Abstract 3222: Biomarker discovery through bioinformatic analysis of genomic profiles of PDX models with different responses to cancer therapies

Patient derived xenograft (PDX) tumor models have been proved to recapitulate the complexity and heterogeneity of their corresponding human tumors by phenotypic and genomic characterization, and thus become to be widely used in recent years in preclinical setting to facilitate drug discovery, translational studies and clinical trials support. Results from increasing number of preclinical studies, especially mouse trials, with PDX models in the past several years, have also demonstrated close correlation between drug response profiles with PDX models and clinical outcomes. GenenDesign has established over 800 PDX tumor models and derived around 100 resistance models to drugs of interest. Genomic profiling data of PDX models are acquired at hot-spot mutation, gene expression, gene copy number and RNA/Exome sequence levels. Through our in-house efforts, PDX models of different tumor types were tested with related SOCs and clinical candidates in biomarker-driven multi-drug multi-arm clinical trial settings. So far, more than 1200 data sets have been generated, including responses to targeted inhibitors against HER2, EGFR, FGFRs, c-Met/ALK, cell cycle regulators, Ras/Raf pathway, PI3K/Akt pathway, epigenetic targets, as well as chemotherapy drugs. In this study, we use bioinformatic tools to compare the genomic profiles of NSCLC PDX models based on their response profiles to multiple chemotherapy drugs. Biomarker signatures associated with SOC treatment sensitivity or resistance are revealed from bioinformatic analysis and being tested with both new NSCLC PDX models and clinical cohorts. The combination of genomic profiles and drug response information to multiple chemo/targeted therapies of over 800 PDX models at GenenDesign would help biomarker discovery for companion diagnosis to meet the increasing needs for precision medicine. Citation Format: Jingjing Jiang, Tengfei Yu, Ying Yan, Wei Du, Tingting Tan, Xuqin Yang, Jiali Gu, Liang Hua, Katherine Xin Ye, Zhenyu Gu. Biomarker discovery through bioinformatic analysis of genomic profiles of PDX models with different responses to cancer therapies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3222. doi:10.1158/1538-7445.AM2015-3222