Development of Tran-Omics Integrated Analysis Platform for Cancer Research

Large-scale cancer genome sequencing studies have been launched by The Cancer Genome Atlas (TCGA) project to characterize the genomic alterations from several types of cancer. In order to systematically identify aberrant proteins derived from alterations in cancer genomes, which may drive tumor initiation, progression and response to treatment, the Cancer Proteomic Tumor Analysis Consortium (CPTAC) has launched the first integrated proteogenomic analysis on colon rectal cancer by connecting mutations from genomic and transcriptomic data sets to aberrant peptides to better understanding cancer biology, which not only reports over 1,000 variant peptides from The Cancer Genome Atlas (TCGA) cancer samples but also presents the complexity of cross-omics data integration to the research community. However, most of the existing pipelines and commercial packages are limited to single ‘omics’ or ‘sample’ analysis, lacking the ability to perform trans-omics data or cross-sample analysis. As cancer research and treatment has been moving towards the idea of personal medicine and personalized omics, there is an increasing need for an integrated analysis platform for translating multi-omics data into biological insights. The present 3 years proposal aimed to establish a trans-omics analysis platform to interrogate cancer mutations from the perspective of central dogma. The aims of this proposal are: 1. To construct automatic bioinformatics pipelines to handle high-throughput sequencing datasets generated from Exome sequencing and RNA-Seq with functionalities: quality control, variant detection, and annotation. 2. To translate mutants from genomics and transcriptomics to mutant proteins/peptides database to improve mutant peptide identification in shotgun proteomics. 3. To establish a high-throughput approach to effectively predict immunogenic mutant peptides by combining whole-exome and transcriptome sequencing analysis with mass spectrometry, neo-epitope prediction and structure simulation. The ultimate goal of this proposal is to develop an integrative analysis platform to link tumor-derived DNA, RNA, and protein measurements into a central-dogma perspective to improve our understanding of cancer biology, identify new diagnostic markers and pave the way to cancer immunotherapy.

Project ID:PA10601-0256
External Project ID:MOST104-2321-B182-007-MY3