Metabolic reprogramming-associated genes predict overall survival for rectal cancer

Area of Science:

• Oncology
• Metabolic Biology
• Bioinformatics

Background:

• Metabolic reprogramming is crucial in tumor biology, with numerous altered genes linked to cancer development.
• The prognostic significance of these metabolic genes in cancer progression remains largely unexplored.

Purpose of the Study:

• To investigate the prognostic role of metabolic genes in rectal cancer.
• To identify survival-related metabolic genes for predicting patient outcomes.
• To explore potential underlying mechanisms through pathway analysis.

Main Methods:

• Utilized messenger RNA expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.
• Employed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression models to screen prognostic metabolic genes.
• Performed gene set enrichment analyses (GSEA) to identify enriched Gene Ontology (GO) terms and pathways.

Main Results:

• Identified specific metabolic genes associated with rectal cancer prognosis.
• Patients categorized as high-risk based on these genes exhibited significantly poorer survival outcomes in both TCGA and GEO datasets.
• Enrichment analyses revealed significantly enriched GO terms and pathways, suggesting underlying biological mechanisms.

Conclusions:

• Several survival-related metabolic genes were identified for rectal cancer prognosis.
• These genes may play critical roles in regulating the metabolic tumor microenvironment.
• The identified genes represent potential biomarkers for predicting prognosis and guiding metabolic therapies in rectal cancer.