Computational analysis reveals histotype-dependent molecular profile and actionable mutation effects across cancers.

ABSTRACT:

Background

Comprehensive mutational profiling data now available on all major cancers have led to proposals of novel molecular tumor classifications that modify or replace the established organ- and tissue-based tumor typing. The rationale behind such molecular reclassifications is that genetic alterations underlying cancer pathology predict response to therapy and may therefore offer a more precise view on cancer than histology. The use of individual actionable mutations to select cancers for treatment across histotypes is already being tested in the so-called basket trials with variable success rates. Here, we present a computational approach that facilitates the systematic analysis of the histological context dependency of mutational effects by integrating genomic and proteomic

SUBMITTER: Heim D 

PROVIDER: S-EPMC6238410 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature