Cancer Systems Biology Consortium

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.

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.

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..

Cancer Systems Biology Center of HoPE (Heterogeneity of Phenotypic Evolution)


Center Title

Cancer Systems Biology Center of HoPE (Heterogeneity of Phenotypic Evolution)

Center Website

Center Summary

Our Cancer Systems Biology Center of HoPE (Heterogeneity of Phenotypic Evolution) focuses on finding effective treatments for resistant tumors by studying the evolution of phenotypes emergent in late-stage breast and ovarian cancer. Our team will develop a suite of systems-based strategies to understand how genomic diversity, clonal evolution, and phenotypic change interact in the progression toward chemoresistant cancer. To evaluate their potential for therapy, we will then test these dynamic models in clinical trials. We hypothesize that acquired resistance emerges from selection acting on phenotypes during tumor evolution, and that simultaneously measuring and modeling subclone genotypes and phenotypes will identify new, and testable, therapeutic targets.

During treatment, the subclones from every patient’s tumor follow unique evolutionary and resistance trajectories. DNA sequencing has revealed significant subclone genotypic diversity within a single tumor, while RNA sequencing has established phenotypic diversity both across and within subclones. This diversity provides the variation required by evolution under the selective pressure created by the tumor microenvironment and treatment. Using computational tools to organize this complex variation, we will develop a new class of dynamical systems models of subclone evolution and acquisition of oncogenic phenotypes during treatment to identify key chemo-resistant cell states using our unique patient cohorts. These mechanistic models will identify points of vulnerability. Our clinical trials will be aimed at blocking transition of tumors to a resistant state by targeting critical resistant phenotypes.

Our Center is comprised of an Administrative, Education/Outreach, Translational, and Computational Cores, in addition to two complementary projects. The synergies are derived from: 1) the merged parameterization of the evolutionary models drawn from deep longitudinal patient progression studies (Project 1) and broad multisite metastatic tumor analyses (Project 2), both resulting in a model to identify resistant states for clinical targeting; and 2) an integrated computational and experimental framework and resources for dissecting tumor heterogeneity and evolution that will contribute to an improved capacity for personalized cancer therapy. Our multidisciplinary team of systems biologists, bioinformaticians, tumor biologists, pharmacologists, mathematical biologists, and clinicians will tackle these scientific challenges. We will create programs to educate the next generation of scientists in systems biology and inform the community about the latest scientific advances and their impact on treatment strategies. We will provide state of the art tools for the analysis of patient samples and tumor genomic complexity. These studies move beyond prior research by integrating cell population dynamics and cellular phenotypes with cellular genotypes, and will deliver approaches and a knowledge base to block or reverse the transition to a resistant state for advanced stage breast and ovarian cancer patients.


Our center is comprised of a multi-disciplinary team with complementary skillsets. Our team shares common goals and interests that have in many cases spanned a decade.

Principal Investigators

Dr. Andrea Bild

Dr. Andrea Bild trained as a pharmacologist with a specialization in genomics and cancer cell biology. Her research program has established the development and clinical translation of a systems biology framework for personalized medicine genomics. Specifically, her research has enabled 1) investigations of signaling pathways and networks in a physiologically relevant setting: patient tumors; 2) algorithms to personalize matching of effective drugs to patients; and 3) systems-guided clinical trials with novel therapeutic strategies. Dr. Bild has previously worked with every investigator that is part of this team, and has many shared publications and clinical trials with investigators on the grant. Dr. Bild has also developed and founded the Genome Science Program at the University of Utah in order to train students and scientists in genomics and systems biology as well as create a rich collaborative structure for faculty across campus with expertise in this field.

Dr. Fred Adler

Dr. Fred Adler trained as an applied mathematician with specialization in dynamical systems and mathematical ecology, and is Director of the Center for Quantitative Biology. His research program, through his joint appointment in the Departments of Mathematics and Biology, ranges from evolutionary ecology to mathematical oncology. These areas are unified through a commitment to finding key mechanisms in complex systems through mathematical modeling and close interaction with experimentalists and data. He has trained 17 graduate students across this broad range of topics, and his most influential research includes modeling the dynamics of cystic fibrosis to optimize the timing of lung transplantation, the dynamics of populations in spatially subdivided landscapes, and modeling of biodiversity in interacting communities. His expertise in collaboration across disciplinary boundaries, linking dynamical systems with data, and mentoring of trainees will effectively integrate the modeling research and computational core into all aspects of this project.

Professor David Bowtell

Professor David Bowtell is Head of the Cancer Genomics and Genetics Program at the Peter MacCallum Cancer Centre (Melbourne, AU), where he was Director of Research (2000-09) and holds a joint appointment as a Group Leader and Senior Principal Research Fellow at the Garvan Institute for Medical Research (Sydney, AU). He is a Visiting Professor at Dana Farber Harvard Cancer Center (Boston, MA). Prof. Bowtell has an extensive background in human cancer genomics. He is Principal Investigator (PI) for the Australian Ovarian Cancer Study (AOCS), one of the largest population-based cohort studies of ovarian cancer in the world, involving over 3000 women, and CASCADE, a rapid autopsy study. Prof. Bowtell’s research has focused on the classification of ovarian cancer and mechanisms of primary and acquired drug resistance.

Dr. Jeffrey Chang

Dr. Jeffrey Chang is a multidisciplinary cancer genomics researcher specializing in breast cancer, metastasis, and the epithelial-to-mesenchymal transition. He uses a range of approaches, including genomics, systems biology, and cell biology. He has developed novel methods for the analysis of gene expression signatures and next generation sequencing data using computer science and Bayesian statistical methods. In addition to his relevant research experience, Dr. Chang has had over 5 years’ experience as the co-founder and previous co-director of the computational and bioinformatics core at the University of Utah, and was the co-founder and former director of the Biopython project. Dr. Chang will co-direct studies on dissecting clonal structure and functional co-operativity in breast cancer metastasis. He will also direct the Computational Core.
Dr. Adam Cohen is a board certified medical oncologist with a master’s degree in mathematics. His research specializes in clinical trials, genomics, and biomarkers. He has developed and been the PI for three investigator-initiated clinical trials and has been the local PI for many multi-site trials. Dr. Cohen has successfully applied genomic biomarkers in his completed clinical trials, and is the PI for a tissue acquisition protocol that has been used in our successful collection of pleural effusion samples.

Dr. Gabor Marth

Dr. Gabor Marth, Professor of Human Genetics and Co-Director of the USTAR Center for Genetic Discovery, is a computational biologist with a long history of algorithm development for genomic data analysis. He developing sequence analysis tools in the C. elegans and the Human Genome Project, and participated in the SNP Consortium and the International HapMap Project. More recently, he played a leading role in the 1000 Genomes Project (1000GP), developing genomic data standards (SAM/BAM, VCF) that are now de facto standards in genomics. Dr. Marth has established critical variant detection algorithms for detecting somatic cancer mutations and for analyzing tumor tissue heterogeneity at the cellular level.
Dr. Philip Moos was trained as an engineer and cell and molecular biologist. He has used genomics in studies including delineation of patient phenotype segregation and pharmacological effects on cellular systems. He is also a senior administrator for several department and college-wide initiatives in the College of Pharmacy, including a role as Director of Graduate Studies and on the professional program admissions committee. This combination of genomic project expertise and administrative leadership will provide a strong base for his governance of the Translational and Outreach cores for this proposal.

Dr. Sunil Sharma

Dr. Sunil Sharma is Chief of Medical Oncology and an international expert in Drug Development at Huntsman Cancer Institute and University of Utah. Dr. Sharma has successfully directed over 100 clinical trials. He is the Director of Center for Investigational Therapeutics. Dr. Sharma is also an expert on epigenetics and Drug discovery in the epigenetic space. He is an author on more than 100 publications and his laboratory developed SP-2577, the Lysine Specific Demethylase (LSD-1) inhibitor. In addition, his laboratory and clinical trials program (Phase 1 Program) has developed novel therapeutics and biomarkers in the areas of epigenetics and signal transduction pathways.
Dr. Theresa Werner is a board certified medical oncologist who specializes in gynecologic and breast malignancies and clinical trials. Her clinical research program centers around targeted therapy for cancer patients with an emphasis on genomic biomarker driven treatment selection. Dr. Werner also serves as Medical Director of the Clinical Trials Office at Huntsman Cancer Institute and serves as PI on over 40 clinical trials at present. Dr. Werner has been integral in developing an infrastructure at our institution to enable successful complex clinical trials with coordination with radiology, pathology, surgery, pharmacy, and basic scientists.


Phenotype evolution during development of resistance in patients treated with chemotherapy. Shown are violin plots showing enrichment of EMT phenotype in single tumor cells both pre- and post-treatment.

Overview of our center’s research. Project 1, focused on evolution of tumors over time and approaches for reinstatement of chemosensitivity, will develop dynamic models that measure tumor cell chemo-response states overusing serial collections of patient tumors collected during chemotherapy treatment. Project 2 will identify common driver phenotypes in space, using multi-site metastatic cancer, and find therapeutic regimens targeting cooperative phenotypes in heterogeneous tumors. For both projects, clinical trials will test models for effective reversal of drug resistance evolution.

Project 1. Dynamic genomic and microenvironmental models of chemoresistance

PIs: Bild, Adler, Sharma; co-Is: Werner, Bowtell


Breast and ovarian cancers are heterogeneous diseases, as a typical tumor contains multiple “subclones”, which are defined as evolutionarily related subpopulations of cells with a different complement of somatically acquired DNA mutations and phenotypes. When chemotherapeutic agents are administered to the patient, some of these subclones may gain a selective advantage and develop resistance to the treatment, resulting in cancer relapse and progression. For this reason, it is imperative to identify these subclones and their evolution across treatment; and to understand how the genomic aberrations within these subclones drive resistance to chemotherapy. We will integrate experimental biology and computational models across temporal samples of patient tumors as they develop a resistant state in order to better understand and combat refractory and terminal cancer. To enable the study of tumor heterogeneity evolution in patients, we will utilize a highly unique collection of metastatic tumor cells from breast and ovarian cancer patients before, during, and after treatments, often across multiple courses of chemotherapy, as well as tumors from a clinical trial taken before and after therapy. We use deep sequencing to find genomic aberrations at each of these time points, and develop systems models to identify the subclones and follow phenotypic changes and their functional impacts of subclone evolution in response to chemotherapy. We hypothesize that 1) Dynamical systems models based on the evolution of subclone structure and acquisition of oncogenic phenotypes during treatment can identify key factors in the development of a chemo-resistant state; and 2) We can delay development of a chemo-resistant cancer state by inhibiting development of phenotypes that emerge over time commonly during treatment. We will model resistant cancer cell populations and both extrinsic and immune microenvironmental factors to identify critical features of acquired resistance and apply these models to a clinical trial aimed at blocking transition to a resistant cancer state. While these components can exhibit co-dependencies, by their nature they can also have vulnerabilities based on these interactive features, and if one can inhibit dependent relationships within a population it may be possible to shift the equilibrium of a tumor from a chemoresistant state to a sensitive state. The algorithms and procedures we are developing in this proposal will for a rational basis for real-time patient monitoring and making treatment choices for refractory patients. The outcomes of this research will deliver approaches to block or reverse the transition to a resistant state for advanced stage breast and ovarian cancer patients.

Project 2. Targeting cooperative phenotypes common in spatial heterogeneity

PIs: Chang, Cohen; co-I: Bowtell
Recent studies in primary tumors have found a remarkable degree of intratumor heterogeneity, where a single tumor is comprised of a range of subclones exhibiting a diversity of phenotypes, including molecular profiles, proliferation capacity, and response to therapies. Although heterogeneity is now widely reported, few studies have investigated the heterogeneity of metastatic tumors at the end stage, despite the fact that metastatic cancer is estimated to be responsible for over 90% of cancer deaths. For breast and ovarian cancer, tumors that progress to metastasis are refractory to treatment. Therefore, there is a great need to determine the mechanisms by which subclonal diversity can affect the metastatic phenotype and underlie the difficulties in treatment. Studying metastatic tumors is difficult due to the challenges in collecting patient tissues. While primary tissues are typically obtained through biopsy, this is rarely performed for metastatic sites. To address this difficulty, we have developed both a rapid autopsy strategy where we collect fresh samples of metastatic tumors within hours of patient death, as well as collections of metastatic tumor biopsies in the clinical trial setting prior to and after drug treatment. These collections enable us to profile multiple metastatic sites and investigate the association between metastatic sites and subclonal evolution in an isogenic background. We propose to leverage this unique data set to investigate the relationship between evolution of tumor subclones during metastatic progression and the phenotypic profiles of these tumors. We hypothesize that, despite the diversity in their genetic mutation profiles, metastatic tumors exhibit clonal dynamics that ultimately leads to convergence on more common cooperative phenotypic networks, and that targeting the key dependencies within this network will lead to increased collapse of the metastatic tumor population. To investigate this, we will profile the tumors by whole genome sequencing, whole exome sequencing, and single cell RNA sequencing. This data, coupled with our newly developed algorithms for dissecting subclonal populations using tree reconstruction algorithms, for eliciting phenotypes from gene expression profiles using Bayesian statistics, and for simulating phenotypic evolution using mathematical models from ecology; will enable us to understand (Aim 1) the subclonal heterogeneity that underlies metastatic initiation and progression; (Aim 2) how cooperative functions evolve to a chemo-refractory signaling network, and therapeutic strategies to target it; and (Aim 3) how these dynamics are manifested human tumors in a clinical trial. Our investigations represent the first characterization of the clonal dynamics of a large multisite metastatic cohort, and will provide a new framework for understanding and treating end-stage tumors based on the evolution of cooperative phenotypes. We will develop these models on patient samples and test them in a unique clinical trial, ensuring the physiological, if not clinical, relevance of our findings.


Translational Shared Resource Core (Moos)


The Translational Shared Resource Core will provide services for both research projects. This core is central to the proposal’s mission as it directly facilitates: 1) collection, processing, pharmacological testing and use of samples from our patient cohorts; and 2) generation and collection of DNA- and RNA-sequencing data, including single-cell sequencing. Specifically, we will collect, process, and maintain patient-derived cells for temporal and spatial samples from the patients we profile. In preparation for sequencing, we will enrich for tumor cells, and separate white blood cells and other normal cell types. For single-cell experiments, we will use microfluidics to isolate individual cells, prior to extracting DNA or RNA that will be amplified for sequencing. The core will also be responsible for comparing sequencing results for bulk tumors with results from single-cell sequencing, which will enable us to continue optimizing our single-cell sequencing process and to perform comparisons that help us better understand temporal and spatial tumor evolution, which is central to the success of the scientific projects.

Computational Core (Chang)

The main purpose of the Computational Core is to support the scientific goals of the center by ensuring correct and reproducible analysis of next generation sequencing data. This will be accomplished through five tasks. 1) Data management: we will store and maintain provenance of the raw and pre-processed data in archives that track relevant metadata, such as creation data and checks on secured servers. 2) Data Preprocessing: we will develop standardized approaches to pre-processing the data, and create reference versions of the pre-processed data ready for further analysis. 3) Algorithm Development: We will coordinate with investigators to develop algorithms for the modeling of tumor heterogeneity and its evolution. The Core will maintain the source code in a git repository and will identify stable working versions that are then tagged and archived. 4) Develop Pipelines: to facilitate the processing of the data, and to ensure its reproducibility, we will develop standardized pipelines for the preprocessing and analysis of the data. 5) Standardize Environments: The processing of next generation sequencing data requires a multitude of software programs, each of which can affect the final result. To mitigate variation due to differences in software, versions, or libraries, we will create standardized analysis environments equipped with validated software and libraries and distribute them as Docker containers.

Education and Outreach Core (Moos and Werner)

This core are to build a singular research community within the consortium, educate students and the community on the latest advances in systems biology, and reach out to cancer advocates and patients regarding the impact of systems biology and cancer heterogeneity on treatment strategies to build excitement for future developments. We will sponsor student exchange programs, seminars, and courses on systems biology, as well as participate in organizations that promote health and cancer awareness. We will invite leaders in systems biology—whose expertise and research interests complement and expand our own—to visit our center sites; meet with our faculty, postdocs, and students; and participate in workshops that encourage spirited dialog and broad participation. We will assess the effectiveness of our outreach efforts through surveys that will provide the feedback necessary to ensure we are meeting our goals.

Administrative Core

The key to our ongoing collaboration has been communication between groups on our weekly to bi-weekly calls and discussions, focused on coordinated project planning and discussion of experiments and results. The Administrative Core will provide oversight of the Center and will manage its day-to-day operations. Specifically, this Core will: 1) schedule and organize meetings among investigators twice a month; 2) provide monthly and yearly summaries of work accomplished, results, and to-do items; 3) manage the budget; 4) plan internal and external advisory panel meetings and implementation of feedback; 5) manage developmental research project selection and support; and 6) perform administrative tasks related to center management.