Computational and functional discovery of isoforms driving cancer and drug resistance

ABSTRACT A major challenge for the cancer genomics community is determining which somatic mutations are contributing to tumorigenesis, which are “passenger” (neutral) mutations, and which mutations will inform personalized treatment decisions. Unfortunately, most functional studies of cancer mutations have largely ignored the impact of altered RNA processing even though this alteration is widespread in cancer, and is a mechanism of both oncogenesis and therapeutic resistance. We hypothesize that we are missing critical information about cancer gene alterations when not considering isoform-specific functions and this is likely to affect cancer treatment. Given the breadth in the lack of understanding of isoform-specific cancer gene function, high-throughput approaches are vitally needed to identify cancer gene isoform variants and functionally characterize their effect on cancer development and treatment. Aim 1 of this study will generate a compendium of human pan-cancer gene isoform variants by performing long-read transcriptome sequencing on a panel of cancer cell lines and primary lung tumors to build a comprehensive set of allele-specific, full-length transcript isoforms. Aim 2 will identify gene isoform variants associated with resistance or variable response to targeted therapies in patient-derived specimens and xenograft models. Aim 3 will perform high-throughput in vitro and in vivo functional characterization of these isoforms driving oncogenesis and drug resistance with and without somatic mutation to identify isoform-specific variant function. All of these aims will focus on genes in the RAS-RTK pathway since this is the most frequently mutated oncogenic pathway and contains many targetable genes. Completion of this study will revolutionize our understanding of isoform-specific functions of cancer genes and their contribution to oncogenesis and cancer treatment. Our approach will provide the cancer research community with a much-needed framework and methodology for other cancer studies and will provide critical insight into mechanisms of tumor response and resistance to cancer therapies.