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Activity Number: 123 - Unraveling Tissue Heterogeneity for Analyzing Omics Data in Cancer Research
Type: Topic Contributed
Date/Time: Monday, August 3, 2020 : 1:00 PM to 2:50 PM
Sponsor: WNAR
Abstract #312444
Title: Multi-Omic Integration to Reveal Functional Consequences of DNA Alterations
Author(s): Xiaoyu Song* and Jiayi Ji and Lin Chen and Pei Wang
Companies: Icahn School of Medicine at Mount Sinai and Ichan School of Medicine at Mount Sinai and University of Chicago and Icahn Medical School at Mount Sinai
Keywords: proteogenomics; multi-omic integration
Abstract:

In order to characterize functional consequences of DNA alterations in tumors, we proposed an integrative analysis tool iProFun to screen for DNA alterations perturbing proteogenomic functional traits. We consider multi-omic molecular quantitative traits simultaneously (e.g. mRNA, protein, and phosphoprotein abundances), and aim to identify genes whose DNA alterations have cis-associations with either some or all omic traits. In comparison with analyzing each molecular trait separately, the joint modeling of multi-omics data enjoys enhanced power and it also achieves better accuracy in inferring cis-associations unique to certain type(s) of molecular trait(s). We applied iProFun to clear cell renal carcinoma, and identified we identified DNA alterations preserving through transcriptional, translational, and post-translational levels (cis-effect cascades), and prioritized gene targets for tumor initiation and progression.


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