Lipid Metabolism-Related Gene Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in...

Area of Science:

• Oncology
• Metabolomics
• Genomics

Background:

• Abnormal lipid metabolism is linked to gastric cancer progression, but mechanisms are unclear.
• Understanding lipid metabolism's role is vital for advanced gastric cancer (AGC) treatment.

Purpose of the Study:

• To analyze the biological significance of lipid metabolism genes in AGC.
• To identify prognostic markers and therapeutic targets for AGC.

Main Methods:

• Utilized TCGA data for gene expression analysis and identified differential lipid metabolism genes in AGC.
• Applied consensus clustering, LASSO-Cox regression, and GSEA to develop a prognostic risk model.
• Integrated immune microenvironment, checkpoint, and infiltration data with WGCNA for hub gene identification.

Main Results:

• Identified 6 prognostic lipid metabolism genes, classifying AGC patients into two distinct survival and immune microenvironment subgroups.
• Developed a validated risk model predicting AGC prognosis, correlating risk scores with immune infiltration and drug sensitivity.
• Demonstrated the model's independence as a prognostic predictor and its utility in guiding chemotherapy selection.

Conclusions:

• Lipid metabolism genes are key predictors of AGC prognosis and immune invasion.
• The developed risk model offers insights into AGC progression and potential therapeutic strategies.
• Findings support the development of targeted therapies based on lipid metabolism pathways in AGC.