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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

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.

Authors who are presenting talks have a * after their name.

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