Columbia CSBC
Center Title: Cancer Systems Therapeutics (CaST) Center
Project Description: The human microbiome is a major and causal marker across clinical outcomes. Our preliminary results [1] support the feasibility and utility of latent-state probabilistic modeling of microbiome population dynamics. Specifically, we model the latent state as a Gaussian process, which is linearly affected by interventions, and linearly responsible to both observed measurements and clinical outcomes. We demonstrate performance on time-series samples across lymphoma patients throughout several weeks before and after stem cell transplantation. This novel idea in the microbiome domain requires development into broadly useful methodology. This involves several aspects of the probabilistic framework:
  1. How to select features of the microbial abundance data that are most conducive for probabilistic modeling? Can phylogenetic or pathway information assist blind feature-selection methods?
  2. How to most effectively model the internal, latent state of the microbial system? Can distance-based methods for dimensionality reduction (tSNE-related) or general non-linear methods (variational auto-encoders) improve on linear systems (principal component analysis or similar) in terms of performance and interpretability? Can sparsity be utilized?
  3. How to leverage latent states to ask particular scientific questions about interaction between changes in microbial composition, their causes and clinical outcomes?

The intern for this project would ideally have some background in machine learning and experience with Python. The project will involve Bayesian modeling, high dimensional optimization, Python/scikit-learn, and pipeline programming.

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Center Title: Cancer Systems Biology at Yale (CaSBY)
Project Description: Melanoma in humans is one of the deadliest diseases if left untreated. This is in part because humans, like many other animals, are very vulnerable to malignancies of melanomas. In stark contrast, some animals, such as cows and horses, are surprisingly resistant to malignancy of melanomas, even though they do develop primary tumors. In our lab, we investigate the molecular mechanisms that make these animals resistant to malignancy. We have identified a number of signaling pathways that are different between cow and human and have shown that manipulating these can increase the resistance of human cells to cancer cell invasion.

Currently, we are engaged in a fine scale study of gene expression evolution in fibroblast cells to narrow down the list of possible candidate mechanisms. The undergraduate’s project will contribute to this effort. Through an evolutionary comparative and experimental approach, the overarching goal of our work is to find new therapeutic targets that could lower the risk of progression to malignancy in patients. The undergraduate student will be exposed to systems biology, molecular biology, cell biology, and evolutionary biology.

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Cornell PS-OC
Center Title: Cornell Center on the physics of cancer metabolism
Project Description: Metastasis, i.e., the dissemination of cancer cells from the primary tumor to distant sites, is responsible for more than 80% of all cancer deaths. A critical first step of the metastatic cascade is the invasion of cancer cells through basement membranes and dissemination into the surrounding tissues. During this process, cancer cells penetrate interstitial tissue pores and gaps as small as 2 µm in diameter, which is substantially smaller than the size of the nucleus. Transendothelial migration during intra- and extravasation requires passage through even smaller openings. Deformation of the large and relatively rigid nucleus can constitute a rate-limiting step in the ability of cells to migrate through such confined conditions. At the same time, confined migration places substantial physical stress on the cell nucleus and can result in nuclear envelope rupture, DNA damage, and redistribution of nuclear proteins. In this PS-ON REU opportunity, we offer the option to work on several research questions related to the role of the nucleus in confined migration, and the energetic cost it poses on the cells. Examples include investigating the molecular mechanism by which cells squeeze the large nucleus through microscopic pores, measuring the metabolic requirements of confined migration, testing how altering cell metabolism can modulate cell migration modes, elucidating the cause of migration-induced DNA damage, and investigating if nuclear deformation during confined migration can induce changes in chromatin modification and gene expression. The REU summer research will involve a combination of cell and molecular biology with advanced biomedical engineering approaches, including work with microfluidic devices to study confined migration and live-cell imaging using novel fluorescent reporters.

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Center Title: The Cancer Cell Map Initiative
Mentor: Dr. Trey Ideker
Project Description: The mission of the Cancer Cell Map Initiative (CCMI) is to enable a new era of cancer discovery and treatment based on the complete elucidation of the molecular networks underlying cancer. This information will be critical for developing computational models of cancer cells that will enable both basic research and clinical decision-making.

For this summer program, the Ideker Lab at UC San Diego is looking for an undergraduate student to study the use of hierarchical cellular model for analyzing tumor genetic mutations. The student will explore whether a hierarchical model that we have recently constructed for predicting cellular growth can be translated to predict aggressiveness of human cancer. The model will be provided, along with access to tumor exomes from both public and internal sources. The goal is to determine whether and to what extent the model can be used to analyze a patient's exome.

