Identification of cervical squamous cell carcinoma feature genes and construction of a prognostic model based on immune-related features.

ABSTRACT: As heterogeneity of cervical squamous cell carcinoma (CSCC), prognosis assessment for CSCC patients remain challenging. To develop novel prognostic strategies for CSCC patients, associated biomarkers are urgently needed. This study aimed to cluster CSCC samples from a molecular perspective. CSCC expression data sets were obtained from The Cancer Genome Atlas and based on the accessed expression profile, a co-expression network was constructed with weighted gene co-expression network analysis to form different gene modules. Tumor microenvironment was evaluated using ESTIMATE algorithm, observing that the brown module was highly associated with tumor immunity. CSCC samples were clustered into three subtypes by consensus clustering based on gene expression profiles in the module. Gene set var

SUBMITTER: He C 

PROVIDER: S-EPMC9441064 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature