Department of Gastrointestinal Surgery Zone 1,Ningde Municipal Hospital of Ningde Normal University, Ningde, Fujian, China , chenkejie1@126.com
Abstract: (7 Views)
Background:To investigate the correlation between immune gene expression patterns and radiotherapy (RT) response, aiming to identify novel biomarkers for personalized rectal cancer treatment. Materials and Methods: Data from rectal cancer patients were clustered into two subgroups based on immune gene expression. Differentially expressed genes (DEGs) between subgroups were identified by using the limma package, and survival analysis was conducted with the Kaplan-Meier (KM) method. ClusterProfiler was used to conduct GO and KEGG pathway enrichment analyses on the DEGs. Protein-protein interaction (PPI) networks were utilized to pinpoint key modules or hub genes through interaction scores. In the TCGA rectal cancer dataset, 165 samples were divided into high (n=39) and low (n=126) immune gene expression groups based on the expression of 1,959 immune-related genes. Results: Between the two groups, 775 DEGs were up-regulated and 35 were down-regulated. Analysis of the GSE35452 dataset revealed 308 up-regulated and 209 down-regulated DEGs between the RT-responsive group (n=24) and the non-responsive group (n=22). PPI analysis showed that PLA2G2A and PLA2G4A exhibited the highest interaction score (value = 0.918). Conclusion: Through gene enrichment and PPI network analysis, potential core targets PLA2G2A and PLA2G4A were identified, providing new biomarkers for personalized treatment in rectal cancer.