A well qualified applicant will have computer programming and scripting skills with experience in Python including Jupyter Notebooks and libraries such as Pandas, Matplotlib and Scikit-learn. The student should also have some basic knowledge of machine learning and genomic biology. The student will work closely with a postdoctoral fellow in the Ideker Lab and be exposed to a unique hands-on learning opportunity.

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

We propose deep phenotyping of cell types and analyzing spatial association between cancer and immune cell in order to better understand tumor immune microenvironment and their functional consequences by using cyclic immunofluorescence imaging of tissue microarrays (TMAs). Since the complexities of the tumor immune microenvironment contribute to the heterogeneities among various features and populations across different samples, we will identify clinically relevant and important associations and understand tumor microenvironment through multiplexing imaging and advanced imaging analysis.

The summer project involves discovery and integrative image analysis of tumor immune microenvironments using cyclic immunofluorescence imaging. This project involves quantitative image analysis, automated segmentation, feature extraction and classification tasks using machine learning and deep learning techniques. The summer student will work together with graduate students and mentors as a team. S/he will be able to access a unique high performance computing cluster system (Exacloud) and learn state-of-art machine learning and deep learning technique with applications in cancer systems biology.

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Center Title: Systems Analysis of Epigenomic Architecture in Cancer Progression
Mentor: Dr. Tim Huang
Project Description: Chromatin looping plays a key role in bringing a distal ERα/AR-bound enhancer to a promoter for transcriptional gene regulation in response to hormone stimuli. Studies uncovered chromatin compartments called topologically associated domains (TADs) that are generally conserved in their genomic locations between cell types. Their boundaries show a clear demarcation, whereby intra-chromatin interactions are frequent within a compartment. However, the boundaries can be disrupted in cancer cells, attributed to genomic amplification, rearrangement, and deletion. Studies have shown that these newly formed domains are usually smaller in size than original TADs. In addition, their boundaries become ambiguous with intensive intra- and inter-chromatin interactions outside a domain. Our studies suggest that a newly formed TAD can serve as a transcription hub, displaying multiple folding of enhancers originating from different genomic regions into a single cluster for concordant gene regulation. In our lab, we test two central hypotheses: 1) frequent hormone (i.e., estrogen or androgen) stimulation leads to the formation of ERα/AR-specific 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, termed transition TADs, continue to be exploited through chromatin redeployment for hormone-independent transcription. To address these hypotheses, the work focuses on omics mapping of ERα/AR-specific TADs in hormone-sensitive and -resistant cancer cells; building 3D spatiotemporal models of transition TADs in hormone-sensitive and -resistant cancer cells; and characterizing functional attributes of transition TADs that facilitate cancer progression and hormone resistance.

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Center Title: University of Pennsylvania PS-OC
Project Description: The PSOC@Pennfocuses on physical changes of tissues, cells, and nuclei that contribute to cancer growth and possibly initiation. As tumors cells invade and displace normal cells, the tissue often changes physically, frequently becoming stiffer, sometimes softer, often heterogeneously. Physical changes sometimes occur even before the cancer is detectable. Primary liver cancer appears representative as it almost always arises in the setting of end-stage liver fibrosis, termed cirrhosis, with various causes including excess alcohol consumption. Liver stiffness is now being measured clinically in living patients, and initial studies already show patients with stiffer livers are far more likely to develop liver cancer within a few years.

Chromatin remodeling, DNA breaks & Cell migration: Discher group
Cells have been seen to squeeze through small gaps of matrix and other cells in many basic processes that range from immune surveillance to disease, and include invasion of cancer cellsinto nearby tissue or entry into blood capillaries. The nucleus is the largest and stiffest organelle in the cell but a cell can often push, pull, and forcibly distort this chromatin-filled organelle through a constriction. Pulling a flexible polymer into a tube is a classic problem in polymer physics, but any relevance to chromatinwithin a nucleus that is being pulled through a pore is unclear, particularly given the crowding estimated as ∼70% chromatin volume fraction. Also unclear are the effects ornot of double-strand breaksin the DNA backbone of chromatin, although such breaks—which seem to be presentatlow levels in all cells and —have been speculated to be enhanced by cell migrationthrough small pores. When cleaved DNA is stretched by optical trapsin single molecule studies, it is held together by a scaffoldof repair factors , but chromatin is made up of many other cohesion-enhancing proteins, which motivates stretching of cleaved chromatin in intact nuclei of living cells.

This summer project for an undergraduate student will focus on relations between rigidity of the cancerous tumor microenvironment and changes in the nucleus. Tumors often change mechanically, sometimes stiffening, andpotentially impacting the nucleus of invading cancer cells. The summer student will help measure various physical and other biochemical aspects of the nucleus and the DNA within

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Moffitt PS-OC
Center Title: Cheating dynamics in prostate cancer
Project Description: When prostate cancer initially presents as a clinical tumor, the vast majority of cancer cells are dependent upon exogenous androgen (testosterone) for survival and growth. As a result, androgen deprivation therapy (ADT) is initially very effective in reducing tumor size. However, after 1 to 2 years nearly all prostate cancers become resistant to therapy and the men progress to a metastatic Castrate-Resistant Prostate Cancer stage. A common mechanism of resistance to ADT is increased expression of CYP17A1, a key enzyme for androgen synthesis. This generates an autocrine loop that replenishes intratumoral testosterone concentrations. Abiraterone acetate, a CYP17A1 inhibitor, reduces PSA, and improves overall survival. In subjects who initially respond to abiraterone, median time to PSA progression ranges from 5.8 to 11.1 months.

The Moffitt PSOC has developed an evolution-informed method (adaptive therapy) of administering abiraterone that greatly increases the time to progression and permits reduced dosing. In developing the mathematical models for therapy, we see an unexpected evolutionary dynamic – termed “cheating.” CYP17A1 expressing cells produce testosterone (TP cells) that leaks into the tumor intercellular space. As a result, it becomes a “public good” that can support the testosterone dependent (T+) cells despite the absence of systemic testosterone. The T+ cells, in this context, are evolutionary “cheaters” that use testosterone but do not incur the cost of producing it. Our current clinical trial shows evidence for cheating in histological sections and in the response to therapy that is often more rapid than expected for just treatment of the TP cells. In this project, we will apply the evolutionary models of cheating dynamics to the ecology of metastatic castrate resistant prostate cancers and explore its potential role in sensitivity and resistance to abiraterone. This will integrate game-theoretic concepts of producer-scrounger games with tumor heterogeneity and possible therapeutic strategies with broad applicability to this and other tumor cell-cell interactions.

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Johns Hopkins PS-OC
Center Title: Johns Hopkins University Institute for NanoBioTechnology
Project Description: The extracellular matrix (ECM) is a vital component of the cancer microenvironment; it contributes to cancer progression via promotion of cellular migration and cancer metastasis. Additionally, hypoxic conditions (0.1%-5% pO2) are vital to the development of mature and resource-seeking cancer cell phenotypes. In vitro hydrogel models to analyze the impact of hypoxic conditions on cancer cell invasion migration have previously been established. This project focuses on applying existing in vitro platforms to the growth and development of cancer spheroids. The impact of oxygen concentration as a modulator of three-dimensional cancer cell migration will be assessed. This approach will be applied to a variety of cancer cell-types with a focus on Ewing’s Sarcoma (TC-71), Undifferentiated Pleomorphic Sarcoma (UPS) and Prostate Cancer (PC3). Migration and proliferation rates as well as cell migration phenotype will be assessed. Furthermore, this project will include examining interactions between cancer cell spheroids and immune cell populations in physiologically-relevant oxygen gradients. Further materials characterization may be included.

Skills required for this project include, but are not exclusive to: cell culture techniques, hydrogel manufacturing and manipulation techniques, confocal microscopy, and rheology.

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Center Title: Quantitative & Functional Characterization of Therapeutic Resistance In Cancer
Project Description: Heterogeneity of tumors is becoming recognized as a central issue underlying cancer drug resistance, and a number of experimental techniques are being increasingly applied to characterize it at any of a variety of levels – genomic, transcriptomic, proteomic, phenotypic, and so forth – and with respect to different approaches to ascertaining subpopulations (including single-cell analysis, stochastic sampling analysis, and others). A main challenge is how to use this emerging information most effectively to understand in a predictive manner what the best combination of drug treatments should be, both in parallel and in sequence, for any given patient. Our MIT-DFCI CSBC project will feature application of potentially powerful computational approaches for generating this aspired predictive capability, based on a spectrum of mathematical frameworks and aimed at new data being produced within our CSBC as well as data available from other investigators.

