A novel signature derived from metabolism-related genes GPT and SMS to predict prognosis of laryngeal squamous cell carcinoma.

ABSTRACT:

Background

A growing body of evidence has suggested the involvement of metabolism in the occurrence and development of tumors. But the link between metabolism and laryngeal squamous cell carcinoma (LSCC) has rarely been reported. This study seeks to understand and explain the role of metabolic biomarkers in predicting the prognosis of LSCC.

Methods

We identified the differentially expressed metabolism-related genes (MRGs) through RNA-seq data of The Cancer Genome Atlas (TCGA) and Gene set enrichment analysis (GSEA). After the screening of protein-protein interaction (PPI), hub MRGs were analyzed by least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic signature. Kaplan-Meier survival analysis and the receiver operating

SUBMITTER: Shen Y 

PROVIDER: S-EPMC9270735 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature