Driver gene mutations based clustering of tumors: methods and applications.

ABSTRACT:

Motivation

Somatic mutations in proto-oncogenes and tumor suppressor genes constitute a major category of causal genetic abnormalities in tumor cells. The mutation spectra of thousands of tumors have been generated by The Cancer Genome Atlas (TCGA) and other whole genome (exome) sequencing projects. A promising approach to utilizing these resources for precision medicine is to identify genetic similarity-based sub-types within a cancer type and relate the pinpointed sub-types to the clinical outcomes and pathologic characteristics of patients.

Results

We propose two novel methods, ccpwModel and xGeneModel, for mutation-based clustering of tumors. In the former, binary variables indicating the status of cancer driver genes in tumors and the genes' involvement in the core canc

SUBMITTER: Zhang W 

PROVIDER: S-EPMC6022677 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature