Unknown

Dataset Information

Identification of Oxidative Stress-Associated Molecular Subtypes and Signature for Predicting Survival Outcome of Cervical Squamous Cell Carcinoma.


ABSTRACT:

Background

Cervical squamous cell carcinoma (CESC) is the gynecologic malignancy with high incidence rate and high mortality rate. Oxidative stress participates in gene regulation and malignant tumor progression, including CESC.

Methods

RNA-seq, clinical information, and genomic mutation were from The Cancer Genome Atlas- (TCGA-) CESC and GSE44001 datasets. Oxidative stress-related genes were obtained from the gene set enrichment analysis (GSEA) website. ConsensusClusterPlus was used for clustering, which was assessed by the Kaplan-Meier (KM) survival curve analysis, mutation analysis, immunocharacteristic analysis, and therapy. Prognostic signatures were built by combining weighted correlation network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO)

SUBMITTER: Wang L 

PROVIDER: S-EPMC9550421 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature