Systems Analysis of Epigenomic Architecture in Cancer Progression
- Systems Analysis of Epigenomic Architecture in Cancer Progression
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.
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.
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
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
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
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.
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.