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.
Events
Calendar

- This event has passed.
Propels: Mentorship Matters: Unlocking Potential
November 3, 2023 @ 12:00 pm - 1:00 pm PDT
Explore the power of mentorship in this dynamic workshop and panel discussion. Join mentors and mentees from SBME’s Career Accelerator program, a collaborative initiative with STEMCELL Technologies and Advice to a Scientist, as they share their experiences and insights.
Discover how mentorship can shape your career, empower you to explore diverse pathways, and develop essential skills.
Registration is required.
Panelists:
• Peter Morin, Technical Scientist, STEMCELL Technologies
• Wendy Tan, Manager, Scientific Support, STEMCELL Technologies
• Coral-Ann Lewis, Associate Director, Product Management, Hematology, STEMCELL Technologies
• Elizabeth Castle, PhD student, SBME