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The 2026 MC2 Center Virtual Symposia bring together the CCBIR, CSBC, MetNet, PS-ON and Cancer TEC for one-day Symposia focused on Cross-Cutting Themes. Identified by all of you, this year’s Symposia will be on Patient-Specific Models of Cancer, The Role of the Immune System, Tumor & Metastasis Microenvironments, and Opportunities in AI.
Symposi will feature talks on breakthroughs and challenges, collaborative sessions, keynote speakers, and more.
Symposia Dates, details on abstract submission, and registration are coming soon!
Dr. Nick Vitanza Dr. Nick Vitanza is an Associate Professor at the University of Washington and a physician-scientist supported by an NIH Method to Extend Research in Time (MERIT)(R37) Award. He completed his pediatric oncology fellowship at New York University, followed by a pediatric neuro-oncology fellowship and postdoctoral research at Stanford University. At Seattle Children’s, he is a pediatric neuro-oncologist, the Scientific Director of the Brain Tumor Research Program, and the CNS CAR T cell Lead. Clinically, he has designed multiple intracranially-dosed first-in-human trials delivering HER2-, EGFR-, B7-H3-, and multi-antigen-targeting CAR T cells to children with CNS tumors. In the Lab, he studies aggressive pediatric brain tumors such as DIPG/DMG, ATRT, and medulloblastoma with a focus on translating discoveries to clinical trials. His team has developed CNS cancer models, identified epigenetic and immunologic cancer vulnerabilities, and engineered cellular therapeutics such as chemotactically-enhanced B7-H3 CAR T cells. His findings have been published in Cancer Cell, Cancer Discovery, Nature Communications, and Nature Medicine. A strong advocate for swift and transparent collaboration, Dr. Vitanza leads international efforts dedicated to curing pediatric brain and spinal cord tumors and participated in the White House’s Cancer Moonshot Brain Cancers Forum. The completed first-in-human phase 1 trial of repeatedly dosed B7-H3 CAR T cells for children with DIPG found the treatment to be feasible and tolerable. Encouraging clinical results have led to a phase 2 pivotal registration trial set to open this summer. Now, new immunocompetent laboratory models that account for the tumor immune microenvironment are providing a platform to further optimize B7-H3 CAR T cells and better understanding mechanisms of neurotoxicity. Session Chair: Valerie Weaver Dr. Weaver is Professor and Director of the Center for Bioengineering and Tissue Regeneration in the Department of Surgery, with a cross appointment in Bioengineering and Therapeutic Sciences at UCSF. She has a BSc in Chemistry from the University of Waterloo, and an Honors BSc and PhD in Biochemistry from the University of Ottawa, Canada. She completed brief postdoctoral training at the Canadian NRC in Ottawa, Canada, and thereafter trained extensively with MJ Bissell at LBNL, Berkeley California. After completing her training, she joined the Pathology Department at the University of Pennsylvania and IME after which she relocated to San Francisco to join the Surgery Department at UCSF. In recognition of her seminal contributions on the biochemical and biophysical properties of the extracellular matrix in tissue development, morphogenesis and cancer she is an elected fellow of the AIMBE and ASCB and has received numerous accolades including DOD BCRP Scholar and Scholar expansion awards, an ASCB WICB Midcareer award, The Colin Thomson Medal of Honor from Worldwide Cancer Research, an Outstanding Investigator award from NC, the Shu Chien Lifetime achievement award from BMES and most recently the 2025 ASCB Keith Porter Lecture amongst other awards. Forcing inflammation to drive tumor initiation and progression Valerie Weaver and colleagues Director, Center for Bioengineering and Tissue Regeneration Professor, Departments of Surgery and Bioengineering and Therapeutic Sciences University of California, San Francisco The Weaver group uses cultured 3D spheroids and organoids, and in vivo PDX and syngeneic models with tuned ECM stiffness, as well as genetically engineering mouse models in which ECM stiffness and integrin mechanosignaling are manipulated to explore the interplay between inflammation and the ECM in cancer risk, progression and treatment. We showed that infiltrating macrophages induce ECM deposition, remodeling and crosslinking to stiffen the ECM and drive tissue fibrosis. We determined that the stiffened ECM thereafter increases STAT3 activity to elevate cytokine levels that further potentiate inflammation. Macrophages exposed to a stiff stroma undergo a YAP/TAZ-dependent pro-tumorigenic synthetic ECM metabolic switch that alters tissue metabolites to repress T cell dependent anti-tumor activity. Consistently, our studies revealed that a stiff ECM, via integrin-mechanosignaling, enhances signaling to disrupt tissue organization, promote cell growth and survival and drive invasion and motility that foster malignant progression. The stiffened ECM also induces an epithelial to mesenchymal transition, enhances tumor cell dissemination and represses anti-tumor immunity to support metastasis. Intriguingly, the infiltrating macrophages also respond to the stiff ECM by elevating ROS production to increase lipid aldehyde-mediated DNA damage that induces pro-tumorigenic pro-metastatic mutations in the epithelium. Chromatin analysis of organoid models revealed that a stiff ECM renders regions within the chromatin that harbor many frequently mutated tumor suppressors including p53 and BRCA1 more accessible, suggesting that a stiff stroma predisposes the epithelium to tumor-associated mutations that promote malignancy. Consistently, women with high mammographic density and those with germline BRCA1 mutations, who exhibit a heighted risk for breast cancer, have a stiffer stroma that contains a higher frequency of pro tumor ECM synthetic tumor-associated macrophages, and their epithelium shows elevated nuclear lipid aldehyde modifications and DNA damage. Thus, a stiffened stroma, in addition to promoting malignant progression, may increase DNA mutations that initiate malignancy. Sarah Heilshorn Sarah Heilshorn is the Rickey/Nielsen Professor of Engineering and Chair of the Department of Materials Science & Engineering at Stanford University, where she is also a Bass University Fellow in Undergraduate Education. Her laboratory integrates concepts from materials science and protein engineering to design new, bioinspired materials for 3D bioprinting, regenerative medicine, and human tissue modeling. Her recognitions include the Senior Scientist Award from the International Society for Biofabrication, a New Innovator Award from the National Institutes of Health (USA), and the Career Award from the National Science Foundation (USA). She is an elected Fellow of the American Institute for Medical and Biological Engineering and currently serves as an Editor for Acta Biomaterialia and on the Board of Directors for the Tissue Engineering and Regenerative Medicine International Society (TERMIS) Americas chapter. Bioengineering technologies for cancer organoid models During development and disease, a cell’s behavior is directly influenced by its surrounding microenvironment, including the extracellular matrix (ECM). Thus, when designing cancer organoid models, ideally each cellular sample would be cultured in its own customizable biomaterial that matches the specific disease state found in vivo. To fulfill this need, my lab designs bespoke biomaterials that can be tailored to fit a range of applications. In one demonstration, I present a family of adaptable biomaterials that support the growth of patient-derived pancreatic ductal adenocarcinoma (PDAC) organoids. Through control of the matrix, we find that PDAC becomes significantly more chemoresistant in stiffer matrices due to mechanosignaling through CD44 receptors, which leads to upregulation of efflux pumps. Excitingly, this chemoresistance is reversible, with PDAC regaining sensitivity to frontline chemotherapy upon softening of the matrix or blockade of CD44 signaling. In a second example, I present a new “pick-and-place” 3D-bioprinting strategy for the spatial positioning of glioma organoids and neural organoids within an adaptable support matrix. Using this method, the organoids fuse together into neural “assembloids” composed of dorsal- and/or ventral-patterned neural organoids together with patient-derived brain cancer spheroids. We envision that these two technologies will be used together in the future to create personalized tissue models of individual patients. Li Ding Andrew Oberst Session Chair: Kristin Swanson (Cedars Sinai) Alexander R. A. Anderson Alexander R. A. Anderson, PhD is Founding Richard O. Jacobson Chair of the Integrated Mathematical Oncology (IMO) Department and Director of the Center of Excellence for Evolutionary Therapy at Moffitt Cancer Center. For the last 20 years he has been developing mathematical models of many different aspects of tumor progression and treatment that require a tight dialogue between theory and experiment. Due to his belief in the crucial role of mathematical models in cancer research and treatment he moved his group from the Mathematics Department at Dundee University to the Moffitt Cancer Center in 2008 to establish the IMO department. Since his arrival, cancer treatment has become a significant driver of his research and using mathematical models that connect our basic science understanding of a given cancer with clinical translation. This has led to the development of evolutionary therapies that seek to control cancer rather than eradicate it. Through smart treatment scheduling and dosing, with combination therapies as well as microenvironment targeted treatments, he has developed novel strategies for prostate, breast, lung and skin cancer treatment. As director for the 1st center of Evolutionary Therapy he has helped facilitate 10 active evolutionary clinical trials at Moffitt that use mathematical models as part of their decision process. Through the development of digital twins based on explicit patient treatment response dynamics and mathematical modeling he has predicted clinical trial outcomes (Phase i trials) and optimized individual patient treatment decisions in the Evolutionary Tumor Board (ETB). The ETB consists of an integrated team of clinical physicians, evolutionary biologists, and mathematicians. The ETB provides guidance on optimal evolution based treatment strategies for individual patients by rigorously formulating and investigating underlying hypotheses for treatment failure and success using mathematical models, patient data and treatment efficacy. Sidi Chen Sidi Chen joined the Yale Faculty in 2015 in the Department of Genetics, Systems Biology Institute, and Yale Cancer Center. His research focuses on providing a global understanding of biological systems and development of novel breakthrough therapeutics. Chen developed and applied genome editing and high-throughput screening technologies, precision CRISPR-based in vivo models of cancer, global mapping of functional drivers of cancer oncogenesis and metastasis. He is leading a research group to seek global understandings of the molecular and cellular factors controlling disease progression and immunity. His group continuously invents versatile systems that enable rapid identification of novel targets and development of new modalities of cancer immunotherapy, cell therapy and gene therapy. His goal is to uncover novel insights in cancer and various other immunological diseases and develop next generation therapeutics. Dr. Chen received a number of national and international awards including the Pershing Square Sohn Prize, DoD Era of Hope Scholar, NIH Director’s New Innovator Award, Blavatnik Innovator Award, Yale Cancer Center Basic Science Research Prize, AACR NextGen Award for Transformative Cancer Research, Ludwig Foundation Award, Damon Runyon Cancer Research Fellow, Dale Frey Award for Breakthrough Scientists, TMKF Innovative/Translation Cancer Research Award, BCA Exceptional Research Grant Award, MRA Young Investigator Award, V Scholar, Bohmfalk Scholar, Ludwig Family Foundation Award, St. Baldrick’s Foundation Award, CRI Clinic & Laboratory Integration Program (CLIP), MIT Technology Review Top 35 Innovators (Regional), and Sontag Foundation Distinguished Scientist Award. Sidi Chen Sidi Chen joined the Yale Faculty in 2015 in the Department of Genetics, Systems Biology Institute, and Yale Cancer Center. His research focuses on providing a global understanding of biological systems and development of novel breakthrough therapeutics. Chen developed and applied genome editing and high-throughput screening technologies, precision CRISPR-based in vivo models of cancer, global mapping of functional drivers of cancer oncogenesis and metastasis. He is leading a research group to seek global understandings of the molecular and cellular factors controlling disease progression and immunity. His group continuously invents versatile systems that enable rapid identification of novel targets and development of new modalities of cancer immunotherapy, cell therapy and gene therapy. His goal is to uncover novel insights in cancer and various other immunological diseases and develop next generation therapeutics. Dr. Chen received a number of national and international awards including the Pershing Square Sohn Prize, DoD Era of Hope Scholar, NIH Director’s New Innovator Award, Blavatnik Innovator Award, Yale Cancer Center Basic Science Research Prize, AACR NextGen Award for Transformative Cancer Research, Ludwig Foundation Award, Damon Runyon Cancer Research Fellow, Dale Frey Award for Breakthrough Scientists, TMKF Innovative/Translation Cancer Research Award, BCA Exceptional Research Grant Award, MRA Young Investigator Award, V Scholar, Bohmfalk Scholar, Ludwig Family Foundation Award, St. Baldrick’s Foundation Award, CRI Clinic & Laboratory Integration Program (CLIP), MIT Technology Review Top 35 Innovators (Regional), and Sontag Foundation Distinguished Scientist Award. Kristin Swanson Dr. Swanson is an internationally recognized mathematical oncologist focused on delivering optimal treatment to patients with brain cancer. Her research lab is driven by the motto that “every patient deserves their own equation.” As a mathematical oncologist, Dr. Swanson’s research interests are in clinical trial design and predictive mathematical modeling for the treatment of patients with brain cancer. Her laboratory group works to generate patient-specific predictive models to effectively and accurately predict tumor growth and response to therapy in individual patients. The group works with clinical and research teams to bring these innovations to the clinic while identifying new predictive models. This work can also be used to inform novel therapy design, resulting in better treatment and outcomes for patients. Dr. Swanson is recipient of the 2017 Mayo Clinic Service Award for Diversity and Inclusion, the 2008 University of Washington Award for Undergraduate Research Mentor of the Year. Her research efforts have been supported through funding by the NIH, the Ivy Foundation, the James S McDonnell Foundation, the James D. Murray Endowed Chair at the University of Washington, Mayo Clinic and Cedars-Sinai. Mukund Varma Dr. Stephen Yi Dr. Stephen Yi is Founding Director of the Center for AI and Biomedical Discovery (AIBD) at Neuroscience Institute, Baylor College of Medicine. He's also Director of Bioinformatics at Baylor Research Institute. Dr. Yi was one of the first to pioneer the 'functional variomics' technology, and demonstrate its use for interpreting mutations for their functional consequence in signaling networks. His lab seeks to understand genetic/genomic variation and signaling perturbation in health and disease, by integrating AI, deep learning, systems/network biology and single cell multi-omics approaches. Dr. Yi has received several honors/awards in his career, including NIH Outstanding Investigator, NCI IMAT Award, Komen CCR Award, TAMEST Medicine Finalist, Scialog Fellow, NIH Career Development Award. He is an active member of the NCI Cancer Systems Biology consortium and the GREGoR consortium. Dr. Yi is also co-chair of the Flagship Writing Group and Disease Focus Group at the NIH IGVF consortium. Dr. Yi was a key organizer for Susan Komen Foundation's inaugural Hackathon Challenge. He also served as co-Chair on the organizing committee for the inaugural CPRIT Computational Oncology Symposium. Dr. Yi was invited to chair and organize a special session on functional genomic mutations in the ISMB and ASHG annual meetings. He has been frequently invited to speak at national institutions or academic conferences, such as the CSHL network biology meeting. Dr. Yi's laboratory has made many seminal discoveries to reveal complex gene regulatory networks in the cell and how perturbation of these signaling networks leads to human disease. His pioneering studies on computational modeling of interactome networks and gene regulatory systems are supported by a strong publication record in high-impact journals, such as Cell, Nature, Nat Biotechnol, Cancer Cell, Nucleic Acids Res, Nat Commun, Nat Comput Sci, etc. Alexander R. A. Anderson Alexander R. A. Anderson, PhD is Founding Richard O. Jacobson Chair of the Integrated Mathematical Oncology (IMO) Department and Director of the Center of Excellence for Evolutionary Therapy at Moffitt Cancer Center. For the last 20 years he has been developing mathematical models of many different aspects of tumor progression and treatment that require a tight dialogue between theory and experiment. Due to his belief in the crucial role of mathematical models in cancer research and treatment he moved his group from the Mathematics Department at Dundee University to the Moffitt Cancer Center in 2008 to establish the IMO department. Since his arrival, cancer treatment has become a significant driver of his research and using mathematical models that connect our basic science understanding of a given cancer with clinical translation. This has led to the development of evolutionary therapies that seek to control cancer rather than eradicate it. Through smart treatment scheduling and dosing, with combination therapies as well as microenvironment targeted treatments, he has developed novel strategies for prostate, breast, lung and skin cancer treatment. As director for the 1st center of Evolutionary Therapy he has helped facilitate 10 active evolutionary clinical trials at Moffitt that use mathematical models as part of their decision process. Through the development of digital twins based on explicit patient treatment response dynamics and mathematical modeling he has predicted clinical trial outcomes (Phase i trials) and optimized individual patient treatment decisions in the Evolutionary Tumor Board (ETB). The ETB consists of an integrated team of clinical physicians, evolutionary biologists, and mathematicians. The ETB provides guidance on optimal evolution based treatment strategies for individual patients by rigorously formulating and investigating underlying hypotheses for treatment failure and success using mathematical models, patient data and treatment efficacy. Session Chair: Vivian Lee (Patient Advocate, Stanford University) James Zou James Zou is an associate professor of Biomedical Data Science, CS and EE at Stanford University. He works on developing cutting-edge AI for biomedical applications. His group developed many widely used innovations including EchoNet AI (FDA cleared for assessing cardiac function), Gradio (used by over a million developers), and SyntheMol (NY Times 2024 Good Tech). He has received the Overton Prize, Sloan Fellowship, NSF CAREER Award, two Chan-Zuckerberg Investigator Awards, a Top Ten Clinical Achievement Award, best paper awards at ICML and other AI conferences, and faculty awards from Google, Amazon, Adobe and Apple. AI agents to accelerate biomedical discoveries AI agents—large language models equipped with tools and reasoning capabilities—are emerging as powerful research enablers. This talk will explore how agentic AI can accelerate scientific discoveries. I’ll first introduce the Virtual Lab—a collaborative team of AI scientist agents conducting in silico research meetings to tackle open-ended research projects. As an example application, the Virtual Lab designed new nanobody binders to recent Covid variants that we experimentally validated. Then I will introduce the Virtual Biotech, a platform where tens of thousands of AI agents work together to advance drug discovery and development. Dr. Olivier Elemento Olivier Elemento, PhD, is the Director at the Englander Institute for Precision Medicine at Weill Cornell Medicine, a large multi-disciplinary institute that uses precision medicine technologies and informatics to uncover the molecular mechanisms of disease and individualize disease treatment and prevention. In addition, he is a full Professor of Systems and Computational Biomedicine, Associate Director of the Institute for Computational Biomedicine at Weill Cornell Medical College, and Associate Director of the Clinical and Translational Science Center at Weill Cornell Medical College. Dr. Elemento’s research group combines Big Data, Artificial Intelligence with experimentation and genomic profiling to accelerate the discovery of cancer cures. Dr. Elemento and his team have published over 500 scientific papers in the area of precision medicine, genomics, epigenomics, artificial intelligence, computational biology and drug discovery. He is a recipient of awards including the NSF CAREER Award, Siegel Family Award for Outstanding Medical Research, the Irma T. Hirschl Career Scientist Award and the Daedalus Fund for Innovation Award. His research group has developed new assays and analytical pipelines for cancer genome and epigenome analysis, clinical sequencing and precision medicine. They led the development of the first New York State approved whole exome sequencing test for oncology and pioneered new methods for assessing tumor-driving pathways, the immune landscape of tumors and predicting immunotherapy responders. In addition, Dr. Elemento and his lab developed methodologies to repurpose existing drugs to target specific pathways, predict drug toxicity and identify synergistic drug combinations. His research has been highlighted in broad audience media outlets, including the New York Times Magazine, NPR, Wired, Popular Science, CBS, Gizmodo, and Huffington Post. Cancer genomes carry the information needed to guide therapy, but turning that information into treatment decisions remains hard. This talk traces an AI pipeline that runs from raw tumor data to therapeutic insight. I will start with whole-genome sequencing as a comprehensive view of the tumor, then describe Tessera, a foundation model that learns representations of genomic alterations including copy-number changes. I will turn to drug target discovery with BANDIT, a Bayesian machine-learning approach that integrates diverse data types to predict drug targets. BANDIT identified the molecular target of ONC201, a compound that had advanced in trials without a known mechanism; that insight helped explain its activity and supported its development, and ONC201 (dordaviprone) has since received FDA approval for H3 K27M-mutant glioma. I will close on where these models earn clinical trust through independent validation and careful data governance — the conditions for deploying AI safely in oncology. James Zou James Zou is an associate professor of Biomedical Data Science, CS and EE at Stanford University. He works on developing cutting-edge AI for biomedical applications. His group developed many widely used innovations including EchoNet AI (FDA cleared for assessing cardiac function), Gradio (used by over a million developers), and SyntheMol (NY Times 2024 Good Tech). He has received the Overton Prize, Sloan Fellowship, NSF CAREER Award, two Chan-Zuckerberg Investigator Awards, a Top Ten Clinical Achievement Award, best paper awards at ICML and other AI conferences, and faculty awards from Google, Amazon, Adobe and Apple. AI agents to accelerate biomedical discoveries AI agents—large language models equipped with tools and reasoning capabilities—are emerging as powerful research enablers. This talk will explore how agentic AI can accelerate scientific discoveries. I’ll first introduce the Virtual Lab—a collaborative team of AI scientist agents conducting in silico research meetings to tackle open-ended research projects. As an example application, the Virtual Lab designed new nanobody binders to recent Covid variants that we experimentally validated. Then I will introduce the Virtual Biotech, a platform where tens of thousands of AI agents work together to advance drug discovery and development. Dr. Olivier Elemento Olivier Elemento, PhD, is the Director at the Englander Institute for Precision Medicine at Weill Cornell Medicine, a large multi-disciplinary institute that uses precision medicine technologies and informatics to uncover the molecular mechanisms of disease and individualize disease treatment and prevention. In addition, he is a full Professor of Systems and Computational Biomedicine, Associate Director of the Institute for Computational Biomedicine at Weill Cornell Medical College, and Associate Director of the Clinical and Translational Science Center at Weill Cornell Medical College. Dr. Elemento’s research group combines Big Data, Artificial Intelligence with experimentation and genomic profiling to accelerate the discovery of cancer cures. Dr. Elemento and his team have published over 500 scientific papers in the area of precision medicine, genomics, epigenomics, artificial intelligence, computational biology and drug discovery. He is a recipient of awards including the NSF CAREER Award, Siegel Family Award for Outstanding Medical Research, the Irma T. Hirschl Career Scientist Award and the Daedalus Fund for Innovation Award. His research group has developed new assays and analytical pipelines for cancer genome and epigenome analysis, clinical sequencing and precision medicine. They led the development of the first New York State approved whole exome sequencing test for oncology and pioneered new methods for assessing tumor-driving pathways, the immune landscape of tumors and predicting immunotherapy responders. In addition, Dr. Elemento and his lab developed methodologies to repurpose existing drugs to target specific pathways, predict drug toxicity and identify synergistic drug combinations. His research has been highlighted in broad audience media outlets, including the New York Times Magazine, NPR, Wired, Popular Science, CBS, Gizmodo, and Huffington Post. Cancer genomes carry the information needed to guide therapy, but turning that information into treatment decisions remains hard. This talk traces an AI pipeline that runs from raw tumor data to therapeutic insight. I will start with whole-genome sequencing as a comprehensive view of the tumor, then describe Tessera, a foundation model that learns representations of genomic alterations including copy-number changes. I will turn to drug target discovery with BANDIT, a Bayesian machine-learning approach that integrates diverse data types to predict drug targets. BANDIT identified the molecular target of ONC201, a compound that had advanced in trials without a known mechanism; that insight helped explain its activity and supported its development, and ONC201 (dordaviprone) has since received FDA approval for H3 K27M-mutant glioma. I will close on where these models earn clinical trust through independent validation and careful data governance — the conditions for deploying AI safely in oncology. Christine Suver Christine Suver, PhD, PMP., is Chief Privacy and Compliance Officer at Sage Bionetworks, where she leads efforts to develop data governance frameworks that enable responsible data sharing while protecting participant privacy. Her work addresses the practical challenges of sharing sensitive biomedical data, obtaining meaningful informed consent, adapting to evolving technologies, promoting ethical use of AI, and translating complex privacy regulations into actionable policies. Dr. Suver contributed to initiatives like the All of Us Research Program and the National COVID Cohort Collaborative (N3C). She currently leads the data governance strategy for large research collaboratives such as the NIH Accelerating Medicine Partnership Program, the SysBio Fairplex initiative, and the ELITE Portals Before joining Sage Bionetworks, Dr. Suver worked at Lifespan Bioscience and Merck & Co. Inc. She holds a Master's in bioengineering from ENSIA AgroParisTech (France) and a Ph.D. in Biochemistry from the University of Washington (USA). Vivian Lee A breast cancer survivor for over 26 years, Vivian applies her personal experience as a patient diagnosed during infertility treatment, and her professional experience as a biotechnology industry consultant, to her cancer advocacy work. Vivian collaborates with research investigators at academic institutions across the US and abroad to provide patient perspective in shaping grant applications and research projects. She is an Advocate Advisor to the University of California’s Athena Breast Health Network for its WISDOM Study on personalized breast cancer screening, as well as for its Patient Counts initiative to provide cancer care navigation for under-resourced communities. With American Cancer Society’s California Chinese Unit, she was active in promoting cancer education resources to Asian American communities. As a member of Bay Area Young Survivors, she mentors young women newly diagnosed with breast cancer to provide emotional support and networking resources. She is a frequent speaker at cancer conferences worldwide, and helps train young research investigators to optimize effectiveness of their lay abstracts in conveying the impact of their research to the non-scientific community. Orion Banks Orion Banks joined Sage Bionetworks in October 2022 after earning a PhD in Chemistry from the University of Oregon, where he studied chromatin organization and dynamics using synthetic biology, biochemistry, and sequencing-based techniques. At Sage Bionetworks, Orion works across several data coordination projects, including the Multi-Consortia Coordinating (MC2) Center, where he helps researchers intentionally prepare and share experimental data to support secondary analysis. Aditya Nath Aditya Nath is a Biomedical Data Manager with experience spanning device development, imaging science, and large-scale data infrastructure. He holds a Master of Science in Biomedical Engineering from Saint Louis University, where he developed a foundation in computational modeling, and has since built a career across the full arc of biomedical research, including work at the Allen Institute for Cell Science, where he contributed to both imaging and computational initiatives. He now works at Sage Bionetworks, supporting multiple disease-focused coordinating centers including the MC2 Center, where he collaborates with research teams to curate publications, datasets, and tools while leading data ingestion efforts that make scientific resources more accessible to the broader community. Ziwei Pan Ziwei Pan is a Data Scientist at Sage Bionetworks specializing in multi-omics analysis and machine learning applications in precision medicine. She holds a PhD in Biomedical Science from UConn Health, where she gained experience in computational methods evaluation and pipeline implementation for cancer genomics. At Sage, she works across multiple coordinating centers including the MC2 Center, harmonizing data for AI applications, building reproducible analysis pipelines, and applying machine learning methods to oncology and rare disease research. Sharing the products of scientific research often includes harmonizing metadata, reviewing documentation, and time-consuming manual entry, each of which presents barriers to dissemination. This interactive workshop introduces participants to Curator, a metadata collection tool designed to simplify and expedite the process of documenting resource metadata. Through integration with Synapse, Curator enables users to capture structured descriptions of shared resources and directly integrate this information into the Cancer Complexity Knowledge Portal. Users also have access to an AI assistant that intelligently infers and suggests entries based on their data and context. During this workshop, we'll begin by exploring why rich, accurate metadata underlies effective resource sharing: well-documented datasets attract more citations, pass repository compliance checks, and enable secondary use by other researchers. Participants will have the opportunity to interact with Curator, where they can leverage the AI assistant to curate example resources derived from real-world scenarios. Attendees will leave with practical, step-by-step instructions for using Curator to capture metadata for their own shared resources, including how to access the tool, review and edit agent suggestions, and store finalized metadata in Synapse. No prior experience with AI tools is required. Please note that a certified Synapse account is required to access the Curator demo. You can find instructions on setting up your Synapse account for Curator here. Once you have your account, please request access to the demo materials via the Synapse Join Team link on this page. Amber Nelson, Community Manager, MC²Center Dr. Roussos Torres Dr. Roussos Torres is an Assistant Professor of Medicine in the Division of Medical Oncology at Keck School of Medicine at USC. She is a physician scientist whose clinical focus as a medical oncologist is focused in breast cancer. Dr. Roussos Torres’ research focus is in tumor immunology and immunotherapy. Dr. Roussos Torres is the Co-Leader of the Tumor Immune Microenvironment Program at the Norris Comprehensive Cancer Center and she runs a translational research program which includes basic science research aimed at identifying mechanisms to control innate immune response in breast cancer and clinical trials with the goal of broadening response to checkpoint inhibition across different stages of disease. Dr. Roussos Torres is passionate about training the next generation of translational researchers and improving patient outcomes. Cancer Systems Immunology unravels complexity of reversing immune suppression in metastatic breast cancer Background: Combination therapy aimed at modulating the tumor microenvironment (TME) is a robust strategy to improve response to checkpoint inhibition and broaden indications for use in patients with metastatic breast cancer. The epigenetic modulator, entinostat when combined with dual checkpoint blockade; nivolumab and ipilimumab demonstrated promising results in our Phase Ib trial (NCI-0944) and in our recent meta-analysis (AACR-3225, 2025). Use of a cancer systems immunology approach accelerated discovery of the complex mechanism of response to treatment. Integration of preclinical modeling and mechanistic investigations also reveals site specific immunity contributes to response efficacy. Lastly, we demonstrate the potential for math modeling to predict response and inform organ specific response, a powerful tool with potential for use toward a more personalized approach for patients. Methods: To identify mechanisms of response to combination therapy in a preclinical model, we used knowledge-guided subclustering of single-cell RNA-sequencing data and cell circuits analysis to predict salient interactions. Multiparametric flow cytometry and ex-vivo immune suppression assays were used to validate preclinical findings across metastatic organs. Imaging mass cytometry and bulk RNA sequencing of patient samples were used to validate findings in patients. Derivation of dynamic mathematical models of tumor-immune modulatory responses were then fit through innovative use of both preclinical (sequencing) and clinical (proteomics) data – to predict that a combination of effects on the TME is necessary for response. Adaptation of this mathematical model was then made to determine its potential for use in prediction of site-specific response in metastatic lesions. We introduced methods employing posterior parameter sampling and simulation to create virtual tumor populations, enabling extrapolation beyond the data to predict probabilities of response in metastatic lesions, even when no data exists at that site. Results: In the mouse lung and liver TME, we identified cell states and salient interactions, of which myeloid, T cell, and B cell subpopulations were most affected by treatment in mice bearing metastatic breast cancer treated with combination therapy. Functional immunologic assays verified inhibition of the ICAM pathway in myeloid cells partially recapitulated treatment effects of entinostat and dual ICIs on CD8+ T cells. We also found evidence that treatment increased anti-tumor IgG production. Analysis of patient biopsies via spatial proteomics corroborated preclinical findings: in responders, we observed increased B cell activation, mature tertiary lymphoid structures (TLS), and increased CD8+ T cell—macrophage distances with treatment. We demonstrated clinical utility of the mathematical model via Bayesian parameter inference with clinical responses measured by RECIST. This revealed that only the immunosuppression parameters were predictive of response; parameters controlling cytotoxicity were uninformative. We also show that the model can predict response at sites that have yet to develop disease—a tool which could be considered for future trials to predict overall response rates based on mechanism of drug response. Conclusions: We conclude that epigenetic modulation via HDACi induces a carefully orchestrated set of changes in plasma cells and CD8 T cells with MDSCs and macrophages to sensitize the TME to checkpoint inhibition. Significant changes in TLS formation and macrophage –T cell interactions in biopsies from patient responders validate findings. More broadly we provide a framework for the discovery of cell-cell interactions that control responses in complex TMEs. We also demonstrate how interdisciplinary data integration fuels this new field of cancer systems immunology to accelerate discovery of mechanisms of successful immunotherapeutic response in previously unresponsive solid tumor types. Session Chair: Kacey Ronaldson-Bouchard, Columbia University Session Chair: Carole Baas, Patient Advocate Alex Carter As a PhD Candidate at Rice University, Alexandria gets to be surrounded by the best and brightest thanks to those at Rice and right across the street at Texas Medical Center. She brings a multidisciplinary background to this city-wide innovation scene having worked in materials science, fluidics, and cancer biology spaces, and she now has the incredible opportunity to combine these fields through her research in Dr. Michael King’s Lab. With a mechnobiology focus, Carter has developed 3D cancer modelling platforms that enable studies of primary tumor as well as circulating tumor cell environments thanks to the tunability of the ATLAS (Advanced Tumor Landscape Analysis System) platform. This system has pushed forward the ability to host heterogeneous cell systems to model to most complex, most dangerous counterparts of cancer in the circulation, and she’s excited to share her most recent work at the upcoming meeting! Metastatic progression is strongly influenced by multicellular organization, stromal interactions, and biomechanical forces within the tumor microenvironment. However, many conventional in vitro systems fail to recapitulate the suspended three-dimensional architectures and dynamic mechanical conditions experienced by tumor clusters during dissemination. Kwaghtaver Desongu Kwaghtaver Samuel Desongu is a Ph.D. Candidate in Chemical Engineering at Auburn University working in Lipke Lab. His research focuses on developing physiologically relevant three-dimensional (3D) in vitro models to investigate colorectal cancer progression, with emphasis on obesity-associated insulin-resistant tumor microenvironments in CMS4 colorectal cancer. Using interdisciplinary approaches, he seeks to develop in vitro models that help uncover mechanisms by which adipocyte-derived factors influence colorectal cancer behavior. Beyond the laboratory, Kwaghtaver is passionate about supporting his peers to excel in their career goals while also inspiring the younger generations to do same. CMS4 colorectal cancer (CMS4-CRC) is the most aggressive CRC subtype and has the worst survival rate. However, CMS4-CRC is not well understood, due in part to the lack of in vitro models, limiting the ability to undertake mechanistic investigations and pre-clinical drug testing. Previously, we established 3D in vitro model employing PDX cells that successfully recapitulated the originating PDX CRC tumor’s key characteristics. However, the extent to which this model could recapitulate key characteristics of stromal-rich CMS4-CRC was unknown. Therefore, this study aims to develop a 3D-engineered CMS4-CRC (3D-eCMS4) in vitro model using PDX cells. To develop a 3D-eCMS4 in vitro model, we encapsulated PDX cells from two CMS4-CRC patients using poly(ethylene glycol)-fibrinogen and cultured for at least 15 days. Cells remained viable in 3D-eCMS4 throughout culture duration. In addition, flow cytometry analysis on days 0, 8, and 15 using the markers B2M (human), Ki67 (proliferation), and CK20 (CRC) indicated that at least 55% of the B2M+, Ki67+, and CK20+ populations in the tumor were maintained in 3D-eCMS4 on day 8 for both patients, while less than 10% of these populations were maintained in 2D cell culture on day 8. We also observed temporal increase to at least 80% B2M- mouse stromal cells on day 15. Additionally, we observed positive immunostaining for these markers on 3D-eCMS4 from both patients using confocal imaging. Furthermore, we observed heterogeneity in some characteristics of the 3D-eCMS4 from the two patients’ tumors, notably, a line-dependent temporal changes in 3D-eCMS4 tissues stiffness on day 15 of culture. Darko Bosnakovski Darko Bosnakovski, DVM, PhD, is an Associate Professor in the Department of Pediatrics at the University of Minnesota. He earned his DVM from the Faculty of Veterinary Science in North Macedonia and his PhD from Hokkaido University in Japan, followed by postdoctoral training at UT Southwestern. Dr. Bosnakovski began his academic career in 2008 at the Faculty of Medical Sciences, University Goce Delchev (North Macedonia), achieving the rank of full professor in 2018. In 2021, he joined the University of Minnesota to establish his laboratory. Today, he leads active research programs dedicated to uncovering mechanisms and therapies for Facioscapulohumeral Muscular Dystrophy (FSHD) and small round blue cell sarcomas. CIC-rearranged sarcomas (C-RS) are rare, highly aggressive small round cell malignancies affecting primarily children and young adults. Approximately 90% of cases harbor CIC::DUX4 fusions, yet the molecular mechanisms driving sarcomagenesis remain poorly understood due to the lack of physiologically relevant experimental models. To address this challenge, we developed an induced pluripotent stem cell (iPSC)-based platform for modeling CIC-rearranged sarcomas in vitro and in vivo. Using doxycycline-inducible CIC fusion constructs integrated into the AAVS1 safe harbor locus, we generated tunable iPSC models of CIC-driven sarcomagenesis. By combining engineered iPSCs with an in vivo organoid-based differentiation strategy, we established iPSC-derived CIC sarcoma cell lines (iCS) that recapitulate the histological, molecular, and transcriptional features of patient tumors. Transcriptomic and chromatin analyses revealed activation of canonical CIC::DUX4 target programs and epigenetic states consistent with primary human sarcomas. Importantly, preliminary studies demonstrate that these models are highly dependent on P300/CBP activity, supporting the therapeutic potential of selective P300/CBP inhibition. iCS cells also retain tumorigenic potential following xenotransplantation, validating their utility as translational preclinical models. Together, these studies establish a novel developmental framework for investigating lineage permissiveness, early transformation events, and therapeutic vulnerabilities in CIC-rearranged sarcomas, while providing broadly applicable tools for modeling rare fusion-driven cancers. Bethany Haliday Bethany is a PhD candidate in Cancer Biology and Genomics at the University of Southern California in Dr. Shannon Mumenthaler's lab at the Ellison Medical Institute. Her research utilizes a patient-derived biomimetic organ-on-chip model to the influence of cancer associated fibroblasts in primary tumor invasion and immune cell recruitment in colorectal cancer. This work aims to recapitulate the complexity of the tumor microenvironment and explore the functional heterogeneity of cancer associated fibroblasts in a tunable in vitro system. The tumor microenvironment (TME) is highly heterogeneous and plays a critical role in cancer progression. In colorectal cancer (CRC), tumors can be classified into distinct consensus molecular subtypes (CMS), each characterized by unique immune and cancer-associated fibroblast (CAF) cell populations that influence disease prognosis. Therefore, tunable models that reflect CRC subtype diversity are needed to uncover the complex cellular interactions occurring within the TME. We developed a microfluidic organ-on-chip model that recapitulates key features of the colon environment by incorporating gut biomechanical cues, including fluid flow-induced shear stress and peristalsis-like motions, as well as epithelial-endothelial tissue interactions. Given the modularity of this model, we established two complementary culture systems. In the first system, patient-derived CAFs and CRC cells are cultured in the top channel, with vascular endothelial cells in the bottom channel. Using confocal microscopy, we tracked GFP-labeled CRC cells intravasating into the vascular channel to quantify invasion rates. These studies revealed patient-specific differences in CAF-mediated CRC invasion, suggesting heterogeneity in CAF function and tumor-promoting abilities. In the second system, patient-derived CRC organoids are cultured in the top channel while peripheral blood mononuclear cells (PBMCs) are flowed through the vascular channel and recruited to the tumor compartment. Using this approach, we observed patient-specific differences in immune cell recruitment which may influence tumor progression. Together, these models enable a better understanding of tumor-stromal and tumor-immune interactions and their contributions to CRC progression. Pilar de la Puente Pilar de la Puente, PhD, is an Associate Scientist / Associate Professor at Sanford Research / University of South Dakota School of Medicine. She earned her PhD in Biomedical Engineering and Biological Sciences at the University of Salamanca in Spain. Dr. de la Puente completed postdoctoral training at Washington University in St Louis School of Medicine in cancer tissue engineering, nanomedicine and translational precision-based drug screenings. The de la Puente lab develops novel, human, precision-based models that empower drug screening by more closely replicating a tissue microenvironment for in vitro assays. She uses her interdisciplinary training in tissue engineering, cancer biology, drug resistance, and immunoengineering to solve pressing questions in chemoresistance, immune evasion and precision medicine for women’s cancer. Dr. de la Puente’s contributions have been recognized through numerous funding including NIH-R37-MERIT Award, American Cancer Society Research Scholar Grant and several other foundation- and NIH-funded grants. Her work has gained national recognition with important awards and recognitions including the American Institute for Medical and Biological Engineering (AIMBE) Emerging Leader, Cell and Molecular Bioengineering (CMBE) Rising Star from the Biomedical Engineering Society (BMES), NIH Early Investigator Advancement Program (EIAP) Scholar from the National Cancer Institute, the “35 under 35” BussinesInsider Spain, she was inducted a ResearchHERS Scholar by the American Cancer Society, acknowledging her as a trailblazing woman researcher, and the Lush Prize 2018. Dr. de la Puente has also demonstrated strong entrepreneurial leadership through the translation of her lab’s technologies into several patents for drug development and precision oncology applications and a start-up company, Cellatrix LLC. Her work bridges the gap between academic innovation and industry, with a clear vision for clinical impact. Hypoxia-Induced ECM Remodeling as a Barrier to Immune Infiltration in Ovarian Tumors: Insights from Engineered Extracellular Matrix Models High grade serous ovarian cancer is characterized by an immunologically “cold” tumor microenvironment, with limited immune infiltration and poor clinical outcomes. A major contributor to this phenotype is extensive extracellular matrix (ECM) remodeling, which is strongly influenced by hypoxia. However, commonly used experimental models fail to adequately recapitulate physiologically relevant oxygen conditions and matrix architecture, limiting progress in understanding tumor–immune interactions and the development of effective therapies. To address this, we developed patient derived tumor–immune models that incorporate cancer cells, cancer associated fibroblasts, and immune cells within engineered matrices composed of autologous plasma or decellularized ovarian tissue. These systems reproduce physiological oxygen levels while enabling controlled manipulation of ECM remodeling. Using this platform, we demonstrate that hypoxia induced ECM remodeling, rather than hypoxia alone, establishes a physical and biochemical barrier that restricts immune cell infiltration into tumor nests. Under hypoxic conditions, fibroblasts generate dense, highly crosslinked ECM that impedes immune trafficking and promotes immune exclusion. Notably, CD8⁺ T cells that infiltrate remodeled matrices exhibit enhanced activation and cytotoxicity, revealing a paradoxical relationship between matrix remodeling and immune function. Mechanistically, we identify TGF β signaling as a key driver of hypoxia mediated ECM remodeling. Pharmacologic inhibition of TGF β attenuates these matrix changes, significantly improves immune cell penetration, and restores tumor–immune interactions. Together, these findings underscore the importance of physiologically relevant stromal and oxygen landscapes in regulating immune accessibility in ovarian cancer. This work highlights ECM remodeling pathways as promising therapeutic targets to convert immunologically “cold” tumors into “hot” tumors and enhance immunotherapy efficacy. Alex Carter As a PhD Candidate at Rice University, Alexandria gets to be surrounded by the best and brightest thanks to those at Rice and right across the street at Texas Medical Center. She brings a multidisciplinary background to this city-wide innovation scene having worked in materials science, fluidics, and cancer biology spaces, and she now has the incredible opportunity to combine these fields through her research in Dr. Michael King’s Lab. With a mechnobiology focus, Carter has developed 3D cancer modelling platforms that enable studies of primary tumor as well as circulating tumor cell environments thanks to the tunability of the ATLAS (Advanced Tumor Landscape Analysis System) platform. This system has pushed forward the ability to host heterogeneous cell systems to model to most complex, most dangerous counterparts of cancer in the circulation, and she’s excited to share her most recent work at the upcoming meeting! Metastatic progression is strongly influenced by multicellular organization, stromal interactions, and biomechanical forces within the tumor microenvironment. However, many conventional in vitro systems fail to recapitulate the suspended three-dimensional architectures and dynamic mechanical conditions experienced by tumor clusters during dissemination. Kwaghtaver Desongu Kwaghtaver Samuel Desongu is a Ph.D. Candidate in Chemical Engineering at Auburn University working in Lipke Lab. His research focuses on developing physiologically relevant three-dimensional (3D) in vitro models to investigate colorectal cancer progression, with emphasis on obesity-associated insulin-resistant tumor microenvironments in CMS4 colorectal cancer. Using interdisciplinary approaches, he seeks to develop in vitro models that help uncover mechanisms by which adipocyte-derived factors influence colorectal cancer behavior. Beyond the laboratory, Kwaghtaver is passionate about supporting his peers to excel in their career goals while also inspiring the younger generations to do same. CMS4 colorectal cancer (CMS4-CRC) is the most aggressive CRC subtype and has the worst survival rate. However, CMS4-CRC is not well understood, due in part to the lack of in vitro models, limiting the ability to undertake mechanistic investigations and pre-clinical drug testing. Previously, we established 3D in vitro model employing PDX cells that successfully recapitulated the originating PDX CRC tumor’s key characteristics. However, the extent to which this model could recapitulate key characteristics of stromal-rich CMS4-CRC was unknown. Therefore, this study aims to develop a 3D-engineered CMS4-CRC (3D-eCMS4) in vitro model using PDX cells. To develop a 3D-eCMS4 in vitro model, we encapsulated PDX cells from two CMS4-CRC patients using poly(ethylene glycol)-fibrinogen and cultured for at least 15 days. Cells remained viable in 3D-eCMS4 throughout culture duration. In addition, flow cytometry analysis on days 0, 8, and 15 using the markers B2M (human), Ki67 (proliferation), and CK20 (CRC) indicated that at least 55% of the B2M+, Ki67+, and CK20+ populations in the tumor were maintained in 3D-eCMS4 on day 8 for both patients, while less than 10% of these populations were maintained in 2D cell culture on day 8. We also observed temporal increase to at least 80% B2M- mouse stromal cells on day 15. Additionally, we observed positive immunostaining for these markers on 3D-eCMS4 from both patients using confocal imaging. Furthermore, we observed heterogeneity in some characteristics of the 3D-eCMS4 from the two patients’ tumors, notably, a line-dependent temporal changes in 3D-eCMS4 tissues stiffness on day 15 of culture. Darko Bosnakovski Darko Bosnakovski, DVM, PhD, is an Associate Professor in the Department of Pediatrics at the University of Minnesota. He earned his DVM from the Faculty of Veterinary Science in North Macedonia and his PhD from Hokkaido University in Japan, followed by postdoctoral training at UT Southwestern. Dr. Bosnakovski began his academic career in 2008 at the Faculty of Medical Sciences, University Goce Delchev (North Macedonia), achieving the rank of full professor in 2018. In 2021, he joined the University of Minnesota to establish his laboratory. Today, he leads active research programs dedicated to uncovering mechanisms and therapies for Facioscapulohumeral Muscular Dystrophy (FSHD) and small round blue cell sarcomas. CIC-rearranged sarcomas (C-RS) are rare, highly aggressive small round cell malignancies affecting primarily children and young adults. Approximately 90% of cases harbor CIC::DUX4 fusions, yet the molecular mechanisms driving sarcomagenesis remain poorly understood due to the lack of physiologically relevant experimental models. To address this challenge, we developed an induced pluripotent stem cell (iPSC)-based platform for modeling CIC-rearranged sarcomas in vitro and in vivo. Using doxycycline-inducible CIC fusion constructs integrated into the AAVS1 safe harbor locus, we generated tunable iPSC models of CIC-driven sarcomagenesis. By combining engineered iPSCs with an in vivo organoid-based differentiation strategy, we established iPSC-derived CIC sarcoma cell lines (iCS) that recapitulate the histological, molecular, and transcriptional features of patient tumors. Transcriptomic and chromatin analyses revealed activation of canonical CIC::DUX4 target programs and epigenetic states consistent with primary human sarcomas. Importantly, preliminary studies demonstrate that these models are highly dependent on P300/CBP activity, supporting the therapeutic potential of selective P300/CBP inhibition. iCS cells also retain tumorigenic potential following xenotransplantation, validating their utility as translational preclinical models. Together, these studies establish a novel developmental framework for investigating lineage permissiveness, early transformation events, and therapeutic vulnerabilities in CIC-rearranged sarcomas, while providing broadly applicable tools for modeling rare fusion-driven cancers. Bethany Haliday Bethany is a PhD candidate in Cancer Biology and Genomics at the University of Southern California in Dr. Shannon Mumenthaler's lab at the Ellison Medical Institute. Her research utilizes a patient-derived biomimetic organ-on-chip model to the influence of cancer associated fibroblasts in primary tumor invasion and immune cell recruitment in colorectal cancer. This work aims to recapitulate the complexity of the tumor microenvironment and explore the functional heterogeneity of cancer associated fibroblasts in a tunable in vitro system. The tumor microenvironment (TME) is highly heterogeneous and plays a critical role in cancer progression. In colorectal cancer (CRC), tumors can be classified into distinct consensus molecular subtypes (CMS), each characterized by unique immune and cancer-associated fibroblast (CAF) cell populations that influence disease prognosis. Therefore, tunable models that reflect CRC subtype diversity are needed to uncover the complex cellular interactions occurring within the TME. We developed a microfluidic organ-on-chip model that recapitulates key features of the colon environment by incorporating gut biomechanical cues, including fluid flow-induced shear stress and peristalsis-like motions, as well as epithelial-endothelial tissue interactions. Given the modularity of this model, we established two complementary culture systems. In the first system, patient-derived CAFs and CRC cells are cultured in the top channel, with vascular endothelial cells in the bottom channel. Using confocal microscopy, we tracked GFP-labeled CRC cells intravasating into the vascular channel to quantify invasion rates. These studies revealed patient-specific differences in CAF-mediated CRC invasion, suggesting heterogeneity in CAF function and tumor-promoting abilities. In the second system, patient-derived CRC organoids are cultured in the top channel while peripheral blood mononuclear cells (PBMCs) are flowed through the vascular channel and recruited to the tumor compartment. Using this approach, we observed patient-specific differences in immune cell recruitment which may influence tumor progression. Together, these models enable a better understanding of tumor-stromal and tumor-immune interactions and their contributions to CRC progression. Pilar de la Puente Pilar de la Puente, PhD, is an Associate Scientist / Associate Professor at Sanford Research / University of South Dakota School of Medicine. She earned her PhD in Biomedical Engineering and Biological Sciences at the University of Salamanca in Spain. Dr. de la Puente completed postdoctoral training at Washington University in St Louis School of Medicine in cancer tissue engineering, nanomedicine and translational precision-based drug screenings. The de la Puente lab develops novel, human, precision-based models that empower drug screening by more closely replicating a tissue microenvironment for in vitro assays. She uses her interdisciplinary training in tissue engineering, cancer biology, drug resistance, and immunoengineering to solve pressing questions in chemoresistance, immune evasion and precision medicine for women’s cancer. Dr. de la Puente’s contributions have been recognized through numerous funding including NIH-R37-MERIT Award, American Cancer Society Research Scholar Grant and several other foundation- and NIH-funded grants. Her work has gained national recognition with important awards and recognitions including the American Institute for Medical and Biological Engineering (AIMBE) Emerging Leader, Cell and Molecular Bioengineering (CMBE) Rising Star from the Biomedical Engineering Society (BMES), NIH Early Investigator Advancement Program (EIAP) Scholar from the National Cancer Institute, the “35 under 35” BussinesInsider Spain, she was inducted a ResearchHERS Scholar by the American Cancer Society, acknowledging her as a trailblazing woman researcher, and the Lush Prize 2018. Dr. de la Puente has also demonstrated strong entrepreneurial leadership through the translation of her lab’s technologies into several patents for drug development and precision oncology applications and a start-up company, Cellatrix LLC. Her work bridges the gap between academic innovation and industry, with a clear vision for clinical impact. Hypoxia-Induced ECM Remodeling as a Barrier to Immune Infiltration in Ovarian Tumors: Insights from Engineered Extracellular Matrix Models High grade serous ovarian cancer is characterized by an immunologically “cold” tumor microenvironment, with limited immune infiltration and poor clinical outcomes. A major contributor to this phenotype is extensive extracellular matrix (ECM) remodeling, which is strongly influenced by hypoxia. However, commonly used experimental models fail to adequately recapitulate physiologically relevant oxygen conditions and matrix architecture, limiting progress in understanding tumor–immune interactions and the development of effective therapies. To address this, we developed patient derived tumor–immune models that incorporate cancer cells, cancer associated fibroblasts, and immune cells within engineered matrices composed of autologous plasma or decellularized ovarian tissue. These systems reproduce physiological oxygen levels while enabling controlled manipulation of ECM remodeling. Using this platform, we demonstrate that hypoxia induced ECM remodeling, rather than hypoxia alone, establishes a physical and biochemical barrier that restricts immune cell infiltration into tumor nests. Under hypoxic conditions, fibroblasts generate dense, highly crosslinked ECM that impedes immune trafficking and promotes immune exclusion. Notably, CD8⁺ T cells that infiltrate remodeled matrices exhibit enhanced activation and cytotoxicity, revealing a paradoxical relationship between matrix remodeling and immune function. Mechanistically, we identify TGF β signaling as a key driver of hypoxia mediated ECM remodeling. Pharmacologic inhibition of TGF β attenuates these matrix changes, significantly improves immune cell penetration, and restores tumor–immune interactions. Together, these findings underscore the importance of physiologically relevant stromal and oxygen landscapes in regulating immune accessibility in ovarian cancer. This work highlights ECM remodeling pathways as promising therapeutic targets to convert immunologically “cold” tumors into “hot” tumors and enhance immunotherapy efficacy. Carole Baas Carole Baas, PhD, became involved in cancer research advocacy following her diagnosis of early–stage breast cancer in 2004. She currently serves as the National Advocate for the Physical Sciences in Oncology Network (PS-ON) at the National Cancer Institute (NCI), where she bridges the gap between scientists and the patient community. Drawing on her background in research and academia as well as her personal cancer experience—including a second breast cancer diagnosis in 2021—Dr. Baas has volunteered with the PS-ON since 2010, currently serving on the Steering Committee and Education & Outreach Working Group and encouraging advocacy efforts across the Network. She holds a PhD in Biomedical Engineering from Texas A&M University. Beyond the PS-ON, Dr. Baas is deeply engaged in national and institutional advocacy efforts. In 2024, she was appointed to the Clinical Imaging Steering Committee and the Patient Advocate Steering Committee for the NCI’s National Clinical Trials Network (NCTN). She also serves as an Advocate in Science for Susan G. Komen, a Community Research Partner for the American Cancer Society (ACS), and a member of the Cancer Research Advocate, Breast Cancer, and Experimental Imaging Sciences Committees at ECOG-ACRIN. In addition, she is a member of the Baylor Research Institute Institutional Review Board in Dallas, Texas, and a RISE Legacy Advocate for the Young Survival Coalition (YSC). Diane Heditsian Diane’s breast cancer advocacy work of twenty-four years is informed by her four breast cancer diagnoses and includes research, patient and policy advocacy. Diane brings to her advocacy work a background in communications and marketing as founder and CEO of deClarity, a 40-year global life science communications consultancy. She is a multiple Project LEAD Institute-trained breast cancer research advocate. She supports researchers and clinicians at Stanford as well as other academic institutions throughout the country as an inaugural member of Susan G. Komen’s Advocates in Science. Through the Christina Curtis Lab at Stanford University she is an advocate member of the NCI’s Metastasis Network. In 2009 Diane joined the University of California, San Francisco, Breast Oncology Program’s Breast Science Advocacy Core. There she serves as a research advocate on the national I-SPY and WISDOM Studies. Diane is also a standing member of the planning committee for RISE UP for Breast Cancer and Women’s Health, serving as advocate lead, for which she developed the model that she will be discussing today. Diane is a member of Cancer Nation’s Cancer Policy and Advocacy Steering Committee helping guide their agenda to improve lives for survivors. For 22 years she has served as a peer counselor to support, educate and empower women at all stages of breast cancer to advocate for their own healthcare. She is a sought-after speaker and keynoted both ASCO’s inaugural Cancer Survivorship Symposium, presenting An Advocate’s Prescription for Survivorship Care as well as a PCORI Annual Meeting. Diane co-led the advocate initiative that succeeded in overturning the Centers for Medicare and Medicaid’s decision to rescind the CMS billing code for DIEP Flap breast reconstruction. Diane was awarded a Fulbright Specialist designation in Cancer Advocacy enabling her to help countries around the world develop cancer advocacy initiatives. Session Chair: Anna Michmerhuizen, University of North Carolina Session Chair: Angie Bowen, Patient Advocate and Project Manager, MC2 Center, Sage Bionetworks Julia Pelesko I am a current PhD student in Mathematical Oncology at Moffitt Cancer Center. My research focuses on personalizing TKI regimens to mitigate toxicities or improve efficacy of these drugs by normalizing their pharmacokinetic profiles. This work involves a combination of bioengineering, Bayesian modeling, and PK/PD modeling. When I’m not in the lab you can find me figure skating or cooking! Inter-individual variability (IIV) in drug metabolism represents an under-explored mechanism of treatment failure and toxicity in cancer pharmacotherapy. Lorlatinib, a third-generation ALK inhibitor approved for non-small cell lung cancer (NSCLC), is primarily metabolized by CYP3A4, an enzyme whose expression varies substantially across patients due to genetic, dietary, pharmacological, and physiological factors. Despite this variability, patients receive a uniform 100mg daily dose, potentially exposing some to sub-therapeutic concentrations while subjecting others to toxic over-exposure. We developed a two-compartment ODE model of Lorlatinib pharmacokinetics parameterized with population mean values and personalized according to individual CYP3A4 expression level. We explored three dosing strategies — dose adjustment, frequency adjustment, and a combined approach — to normalize key PK metrics (AUC, Cmax, Cmin) to standard-of-care baseline values across a spectrum of metabolizer phenotypes. Our results demonstrate that dose reduction successfully normalizes PK metrics in low CYP3A4 expressors, while increased dosing frequency restores drug exposure in high expressors. However, patients at expression extremes present a greater challenge: ultra-high expressors require dosing every 2.4 hours — clinically infeasible for oral administration — while ultra-low expressors require 10mg dosing, below the minimum available 25mg tablet formulation. These patients may require IV infusion or pharmacological CYP3A4 modulation, respectively. These findings demonstrate the clinical potential of CYP3A4-guided personalized dosing in Lorlatinib treatment and motivate future integration of pharmacodynamic modeling to assess impact on tumor control and toxicity. Veronika Pister Veronika Pister is a PhD student in Biological Engineering at the Massachusetts Institute of Technology in Ernest Fraenkel's lab. Her research uses spatial omics and computational methods to study interactions between tumor and immune cells in the tumor microenvironment, with the goal of better understanding cancer biology and treatment response. Before graduate school, Veronika earned her bachelor's degree in Bioengineering: Bioinformatics from the University of California, San Diego. Understanding how drug treatments alter immune and metabolic states within intact tumors remains a barrier to developing improved therapies. We introduce a spatial pharmacology platform that enables parallel analysis of multiple agents within a single tumor, linking local drug exposure to immune and metabolic remodeling. Using a microdevice to release localized doses of therapeutics, we generate a uniquely large paired CyCIF–MALDI spatial dataset (1.5 million cells) spanning 27 MMTV-PyMT tumor sections across nine treatment programs, providing first-in-field integrated microdevice spatial pharmacology. Metabolic signatures robustly predict proteomic spatial neighborhoods (ROC-AUC 0.86), establishing metabolism as a powerful predictor of local drug response. Within this framework, we identify a dominant metabolic axis defined by the myeloid polarization between CSF1R+ tumor-associated macrophages and MPO+ infiltrating myeloid cells localized near regions of tumor cell death. Finally, we confirm the in situ presence of scRNA-seq–defined lipid-associated macrophages (LAMs) within drug-resistant treatment regions in breast tumors. Naheel Khatri Naheel Khatri is an MD/PhD student at the Renaissance School of Medicine at Stony Brook University, where he investigates cancer biology using spatial multi-omics and computational modeling. His work integrates imaging mass spectrometry, multiplex tissue imaging, spatial transcriptomics, and machine learning to characterize tumor ecosystems and their response to therapy. By combining experimental and computational approaches, his research aims to uncover mechanisms of cancer progression and develop novel tools for precision oncology. He received his B.S. in Molecular Life Sciences and Neuroscience from Indiana University Bloomington in 2020. Addressing patient-specific radioresistance in early-stage breast cancer remains an unmet clinical need, yet no validated method exists to tailor dosing to individual radiosensitivity. We hypothesized that the complex, resource-depleted tumor microenvironment (TME) emerging from diffusion gradients in larger tumors drives eco-evolutionary selection of ferroptosis-resistant phenotypes defining radioresistance. 3D spheroids of MCF7, T47D, and MDA-MB231 were grown as small (300 µm) and irradiated (10 Gy). Sequential sections underwent multiplexed immunofluorescence (mIF; CAIX, CAXII, GLUT1, GLUT3, LAMP2b) and MALDI-based spatial lipidomics. Ecological territories were constructed from mIF marker intensities, spatial statistics, and nuclear morphology, then analyzed via PHATE for pseudotime trajectory mapping, with lipid enrichment overlaid from registered MALDI sections. Large spheroids were significantly more radioresistant in MCF7 and T47D spheroids. PHATE revealed distinct territorial phenotypes: small spheroids harbored CAXII/GLUT3-high territories enriched with PE(38:4), a ferroptosis-permissive PUFA-phospholipid, while large spheroids displayed heterogeneous territories reflecting adaptation to a harsh, metabolically stressed TME, with variable LAMP2b, GLUT1, and GLUT3 expression and enrichment in PI, PS, PA, and PE species. Notably, CAIX-high territories in large spheroids were specifically enriched with MUFA-PEs, suggesting acid-mediated upregulation of MUFA-PLs as a convergent mechanism of ferroptosis inhibition. One-week post-irradiation, large spheroids were dominated by GLUT1-high/LAMP2b-high territories enriched with cholesterol sulfate, PIs, and PSs, consistent with broader membrane remodeling as a radioprotective program. Ferroptosis induction via Erastin and RSL3 resensitized large spheroids to radiation at low doses. These findings demonstrate that TME ecological complexity selects for ferroptosis-adapted lipid territories conferring radioresistance, nominating TME metabolic ecology as actionable biomarkers for patient stratification and individualized radiation dosing. Michalina Janiszewska Michalina Janiszewska, Ph.D. is an Associate Professor at the Department of Neurosurgery, University of Colorado Anschutz. Her research group investigates different aspects of tumor cell diversity in highly aggressive brain tumors, aiming to understand and disrupt the cancer ecosystem. Glioblastoma (GBM) remains the deadliest primary brain cancer, with the average patient survival of only 16 months after diagnosis. This dismal outlook persists despite decades of efforts and extensive clinical trials, because GBM tumors harbor extreme intratumor heterogeneity that undermines both targeted and immunotherapeutic strategies. Each GBM tumor contains multiple co-existing subpopulations of cells with distinct phenotypes, whose collective function fuels the disease. Yet, how these heterogenous subpopulations interact with each other, with the surrounding tissue, and with the immune cells and drive the aggressive behavior of the tumor remains largely unknown. Dr. Janiszewska aims to elucidate these interdependencies and leverage this knowledge to disrupt the GBM cancer ecosystem. Dr. Janiszewska received her BSc in Biotechnology and MSc in Medical Biotechnology from the University of Wroclaw, Poland, and PhD in Life Sciences from the University of Lausanne, Switzerland. Her thesis work, under supervision of Ivan Stamenkovic, MD, focused on cancer stem cell biology. After obtaining her degree in 2012, she moved to work with Kornelia Polyak, MD, PhD, the expert on breast cancer tumor heterogeneity at Dana-Farber Cancer Institute, Harvard Medical School. In 2016, Dr. Janiszewska was promoted to Instructor of Medicine at DFCI/HHMS and in September 2018 she opened her independent lab at Scripps Research, FL campus (now named the Wertheim UF Scripps Institute). In April 2026, Dr. Janiszewska joined the Department of Neurosurgery at University of Colorado Anschutz. Dr. Janiszewska is a recipient of several fellowships and grants, including EMBO and Swiss National Science Foundation fellowship for her postdoctoral work and NIH K99/R00 Career Development Award. As an independent investigator, she has been awarded grants from Florida Center for Brain Tumor Research, American Cancer Society Institutional Research Grant, MacKenzie Foundation Grant, Florida Department of Health Live Like Bella Pediatric Cancer Initiative grant and Bankhead-Coley grant. She has also been selected as 2019 American Association for Cancer Research NextGen Star and 2023 Best Mentor by Society of Research Fellows at UF Scripps. Glioblastoma (GBM) remains an unmet medical need, with average survival of only 18 months post-diagnosis and 5-year survival rates of 6.8%. Intratumor heterogeneity (ITH) is one of the main reasons for the lack of effective targeted therapies for GBM. Imaging-guided surgical navigation allows for tumor-wide sampling to account for variation across distant regions of the tumor, but typical drug screening is performed on cell lines derived from a single biopsy and does not account for GBM heterogeneity. To improve pre-clinical modeling of GBM ITH, we collected MRI-guided multi-region primary tumor biopsies from 6 GBM cases (n=40 biopsies) and derived neurosphere cultures (n=30) from these spatially distinct tumor samples. We characterized these samples by transcriptomic analysis and phylogenetic reconstruction of the tumor. Neurosphere cultures derived from these multi-region biopsies were tested for their proliferation, drug sensitivity, and transcriptomic similarity to their biopsy-of-origin. We found that in vitro cultures derived from distinct regions of the same tumor display divergent phenotypes, proliferative capacity and ability to accumulate 5-aminolevulinic acid, used to visualize cancer cells during surgery. Using a machine learning-based model we found that the differential drug response of the multi-region neurospheres remains linked to the gene expression of the original tumor biopsies. Our work demonstrates that joint profiling of the cell lines and their corresponding biopsies captures GBM ITH and enables more faithfully modeling of tumor heterogeneity for therapeutic testing. Luca Zanella Luca Zanella is a postdoctoral research scientist in the Andrea Califano’s laboratory at the Department of Systems Biology, Columbia University, New York. His research lies at the intersection between computer science, precision medicine and systems biology and involves the use of network-based computational methodologies to study tumor heterogeneity and drug repurposing in IDH-mutant glioma and dissect cancer cell adaptation mechanisms from perturbational data at single-cell resolution in several tumor contexts. Next generation cancer models, including organoids, neurospheres and conditionally reprogrammed cell lines, are significantly advancing our ability to study individual human tumors in vitro and to develop novel cancer therapeutics. However, questions emerged as to the degree to which in vitro models faithfully represent intra- and inter-patient cell state heterogeneity at the single-cell level. The Human Cancer Models Initiative (HCMI), a global collaboration involving the NCI (NIH), Cancer Research UK, the Wellcome Sanger Institute and the Hubrecht Organoid Technology foundation, has generated 665 patient-derived next-generation cancer models with matching parental tumor and clinical annotations. We performed tumor-model fidelity analysis using bulk RNA-seq, confirming strong cell-state concordance between models and parental tumors across most HCMI pairs, showcasing their ability to retain key tumor attributes. However, Julia Pelesko I am a current PhD student in Mathematical Oncology at Moffitt Cancer Center. My research focuses on personalizing TKI regimens to mitigate toxicities or improve efficacy of these drugs by normalizing their pharmacokinetic profiles. This work involves a combination of bioengineering, Bayesian modeling, and PK/PD modeling. When I’m not in the lab you can find me figure skating or cooking! Inter-individual variability (IIV) in drug metabolism represents an under-explored mechanism of treatment failure and toxicity in cancer pharmacotherapy. Lorlatinib, a third-generation ALK inhibitor approved for non-small cell lung cancer (NSCLC), is primarily metabolized by CYP3A4, an enzyme whose expression varies substantially across patients due to genetic, dietary, pharmacological, and physiological factors. Despite this variability, patients receive a uniform 100mg daily dose, potentially exposing some to sub-therapeutic concentrations while subjecting others to toxic over-exposure. We developed a two-compartment ODE model of Lorlatinib pharmacokinetics parameterized with population mean values and personalized according to individual CYP3A4 expression level. We explored three dosing strategies — dose adjustment, frequency adjustment, and a combined approach — to normalize key PK metrics (AUC, Cmax, Cmin) to standard-of-care baseline values across a spectrum of metabolizer phenotypes. Our results demonstrate that dose reduction successfully normalizes PK metrics in low CYP3A4 expressors, while increased dosing frequency restores drug exposure in high expressors. However, patients at expression extremes present a greater challenge: ultra-high expressors require dosing every 2.4 hours — clinically infeasible for oral administration — while ultra-low expressors require 10mg dosing, below the minimum available 25mg tablet formulation. These patients may require IV infusion or pharmacological CYP3A4 modulation, respectively. These findings demonstrate the clinical potential of CYP3A4-guided personalized dosing in Lorlatinib treatment and motivate future integration of pharmacodynamic modeling to assess impact on tumor control and toxicity. Veronika Pister Veronika Pister is a PhD student in Biological Engineering at the Massachusetts Institute of Technology in Ernest Fraenkel's lab. Her research uses spatial omics and computational methods to study interactions between tumor and immune cells in the tumor microenvironment, with the goal of better understanding cancer biology and treatment response. Before graduate school, Veronika earned her bachelor's degree in Bioengineering: Bioinformatics from the University of California, San Diego. Understanding how drug treatments alter immune and metabolic states within intact tumors remains a barrier to developing improved therapies. We introduce a spatial pharmacology platform that enables parallel analysis of multiple agents within a single tumor, linking local drug exposure to immune and metabolic remodeling. Using a microdevice to release localized doses of therapeutics, we generate a uniquely large paired CyCIF–MALDI spatial dataset (1.5 million cells) spanning 27 MMTV-PyMT tumor sections across nine treatment programs, providing first-in-field integrated microdevice spatial pharmacology. Metabolic signatures robustly predict proteomic spatial neighborhoods (ROC-AUC 0.86), establishing metabolism as a powerful predictor of local drug response. Within this framework, we identify a dominant metabolic axis defined by the myeloid polarization between CSF1R+ tumor-associated macrophages and MPO+ infiltrating myeloid cells localized near regions of tumor cell death. Finally, we confirm the in situ presence of scRNA-seq–defined lipid-associated macrophages (LAMs) within drug-resistant treatment regions in breast tumors. Naheel Khatri Naheel Khatri is an MD/PhD student at the Renaissance School of Medicine at Stony Brook University, where he investigates cancer biology using spatial multi-omics and computational modeling. His work integrates imaging mass spectrometry, multiplex tissue imaging, spatial transcriptomics, and machine learning to characterize tumor ecosystems and their response to therapy. By combining experimental and computational approaches, his research aims to uncover mechanisms of cancer progression and develop novel tools for precision oncology. He received his B.S. in Molecular Life Sciences and Neuroscience from Indiana University Bloomington in 2020. Addressing patient-specific radioresistance in early-stage breast cancer remains an unmet clinical need, yet no validated method exists to tailor dosing to individual radiosensitivity. We hypothesized that the complex, resource-depleted tumor microenvironment (TME) emerging from diffusion gradients in larger tumors drives eco-evolutionary selection of ferroptosis-resistant phenotypes defining radioresistance. 3D spheroids of MCF7, T47D, and MDA-MB231 were grown as small (300 µm) and irradiated (10 Gy). Sequential sections underwent multiplexed immunofluorescence (mIF; CAIX, CAXII, GLUT1, GLUT3, LAMP2b) and MALDI-based spatial lipidomics. Ecological territories were constructed from mIF marker intensities, spatial statistics, and nuclear morphology, then analyzed via PHATE for pseudotime trajectory mapping, with lipid enrichment overlaid from registered MALDI sections. Large spheroids were significantly more radioresistant in MCF7 and T47D spheroids. PHATE revealed distinct territorial phenotypes: small spheroids harbored CAXII/GLUT3-high territories enriched with PE(38:4), a ferroptosis-permissive PUFA-phospholipid, while large spheroids displayed heterogeneous territories reflecting adaptation to a harsh, metabolically stressed TME, with variable LAMP2b, GLUT1, and GLUT3 expression and enrichment in PI, PS, PA, and PE species. Notably, CAIX-high territories in large spheroids were specifically enriched with MUFA-PEs, suggesting acid-mediated upregulation of MUFA-PLs as a convergent mechanism of ferroptosis inhibition. One-week post-irradiation, large spheroids were dominated by GLUT1-high/LAMP2b-high territories enriched with cholesterol sulfate, PIs, and PSs, consistent with broader membrane remodeling as a radioprotective program. Ferroptosis induction via Erastin and RSL3 resensitized large spheroids to radiation at low doses. These findings demonstrate that TME ecological complexity selects for ferroptosis-adapted lipid territories conferring radioresistance, nominating TME metabolic ecology as actionable biomarkers for patient stratification and individualized radiation dosing. Michalina Janiszewska Michalina Janiszewska, Ph.D. is an Associate Professor at the Department of Neurosurgery, University of Colorado Anschutz. Her research group investigates different aspects of tumor cell diversity in highly aggressive brain tumors, aiming to understand and disrupt the cancer ecosystem. Glioblastoma (GBM) remains the deadliest primary brain cancer, with the average patient survival of only 16 months after diagnosis. This dismal outlook persists despite decades of efforts and extensive clinical trials, because GBM tumors harbor extreme intratumor heterogeneity that undermines both targeted and immunotherapeutic strategies. Each GBM tumor contains multiple co-existing subpopulations of cells with distinct phenotypes, whose collective function fuels the disease. Yet, how these heterogenous subpopulations interact with each other, with the surrounding tissue, and with the immune cells and drive the aggressive behavior of the tumor remains largely unknown. Dr. Janiszewska aims to elucidate these interdependencies and leverage this knowledge to disrupt the GBM cancer ecosystem. Dr. Janiszewska received her BSc in Biotechnology and MSc in Medical Biotechnology from the University of Wroclaw, Poland, and PhD in Life Sciences from the University of Lausanne, Switzerland. Her thesis work, under supervision of Ivan Stamenkovic, MD, focused on cancer stem cell biology. After obtaining her degree in 2012, she moved to work with Kornelia Polyak, MD, PhD, the expert on breast cancer tumor heterogeneity at Dana-Farber Cancer Institute, Harvard Medical School. In 2016, Dr. Janiszewska was promoted to Instructor of Medicine at DFCI/HHMS and in September 2018 she opened her independent lab at Scripps Research, FL campus (now named the Wertheim UF Scripps Institute). In April 2026, Dr. Janiszewska joined the Department of Neurosurgery at University of Colorado Anschutz. Dr. Janiszewska is a recipient of several fellowships and grants, including EMBO and Swiss National Science Foundation fellowship for her postdoctoral work and NIH K99/R00 Career Development Award. As an independent investigator, she has been awarded grants from Florida Center for Brain Tumor Research, American Cancer Society Institutional Research Grant, MacKenzie Foundation Grant, Florida Department of Health Live Like Bella Pediatric Cancer Initiative grant and Bankhead-Coley grant. She has also been selected as 2019 American Association for Cancer Research NextGen Star and 2023 Best Mentor by Society of Research Fellows at UF Scripps. Glioblastoma (GBM) remains an unmet medical need, with average survival of only 18 months post-diagnosis and 5-year survival rates of 6.8%. Intratumor heterogeneity (ITH) is one of the main reasons for the lack of effective targeted therapies for GBM. Imaging-guided surgical navigation allows for tumor-wide sampling to account for variation across distant regions of the tumor, but typical drug screening is performed on cell lines derived from a single biopsy and does not account for GBM heterogeneity. To improve pre-clinical modeling of GBM ITH, we collected MRI-guided multi-region primary tumor biopsies from 6 GBM cases (n=40 biopsies) and derived neurosphere cultures (n=30) from these spatially distinct tumor samples. We characterized these samples by transcriptomic analysis and phylogenetic reconstruction of the tumor. Neurosphere cultures derived from these multi-region biopsies were tested for their proliferation, drug sensitivity, and transcriptomic similarity to their biopsy-of-origin. We found that in vitro cultures derived from distinct regions of the same tumor display divergent phenotypes, proliferative capacity and ability to accumulate 5-aminolevulinic acid, used to visualize cancer cells during surgery. Using a machine learning-based model we found that the differential drug response of the multi-region neurospheres remains linked to the gene expression of the original tumor biopsies. Our work demonstrates that joint profiling of the cell lines and their corresponding biopsies captures GBM ITH and enables more faithfully modeling of tumor heterogeneity for therapeutic testing. Luca Zanella Luca Zanella is a postdoctoral research scientist in the Andrea Califano’s laboratory at the Department of Systems Biology, Columbia University, New York. His research lies at the intersection between computer science, precision medicine and systems biology and involves the use of network-based computational methodologies to study tumor heterogeneity and drug repurposing in IDH-mutant glioma and dissect cancer cell adaptation mechanisms from perturbational data at single-cell resolution in several tumor contexts. Next generation cancer models, including organoids, neurospheres and conditionally reprogrammed cell lines, are significantly advancing our ability to study individual human tumors in vitro and to develop novel cancer therapeutics. However, questions emerged as to the degree to which in vitro models faithfully represent intra- and inter-patient cell state heterogeneity at the single-cell level. The Human Cancer Models Initiative (HCMI), a global collaboration involving the NCI (NIH), Cancer Research UK, the Wellcome Sanger Institute and the Hubrecht Organoid Technology foundation, has generated 665 patient-derived next-generation cancer models with matching parental tumor and clinical annotations. We performed tumor-model fidelity analysis using bulk RNA-seq, confirming strong cell-state concordance between models and parental tumors across most HCMI pairs, showcasing their ability to retain key tumor attributes. However, Angie Bowen Dr. Angie Bowen is recovering from Stage II Invasive Ductal Carcinoma. After being dismissed by her primary care physician initially, she pressed for diagnostic testing that confirmed cancer. The cancer journey has included concurrent mastectomy and reconstruction, hysterectomy and management of complex medication interactions and side effects. Since her diagnosis, she has leveraged her graduate and postdoctoral specialty in lactation and reproductive physiology and clinical operations experience to advocate for herself with her former physician, current medical team and for others through guidance and peer support. This experience coincided with her hiring at the MC2 Center and has resulted in a unique lived experience that informs her approach to education and outreach in the cancer biology community. Amber Nelson, MC² Center / Sage Bionetworks Christina Leslie Christina Leslie did her undergraduate degree in Pure and Applied Mathematics at the University of Waterloo in Canada. She was awarded an NSERC 1967 Science and Engineering Fellowship for graduate study and did a PhD in Mathematics at the University of California, Berkeley, with thesis work in differential geometry and representation theory. She won an NSERC Postdoctoral Fellowship and did her postdoctoral training in the Mathematics Department at Columbia University in 1999- 2000. She then joined the faculty of the Computer Science Department and later the Center for Computational Learning Systems at Columbia University, where she began to work in computational biology and machine learning. In 2007, she moved her lab to Memorial Sloan Kettering Cancer Center, where she is currently a Member of the Computational and Systems Biology Program. Dr. Leslie's research group uses computational methods to study the regulation of gene expression in mammalian cells and the dysregulation of expression programs in cancer. She is well known for developing machine learning and artificial intelligence (ML/AI) approaches for modeling single-cell, spatial, and 3D genomics data. Major biological domain areas include basic and cancer immunology, cancer epigenetics, and stem cell and developmental biology. Session Chair: Stephen Yi, Baylor College of Medicine Session Chair: Andrew Gentles (Stanford) and Paolo Provenzano (University of Minnesota) Dr. Justin Eyquem Justin Eyquem, PhD, is an Associate Professor of Medicine in the Division of Hem/Onc at UCSF. He is also an Investigator at the Gladstone-UCSF Institute for Genomic Immunology and the Parker Institute for Cancer Immunotherapy. He holds Master’s degrees in bioengineering and genetics from the Paris School of Agronomy (AgroParisTech) and the University of Paris. He earned his PhD in immunology and molecular biology from University of Paris and trained as a postdoctoral fellow in the laboratory of Michel Sadelain at Memorial Sloan-Kettering Cancer Center. In 2019, he joined UCSF as a Parker Fellow and became an Assistant Professor in 2021. Dr. Eyquem’s research focuses on optimizing genetically modified immune T cells, known as CAR-T cells, to fight cancers and other diseases. He has pioneered methods to edit the genome of human CAR-T cells and developed techniques to reprogram their functions both outside the body (ex vivo) and inside the body (in vivo). Additionally, he leads a preclinical team dedicated at designing the most effective therapies for a UCSF clinical pipeline. His work has earned him several awards, including the 2019 Parker Fellow Award, the 2023 ASGCT Outstanding New Investigator Award, and the 2024 Pew-Stewart Award. Ex vivo and In vivo genome engineering to reprogram T cells Advances in genome engineering and synthetic immunology are rapidly redefining how T cells can be designed and deployed against cancer. In this talk, I will present our CRISPR-based platforms for precise CAR T cell engineering, enabling site-specific integration and uniform, physiologic transgene expression. I will highlight our scalable discovery framework for accelerating CAR design and uncovering novel signaling protein variants through massively parallel, in situ functional screening. Finally, I will describe our recent progress in in vivo, site-specific CAR T cell engineering, enabling direct reprogramming of T cells without ex vivo manufacturing. Together, these efforts establish an integrated pipeline that spans from fundamental tool development to clinical translation, with the goal of bringing next-generation cell therapies from bench to bedside. Yining Chen Yining (Katherine) Chen is a PhD candidate at Columbia University. Their research focuses on pancreatic ductal adenocarcinoma (PDAC), specifically leveraging high-throughput transcriptomic profiling to identify and repurpose drugs capable of modulating tumor states. Katherine’s work further models how distinct PDAC states reprogram macrophages and explores the resulting therapeutic vulnerabilities. Targeting Tumor-Intrinsic Transcriptional States to Reprogram the Immunosuppressive Microenvironment in Pancreatic Ductal Adenocarcinoma (PDAC) PDAC remains among the most lethal malignancies, driven by extreme transcriptional plasticity and a profoundly immunosuppressive tumor microenvironment (TME). PDAC cells exist in distinct functional states, Gastrointestinal-like (GLS), Morphogenic (MOS), and Primitive (PLS), driven by Master Regulator (MR) proteins. Identifying state-specific therapeutic vulnerabilities while understanding how these states shape the surrounding immune landscape is critical to overcoming therapeutic resistance. In this study, we developed a systematic framework to investigate tumor-macrophage interactions in the context of PDAC transcriptional heterogeneity. We first developed pro- and anti-inflammatory transcriptional signatures across THP-1, PBMC, and iPSC-derived macrophage models to establish a robust baseline for myeloid differentiation and polarization. Preliminary co-culture assays reveal that distinct malignant states, specifically the MOS subtype, preferentially drive macrophages toward an immunosuppressive phenotype, suggesting that tumor-intrinsic MR activity contributes to immune evasion. To therapeutically intercept these subtypes, we integrated a network-based drug discovery pipeline, predicting state-specific compounds from a PLATE-seq based drug screen via the OncoTreat algorithm, then selected the top candidates for experimental validation using single-cell transcriptional profiling. We identified compounds with potent state-specific activity, including doxorubicin whose identification is consistent with prior evidence of activity in PDAC contexts, and the pan-RAS inhibitor RMC-7977, that shows robust targeting and transcriptional reprograming of defined PDAC malignant states. Together, this work provides a framework for mapping the relationship between PDAC transcriptional heterogeneity and immune reprogramming. By combining immune-phenotype benchmarking with network-based drug repurposing, we identify candidate strategies to simultaneously target malignant cell states and their associated remodeling of the immunosuppressive TME. Pawel Osmulski Interplay of strategies of mechanical adaptations of circulating tumor cells with their immune microenvironment in prostate cancer. Tumors of epithelial origin release cells into the bloodstream. Majority of them are eliminated due to fluid shear stress (FSS), anoikis or leukocyte attacks. However, surviving circulating tumor cells (CTCs) are detectable even in pre-metastatic patients. In a quest for origins of CTCs resilience in blood we focused on their essential properties distinguishing them from tumor-residing cells. We analyzed over 1200 CTCs from 78 patients. First, with nanomechanical phenotyping, we found that to survive FSS they have to be “mechanically fit”. We propose that the fitness comes in distinctive strategies of mechanical adaptations: “adhesive for clustering”, “deformable – leukocyte like” and “stiff – erythrocyte like”. Then, with immunocytochemical phenotyping and enumeration we investigated the “CTC microenvironment”: the particular setup of epithelial-like and mesenchymal-like CTCs, circulating tumor-associated macrophages, tumor-hybrid cells (fusion cells; THCs), and their clusters. THCs display epithelial tumor and macrophage specific markers, are found both in tumors and in circulation and are hallmark of aggressive disease. Importantly, particular strategies of adaptations seem connected to specific immune microenvironments. Not surprisingly, the CTC clusters were abundant in patients with numerous adhesive CTCs. In turn, the “leukocyte-like” strategy of CTCs was accompanied by abundant TMHs and circulating macrophages. By considering both nanomechanical and immune microenvironment phenotypes were able to stratify patients according to their risk of disease progression, from hormone sensitive to resistant and from oligometastatic to polymetastatic. We postulate that mechanical and immune microenvironment characteristics of CTCs may constitute predictive and prognostic biomarkers in prostate cancer. Professor (Research): Department of Molecular Medicine, UT Health San Antonio MSc and PhD (Molecular Biology and Biophysics): University of Lodz, Poland Postdoctoral (Physics/Biochemistry): University of Illinois at Urbana-Champaign Postdoctoral (Biological Chemistry) Harvard University My research interest centers around the biophysical characterization of cells and biomacromolecules with atomic force microscopy (AFM) to gain a deeper understanding of biological processes behind human health and disease, to identify novel therapies and develop drugs and biomarkers. I have over 25 years of experience with scanning probe microscopy/atomic orce microscopy of biological objects, with publications in Current Biology, PNAS, Nat. Struct. Mol. Biol., Nat. Comm, Structure and Cancer Research, among others. As Director of the AFM branch of BioAnalytics and Single Cell Institutional Core (BASiC), I have developed an AFM based single cell technology platform for comprehensive mechanical profiling of patient-isolated circulating tumor cells (CTCs) and other cancer cells. I introduced “nanomechanical phenotyping” of CTCs as an exceptionally sensitive way (predictive biomarker potential) to determine tumor cells’ invasive phenotype. The work resulted in multiple published papers (earliest: Prostate 2013 and 2014), including the 2021 Cancer Research cover story. Pointing at the significance of CTC adhesion in the cells’ metastatic potential is the most unique contribution of these works. On the “molecular” side of AFM, together with Dr. Gaczynska (a husband-wife research team) I developed mapping of allosteric transitions of the proteasome by AFM, of unique body of work that led to development of potential drug leads (four patents). I am involved in multiple collaborative molecular and cellular AFM projects on a variety of subjects ranging from the structure of protein-DNA complexes, amyloids and biomaterials to chemical affinity AFM and force spectrometry of cell-cell interactions. Gaetano Viscido Elucidation and pharmacologic targeting of Master Regulator proteins representing mechanistic determinants of macrophage state and immunoevasive potential Macrophages (mΦ) exhibit extensive transcriptional plasticity within the tumor microenvironment. While M1 mΦ promote anti-tumor immunity, M2 mΦ drive tumor progression and resistance to immune checkpoint therapy. In a recent study, Obradovic et al. (Cell 2021) used VIPER, a network-based algorithm inferring protein activity from transcriptomic data, to identify a highly immunosuppressive TAM subset in clear cell renal carcinoma characterized by TREM2⁺/C1Q⁺/APOE⁺ (TCA⁺) expression, associated with poor prognosis, metastasis, and immune evasion. We aim to identify Master Regulator (MR) proteins that mechanistically control the TCA⁺ program and may serve as actionable targets for selective depletion or reprogramming of these cells toward neutral (M0) or pro-inflammatory (M1) states. We performed pooled single-cell CRISPRi via Perturb-seq targeting 50 candidate MRs identified by VIPER from genes differentially expressed in TCA⁺ versus M0/M1 mΦs, followed by time-resolved scRNA-seq. THP-1 monocytes were differentiated to M2 using IL-4/IL-13 and profiled across seven time points (0–192 hr), with ~100,000 cells per time point and ~10,000 unperturbed M0, M1, and M2 mΦs as references. Additionally, we will generate perturbational RNA-seq profiles of TCA⁺ mΦs with >350 drugs using PLATE-seq to identify compounds targeting individual MRs (OncoTarget) or inverting the global MR-activity signature (OncoTreat). We generated ~700,000 time-resolved, genetically perturbed mΦs, enabling high-resolution characterization of MR-specific transcriptional responses across M2/TCA⁺ polarization. Integration with drug-perturbation profiles will establish a pharmacologic resource for identifying compounds capable of shifting the TCA⁺ transcriptional program. This framework offers a path to neutralize mΦ-mediated immunosuppression and improve responses to immune checkpoint therapy. Pilar de la Puente Pilar de la Puente, PhD, is an Associate Scientist / Associate Professor at Sanford Research / University of South Dakota School of Medicine. She