Comprehensive analysis of potential biomarkers for the diagnosis and prognosis of Cervical squamous cell carcinoma - based on GEO and TCGA databases.

ABSTRACT:

Background

Cervical squamous cell carcinoma (CESC) constitutes a substantial global health burden, especially in resource-limited regions. The identification of reliable biomarkers is critical for developing a clinically applicable nomogram to predict survival outcomes and evaluate immune infiltration in CESC patients.

Methods

This study integrated RNA-seq data from GEO and TCGA databases to identify key genes associated with CESC through differential expression analysis and machine learning techniques. Prognostic models were constructed and validated, with additional analyses exploring immune cell infiltration and gene function via GSEA and clinical correlation. Finally, key genes were validated via qRT-PCR in CESC tissues.

Results

A total of 112 differentially expre

SUBMITTER: Chen Y 

PROVIDER: S-EPMC12094959 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature