SBME Research Seminar - Dr. Hannah Carter
Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. We used machine learning to predict ICB response from germline and somatic biomarkers and studied feature usage by the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I Major Histocompatibility Complex (MHC-I). Further investigation uncovered different ICB responses in MHC-I versus MHC-II neoantigen reliant tumors across patients. Despite similar response rates, MHC-II reliant responses were associated with significantly longer durable clinical benefit (Discovery: Median OS=63.6 vs. 34.5 months P=0.0074; Validation: Median OS=37.5 vs. 33.1 months, P=0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC-II but not MHC-I reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses.
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Special Seminar: Bioinspired protein-based cancer immunotherapy
February 28, 2024 @ 1:00 pm - 2:00 pm PST
Special Seminar: Bioinspired protein-based cancer immunotherapy
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Seminar Abstract:
Immunotherapy has revolutionized the field of cancer treatment over the past two decades, though only a small fraction of patients treated will achieve complete remission. As such, new paradigms to overcome resistance to immunotherapies are urgently needed. My research seeks to tailor immunotherapies towards individual differences in immune systems and the inherent heterogeneity of cancer. For this talk, I will share my work on a key therapeutic target against cancer called the STimulator of INterferon Genes (STING) signaling. I first addressed an innate immunodeficiency caused by a loss-of-function mutation of STING protein affecting 20% of the human population, using the cytosolic domain of STING (STINGΔTM) as a functional agonist carrier to activate signaling in STING-deficient cells. Subsequently, I developed a therapeutic cancer vaccine based on this platform by fusing STINGΔTM with immune checkpoint blockade (ICB) nanobodies. The treatment eliminated subcutaneous colon and melanoma tumors in 70-100% of mice and protected all cured mice against rechallenge, while mechanistic studies revealed a distinct STING-mediated anti-tumor immunity driven by robust TH1 polarization and Treg suppression in CD4+ T cells, followed by the collaboration of CD8+ T and NK cells to eliminate tumors. For my independent group, I will continue these prospects in designing protein therapeutics and leveraging the full potential of CD4+ T cells, initially towards personalized cancer immunotherapies and expanding to other monogenic immunodeficiencies and drug delivery challenges in the long run.
Dr. Yanpu He’s Bio:
Yanpu He (he/him/his) is a postdoctoral associate advised by Prof. Angela Belcher in the Department of Biological Engineering at the Massachusetts Institute of Technology (MIT). He completed his Ph.D. in Chemical Engineering at MIT in 2021, co-advised by Profs. Paula Hammond and Darrell Irvine. Prior to that, he graduated from University of Minnesota, Twin Cities in 2015 with dual degrees of B.S. in Chemical Engineering and B.A. in Mathematics. He received MIT Marble Center Cancer Nanomedicine postdoctoral fellowship from 2021-2023 and was named Convergence Scholar at MIT Koch Institute in 2021.
Location:
MSL 102 LT