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Columbia PS-OC
Center Title: Columbia University Center for Topology of Cancer Evolution and Heterogeneity
Project Description: Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies. This proposition, however, is complicated by spatial and temporal heterogeneity. Furthermore, there is growing evidence of the important role that the tumor micro-environment plays in determining the response to therapy. In glioblastoma multiforme (GBM) most clinical trials on targeted therapy have shown limited clinical success. Single-cell RNA- and DNA-sequencing allow to study the composition of tumors and their micro-environments with single-cell resolution. Using this technology, we plan to study the sub-clonal structure of GBM tumors from several patients from the Columbia University Medical Center, as well as the composition of the tumor micro-environment. We will try to infer commonalities between the genetic and transcriptional alterations of the patients, and how these affect the evolution of the tumors and their response to therapy. To that end, we will also make use of the analytic approaches developed by the Center, building upon techniques of topological data analysis. The undergraduate student will participate in the analysis of the data produced by the sequencing facility and will collaborate in the implementation and development of the algorithms produced by the mathematical core of the Center. A simultaneous background in biology and some quantitative discipline, such as physics, mathematics, or computer science is preferred.

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COH CSBC (Houston TX)
Center Title: Combating Tumor Heterogeneity
Project Description: Our research program is focused on understanding drivers of metastatic progression in breast and ovarian cancer. We are using a systems-based approach to understand how genomic diversity, clonal evolution, and phenotypic change promote metastatic dissemination, progression, and chemoresistance. We hypothesize that after colonization, metastatic tumors evolve to acquire phenotypes that lead to an end stage disease. To understand this progression, we will use a unique data set consisting of single cell profiles of metastatic tumors acquired across sites of metastases. We will develop bioinformatics algorithms to characterize the phenotypes and identify therapeutic targets. We will test our predictions in experimental models, and ultimately in clinical trials to determine if we can predict the “resistant state” of a tumor and a patient’s response to therapies. We will together execute a project that focuses on understanding how single cells with a patient’s tumor change during metastatic progression. We will then block those phenotypes using targeted cancer drugs to reverse the resistant state and re-instate a tumor’s response to chemotherapy.

The summer research project will provide the opportunity to work closely in the context of a multi-institute systems biology center comprised of a multi-disciplinary team of a cancer systems biologist (Chang, Andrea Bild), geneticist (David Bowtell), mathematician (Fred Adler), and medical oncologist clinician (Adam Cohen) to carry out translational research. As we know very little about the cancer that actually kills the patient, we expect our studies will illuminate the landscape of end-stage ovarian and breast cancer. The outcome from this research will be new approaches to block or reverse the transition to a resistant state for advanced stage breast and ovarian cancer patients

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Houston Methodist PS-OC
Center Title: Center for Immunotherapeutic Transport Oncophysics
Project Description: Success in cancer immunotherapy relies on tumor infiltration of T lymphocytes. To stimulate anti-tumor immunity in the non-inflamed cancer types, such as breast and pancreatic cancers, investigators in CITO have developed a dendritic cell vaccine (DC vaccine) platform to generate tumor antigen-specific CD8+ T cells and promote T cell accumulation in tumor tissues. In order to maximize vaccine activity, the DCs need to leave the inoculation site and migrate to lymphatic organs efficiently. We hypothesize that DC migration in the lymphatic system is controlled by a group of key genes, and manipulation of expression of such genes can facilitate DC vaccine accumulation in lymph nodes for antigen processing and presentation. We have set up a screening process to isolate candidate genes.

The summer project involves characterization of individual genes and pathways on DC transport. The student(s) will generate overexpression or knockout constructs, and apply them to modulate expression of the gene(s)-of-interest in DCs. The cells will be transported into the upper chamber of a two-chamber assay system, and cell migration into the bottom chamber will be monitored and quantified. Response to cytokines and chemokines in the bottom chamber will also be determined. The essential roles of the selected gene(s) on DC transport will be further confirmed in an in vivo setting afterwards. Throughout the process, the student(s) will learn a range of techniques in cell biology, molecular biology, and molecular imaging.

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Memorial Sloan-Kettering Cancer Center CSBC
Center Title: The CSBC Research Center for Cancer Systems Immunology at MSKCC
Project Description: The goal of the CSBC Research Center for Cancer Systems Immunology at MSKCC is to bring the tools of systems biology to decipher tumor-immune system interactions in early tumorigenesis, established tumors, and latent disease, and to identify the molecular and systems-level determinants of response to cancer immunotherapies. Our research program combines in vivo studies, in vitro and in silico quantitative modeling, and molecular analysis of patient samples from cancer immunotherapy trials at MSKCC.

