Development and validation of hyperlipidemia-related genes for prognosis prediction in colorectal cancer

Background: Colorectal cancer (CRC) often presents with high mortality and a poor prognosis. Numerous studies have demonstrated the association between hyperlipidemia and CRC metastasis. This study aimed to characterize hyperlipidemia-related genes (HRGs) and thereby lay a theoretical foundation for the early diagnosis and treatment of CRC. Methods: We derived differentially expressed HRGs (DE-HRGs) by intersecting differentially expressed genes, Weighted Gene Co-expression Network Analysis (WGCNA) key module genes, and predefined HRGs from the TCGA-CRC and GSE39582 datasets. Protein-Protein Interaction (PPI)s were employed, followed by the application of machine learning for subsequent identification of biomarkers. Following validation of biomarker expression in the TCGA-CRC and GSE39582 datasets, their diagnostic value was assessed by receiver operating characteristic (ROC) analysis. Further investigations encompassed Kaplan-Meier survival analysis, nomogram development, immune infiltration profiling, regulatory network mapping, and drug prediction, culminating in quantitative reverse transcription polymerase chain reaction (qRT-PCR) confirmation. Results: A total of 44 DE-HRGs were identified. GCG, SST, SLC30A10, and SLC22A5 were identified as biomarkers associated with hyperlipidemia and affecting the progression of CRC, which could effectively diagnose CRC patients in both datasets. A significant difference in GCG expression was found between the risk groups via survival analysis. Meanwhile, the nomogram constructed based on biomarkers exhibited an excellent prediction effect for CRC patients. Through immune infiltration analysis, it was found that activated CD8 T cells had a striking positive correlation with SST and a significant negative correlation with SLC22A5. The established regulatory network contained 4 mRNAs, 11 miRNAs, and 17 lncRNAs, and the regulatory relationships included LINC01915-Hsa-miR-450b-5p-SLC30A10 and others. 16 therapeutic drugs were predicted, such as Naltrexone, Streptozocin, and Carnitine, et al. Importantly, the qRT-PCR results showed that the biomarkers had down-regulated expression in the CRC group, and the direction of this expression trend was consistent with that of the datasets. Conclusion: The identification of GCG, SST, SLC30A10, and SLC22A5 as hyperlipidemia-related biomarkers in CRC contributes a scientific basis for future research.