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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SBME Seminar: Challenges toward ultrahigh-speed proteomics with high-sensitivity, high-depth and high-robustness – Dr. Yasushi Ishihama
July 8, 2024 @ 2:30 pm - 3:30 pm PDT
SBME Seminar: Challenges toward ultrahigh-speed proteomics with high-sensitivity, high-depth and high-robustness – Dr. Yasushi Ishihama
Seminar Abstract:
Understanding proteins and protein complexes as molecules responsible for biological functions is an essential step in understanding biological homeostasis and the diseases that result from its disruption. Although proteome sequencers based on LC/MS/MS as a core technology have been rapidly developed, they have not yet fully met the expectations of the research community. We have focused on accelerating the LC/MS/MS sequencing technology and have investigated various methods to complete proteome sequencing in about 1 minute. By optimizing various parameters under capillary LC flow rates, we have succeeded in achieving the protein identification number of >3000 from 100 ng of HeLa lysates in 1000 samples per day. In this talk, I will introduce our practical and robust high-speed proteome sequencer and report on applications that take advantage of its ultra-high speed.
Location:
LSC 1003 LT3