry based proteomics (iii) high dimensional single cell imaging and (iv) data analysis and data science based on supervised and unsupervised machine learning as well as two technologies based in the laboratories of CCSP investigators (i) metabolomics profiling (via Haigis lab) and (ii) immune profiling of blood using flow cytometry and multiplex cytokine assays (via the DFCI Immune Profiling Lab). These activities do not take place in isolation, and all of our platform technologies work closely with HMS core facilities in a hub and spoke model..

Center for Cancer Systems Therapeutics (CaST)


Center Title

Columbia University Center for Cancer Systems Therapeutics

Center Website

Center Summary

The Columbia University Center for Cancer Systems Therapeutics (CaST) is developing a new conceptual framework capable of accounting for the extreme biological heterogeneity seen in cancer. Instead of focusing on the highly diverse, patient-specific spectrum of mutations that can initiate cancer, CaST is concentrating on the regulatory machinery found within cancer cells that is responsible for tumor homeostasis and tumor canalization. Just as regulatory networks have been shown to enable cells to differentiate during development and maintain stable phenotypes, CaST is testing the hypothesis that similar regulatory principles can be used to understand how cancer cells survive and propagate as tumors grow and respond to treatment. Understanding the regulatory logic behind tumor homeostasis and canalization over the time course of disease is critical for addressing several key challenges facing precision medicine; namely, how malignant tumors evade treatment, induce disease progression, and develop drug resistance. We are studying this machinery across multiple levels of granularity — including interactions between tumors and their microenvironment as well as single-cell heterogeneity and plasticity — representing the full, systems-wide complexity of the tumor phenotype.

Our approach is based on the proposition, validated repeatedly in previous research at Columbia, that tumor homeostasis is controlled by a small number of proteins and other gene products called master regulators (MRs), which work in concert within tightly autoregulated modules called tumor checkpoints to maintain cancer-related phenotypes. Similar to a traffic checkpoint, the aberrant signals that contribute to the implementation and maintenance of tumor cell state must converge on these modules, where they are integrated and translated into downstream transcriptional programs that generate the tumor signature. As our past research has shown, such tumor checkpoints are likely much more limited in number than the possible number of cancer-initiating mutations, and therefore constitute a unique kind of oncogene-independent “Achilles heel” of cancer, offering a distinct category of potential therapeutic targets. We aim to develop methods for systematically identifying master regulators of tumor homeostasis and tumor state transitions, and connect them to drugs capable of modulating them.


Principal Investigators

Andrea Califano, Ph.D.

Andrea Califano, Ph.D. is the Clyde and Helen Wu Professor of Chemical Systems Biology at Columbia University Medical Center. He is the Founding Chair of the Columbia University Department of Systems Biology, Director of the JP Sulzberger Columbia Genome Center, and Associate Director for Bioinformatics of the Herbert Irving Comprehensive Cancer Center. He is also the founder of Darwin Health. The Califano Lab uses a combination of computational and experimental methodologies to reconstruct the regulatory logic of human cells in a genome-wide fashion. He has shown that analysis of this logic can identify master regulator proteins responsible for human disease, including cancer and neurodegenerative syndromes, as well as for normal tissue development. In addition, his lab has developed methods for discovering compounds and compound combinations that can inactivate these proteins, thus providing valuable therapeutic strategies. These findings have been translated into several clinical studies, including an innovative set of N-of-1 clinical trials in which disease master regulators are identified and pharmacologically targeted on an individual patient basis, using a systems biology approach to precision medicine.

Barry Honig, Ph.D.

Barry Honig, Ph.D. is professor of Biochemistry and Molecular Biophysics and is director of the Center for Computational Biology and Bioinformatics (C2B2). He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and is a Howard Hughes Medical Institute (HHMI) Investigator. Dr. Honig has developed methods that combine information about protein sequence with biophysical analysis to reveal how biological specificity is encoded on protein structures. His laboratory also uses methods from biophysics and bioinformatics to study the structure and function of proteins, nucleic acids, and membranes. His work includes fundamental theoretical research, the development of software tools, and applications to problems of biological importance.

Participating Investigators

Cory Abate-Shen, Ph.D.

Cory Abate-Shen, Ph.D. is the Michael and Stella Chernow Professor of Urologic Sciences, director of research in the Columbia University Department of Urology, and an associate director of the Herbert Irving Comprehensive Cancer Center and leader of its Prostate Program. In her research she investigates the molecular mechanisms of homeobox genes in development and cancer. Her laboratory has provided groundbreaking insights on the molecular bases of how homeoproteins achieve target gene recognition in vivo. She has also developed mouse models of prostate cancer that have been widely used to investigate the molecular bases of prostate tumorigenesis and as preclinical models for intervention and therapy.

Dimitris Anastassiou, Ph.D.

Dimitris Anastassiou, Ph.D. is Charles Batchelor Professor and director of the Genomic Information Systems Laboratory at the
Department of Electrical Engineering, and a member of the Department of Systems Biology, Center for Computational Biology and Bioinformatics, and the Center for Cancer Systems Therapeutics (CaST). His current research is focused on the discovery and elucidation of “pan-cancer” biomolecular mechanisms shared by multiple cancer types, as well as potential diagnostic, prognostic, and therapeutic applications associated with these mechanisms.

Filemon Dela Cruz, M.D.

Filemon Dela Cruz, M.D. is an assistant professor of pediatrics at Memorial Sloan Kettering Cancer Center. His current work focuses on the development and application of mouse models for the study of the development of solid tumors, with a particular focus on sarcomas.

Charles Karan, Ph.D.

Charles Karan, Ph.D. is the scientific director for the High-Throughput Screening Facility at the JP Sulzberger Columbia Genome Center. In this role, he assists researchers at Columbia and from other institutions to develop and implement high-throughput screening protocols tailored to the goals of individual research projects. He also manages all operations of the HTS facility.
Andrew Kung, M.D. is a physician-scientist and Chair of the Department of Pediatrics at Memorial Sloan Kettering. He oversees the clinical, research, and educational missions of the department. As a physician, he specializes in caring for patients using cancer genomics, precision medicine, and stem cell transplantation. In his research, he focuses on identifying the causes of pediatric cancers and developing new treatments to benefit children and teens with cancer.

Diana Murray, Ph.D.

Diana Murray, Ph.D. is a Research Scientist and the Program Director of Research and Outreach in the Department of Systems Biology. Her research focuses on integrating structure-based protein-protein interaction networks with gene regulatory networks to provide molecular-level descriptions for mechanisms underlying normal and aberrant cellular signaling. Building on a computational framework for examining phosphoinositide signaling, she will participate in CaST’s research by incorporating proteomic and genomic information on protein-lipid interactions into structure-informed network models. In addition, Dr. Murray is leading the CaST Outreach Corer.

Kenneth Olive, Ph.D.

Kenneth Olive, Ph.D. is Assistant Professor of Medicine and Pathology at the Columbia University College of Physicians & Surgeons. His laboratory performs preclinical therapeutics trials using advanced genetically engineered mouse models, with a particular emphasis on pancreatic cancer. The lab uses advanced small animal imaging technologies to track tumor response to treatment, as well as pharmacokinetic and pharmacodynamics analyses, functional imaging, microscopy, and biochemistry and molecular biology techniques to assess drug mechanisms and understand relevant signaling pathways.

Itsik Pe’er, Ph.D.

Itsik Pe’er, Ph.D. is an associate professor in the Department of Computer Science. His laboratory develops and applies computational methods for the analysis of high-throughput data in germline human genetics. Specifically, he has a strong interest in isolated populations such as Pacific Islanders and Ashkenazi Jews. Using high-throughput sequencing methods, Pe’er has focused on characterizing genetic variation that is unique to isolated populations, including the effects of such variation on phenotype.

Raul Rabadan, Ph.D.

Raul Rabadan, Ph.D. is an Associate Professor with joint appointments in the Departments of Systems Biology and Biomedical Informatics. He is also a member of the Scientific Advisory Board of the JP Sulzberger Columbia Genome Center, and codirector of the Center for Topology of Cancer Evolution and Heterogeneity, a center in the NCI’s Physical Sciences–Oncology Network. At Columbia University, Dr. Rabadan leads an interdisciplinary lab with researchers from the fields of mathematics, physics, computer science, engineering, and medicine who share the common goal of solving pressing biomedical problems through quantitative computational models. His work is focused on developing tools to analyze genomic data, and extracting relevant information to understand the molecular biology, population genetics, evolution, and epidemiology of cancer.

Nicholas Tatonetti, Ph.D.

Nicholas Tatonetti, Ph.D. is Herbert Irving Assistant Professor of Biomedical Informatics at Columbia University with interdisciplinary appointments in the Department of Systems Biology and the Department of Medicine. Dr. Tatonetti researches the use of observational clinical data and high-throughput molecular data to identify and explain the pharmacological effects of drugs and drug combinations. He also develops large-scale statistical and data mining techniques to address issues of bias and confounding in large observational data sets.

Dennis Vitkup, Ph.D.

Dennis Vitkup, Ph.D. is an associate professor in the Departments of Systems Biology and Biomedical Informatics. His laboratory develops and applies novel probabilistic techniques to analyze cellular networks, connecting network structure to function to phenotypes, including experimentally verifiable predictions. Research in the Vitkup Lab focuses on three main topics: 1) the global probabilistic reconstruction and analysis of metabolic networks based on completely sequenced genomes; 2) the development of methods to identify new human disease genes and genetic disease modules using probabilistic functional networks; and 3) the development of methods to combine mechanistic and probabilistic approaches for the dynamic simulation of biological pathways.

Harris Wang, Ph.D.

Harris Wang, Ph.D. is an Assistant Professor in the Department of Systems Biology and Department of Pathology and Cell Biology at Columbia University Medical Center. Using approaches from genome engineering, DNA synthesis, and next-generation sequencing, he is currently studying how genomes in microbial populations form, maintain themselves, and change over time, both within and across microbial communities. His goal is to use synthetic biology approaches to engineer ecologies of microbial populations, such as those found in the gut and elsewhere in the human body, in ways that could improve human health.

Core Director

Peter Sims, Ph.D.

Peter Sims, Ph.D. is an assistant professor in the Departments of Systems Biology, and Biochemistry and Molecular Biophysics at Columbia University, and associate director of the JP Sulzberger Columbia Genome Center. Trained in physical chemistry, he is interested in developing new tools for single-cell analysis, applying cutting-edge microscopy, next-generation sequencing, and microfabrication to enable unbiased, system-wide measurements of biological samples. He and his colleagues focus on single-cell transcriptomics and sequencing technology along with novel approaches to proteomics, where current tools lag far behind those available for nucleic acid analysis. He is leading the CaST Molecular Profiling Core.

Project Manager

Aris Floratos, Ph.D.

Aris Floratos, Ph.D. is an assistant professor in the Departments of Systems Biology and Biomedical Informatics and executive research director at the Center for Computational Biology and Bioinformatics. He has led the development of GeWorkbench, a free, open source bioinformatics application that gathers the Department’s software and databases into one integrated software platform.


Project 1: Elucidating the regulatory logic that is responsible for maintaining cancer cell state, independent of specific initiating events and endogenous/exogenous perturbations


In project 1, CaST is attempting to move beyond current approaches for elucidating tumor checkpoints and master regulators, which are largely static and not designed to predict how tumors respond to pharmacological and genomic perturbations over time. Thus, we are developing novel methodologies to mechanistically uncover the regulatory machinery that maintains cancer cell state and governs cell state transition. We are also working to define the role of regulatory networks in implementing distinct tumor phenotypes, from metastatic progression, to immunoevasion, to drug resistance. This effort will leverage and integrate time-course data from gene expression and computationally inferred protein activity profiles, generated by small molecules and RNAi/CRISPR perturbations.

Project 2: Elucidating time-dependent mechanisms of genetic and epigenetic reprogramming of individual cancer cells underlying cancer-state transitions to drug resistance and progression

We are investigating cell state plasticity and tumor/microenvironment heterogeneity, which represent formidable obstacles to successful treatment of human malignancies. This interest is driven by a growing awareness that tumors can harbor distinct niches that include genetically distinct subclones (which have identical or distinct tumor checkpoints), as well as isogenic niches (which present with orthogonal checkpoints). Our goal is to compile a comprehensive inventory of tumor dependencies among such heterogeneous niches that can be targeted pharmacologically, We are studying these mechanisms by developing new methods to identify distinct tumor compartments and heterogeneity at the single-cell level.

Project 3: Developing novel methodologies for the systematic prioritization of compounds and compound combinations capable of abrogating tumorigenesis in vivo

We are developing and validating computational methods for the prioritization of master regulator-targeting drugs and drug combinations to either implement or prevent specific tumor state transitions. This includes inducing irreversible commitment to cell death, preventing progression to a malignant tumor stage, and rescuing drug sensitivity. In addition, we are attempting to address a broad range of questions related to the heterogeneity of tumor response, including mechanisms that allow tumor cells to compensate for MR-targeted therapy. We propose that addressing tumor plasticity and potential escape routes implemented by tumor state reprograming is going to be critically relevant for the chronic management of cancer in patients.


Molecular Profiling Core

A technical requirement for achieving CaST’s scientific goals is access to cost-effective, cutting-edge molecular profiling, high-throughput screening, and single-cell analysis tools utilizing robotics and microfluidics. The Molecular Profiling Core (MPC) provides three key capabilities: 1) PLATESeq: a novel platform for integrating high-throughput screening with genome-wide expression profiling; 2) microfluidics: a highly multiplexed, microfluidic implementation of PLATESeq that produces expression profiles across hundreds of single cells in parallel; and 3) single-cell whole genome sequencing: a pipeline that combines microscopy-based single cell isolation with whole genome amplification for single-cell whole genome sequencing.

Outreach Core

In addition to pursuing research, CaST conducts outreach to disseminate the software and methods developed by the Center, foster discussion on related issues within the larger scientific community, support community-based research efforts, and mentor young scientists. These activities include 1) supporting the DREAM challenges; 2) a cross-training program to help investigators gain experience with complementary methods and perspectives; 3) a “CaST Scholars” program that enables undergraduate students to participate in our research; and 4) organizing scientific meetings on related topics in cooperation with the New York Academy of Sciences Systems Biology Discussion Group.