earned her PhD in Biomedical Engineering and Biological Sciences at the University of Salamanca in Spain. Dr. de la Puente completed postdoctoral training at Washington University in St Louis School of Medicine in cancer tissue engineering, nanomedicine and translational precision-based drug screenings. The de la Puente lab develops novel, human, precision-based models that empower drug screening by more closely replicating a tissue microenvironment for in vitro assays. She uses her interdisciplinary training in tissue engineering, cancer biology, drug resistance, and immunoengineering to solve pressing questions in chemoresistance, immune evasion and precision medicine for women’s cancer. Dr. de la Puente’s contributions have been recognized through numerous funding including NIH-R37-MERIT Award, American Cancer Society Research Scholar Grant and several other foundation- and NIH-funded grants. Her work has gained national recognition with important awards and recognitions including the American Institute for Medical and Biological Engineering (AIMBE) Emerging Leader, Cell and Molecular Bioengineering (CMBE) Rising Star from the Biomedical Engineering Society (BMES), NIH Early Investigator Advancement Program (EIAP) Scholar from the National Cancer Institute, the “35 under 35” BussinesInsider Spain, she was inducted a ResearchHERS Scholar by the American Cancer Society, acknowledging her as a trailblazing woman researcher, and the Lush Prize 2018. Dr. de la Puente has also demonstrated strong entrepreneurial leadership through the translation of her lab’s technologies into several patents for drug development and precision oncology applications and a start-up company, Cellatrix LLC. Her work bridges the gap between academic innovation and industry, with a clear vision for clinical impact. Hypoxia-Induced ECM Remodeling as a Barrier to Immune Infiltration in Ovarian Tumors: Insights from Engineered Extracellular Matrix Models High grade serous ovarian cancer is characterized by an immunologically “cold” tumor microenvironment, with limited immune infiltration and poor clinical outcomes. A major contributor to this phenotype is extensive extracellular matrix (ECM) remodeling, which is strongly influenced by hypoxia. However, commonly used experimental models fail to adequately recapitulate physiologically relevant oxygen conditions and matrix architecture, limiting progress in understanding tumor–immune interactions and the development of effective therapies. To address this, we developed patient derived tumor–immune models that incorporate cancer cells, cancer associated fibroblasts, and immune cells within engineered matrices composed of autologous plasma or decellularized ovarian tissue. These systems reproduce physiological oxygen levels while enabling controlled manipulation of ECM remodeling. Using this platform, we demonstrate that hypoxia induced ECM remodeling, rather than hypoxia alone, establishes a physical and biochemical barrier that restricts immune cell infiltration into tumor nests. Under hypoxic conditions, fibroblasts generate dense, highly crosslinked ECM that impedes immune trafficking and promotes immune exclusion. Notably, CD8⁺ T cells that infiltrate remodeled matrices exhibit enhanced activation and cytotoxicity, revealing a paradoxical relationship between matrix remodeling and immune function. Mechanistically, we identify TGF β signaling as a key driver of hypoxia mediated ECM remodeling. Pharmacologic inhibition of TGF β attenuates these matrix changes, significantly improves immune cell penetration, and restores tumor–immune interactions. Together, these findings underscore the importance of physiologically relevant stromal and oxygen landscapes in regulating immune accessibility in ovarian cancer. This work highlights ECM remodeling pathways as promising therapeutic targets to convert immunologically “cold” tumors into “hot” tumors and enhance immunotherapy efficacy. Dr. Justin Eyquem Justin Eyquem, PhD, is an Associate Professor of Medicine in the Division of Hem/Onc at UCSF. He is also an Investigator at the Gladstone-UCSF Institute for Genomic Immunology and the Parker Institute for Cancer Immunotherapy. He holds Master’s degrees in bioengineering and genetics from the Paris School of Agronomy (AgroParisTech) and the University of Paris. He earned his PhD in immunology and molecular biology from University of Paris and trained as a postdoctoral fellow in the laboratory of Michel Sadelain at Memorial Sloan-Kettering Cancer Center. In 2019, he joined UCSF as a Parker Fellow and became an Assistant Professor in 2021. Dr. Eyquem’s research focuses on optimizing genetically modified immune T cells, known as CAR-T cells, to fight cancers and other diseases. He has pioneered methods to edit the genome of human CAR-T cells and developed techniques to reprogram their functions both outside the body (ex vivo) and inside the body (in vivo). Additionally, he leads a preclinical team dedicated at designing the most effective therapies for a UCSF clinical pipeline. His work has earned him several awards, including the 2019 Parker Fellow Award, the 2023 ASGCT Outstanding New Investigator Award, and the 2024 Pew-Stewart Award. Ex vivo and In vivo genome engineering to reprogram T cells Advances in genome engineering and synthetic immunology are rapidly redefining how T cells can be designed and deployed against cancer. In this talk, I will present our CRISPR-based platforms for precise CAR T cell engineering, enabling site-specific integration and uniform, physiologic transgene expression. I will highlight our scalable discovery framework for accelerating CAR design and uncovering novel signaling protein variants through massively parallel, in situ functional screening. Finally, I will describe our recent progress in in vivo, site-specific CAR T cell engineering, enabling direct reprogramming of T cells without ex vivo manufacturing. Together, these efforts establish an integrated pipeline that spans from fundamental tool development to clinical translation, with the goal of bringing next-generation cell therapies from bench to bedside. Pilar de la Puente Pilar de la Puente, PhD, is an Associate Scientist / Associate Professor at Sanford Research / University of South Dakota School of Medicine. She earned her PhD in Biomedical Engineering and Biological Sciences at the University of Salamanca in Spain. Dr. de la Puente completed postdoctoral training at Washington University in St Louis School of Medicine in cancer tissue engineering, nanomedicine and translational precision-based drug screenings. The de la Puente lab develops novel, human, precision-based models that empower drug screening by more closely replicating a tissue microenvironment for in vitro assays. She uses her interdisciplinary training in tissue engineering, cancer biology, drug resistance, and immunoengineering to solve pressing questions in chemoresistance, immune evasion and precision medicine for women’s cancer. Dr. de la Puente’s contributions have been recognized through numerous funding including NIH-R37-MERIT Award, American Cancer Society Research Scholar Grant and several other foundation- and NIH-funded grants. Her work has gained national recognition with important awards and recognitions including the American Institute for Medical and Biological Engineering (AIMBE) Emerging Leader, Cell and Molecular Bioengineering (CMBE) Rising Star from the Biomedical Engineering Society (BMES), NIH Early Investigator Advancement Program (EIAP) Scholar from the National Cancer Institute, the “35 under 35” BussinesInsider Spain, she was inducted a ResearchHERS Scholar by the American Cancer Society, acknowledging her as a trailblazing woman researcher, and the Lush Prize 2018. Dr. de la Puente has also demonstrated strong entrepreneurial leadership through the translation of her lab’s technologies into several patents for drug development and precision oncology applications and a start-up company, Cellatrix LLC. Her work bridges the gap between academic innovation and industry, with a clear vision for clinical impact. Hypoxia-Induced ECM Remodeling as a Barrier to Immune Infiltration in Ovarian Tumors: Insights from Engineered Extracellular Matrix Models High grade serous ovarian cancer is characterized by an immunologically “cold” tumor microenvironment, with limited immune infiltration and poor clinical outcomes. A major contributor to this phenotype is extensive extracellular matrix (ECM) remodeling, which is strongly influenced by hypoxia. However, commonly used experimental models fail to adequately recapitulate physiologically relevant oxygen conditions and matrix architecture, limiting progress in understanding tumor–immune interactions and the development of effective therapies. To address this, we developed patient derived tumor–immune models that incorporate cancer cells, cancer associated fibroblasts, and immune cells within engineered matrices composed of autologous plasma or decellularized ovarian tissue. These systems reproduce physiological oxygen levels while enabling controlled manipulation of ECM remodeling. Using this platform, we demonstrate that hypoxia induced ECM remodeling, rather than hypoxia alone, establishes a physical and biochemical barrier that restricts immune cell infiltration into tumor nests. Under hypoxic conditions, fibroblasts generate dense, highly crosslinked ECM that impedes immune trafficking and promotes immune exclusion. Notably, CD8⁺ T cells that infiltrate remodeled matrices exhibit enhanced activation and cytotoxicity, revealing a paradoxical relationship between matrix remodeling and immune function. Mechanistically, we identify TGF β signaling as a key driver of hypoxia mediated ECM remodeling. Pharmacologic inhibition of TGF β attenuates these matrix changes, significantly improves immune cell penetration, and restores tumor–immune interactions. Together, these findings underscore the importance of physiologically relevant stromal and oxygen landscapes in regulating immune accessibility in ovarian cancer. This work highlights ECM remodeling pathways as promising therapeutic targets to convert immunologically “cold” tumors into “hot” tumors and enhance immunotherapy efficacy. Pawel Osmulski Interplay of strategies of mechanical adaptations of circulating tumor cells with their immune microenvironment in prostate cancer. Tumors of epithelial origin release cells into the bloodstream. Majority of them are eliminated due to fluid shear stress (FSS), anoikis or leukocyte attacks. However, surviving circulating tumor cells (CTCs) are detectable even in pre-metastatic patients. In a quest for origins of CTCs resilience in blood we focused on their essential properties distinguishing them from tumor-residing cells. We analyzed over 1200 CTCs from 78 patients. First, with nanomechanical phenotyping, we found that to survive FSS they have to be “mechanically fit”. We propose that the fitness comes in distinctive strategies of mechanical adaptations: “adhesive for clustering”, “deformable – leukocyte like” and “stiff – erythrocyte like”. Then, with immunocytochemical phenotyping and enumeration we investigated the “CTC microenvironment”: the particular setup of epithelial-like and mesenchymal-like CTCs, circulating tumor-associated macrophages, tumor-hybrid cells (fusion cells; THCs), and their clusters. THCs display epithelial tumor and macrophage specific markers, are found both in tumors and in circulation and are hallmark of aggressive disease. Importantly, particular strategies of adaptations seem connected to specific immune microenvironments. Not surprisingly, the CTC clusters were abundant in patients with numerous adhesive CTCs. In turn, the “leukocyte-like” strategy of CTCs was accompanied by abundant TMHs and circulating macrophages. By considering both nanomechanical and immune microenvironment phenotypes were able to stratify patients according to their risk of disease progression, from hormone sensitive to resistant and from oligometastatic to polymetastatic. We postulate that mechanical and immune microenvironment characteristics of CTCs may constitute predictive and prognostic biomarkers in prostate cancer. Professor (Research): Department of Molecular Medicine, UT Health San Antonio MSc and PhD (Molecular Biology and Biophysics): University of Lodz, Poland Postdoctoral (Physics/Biochemistry): University of Illinois at Urbana-Champaign Postdoctoral (Biological Chemistry) Harvard University My research interest centers around the biophysical characterization of cells and biomacromolecules with atomic force microscopy (AFM) to gain a deeper understanding of biological processes behind human health and disease, to identify novel therapies and develop drugs and biomarkers. I have over 25 years of experience with scanning probe microscopy/atomic orce microscopy of biological objects, with publications in Current Biology, PNAS, Nat. Struct. Mol. Biol., Nat. Comm, Structure and Cancer Research, among others. As Director of the AFM branch of BioAnalytics and Single Cell Institutional Core (BASiC), I have developed an AFM based single cell technology platform for comprehensive mechanical profiling of patient-isolated circulating tumor cells (CTCs) and other cancer cells. I introduced “nanomechanical phenotyping” of CTCs as an exceptionally sensitive way (predictive biomarker potential) to determine tumor cells’ invasive phenotype. The work resulted in multiple published papers (earliest: Prostate 2013 and 2014), including the 2021 Cancer Research cover story. Pointing at the significance of CTC adhesion in the cells’ metastatic potential is the most unique contribution of these works. On the “molecular” side of AFM, together with Dr. Gaczynska (a husband-wife research team) I developed mapping of allosteric transitions of the proteasome by AFM, of unique body of work that led to development of potential drug leads (four patents). I am involved in multiple collaborative molecular and cellular AFM projects on a variety of subjects ranging from the structure of protein-DNA complexes, amyloids and biomaterials to chemical affinity AFM and force spectrometry of cell-cell interactions. Yining Chen Yining (Katherine) Chen is a PhD candidate at Columbia University. Their research focuses on pancreatic ductal adenocarcinoma (PDAC), specifically leveraging high-throughput transcriptomic profiling to identify and repurpose drugs capable of modulating tumor states. Katherine’s work further models how distinct PDAC states reprogram macrophages and explores the resulting therapeutic vulnerabilities. Targeting Tumor-Intrinsic Transcriptional States to Reprogram the Immunosuppressive Microenvironment in Pancreatic Ductal Adenocarcinoma (PDAC) PDAC remains among the most lethal malignancies, driven by extreme transcriptional plasticity and a profoundly immunosuppressive tumor microenvironment (TME). PDAC cells exist in distinct functional states, Gastrointestinal-like (GLS), Morphogenic (MOS), and Primitive (PLS), driven by Master Regulator (MR) proteins. Identifying state-specific therapeutic vulnerabilities while understanding how these states shape the surrounding immune landscape is critical to overcoming therapeutic resistance. In this study, we developed a systematic framework to investigate tumor-macrophage interactions in the context of PDAC transcriptional heterogeneity. We first developed pro- and anti-inflammatory transcriptional signatures across THP-1, PBMC, and iPSC-derived macrophage models to establish a robust baseline for myeloid differentiation and polarization. Preliminary co-culture assays reveal that distinct malignant states, specifically the MOS subtype, preferentially drive macrophages toward an immunosuppressive phenotype, suggesting that tumor-intrinsic MR activity contributes to immune evasion. To therapeutically intercept these subtypes, we integrated a network-based drug discovery pipeline, predicting state-specific compounds from a PLATE-seq based drug screen via the OncoTreat algorithm, then selected the top candidates for experimental validation using single-cell transcriptional profiling. We identified compounds with potent state-specific activity, including doxorubicin whose identification is consistent with prior evidence of activity in PDAC contexts, and the pan-RAS inhibitor RMC-7977, that shows robust targeting and transcriptional reprograming of defined PDAC malignant states. Together, this work provides a framework for mapping the relationship between PDAC transcriptional heterogeneity and immune reprogramming. By combining immune-phenotype benchmarking with network-based drug repurposing, we identify candidate strategies to simultaneously target malignant cell states and their associated remodeling of the immunosuppressive TME. Gaetano Viscido Elucidation and pharmacologic targeting of Master Regulator proteins representing mechanistic determinants of macrophage state and immunoevasive potential Macrophages (mΦ) exhibit extensive transcriptional plasticity within the tumor microenvironment. While M1 mΦ promote anti-tumor immunity, M2 mΦ drive tumor progression and resistance to immune checkpoint therapy. In a recent study, Obradovic et al. (Cell 2021) used VIPER, a network-based algorithm inferring protein activity from transcriptomic data, to identify a highly immunosuppressive TAM subset in clear cell renal carcinoma characterized by TREM2⁺/C1Q⁺/APOE⁺ (TCA⁺) expression, associated with poor prognosis, metastasis, and immune evasion. We aim to identify Master Regulator (MR) proteins that mechanistically control the TCA⁺ program and may serve as actionable targets for selective depletion or reprogramming of these cells toward neutral (M0) or pro-inflammatory (M1) states. We performed pooled single-cell CRISPRi via Perturb-seq targeting 50 candidate MRs identified by VIPER from genes differentially expressed in TCA⁺ versus M0/M1 mΦs, followed by time-resolved scRNA-seq. THP-1 monocytes were differentiated to M2 using IL-4/IL-13 and profiled across seven time points (0–192 hr), with ~100,000 cells per time point and ~10,000 unperturbed M0, M1, and M2 mΦs as references. Additionally, we will generate perturbational RNA-seq profiles of TCA⁺ mΦs with >350 drugs using PLATE-seq to identify compounds targeting individual MRs (OncoTarget) or inverting the global MR-activity signature (OncoTreat). We generated ~700,000 time-resolved, genetically perturbed mΦs, enabling high-resolution characterization of MR-specific transcriptional responses across M2/TCA⁺ polarization. Integration with drug-perturbation profiles will establish a pharmacologic resource for identifying compounds capable of shifting the TCA⁺ transcriptional program. This framework offers a path to neutralize mΦ-mediated immunosuppression and improve responses to immune checkpoint therapy. Session Chair: Shari Pilon-Thomas (Moffitt Cancer Center), Ziwei Pan (Sage Bionetworks) Jiyang Yu Jiyang Yu, PhD, is a Member and Interim Chair of the Department of Computational Biology at St. Jude Children’s Research Hospital. He received his BS in Computer Science from Zhejiang University (2006) and his PhD in Biomedical Informatics from Columbia University (2012), where he trained in Dr. Andrea Califano’s laboratory. Following his PhD, Dr. Yu worked as a senior scientist in Pfizer Oncology focusing on cancer precision medicine. He joined St. Jude in 2016 as an Assistant Member, was promoted to Associate Member in 2021, and became a Member in 2025. Dr. Yu’s laboratory integrates computational and experimental biology to elucidate intracellular and intercellular networks that drive complex biological systems and diseases, particularly cancer. Leveraging multi-omics approaches—including single-cell and spatial omics—his team uncovers “hidden” drivers and develops therapeutic strategies that advance toward patient care. Several of the lab’s discoveries have led to clinical trials across multiple cancer types. Dr. Yu has authored over 80 peer-reviewed publications in leading journals, including Nature, Cell, Cancer Cell, Cancer Discovery, Nature Cancer, and Nature Methods. Learn more: https://www.stjude.org/research/labs/yu-lab.html. Diviya Sinha Diviya Sinha is a recent MIT PhD graduate specializing in immune engineering and drug delivery. She also holds an MS from MIT and a BTech in Chemical Engineering from IIT Kanpur, India. Diviya currently serves as Chair of the MC² Spatial Profiling Special Interest Group and is in transition between postdoctoral positions. She is an active STEM community organizer with MASS AWIS, where she leads outreach and professional development initiatives supporting women scientists. Energizing the skin immune system with ultrasound microbubbles and surfactant sodium lauryl sulfate for adjuvant free T cell tumor therapy Needle-based intramuscular immunizations, widely used with simple protein formulations, rarely elicit strong CD8 T cell responses that are vital for protection against viral infections and cancer. The skin's rich immune cell content is an attractive alternative; however, the topmost layer serves as the primary diffusion barrier for topical antigens to access the skin's immune network effectively. In this work, we overcome this challenge by combining low-frequency ultrasound with an aqueous 1% (w/v) sodium lauryl sulfate surfactant solution. Ultrasound applied in an aqueous medium creates microbubbles due to oscillating pressure waves, which form tiny microjets that impinge on the skin surface, resulting in a safe and reversible permeabilization of the skin barrier. Transcriptomic profiling demonstrates that this treatment upregulates inflammatory and chemotactic genes, and that this effect is further enhanced and prolonged in the presence of the surfactant. Antigen-specific T cell assays show a strong correlation between induced proliferation and skin perturbation, as measured by skin impedance, which further informs treatment optimization for skin immunization technologies. Activated T cells displayed a Th1-skewed, polyfunctional phenotype and durable memory that was capable of robust recall months later to a viral challenge. In tumor models, ultrasound immunization led to complete tumor rejection (EG7-OVA) and extended survival (B16-OVA), showing strong antitumor effects. Overall, low-frequency ultrasound, when paired with surfactant, activates skin immunity, drives potent T cell responses, and confers therapeutic benefits in tumors. This approach is safe, scalable, and suitable for cancer vaccines and combination immunotherapies. Sandhya Prabhakaran Dr. Sandhya Prabhakaran is a Research Scientist with Dr. Alexander (Sandy) Anderson at the Integrated Mathematical Oncology (IMO) department, Moffitt Cancer Centre, Florida. Before that she was a Research Scientist at Memorial Sloan Kettering Cancer Centre and Columbia University. Her Ph.D. in Computer Science is from University of Basel and her Masters in Intelligent Systems (Robotics) is from University of Edinburgh where she was a fully funded Scottish International Scholar. Sandhya's research deals with developing statistical theory, mathematical mechanistic models (ODEs, Agent-based models), PINNs, vision transformers, and Bayesian inference models, particularly to problems in Cancer Biology and Computer Vision. She works with both high-dimensional data (images, genomics) and low-dimensional experimental data. She is keen to understand the spatio-temporal dynamics of tumor-immune interactions, with and without drugs, and studies these interactions at the patient level to better predict optimal treatment strategies. She is also interested in connecting these studies with patient toxicity. Prior to academics, Sandhya was an Assembler programmer working with the Mainframe Operating System (z/OS) at IBM Software Laboratories and has developed Mainframe applications. She has completed 4 out of the 6 World Marathon Majors. Website: https://sandhyaprabhakaran.com/ Evolutionary immunotherapy in NSCLC: identifying optimal dosing strategies in adoptive cell therapies using agent-based modeling PURPOSE: Our study examines tumor growth dynamics and immunosuppression under the presence of immune attack to identify optimal immune pulsing treatment strategies. BACKGROUND: TIL therapy is an emerging immunotherapy where activated T cells are injected into the patient. This therapy can fail due to tumor-induced immunosuppression, for example via the PDL1/PD1 axis. PDL1 expression has been studied and can increase under IFNg, released by activated T cells, but PD-L1 relaxation is not understood. We hypothesize that there may be better strategies of therapy delivery that maximize tumor kill while minimizing immune suppression. We investigate these complex PD-L1 driven dynamics through a unique combination of in vitro studies and mathematical modeling. METHODS: We have collected in vitro PD-L1 expression on NSCLC cells, which were either untreated or treated for 48 hours with high dose IFNg. To reinforce our in vitro findings, we developed a hybrid agent-based model (ABM). The agents in the ABM are tumor cells having variable PD-L1 expression, and immune cells that secrete IFNg and can kill tumor cells. We model TIL therapy as an immune cell pulse, given at regular or irregular intervals. RESULTS: Our ABM is calibrated to capture in vitro data dynamics. Under certain combinations of spatial configurations of the tumor and intermittent immune dosing schedules, we observe the presence of ‘sweet spots’ where tumor extinction is possible and immune exhaustion is avoided. This indicates that an appropriate pulsing of TIL therapy may lead to better overall immune efficacy than a bolus injection or continuous immunotherapy. Our novel findings can potentially benefit clinical cancer research by giving multiple insights related to the tumor extinction, equilibrium and escape phenomena. Michelle Loui Michelle Loui, a graduate student in the bioengineering department at UCLA, is researching adaptive immunity in ovarian cancer. She employs systems biology approaches to understand B cell-mediated anti-tumor immunity in therapeutically resistant cancers Systems serology of responses against tumor antigens in ovarian cancer reveal disrupted Fc-mediated immunity High-grade serous ovarian cancer (HGSOC) represents 75% of ovarian cancer cases and 80% of deaths, with most patients relapsing despite initial treatment response. The limited effectiveness of immunotherapies in HGSOC indicates urgent need for novel therapeutic approaches. HGSOC patients produce tumor-binding autoantibodies (TBAs) with high tumor selectivity. Since effective antibody-mediated tumor cell killing requires Fc domain interactions with immune cells, we hypothesized that, although TBAs recognize tumor cells, they might still poorly elicit cell killing responses. Using a systems serology approach, we profiled TBA subclass and biophysical interactions with Fc receptors in HGSOC, comparing them to antiviral antibody responses. TBAs were consistently identified within ascites and serum and were heterogeneous in subclass composition. However, TBAs consistently lacked the capacity to bind FcγRIIIa despite abundant interaction with FcγRIIa and poorly elicited antibody-dependent cellular cytotoxicity, suggesting their Fc features prevent cell killing responses. Restoring FcγRIIIa interaction may be a promising therapeutic approach in HGSOC. Ligand presentation format on biomaterials controls CAR-T cell expansion - Qinghe Zeng, Drexel University Microglia Characterization in Hyaluronic-Acid Based Hydrogels - Shabnam Nejat, University of Texas at Austin Reprogramming T Cell Motility and Function Through the RhoA Pathway - Hongrong Zhang, University of Minnesota HIV Nef amplifies mechanical heterogeneity to promote immune evasion - Farrah Mustapha, Memorial Sloan Kettering Cancer Center Michelle Loui Michelle Loui, a graduate student in the bioengineering department at UCLA, is researching adaptive immunity in ovarian cancer. She employs systems biology approaches to understand B cell-mediated anti-tumor immunity in therapeutically resistant cancers Systems serology of responses against tumor antigens in ovarian cancer reveal disrupted Fc-mediated immunity High-grade serous ovarian cancer (HGSOC) represents 75% of ovarian cancer cases and 80% of deaths, with most patients relapsing despite initial treatment response. The limited effectiveness of immunotherapies in HGSOC indicates urgent need for novel therapeutic approaches. HGSOC patients produce tumor-binding autoantibodies (TBAs) with high tumor selectivity. Since effective antibody-mediated tumor cell killing requires Fc domain interactions with immune cells, we hypothesized that, although TBAs recognize tumor cells, they might still poorly elicit cell killing responses. Using a systems serology approach, we profiled TBA subclass and biophysical interactions with Fc receptors in HGSOC, comparing them to antiviral antibody responses. TBAs were consistently identified within ascites and serum and were heterogeneous in subclass composition. However, TBAs consistently lacked the capacity to bind FcγRIIIa despite abundant interaction with FcγRIIa and poorly elicited antibody-dependent cellular cytotoxicity, suggesting their Fc features prevent cell killing responses. Restoring FcγRIIIa interaction may be a promising therapeutic approach in HGSOC. Diviya Sinha Diviya Sinha is a recent MIT PhD graduate specializing in immune engineering and drug delivery. She also holds an MS from MIT and a BTech in Chemical Engineering from IIT Kanpur, India. Diviya currently serves as Chair of the MC² Spatial Profiling Special Interest Group and is in transition between postdoctoral positions. She is an active STEM community organizer with MASS AWIS, where she leads outreach and professional development initiatives supporting women scientists. Energizing the skin immune system with ultrasound microbubbles and surfactant sodium lauryl sulfate for adjuvant free T cell tumor therapy Needle-based intramuscular immunizations, widely used with simple protein formulations, rarely elicit strong CD8 T cell responses that are vital for protection against viral infections and cancer. The skin's rich immune cell content is an attractive alternative; however, the topmost layer serves as the primary diffusion barrier for topical antigens to access the skin's immune network effectively. In this work, we overcome this challenge by combining low-frequency ultrasound with an aqueous 1% (w/v) sodium lauryl sulfate surfactant solution. Ultrasound applied in an aqueous medium creates microbubbles due to oscillating pressure waves, which form tiny microjets that impinge on the skin surface, resulting in a safe and reversible permeabilization of the skin barrier. Transcriptomic profiling demonstrates that this treatment upregulates inflammatory and chemotactic genes, and that this effect is further enhanced and prolonged in the presence of the surfactant. Antigen-specific T cell assays show a strong correlation between induced proliferation and skin perturbation, as measured by skin impedance, which further informs treatment optimization for skin immunization technologies. Activated T cells displayed a Th1-skewed, polyfunctional phenotype and durable memory that was capable of robust recall months later to a viral challenge. In tumor models, ultrasound immunization led to complete tumor rejection (EG7-OVA) and extended survival (B16-OVA), showing strong antitumor effects. Overall, low-frequency ultrasound, when paired with surfactant, activates skin immunity, drives potent T cell responses, and confers therapeutic benefits in tumors. This approach is safe, scalable, and suitable for cancer vaccines and combination immunotherapies. Qinghe Zeng Ligand presentation format on biomaterials controls CAR-T cell expansion Enhancing T cell persistence is essential for achieving durable clinical responses in chimeric antigen receptor (CAR) T cell therapy. We developed a CAR-engaging particle (CAREp) consisting of a PLGA core with surface DNA scaffolds that enable sustained CAR-T cell proliferation and promote a memory-like phenotype. CAREp stimulation supported continuous CAR-T cell proliferation for over 100 days, achieving cumulative expansions of ~10¹²–10¹⁸-fold across multiple donors and CAR constructs, far exceeding expansion induced by cancer cells or CD3/CD28 Dynabeads. CAREp stimulation also improved mitochondrial fitness, and transcriptomic upregulation of pathways associated with DNA repair, cell cycle progression, chromatin remodeling, protein translation, telomere maintenance, and mitochondrial function. Although our biomaterial represents a promising strategy to enhance CAR-T cell persistence, the key factors determining whether biomaterials can affect the expansion of CAR-T cells have not yet been identified. We hypothesized that the physical format of biomaterial-mediated ligand presentation—including scaffold structure, ligand stability, particle size, antigen density, and core stiffness—regulates immune synapse formation between CAR-T cells and biomaterials and thereby determines CAR-T cell expansion outcomes. To test this hypothesis, we systematically compared particles with distinct ligand presentation formats and material properties. PEG-based antigen presentation failed to sustain long-term proliferation despite similar antigen density, and increased ligand detachability resulted in ~50-fold lower EGFR-CD28 CAR-T cell expansion than CAREp, highlighting the importance of ligand presentation format. Together, these findings demonstrate that the physical format of antigen presentation is a key determinant of CAR-T cell expansion and provide a foundation for next-generation CAR-T manufacturing strategies. Shabnam Nejat Microglia Characterization in Hyaluronic-Acid Based Hydrogels Microglia are resident immune cells of the central nervous system (CNS) that modulate inflammatory responses in injury, pathology, and neurodegenerative conditions. However, persistent and imbalances of microglia activation states can result in chronic neuroinflammation, neurotoxic tissue damage, and/or neurodegeneration. Since the role of microglia in pathological conditions remains unclear, hyaluronic acid (HA)-based biomaterial scaffolds can be independently tuned as a promising experimental system to evaluate microglia cell behavior. HA is a key glycosaminoglycan in the brain and used in our scaffolds to mimic the natural tissue microenvironment. Following CNS injury or disease, tissue regions are known to significantly soften or stiffen. Stiffness and viscosity mechanical changes can be independently tuned in our previously developed HA-based elastic (single network) and visco-elastic (double network) hydrogels to characterize and study microglia cell activation (inflammatory responses). Human microglia immortalized cells (hTERT) are polarized towards a pro-inflammatory phenotype using lipopolysaccharides (LPS) and interferon gamma (IFNY) and towards an anti-inflammatory phenotype using interleukin-4 (IL-4) to characterize cell morphology, quantify inflammatory proteins, and evaluate phagocytotic abilities in 2D culture and compare to 3D hydrogel systems when viscosity and stiffness are independently varied. Our results demonstrate the importance of considering multiple mechanical features of viscoelastic matrices when designing brain-mimetic models to study neuroinflammation. Hongrong Zhang Reprogramming T Cell Motility and Function Through the RhoA Pathway Despite being the 14th most common cancer, pancreatic cancer—particularly pancreatic ductal adenocarcinoma (PDA)—is projected to become the second leading cause of cancer-related deaths due to late diagnosis, aggressive progression, and limited treatment options. T cell-based immunotherapy offers a promising alternative. Indeed, higher densities of peritumoral CD8⁺ T cells are associated with improved survival in PDA and other solid tumors. However, T cell presence alone is insufficient; effective anti-tumor immunity requires robust infiltration, sustained tumor engagement, and cytotoxic activity. Enhancing T cell trafficking, intratumoral migration, and interaction with tumor cells is therefore critical for improving immunotherapy efficacy. In this study, we engineered CD8⁺ T cells to express a constitutively active RhoA mutant using CRISPR/Cas9 genome editing and evaluated their migratory behavior, metabolic profile, differentiation status, and tumor interaction. Engineered T cells exhibited significantly increased total RhoA and RhoA-GTP levels without affecting proliferation or viability, indicating that sustained RhoA activation does not impose a metabolic burden. Functionally, these cells exhibited enhanced motility in 3D collagen matrices and live PDA tumor slices, adopting an amoeboid migration phenotype with increased metabolic activity and cortical tension. To assess therapeutic relevance, we incorporated the RhoA mutation into mesothelin-targeting CAR T cells (mesoCAR). While cytotoxicity remained comparable in 2D assays, RhoA mutant mesoCAR T cells showed significantly higher tumor interaction frequency in 3D cultures, suggesting improved tumor search efficiency. Overall, these suggest RhoA as a potent driver of T cell motility, offering a novel approach to overcome physical barriers in PDA and enhance immunotherapy outcomes. Farah Mustapha HIV Nef amplifies mechanical heterogeneity to promote immune evasion Intracellular pathogens must evade cytotoxic immunity to establish persistent infection. Although immune escape is typically viewed through a biochemical lens, the ability of certain pathogens to alter mechanical properties of infected cells suggests that biophysical mechanisms may also contribute. Here, we show that a subset of CD4+ T cells infected with the human immunodeficiency virus (HIV) resist elimination through a soft phenotype that impairs killing by mechanosensitive cytotoxic T lymphocytes (CTLs). This phenotype arises from the combined effects of the HIV virulence factor Nef, which remodels the actin cytoskeleton, and intrinsic heterogeneity in basal cytoskeletal properties of T cells. Although cells that are sufficiently soft to resist CTLs are relatively rare, this property can be detected in HIV-infected CD4+ T cell clones from people living with HIV, implicating a role for this mechanism in reservoir persistence. These findings define a biophysical paradigm of immune evasion with implications for HIV cure strategies. Sandhya Prabhakaran Dr. Sandhya Prabhakaran is a Research Scientist with Dr. Alexander (Sandy) Anderson at the Integrated Mathematical Oncology (IMO) department, Moffitt Cancer Centre, Florida. Before that she was a Research Scientist at Memorial Sloan Kettering Cancer Centre and Columbia University. Her Ph.D. in Computer Science is from University of Basel and her Masters in Intelligent Systems (Robotics) is from University of Edinburgh where she was a fully funded Scottish International Scholar. Sandhya's research deals with developing statistical theory, mathematical mechanistic models (ODEs, Agent-based models), PINNs, vision transformers, and Bayesian inference models, particularly to problems in Cancer Biology and Computer Vision. She works with both high-dimensional data (images, genomics) and low-dimensional experimental data. She is keen to understand the spatio-temporal dynamics of tumor-immune interactions, with and without drugs, and studies these interactions at the patient level to better predict optimal treatment strategies. She is also interested in connecting these studies with patient toxicity. Prior to academics, Sandhya was an Assembler programmer working with the Mainframe Operating System (z/OS) at IBM Software Laboratories and has developed Mainframe applications. She has completed 4 out of the 6 World Marathon Majors. Website: https://sandhyaprabhakaran.com/ Evolutionary immunotherapy in NSCLC: identifying optimal dosing strategies in adoptive cell therapies using agent-based modeling PURPOSE: Our study examines tumor growth dynamics and immunosuppression under the presence of immune attack to identify optimal immune pulsing treatment strategies. BACKGROUND: TIL therapy is an emerging immunotherapy where activated T cells are injected into the patient. This therapy can fail due to tumor-induced immunosuppression, for example via the PDL1/PD1 axis. PDL1 expression has been studied and can increase under IFNg, released by activated T cells, but PD-L1 relaxation is not understood. We hypothesize that there may be better strategies of therapy delivery that maximize tumor kill while minimizing immune suppression. We investigate these complex PD-L1 driven dynamics through a unique combination of in vitro studies and mathematical modeling. METHODS: We have collected in vitro PD-L1 expression on NSCLC cells, which were either untreated or treated for 48 hours with high dose IFNg. To reinforce our in vitro findings, we developed a hybrid agent-based model (ABM). The agents in the ABM are tumor cells having variable PD-L1 expression, and immune cells that secrete IFNg and can kill tumor cells. We model TIL therapy as an immune cell pulse, given at regular or irregular intervals. RESULTS: Our ABM is calibrated to capture in vitro data dynamics. Under certain combinations of spatial configurations of the tumor and intermittent immune dosing schedules, we observe the presence of ‘sweet spots’ where tumor extinction is possible and immune exhaustion is avoided. This indicates that an appropriate pulsing of TIL therapy may lead to better overall immune efficacy than a bolus injection or continuous immunotherapy. Our novel findings can potentially benefit clinical cancer research by giving multiple insights related to the tumor extinction, equilibrium and escape phenomena.
Agenda
07/30/2026 09:00
Welcome / Business
07/30/2026 09:15
Keynote: B7-H3 CAR T cells: from the 1st intracranial dose to a child with DIPG to iterative laboratory design
Associate Professor
University of Washington
Dr. Nick Vitanza
B7-H3 CAR T cells: from the 1st intracranial dose to a child with DIPG to iterative laboratory design
07/30/2026 10:00
Forcing inflammation to induce mutations that initiate cancer and drive metastasis
Professor and Director
UCSF
Valerie Weaver
07/30/2026 10:15
Bioengineering technologies for cancer organoid models
Stanford
Sarah Heilshorn
07/30/2026 10:30
Dr. Li Ding, Washington University in St. Louis
Washington University in St. Louis
Li Ding
07/30/2026 10:45
Andrew Oberst, University of Washington.
University of Washington
Andrew Oberst
07/30/2026 11:00
Panel Discussion
06/25/2026 09:00
Welcome / Business
06/25/2026 09:15
Session 1: AI Applications in Research
06/25/2026 09:15
How AI can be applied and used to facilitate, improve, or speed up current research
Director of the Center of Excellence for Evolutionary Therapy
Moffitt
Alexander R. A. Anderson
06/25/2026 09:30
DeepScan - AI-guided platform for generation of novel surface display elements
Associate Professor
Yale
Sidi Chen
06/25/2026 09:45
Session 1 Panel Discussion
Associate Professor
Yale
Sidi Chen
Cedars Sinai
Kristin Swanson
Senior Director of Bio Machine Learning
UC San Diego, Ideker Lab
Mukund Varma
Mukund Varma is Senior Director of Bio Machine Learning at UC San Diego's Ideker Lab, where he leads AI research for the ARPA-H ADAPT program, developing interpretable AI systems that predict therapy outcomes and anticipate tumor evolution to deliver the right therapy to the right patient at the right time. He brings over a decade of experience at the forefront of applied machine learning in the life sciences, spanning therapeutics, diagnostics, and fundamental biology. Before UCSD, Mukund served as Principal Scientist and ML Engineering Lead at Caris Life Sciences, an AI-biotech focused on cancer diagnostics, where he built and deployed multimodal AI models featured in the AI Insights section of Caris's reports to guide clinical decisions for cancer patients. At Celsius Therapeutics, he developed algorithms leveraging single-cell RNA sequencing to identify novel cell-type specific targets, serving as computational biology and precision medicine lead for CEL383 (now ABBV-8736), a TREM1-targeting IBD therapy, acquired by AbbVie for $250M. His earlier career included computational roles at the Broad Institute's Xavier Lab and graduate research at MIT and CERN on the CMS experiment. He holds an S.M. in Physics from MIT and a B.Tech from IIT Bombay.
Founding Director
AI and Biomedical Discovery (AIBD) at Neuroscience Institute
Dr. Stephen Yi
Director of the Center of Excellence for Evolutionary Therapy
Moffitt
Alexander R. A. Anderson
06/25/2026 10:15
Session 2: Policy, Security and Ethics in AI Research
06/25/2026 10:15
How do we ensure all research is ethical, as well as compliant with federal and local policies
Stanford
James Zou
06/25/2026 10:30
From Whole Genomes to Approved Drugs: Foundation Models and Bayesian AI in Precision Oncology
Director
Englander Institute
Dr. Olivier Elemento
06/25/2026 10:45
Session 2 Panel Discussion
Stanford
James Zou
Director
Englander Institute
Dr. Olivier Elemento
Chief Privacy and Compliance Officer
Sage Bionetworks
Christine Suver
Patient Advocate
Stanford University
Vivian Lee
06/25/2026 11:15
Streamlining Resource Curation for the Cancer Complexity Knowledge Portal: A Hands-On Workshop
Sage Bionetworks
Orion Banks
Biomedical Data Manager
Sage Bionetworks
Aditya Nath
Data Scientist
Sage Bionetworks
Ziwei Pan
06/17/2026 09:00
Welcome Remarks
06/17/2026 09:15
Keynote Talk: Cancer Systems Immunology unravels complexity of reversing immune suppression in metastatic breast cancer
Assistant Professor
Keck School of Medicine at USC
Dr. Roussos Torres
06/17/2026 10:00
Session 1: Patient-Specific Models for Mechanism/Discovery
06/17/2026 10:00
A Rapidly Fabricated Superhydrophobic Platform for Investigating Tumor–Stroma Mechanobiology in 3D Cancer Models
Graduate Student
Rice University
Alex Carter
A Rapidly Fabricated Superhydrophobic Platform for Investigating Tumor–Stroma Mechanobiology in 3D Cancer Models
Here, we present ATLAS (Advanced Tumor Landscape Analysis System), a rapidly fabricated superhydrophobic microwell platform engineered for scalable generation of suspended three-dimensional tumor models. Fabricated through a streamlined 3D-printing workflow, ATLAS preserves the hierarchical roughness and low-surface-energy properties necessary for stable multicellular aggregation while improving accessibility and manufacturability of superhydrophobic culture systems.
ATLAS enables reproducible formation of both spheroids and circulating tumor cell (CTC) clusters and was used to investigate the role of cancer-associated fibroblasts in prostate cancer metastasis. The first indication for this technology was to investigate the effects of transient fluid shear exposure on collective CTC survival and stromal signaling responses associated with metastatic dissemination. Heterotypic clusters demonstrated enhanced survival under shear conditions compared to single cells, alongside sustained alterations in cytokine signaling following mechanical conditioning.
Collectively, these findings establish ATLAS as a scalable platform for studying tumor mechanobiology, multicellular survival strategies, and tumor–stroma communication in physiologically relevant 3D systems. This work highlights the utility of engineered superhydrophobic platforms for investigating mechanisms underlying metastatic progression and for enabling future development of more predictive ex vivo cancer models.
06/17/2026 10:12
Establishment of an Engineered Tissue Model of Consensus Molecular Subtype 4 (CMS4) Colorectal Cancer Using Patient-derived Xenograft (PDX) Tumor Cells
Graduate Student
Auburn University
Kwaghtaver Desongu
06/17/2026 10:24
Induced Pluripotent Stem Cells: A Rare Opportunity for Modeling Ultra-Rare CIC-Rearranged Sarcomas
PI
University of Minnesota
Darko Bosnakovski
06/17/2026 10:36
Integration of stromal and immune cells into a colorectal cancer organoid-on-chip model for studying tumor microenvironment interactions
Graduate Student
University of Southern California
Bethany Haliday
06/17/2026 10:48
Patient-Plasma–Driven 3D Tumoroid Models Enable Reproducible and Predictive Drug Response Profiling in High-Grade Serous Carcinoma
Associate Scientist / Associate Professor
Sanford Research / University of South Dakota School of Medicine
Pilar de la Puente
06/17/2026 11:00
Session 1 Panel Discussion
Graduate Student
Rice University
Alex Carter
A Rapidly Fabricated Superhydrophobic Platform for Investigating Tumor–Stroma Mechanobiology in 3D Cancer Models
Here, we present ATLAS (Advanced Tumor Landscape Analysis System), a rapidly fabricated superhydrophobic microwell platform engineered for scalable generation of suspended three-dimensional tumor models. Fabricated through a streamlined 3D-printing workflow, ATLAS preserves the hierarchical roughness and low-surface-energy properties necessary for stable multicellular aggregation while improving accessibility and manufacturability of superhydrophobic culture systems.
ATLAS enables reproducible formation of both spheroids and circulating tumor cell (CTC) clusters and was used to investigate the role of cancer-associated fibroblasts in prostate cancer metastasis. The first indication for this technology was to investigate the effects of transient fluid shear exposure on collective CTC survival and stromal signaling responses associated with metastatic dissemination. Heterotypic clusters demonstrated enhanced survival under shear conditions compared to single cells, alongside sustained alterations in cytokine signaling following mechanical conditioning.
Collectively, these findings establish ATLAS as a scalable platform for studying tumor mechanobiology, multicellular survival strategies, and tumor–stroma communication in physiologically relevant 3D systems. This work highlights the utility of engineered superhydrophobic platforms for investigating mechanisms underlying metastatic progression and for enabling future development of more predictive ex vivo cancer models.
Graduate Student
Auburn University
Kwaghtaver Desongu
PI
University of Minnesota
Darko Bosnakovski
Graduate Student
University of Southern California
Bethany Haliday
Associate Scientist / Associate Professor
Sanford Research / University of South Dakota School of Medicine
Pilar de la Puente
Cancer Research Advocate
National Cancer Institute
Carole Baas
06/17/2026 11:30
Break
06/17/2026 11:45
A Patient-Centered Model: Embedding Advocates As Structural Partners in Oncology Conferences for Patient Benefit
Patient Advocate
Stanford / Christina Curtis Lab
Diane Heditsian
06/17/2026 12:00
Session 2: Precision-based Clinical Decisions
06/17/2026 12:00
A Personalized Lorlatinib Dosing Framework to Normalize Inter-Patient Pharmacokinetic Variability
Graduate Student
Moffitt Cancer Center
Julia Pelesko
06/17/2026 12:12
Cell metabolic programs predict immunogenic niches and treatment responses in a mouse model of breast cancer
Graduate Student
MIT
Veronika Pister
06/17/2026 12:24
Ecological Markers of Radioresistance in Breast Cancer: A Spatial Multi-Omics Approach
Graduate Student
Stony Brook University
Naheel Khatri
06/17/2026 12:36
Multi-region biopsies and patient-derived neurosphere cultures reveal spatial divergence in glioblastoma
PI
University of Colorado Anschutz Medical Campus
Michalina Janiszewska
06/17/2026 12:48
Single cell transcriptional dynamics in the HCMI cancer model collection
Postdoc
Columbia University
Luca Zanella
06/17/2026 13:00
Session 2 Panel Discussion
Graduate Student
Moffitt Cancer Center
Julia Pelesko
Graduate Student
MIT
Veronika Pister
Graduate Student
Stony Brook University
Naheel Khatri
PI
University of Colorado Anschutz Medical Campus
Michalina Janiszewska
Postdoc
Columbia University
Luca Zanella
MC2 Centrer
Angie Bowen
05/28/2026 09:00
Welcome + Goals + Business
05/28/2026 09:15
Keynote: Dissecting the tumor-immune microenvironment at single-cell and spatial resolution
Member of the Computational and Systems Biology Program
Memorial Sloan Kettering Cancer Center
Christina Leslie
05/28/2026 10:00
Session 1: Targeted therapies - how does it effect the immune response
05/28/2026 10:00
Ex vivo and In vivo genome engineering to reprogram T cells
UCSF
Dr. Justin Eyquem
05/28/2026 10:15
Targeting Tumor-Intrinsic Transcriptional States to Reprogram the Immunosuppressive Microenvironment in Pancreatic Ductal Adenocarcinoma (PDAC)
Graduate Student
Columbia University
Yining Chen
05/28/2026 10:30
Interplay of strategies of mechanical adaptations of circulating tumor cells with their immune microenvironment in prostate cancer
Investigator
University of Texas Health San Antonio
Pawel Osmulski
05/28/2026 10:45
Elucidation and pharmacologic targeting of Master Regulator proteins representing mechanistic determinants of macrophage state and immunoservasive potential
Postdoc
Columbia University
Gaetano Viscido
Gaetano Viscido is a postdoctoral researcher in cancer systems biology at Columbia University. His research focuses on tumor-associated macrophages, single-cell transcriptomics, and the identification of Master Regulator proteins controlling immunosuppressive cell states in cancer. His work centers on developing and applying experimental models and functional approaches to identify novel therapeutic strategies aimed at improving cancer immunotherapy responses. He is the recipient of the 2024 Precision Oncology and Systems Biology (POSB) Postdoctoral Pilot Award.
05/28/2026 11:00
Hypoxia-Induced ECM Remodeling as a Barrier to Immune Infiltration in Ovarian Tumors: Insights from Engineered Extracellular Matrix Models
Associate Scientist / Associate Professor
Sanford Research / University of South Dakota School of Medicine
Pilar de la Puente
05/28/2026 11:15
Session 1 Panel Discussion
UCSF
Dr. Justin Eyquem
Associate Scientist / Associate Professor
Sanford Research / University of South Dakota School of Medicine
Pilar de la Puente
Investigator
University of Texas Health San Antonio
Pawel Osmulski
Graduate Student
Columbia University
Yining Chen
Postdoc
Columbia University
Gaetano Viscido
Gaetano Viscido is a postdoctoral researcher in cancer systems biology at Columbia University. His research focuses on tumor-associated macrophages, single-cell transcriptomics, and the identification of Master Regulator proteins controlling immunosuppressive cell states in cancer. His work centers on developing and applying experimental models and functional approaches to identify novel therapeutic strategies aimed at improving cancer immunotherapy responses. He is the recipient of the 2024 Precision Oncology and Systems Biology (POSB) Postdoctoral Pilot Award.
05/28/2026 11:45
Break
05/28/2026 12:00
Session 2: Cell Therapies & Adaptive Immunity
05/28/2026 12:00
Identifying Hidden Drivers of CAR-T Persistence
St. Jude Research
Jiyang Yu
05/28/2026 12:15
Energizing the skin immune system with ultrasound microbubbles and surfactant sodium lauryl sulfate for adjuvant free T cell tumor therapy
Postdoc
Massachusetts Institute of Technology
Diviya Sinha
05/28/2026 12:30
Evolutionary immunotherapy in NSCLC: identifying optimal dosing strategies in adoptive cell therapies using agent-based modeling
Moffitt Cancer Center
Sandhya Prabhakaran
05/28/2026 12:45
Systems serology of responses against tumor antigens in ovarian cancer reveal disrupted Fc-mediated immunity
Student
Bioengineering Department, UCLA
Michelle Loui
05/28/2026 13:00
JI Lightning Talks
05/28/2026 13:15
Session 2 Panel Discussion
Student
Bioengineering Department, UCLA
Michelle Loui
Postdoc
Massachusetts Institute of Technology
Diviya Sinha
Graduate Student
Drexel University
Qinghe Zeng
Graduate Student
University of Texas at Austin
Shabnam Nejat
Graduate Student
University of Minnesota - Twin Cities
Hongrong Zhang
Postdoc
Memorial Sloan Kettering Cancer Center
Farah Mustapha
Moffitt Cancer Center
Sandhya Prabhakaran
The Multi-Consortia Coordinating (MC2) Center
Email: mc2center@sagebase.org
