A novel machine learning derived RNA-binding protein gene-based score system predicts prognosis of hepatocellular carcinoma patients.

ABSTRACT:

Background

Although the expression of RNA-binding protein (RBP) genes in hepatocellular carcinoma (HCC) varies and is associated with tumor progression, there has been no overview study with multiple cohorts and large samples. The HCC-associated RBP genes need to be more accurately identified, and their clinical application value needs to be further explored.

Methods

First, we used the robust rank aggregation (RRA) algorithm to extract HCC-associated RBP genes from nine HCC microarray datasets and verified them in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and International Cancer Genome Consortium (ICGC) Japanese liver cancer (ICGC-LIRI-JP) cohort. In addition, the copy number variation (CNV), single-nucleotide variant (SNV), and promoter-regi

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC8697767 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature