The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine.

ABSTRACT:

Background

The diversity of clinical tumor profiling approaches (small panels to whole exomes with matched or unmatched germline analysis) may engender uncertainty about their benefits and liabilities, particularly in light of reported germline false positives in tumor-only profiling and use of global mutational and/or neoantigen data. The goal of this study was to determine the impact of genomic analysis strategies on error rates and data interpretation across contexts and ancestries.

Methods

We modeled common tumor profiling modalities-large (n = 300 genes), medium (n = 48 genes), and small (n = 15 genes) panels-using clinical whole exomes (WES) from 157 patients with lung or colon adenocarcinoma. We created a tumor-only analysis algorithm to assess germline false positive

SUBMITTER: Garofalo A 

PROVIDER: S-EPMC4962446 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature