Identification of colorectal cancer immune biomarkers <i>via</i> eQTL mapping: a Mendelian randomization and transcriptomic analysis study

Background: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. The identification of effective molecular targets is crucial for advancing precision medicine and prognostic strategies. This study aims to uncover key CRC biomarkers through integrative bioinformatics analyses, providing mechanistic insights for therapeutic development. Methods: We analyzed three CRC datasets from the Gene Expression Omnibus (GEO) database. Expression quantitative trait loci (eQTL) analysis was performed to identify instrumental variables (IVs), which were subsequently used in Mendelian Randomization (MR) analysis with CRC Genome-Wide Association Study (GWAS) data. MR-associated genes were intersected with differentially expressed genes (DEGs) to screen disease-related key genes. Functional enrichment analyses were conducted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Additionally, immune cell infiltration and gene-immune correlation analyses were performed. Finally, validation was performed using independent GEO, The Cancer Genome Atlas (TCGA) datasets, summary data-based Mendelian randomization (SMR) and quantitative reverse transcription polymerase chain reaction (qRT-PCR) in CRC cell lines. Results: < 0.05). Discussion: may be involved in CRC development, providing a reference for targeted and immunotherapy research.