Evaluation and prediction of hepatocellular carcinoma prognosis based on molecular classification.

ABSTRACT:

Purpose

Prediction of hepatocellular carcinoma (HCC) prognosis faced great difficulty due to tumor heterogeneity. We aimed to identify the prognosis-associated molecular subtypes existing in HCC patients and construct an evaluation model based on identified molecular classification.

Materials and methods

Non-negative matrix factorization consensus clustering was performed using 371 HCC patients from The Cancer Genome Atlas (TCGA) to identify molecular subtypes, based on the expression profile of the survival-associated genes. Signature genes for different subtypes were identified by Significance Analysis of Microarray and Prediction Analysis for Microarrays. Model for subtype discrimination and prognosis evaluation was established using binary logistic regression. The model

SUBMITTER: Ke K 

PROVIDER: S-EPMC6225913 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature