An integrated functional proteomics platform for accelerated discovery of isoform-specific determinants of cancer

PROJECT SUMMARY Aberrant splicing is a major mechanism leading to the progression of cancer, and newly emerging experimental and computational approaches reveal a critically important, high-resolution view of the heterogeneity of cancer to most directly pinpoint biomarkers, drug targets, and neoantigens for immunotherapies. Current gene-targeted cancer therapies are primarily hampered by the extreme genetic heterogeneity observed across patient populations. “One gene, one function, one disease” model cannot reconcile with the complexity that different mutations of the same gene often lead to different phenotypes. A recent pan-cancer characterization of aberrant splicing we conducted revealed thousands of potential driver mutations that alter the activity of splice regulatory regions and their target protein isoforms. In the recent past, genome and exome sequencing projects have identified thousands of genetic mutations in cancer patients, including somatic and germline mutations. To date, most literature has focused on studying mutations that affect the encoded protein amino acid sequence. Recent evidence has emerged to indicate possible functions of “silent” mutations, which act to deregulate alternative splicing, leading to production of aberrant levels or identities of distinct protein isoforms. Here we propose a set of innovative, broadly applicable technologies to systematically link silent cancer mutations to splicing events and the functional impacts of their consequent protein isoforms. Specifically we will pursue the following two aims: (1) SysMap-Splice: An integrated systems approach coupled with long-read sequencing to discover and characterize full-length protein isoform drivers in cancer; and (2) Can-IsoPPI: An enhanced platform to investigate full-length splice isoform-mediated PPI rewiring in cancer, based on affinity purification-mass spectrometry. Together, our integrative approach is both innovative and significant, because it will provide insights in prioritizing cancer-causing genotypes that have a direct impact on protein isoform expression of a patient, a critical step towards isoform- resolved personalized precision medicine, drug targets, and neoantigen discovery. 1