Identification of Predictive Biomarkers for Chemoradiotherapy Response in Rectal Cancer

Chemoradiotherapy (CRT) is a standard treatment for rectal cancer, yet patients show marked variability in response. Identifying reliable biomarkers that predict CRT response remains an unmet clinical need.

Pretreatment biopsy samples from patients who received neoadjuvant CRT were analyzed using RNA sequencing. Differentially expressed genes (DEGs) were identified between responders and nonresponders, followed by functional enrichment analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. To complement DEG-based results, gene-set enrichment analysis (GSEA) was performed to assess pathway activity across the ranked transcriptome and to prioritize biologically relevant pathways. Pathway-derived gene signatures were evaluated using receiver operating characteristic curves and validated in three independent data sets.

A total of 1,477 DEGs were detected, including 729 upregulated and 748 downregulated genes in responders. Functional enrichment analysis indicated immune activation and epithelial polarity in responders, whereas nonresponders showed enrichment of extracellular matrix organization, focal adhesion, and phosphoinositide 3-kinase-protein kinase B signaling. GSEA further identified four pathways associated with CRT response: antigen presentation, extracellular matrix-receptor interaction, focal adhesion, and drug metabolism. Among these, the antigen presentation pathway consistently predicted treatment response across data sets. Elastic net regression defined a six-gene signature (KLRC1, CTSS, HLA-DMA, HLA-DQB1, HLA-DQB2, and CIITA) with strong predictive performance, with area under the curve values ranging from 0.76 to 0.81.

These genes participate in major histocompatibility complex class II antigen-processing and immune-regulatory pathways that enhance CD4 T-cell activation. Overall, the findings indicate that an immune-active, antigen presentation phenotype underlies radiosensitivity in rectal cancer and that the six-gene signature may serve as a biomarker to guide personalized treatment strategies.