Identification and Characterization of Mutation-Induced Alternative Splicing Events in Cancer Using Multi-Omics Data

About This Grant

Identification and Characterization of Mutation-Induced Alternative Splicing Events in Cancer Using Multi-Omics Data Project Summary The goal of this project is to discover mutation-induced alternative splicing events (MAS), understand their functional relevance, and identify neoantigens arising from these events to advance cancer immunotherapy. Large-scale sequencing efforts such as The Cancer Genome Atlas (TCGA) have primarily focused on identifying driver mutations in tumors, including single amino acid changes, insertions, deletions, and alterations that truncate or elongate wild-type protein sequences. However, traditional DNA mutation annotations often rely on canonical transcripts and may overlook alternative splicing events, and some mutations, such as synonymous changes, are considered silent despite their potential impact on splicing. Previously, we developed the MiSplice pipeline to detect mutation-induced splice sites and, when applied to TCGA data, identified thousands of somatic mutations that create cryptic splice sites. In this proposal, we aim to systematically investigate mutation-induced alternative splicing and its functional relevance in cancer, while also identifying the resulting neoantigens by leveraging data from the Clinical Proteomic Tumor Analysis Consortium 3 (CPTAC-3), which includes comprehensive exome sequencing, RNA-Seq, and mass spectrometry data for 774 tumors across seven cancer types, as well as 126 prospective breast cancer samples from CPTAC-2. We hypothesize that mutation-induced alternative splicing plays a significant role in cancer etiology and that the associated neoantigens can serve as novel immunogenic peptide candidates for cancer immunotherapy. We propose to test these hypotheses through two specific aims. Aim 1: Identify mutation-induced alternative splicing events and assess their functional relevance in cancer using multi-omics data (Years 1 & 2). We will use MiSplice to detect mutation-induced alternative splicing events from CPTAC data and evaluate their impact by analyzing changes in protein and phosphorylation expression, as well as pathway activation. Aim 2: Identify neoantigens arising from mutation-induced alternative splicing events with mass spectrometry support (Years 1 & 2). We will construct a tailored protein database that integrates both reference proteins and mutant proteins generated from MAS events. Using state-in-art tools such as PepQuery, we will search for corresponding peptides in the mass spectrometry data, enabling identification of mutant proteins. Neoantigen peptides derived from these expressed mutant proteins will then be prioritized as candidates for cancer immunotherapy.