SubcloneSeeker: a computational framework for reconstructing tumor clone structure for cancer variant interpretation and prioritization.

Yi Qiao,Aaron R Quinlan,Gabor T Marth,David A Wheeler,Amir A Jazaeri,Roeland Gw Verhaak

doi:10.1186/s13059-014-0443-x

Abstract

Many tumors are composed of genetically divergent cell subpopulations. We report SubcloneSeeker, a package capable of exhaustive identification of subclone structures and evolutionary histories with bulk somatic variant allele frequency measurements from tumor biopsies. We present a statistical framework to elucidate whether specific sets of mutations are present within the same subclones, and the order in which they occur. We demonstrate how subclone reconstruction provides crucial information about tumorigenesis and relapse mechanisms; guides functional study by variant prioritization, and has the potential as a rational basis for informed therapeutic strategies for the patient. SubcloneSeeker is available at: https://github.com/yiq/SubcloneSeeker.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0443-x) contains supplementary material, which is available to authorized users.

Highlights

Identifying the few genetic changes that drive chemoresistance or metastasis from hundreds or thousands of somatic variants found in whole-exome or wholegenome sequencing [1,2] of matched tumor-normal patient tissue samples is a daunting task
Our computational procedure for subclone structure analysis Here we briefly describe the main characteristics of the algorithm to investigate the relationships among somatic events from unlinked, bulk allele frequency measurements at somatic mutation sites (Figure 1, section ‘Method’)
A unified framework for subclone structure reconstruction that incorporates all types of genomic variants We define a subclone as a collection of cells in the tumor sample that harbor the same set of genomic variants, including Single nucleotide variant (SNV), structural variations (SV), copy number variations (CNV), loss of heterozygosity (LOH), and so on

Summary

Introduction

Identifying the few genetic changes that drive chemoresistance or metastasis from hundreds or thousands of somatic variants found in whole-exome or wholegenome sequencing [1,2] of matched tumor-normal patient tissue samples is a daunting task. Current variant prioritization approaches examine predicted variant impact in candidate genes, or deploy pathway analysis to narrow down the long list of candidate mutations to a manageable number [3]. We report an alternative approach to variant prioritization, exploiting the patterns of genetic heterogeneity often observed in diverse types of cancers. The presence of such genetically divergent subpopulations of cells within a single tumor mass has been reported in various tumor types [4-23]. With multiple groups of somatic mutations present at different

Methods

Results

Conclusion