Invited Session 2: Translational Research in Cancer Immunology

Chair: Li Zhang, Professor of Biostatistics, UCSF

Dr. Li Zhang is a Professor in the Department of Medicine and the Department of Epidemiology and Biostatistics at the University of California San Francisco (UCSF). After she obtained her Ph.D. in Statistics from the University of Florida, she joined the Cleveland Clinic as an Assistant Professor. She has extensive experience in applying statistics in biomedical research. She has published over 100 papers and designed over 50 Phase I and II clinical trials. Dr. Zhang also serves on Global Action Plan 6 Project for Movember Foundation as the UCSF site PI. She has been or is a co-Investigator on multiple NIH, DOD, and foundation grants. Her research interest focuses on Immuno-informatics, and she is currently the PI on NIH R21 and R01 projects focusing on cancer immunotherapy. Dr. Zhang was the president of the San Francisco Bay Area Chapter of the American Statistical Association (SFASA) and now serves as the Director of Education in SFASA. She has been the reviewer for ASCO YIA and NIH study sections.

High dimensional analysis of the circulating immune response in biliary tract cancer reveals suppressive monocytes associated with anti-PD-1 resistance

Speaker: Bridget Keenan, MD, PhD, Assistant Professor, Division of Hematology/Oncology, UCSF

I am a physician scientist and an Assistant Professor at UCSF in Hematology/Oncology. I earned my medical degree and a doctorate in immunology at the Johns Hopkins University School of Medicine, and completed my internal medicine residency and oncology fellowship at UCSF. My clinical practice is in the Cancer Immunotherapy Clinic, where I work with patients with solid organ cancers who are being treated on early phase immunotherapy trials. My research interests are in studying the mechanisms of response and resistance to immunotherapy, with a focus on gastrointestinal cancers.

Abstract

Resistance to checkpoint inhibitors is a crucial unmet need in oncology, including in biliary tract cancer. Multiplexed simultaneous single cell RNA sequencing and cell surface proteomics (CITEseq) yields high resolution profiling of the immune system. Here, we leveraged CITEseq to investigate mechanisms of resistance to immunotherapy in serially collected samples from a cohort of advanced biliary tract patients undergoing checkpoint inhibitor therapy with pembrolizumab (anti-PD-1). We identified a population of circulating monocytes associated with resistance to anti-PD-1, characterized by suppressive chemokine and cytokine expression. Following validation of cell surface proteins, we isolated the specific monocyte population and demonstrated that they suppress T cell proliferation and induce an “immune-paralyzed” phenotype in T cells in vitro. We applied the gene signature of the suppressive monocytes to additional patient cohorts across a variety of tumor types, confirming the association with poor prognosis and worse outcome with immunotherapy. A deeper understanding of immune cell biology and association with clinical outcomes may provide insights for developing novel therapeutics that can overcome immunotherapy resistance in biliary cancer as well as other tumor types.

The Utility of Clinical Biomarkers in Advancing Oncology Therapeutic Molecules from Phase 1 Studies to Regulatory Approval

Speaker: Nathan Standifer, PhD, Executive Director, Translational Science, Tempest Therapuetics

Nathan E. Standifer received his Ph.D. in Microbiology and Immunology from the University of Texas Health Science Center. His dissertation focused on identifying mechanisms of T cell tolerance escape in a rodent model of myasthenia gravis. He performed his post-doctoral work in the laboratory of Dr. Gerald T. Nepom M.D., Ph.D., at the Benaroya Research Institute at Virginia Mason in Seattle, WA at which he characterized early immunologic markers of Type 1 Diabetes onset and elucidated mechanisms of autoimmunity. He then joined the Clinical Immunology Dept at Amgen, Inc. where he developed cell-based biomarker assays to support development of therapies for immune-mediated diseases including psoriasis and lupus. He joined the Clinical Pharmacology Bioanalysis group at MedImmune/AstraZeneca developing biomarker assays to support development of immune-oncology therapeutic compounds and built New Modalities Bioanalysis and Biomarkers group, which supported cellular, RNA-based and viral therapeutic modalities. He is the Executive Director of Translational Science at Tempest Therapeutics. He is the author of thirty manuscripts and has co-authored pharmacodynamic sections of FDA Biologics Licensing Applications for three marketed, oncology therapies including durvalumab (anti-PD-L1), moxetumomab pasudotox (anti-IL-22 immuno-toxin) and tremelimumab (anti-CTLA-4).

Abstract

The identification of biomarkers that predict clinically responsive patients is a key goal in the development of oncology therapeutic molecules, and companion diagnostic assays derived from such biomarkers can hasten marketing approval. In addition, clinical biomarkers can be used to confirm target engagement, elucidate mechanistic activities, and aid in dose-optimization. In this presentation, methodologies used to identify clinical biomarkers of a novel, small molecule inhibitor of Peroxisome Proliferator Activated Receptor-Alpha (TPST-1120, Tempest Therapeutics) and therapeutic antibodies targeting Programmed Death Ligand-1 (PD-L1, durvalumab, AstraZeneca) or Cytotoxic T Lymphocyte-Associated Protein-4 (CTLA-4, tremelimumab, AstraZeneca) will be discussed. The role of anti-PD-L1 and anti-CTLA-4 clinical biomarkers in dose-optimization and characterization of combined therapeutic activities will be highlighted. Finally, the role of biomarker data in supporting regulatory submissions will be presented.

TCR-L: An Analysis Tool for Evaluating the Association between the T-Cell Receptor Repertoire and Clinical Phenotypes

Speaker: Chad (Qianchuan) He, PhD, Associate Professor, Fred Hutch

Dr. He is Associate Professor in the Biostatistics Program at Fred Hutchinson Cancer Center. His research is focused on the development of new methods and computational tools for the analysis of genomic data related to cancer and other complex diseases. Dr. He has published methods on somatic mutation analysis, genetic pathway analysis, and T cell receptor analysis, among others. Dr. He's biostatistical analysis has been used for studies of breast and liver cancers, tumor microenvironment in sarcoma, as well as risk factors in colon cancer.

Abstract

T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the TCR repertoire at the population level. We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and clinical phenotypes. The TCR-L can accommodate features that can be extracted from the TCR sequences as well as features that are hidden in the TCR sequences. Simulation studies show that the proposed approach has well controlled type I errors and good power to identify associations between TCR repertoire and disease outcomes. An application of the proposed approach to a cancer study will be shown as well.