Paired Transcriptomic Profiling Identifies Shared Liver Metastasis-Associated Molecular Features in Colorectal Cancer

Abstract

Colorectal cancer liver metastasis (CCLM) is closely associated with poor patient prognosis, yet patient-specific molecular heterogeneity complicates the identification of recurrent molecular changes during metastasis. To address this, we performed RNA sequencing on paired primary tumors and liver metastases synchronously resected from six patients and analyzed gene expression changes using a paired design that accounted for interpatient variability. This analysis identified differentially expressed genes (DEGs) and metastasis-associated pathways through functional enrichment analysis and gene set enrichment analysis (GSEA). The reproducibility of these changes was further assessed across multiple independent publicly available transcriptomic datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Selected candidate genes were additionally evaluated in a metastasis-selected colorectal cancer cell model, in which several genes showed expression changes consistent with the transcriptomic findings. Together, these results indicate that recurrent molecular changes accompany CCLM despite substantial interpatient heterogeneity and provide a strategy for identifying metastasis-associated molecular features and potential therapeutic targets.