Identification of shared genetic features and molecular mechanisms of metabolic syndrome and colorectal cancer based on transcriptomic data

Abstract:

Objective To identify shared genetic features and biological pathways between metabolic syndrome（MetS） and colorectal cancer（CRC），and to screen for prognostic biomarkers associated with MetS in CRC.Methods First，differential analysis was performed on MetS，CRC，and their corresponding control samples to identify genes with differential expression，which were used as disease-related genes. Subsequently，functional enrichment analysis was performed based on the expression characteristics of these genes to identify the regulated biological functions. Then，single-factor Cox regression was used to identify MetS genes associated with CRC prognosis，and LASSO and multivariate Cox regression analysis were used to construct a model for prediction of CRC prognosis. Finally，the causal relationship between MetS genes and CRC prognosis was further confirmed through Summary-data-based Mendelian Randomization.Results A total of 325 genes were upregulated and 281 genes were downregulated in both MetS and CRC. Apelin signaling and endocytosis pathways were inhibited and the nucleotide excision repair pathway was activated in both diseases. Among them，60 genes shared between MetS and CRC were associated with CRC prognosis. Eighteen genes were employed to construct a prediction model. In the CRC cohort of the TCGA database，the model demonstrated robust prediction performance with the area under the curve exceeding 0.75 for the 1-5 year period. Summary-data-based Mendelian Randomization analysis confirmed the causal relationship of P4HA1 and LARS2 with CRC prognosis.Conclusion MetS and CRC share genetic features and pathways，with inflammation as a possible link between these two diseases. Shared genes can influence the prognosis of CRC.