Summer undergraduate research opportunities are available within multiple Research Projects in the Center for a student with either a strong computational/quantitative background or a student with an experimental biology background together with significant computational skills. Specific research projects focus on learning machine learning models of dysfunctional epigenetic programs of tumor-infiltrating lymphocytes, building ecological models of cancer and diverse immune cell and stromal cell populations in the tumor ecosystem, and developing quantitative cell-cell interaction models for innate immune cell control of latent disease. A Shared Research Core devoted to droplet sequencing technology development – including single-cell RNA-seq and droplet TCR sequencing – and novel computational methods interacts with all research projects. The undergraduate research student will be teamed up with both a computational/quantitative mentor and an experimental mentor for optimal interdisciplinary training from the Leslie Lab.

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Minnesota PS-OC
Center Title: UMN Physical Sciences in Oncology Center
Project Description: Understanding cancer cell migration in the local tissue microenvironment is critical to advancing cancer therapies (drug testing and screening). Existing studies lack in vitro methods to fully explore how cancer cells migrate in surrounding three-dimensional (3D) tissues. Our research program (team) focuses on utilizing recent advances in extrusion-based 3D printing to generate a new type of biomimetic tumor model (“tumor-on-a-chip”) by precisely capturing the architectural conditions within which cell migrations occur. Given our progress, the student will build vascularized models that more closely resemble the appearance and behavior of natural vessels through a “4D printing” approach, which will allow us to gain better control over the cell alignment and to create structures that more closely mimic in vivo cancer tissues. A step above 3D printing, 4D printing technology, where ‘‘time’’ is integrated as the fourth dimension, can be defined as self-transformation in the form or function of the printed objects upon exposure to predetermined external stimuli, including pressure, heat, current, light, or other energy sources. With this platform established, the student will: (i) gain technical experiences in 3D printing (live cell printing), 3D graphic design (computer-aided design software), synthesizing hydrogel-based biomaterials, cell culture in 3D hydrogel, live cell microscopy (time-lapse imaging), analysis of cellular responses, and computational modeling of hydrogel deformation (folding-mechanism); and (ii) enjoy a cutting-edge research experience at the interface of advanced manufacturing and biomedical engineering and physical oncology.

The student will be co-mentored by Dr. Paolo Provenzano. Dr. Provenzano will train the student on time-lapse microscopy and will support the student's efforts to collect preliminary cell migration data from pancreatic ductal adenocarcinomas cell lines using the use of the bio-printed experimental platform.

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Stanford CSBC
Center Title: Modeling the Role of Lymph Node Metastases in Tumor-Mediated Immunosuppression
Mentors: Dr. Garry Nolan
Project Description: Using multidimensional in situ cytometry to investigate the impact of cellular neighborhood on cytokine production in immune organs during inflammation and cancer.

It has been widely recognized that depending on the readout of local microenvironment – the immune system can create immuno-modulatory conditions that either promote or inhibit disease. In many cases this effect is mediated by combination of pro– and anti- inflammatory cytokines secreted by immune cells infiltrating the afflicted tissue. Curiously, even within a homogeneous population of potential producers only a fraction of cells are actually participating in cytokine production. The nature of factors involved in selection of such cells is unclear. We propose to investigate the impact of local tissue microarchitecture (niche) on capacity of immune cells to produce a particular cytokine profile. To this end our lab has recently developed a highly multiplexed tissue staining technique (CODEX), which is based on reiterative rendering of antibodies barcoded with DNA tags. CODEX enables co-incident imaging of up to 60 intracellular and extracellular protein markers and hence precise identification of cell types and their positional information in the tissue. Due to solubility of cytokines in the intracellular medium and short time between secretion and consumption by target cells the antibody–protein based detection of cytokine secreting cells is technically hard. We therefore propose to merge protein based CODEX with in situ RNA FISH for co-detection of the surface markers (for cell type identification) with mRNA of selected cytokines. Alternatively rather then using RNA-FISH we will also employ cre-driven GFP tagging of cytokine genomic loci for the same purpose. The goal of this project is to identify cellular niches driving the cytokine response and potentially pathways and or cellular population that can be used for its modulation or “correction”.

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