Project 3

点击翻译按钮获取中文摘要

PROJECT SUMMARY Genotype directed therapy is the standard of care for the significant proportion of advanced non- small cell lung cancer patients whose tumors harbor a targetable genetic mutation within EGFR, ALK, ROS1, BRAF, RET, MET, NTRK or HER2. Although this therapeutic approach is effective, acquired drug resistance inevitably occurs. The current management strategy for acquired resistance is to evaluate the mechanism of resistance with a biopsy to help guide subsequent treatment. However, mechanisms of resistance can be heterogenous and not all patients’ tumors harbor an actionable resistance mechanism. Moreover, even when a targetable mechanism of resistance is identified and a subsequent therapy available, acquired resistance will develop again. An alternative strategy is to intervene therapeutically prior to the clinical development of acquired drug resistance by specifically targeting the residual drug tolerant persister (DTP) cells, a small population of cells that remain after effective genotype directed therapies and ultimately give rise to acquired resistance. There have been no clinical strategies developed against DTPs, in part due to the lack of the biological and mechanistic understanding of this state. In this project we will lay the foundation for clinical therapeutic strategies aimed at DTP cells by uncovering factors that lead to formation of the DTP state and identifying targets that can kill DTP cells. We will build on prior research from our group centered around the DTP state in EGFR- mutant lung cancer showing: 1) YAP/TEAD activation results in transcriptional repression of the pro-apoptotic protein BMF and thus limits EGFR inhibitor mediated apoptosis; 2) the DTP state displays some features of cellular senescence and anti-apoptosis agents may be an effective strategy; and 3) cancer-associated fibroblasts in the tumor microenvironment can facilitate DTP emergence and modulate the senescence phenotype of established DTPs. Building upon this foundation, the experiments detailed in this project utilize a combination of innovative techniques and a unique and large collection of patient-derived cancer and fibroblast models from genomically-driven cancers to understand the vulnerabilities of the DTP state and design optimal clinical approaches to combat these harbingers of drug resistance in patients.