Abstract 2806: Patient-derived cell-based pharmacogenomic platform to uncover resistance mechanisms and novel therapeutics for advanced lung cancer

To uncover resistance mechanism and effective drugs for advanced lung cancer patients, we stablished a pharmacogenomic platform using patient-derived cells (PDC). Drug response screening and multi-omics datasets were obtained from lung cancer PDCs (n=102). We interrogated sensitive drugs from variant, gene expression, and clinical profiles. Machine learning approaches were applied to extract molecular target signatures and pathways associated with sensitive drugs. Next, acquired resistance pathways and drug candidates were investigated from patients to receive serial EGFR-TKI treatments. Our PDC model resembled with TCGA genomic profile. Three RNA subtypes were identified from gene expression: (1) MYC, (2) epithelial-to-mesenchymal (EMT), and (3) inflammatory activation. Drugs for mutations and subtypes were extracted. Especially, SCLC harboring both TP53 and RB1 mutations was abundant in RNA subtype 1 and showed sensitivity to cell cycle inhibitors. Among EGFR-TKI treatment groups, Osimertinib resistant group was enriched in EMT-like subtype 2 with vanishing EGFR T790M mutation and activating TGF-β pathway. The group showed sensitivity to YAP/TAZ inhibitor. Our PDC pharmacogenetic platform predict plausible drug candidates and markers for refractory lung cancer patients. We expect further studies for precision medicine by novel analysis and cohort expansion. Citation Format: Charny Park, Namhee Yu, Mihwa Hwang, Youngjoo Lee, Bo Ram Song, Eun Hye Kang, Hanna Sim, Beung-Chul Ahn, Kum Hui Hwang, Sehwa Hong, Sunshin Kim, Ji-Youn Han. Patient-derived cell-based pharmacogenomic platform to uncover resistance mechanisms and novel therapeutics for advanced lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2806.