Inferring Intra-Tumor Heterogeneity by Jointly Modeling Copy Number Aberrations and Somatic Point Mutations

• Activity Number: 418 - Contributed Poster Presentations: Section on Statistics in Genomics and Genetics
• Type: Contributed
• Date/Time: Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Chong Jin* and Wei Sun and Mengjie Chen
• Companies: and Fred Hutchinson Cancer Research Center and Department of Medicine, University of Chicago
• Keywords: cancer ; intra-tumor heterogeneity ; exome-seq

Abstract

A tumor sample of a single patient often includes a conglomerate of heterogeneous cells. Understanding intra-tumor heterogeneity may help us identify useful biomarkers to guide the practice of precision medicine. We have developed a new statistical method, SHARE (Statistical method for Heterogeneity using Allele-specific REads and somatic point mutations), that reconstructs clonal evolution history using whole exome sequencing data of matched tumor and normal samples. Our method jointly models copy number aberrations and somatic point mutations using both total and allele-specific read counts. Cellular prevalence, allele-specific copy number and multiplicity of point mutations within each subclone can be estimated by maximizing the model likelihood. We apply our method to infer the subclonal composition in tumor samples from TCGA colon cancer patients.