A comprehensive genomic pan-cancer classification using The Cancer Genome Atlas gene expression data.

ABSTRACT:

Background

The Cancer Genome Atlas (TCGA) has generated comprehensive molecular profiles. We aim to identify a set of genes whose expression patterns can distinguish diverse tumor types. Those features may serve as biomarkers for tumor diagnosis and drug development.

Methods

Using RNA-seq expression data, we undertook a pan-cancer classification of 9,096 TCGA tumor samples representing 31 tumor types. We randomly assigned 75% of samples into training and 25% into testing, proportionally allocating samples from each tumor type.

Results

We could correctly classify more than 90% of the test set samples. Accuracies were high for all but three of the 31 tumor types, in particular, for READ (rectum adenocarcinoma) which was largely indistinguishable from COAD (colon adenoca

SUBMITTER: Li Y 

PROVIDER: S-EPMC5496318 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature