Abstract 6238: Integrated multi-omic/modal profiling enables improved characterization of oncogenic processes, with impact to clinical actionability in the GenMineTOP tested population

Abstract Introduction: It is becoming increasingly apparent that tumor gene expression and spatial H 1e-7) but also strongly suggests that nonlinear differential expression drives the improvement in MSI prediction. Our multi-modality results demonstrate that mining the spatial context of endogenous tumor immune response has nontrivial prognostic utility (p. 05). Citation Format: Bojan Losic, Kenji Tatsuno, Vasanth R. Singan, Hiroki Ueda, Aya Shinozaki Ushiku, Vasanthan Jayakumar, Emi Hattori, Toshimitsu Ichijo, Takuma Sasa, Masakazu Akahori, Shinya Hayashi, Esther Hsiao, Stephanie Feupe, Dan Vo, Tiantian Geier, Shuichi Tsutsumi, Tetsuo Ushiku, Kousuke Watanabe, Katsutoshi Oda, Hidenori Kage, Joy Radecki-Crandall, Donavan T. Cheng, Hiroyuki Aburatani. Integrated multi-omic/modal profiling enables improved characterization of oncogenic processes, with impact to clinical actionability in the GenMineTOP tested population abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 6238.