Identification and validation of gene markers for early detection and prognosis in colorectal cancer: a comprehensive RNA-seq based approach.

[BACKGROUND] Reliable molecular biomarkers are urgently needed for early diagnosis of colorectal cancer (CRC). This study aimed to identify and validate a robust diagnostic gene signature using integrated transcriptomic analysis.

[METHODS] Eleven public gene expression datasets published between 2014 and 2024 were combined, including 329 CRC samples and 48 normal controls. Batch effects were corrected using the COMBAT algorithm. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology, KEGG, and REACTOME enrichment analyses. A protein-protein interaction network was constructed to screen hub genes. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis and a disease risk score (DRS), followed by external validation in independent cohorts.

[RESULTS] A total of 1,101 DEGs were identified, including 544 upregulated and 557 downregulated genes. Functional enrichment analysis indicated that upregulated genes were mainly involved in extracellular matrix organization and inflammatory signaling, whereas downregulated genes were associated with transport and metal ion homeostasis. A ten-gene signature was established. The DRS demonstrated strong diagnostic performance in the pooled dataset (AUC = 0.96) and in external validation cohorts (AUC = 0.985). Stage-stratified analysis confirmed robust discrimination across all CRC stages, including early disease.

[CONCLUSIONS] This integrative analysis identified a stable ten-gene diagnostic signature with potential clinical utility for CRC detection.