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Updated: Jan 7, 2026
Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer
Published on: March 14, 2019
Immune Microenvironment Signatures Predict Response and Survival in Rectal Cancer Patients After Neoadjuvant
Bo-Hyung Kim1, Jiyoon Lee2, Donghwan Lee2
1Department of Clinical Pharmacology and Therapeutics, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea.
Background/Aim:
Response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer varies. Recent studies have highlighted the role of the tumor immune microenvironment in influencing tumor behavior. Herein, we aimed to assess immune-related gene expression in rectal cancer following nCRT and to investigate their potential as predictive and prognostic biomarkers.
Materials And Methods:
Expression profiling of 730 immune-related genes was conducted in 48 post-nCRT rectal cancer using the NanoString nCounter platform and the PanCancer Immune Profiling panel. Differentially expressed genes were compared between good and poor responders, and gene set enrichment analysis was conducted. The prognostic significance of these genes was analyzed. A genetic model was generated to predict nCRT responses.
Results:
We identified 24 immune-associated genes that were differentially expressed between good and poor responders, among which S100A8, SPINK5, ANXA1, FOXJ1, and CLEC7A showed high expression levels in good responders (Log2 fold change >1, p<0.05). Pathway analysis revealed that these genes were mainly involved in biological process associated with natural killer cell-mediated cytotoxicity. S100A8 and SPINK5 expression levels were associated with relapse-free survival (p=0.001 and 0.036, respectively), and these findings were validated in a publicly available dataset (S100A8; p=0.015, and SPINK5; p=0.024). The accuracy of the predictive model comprising TLR4, CCND3, TCF7, CREB5, TNFRSF10B, DPP4, PBK, DUSP4, and MUC1 was 85.7%.
Conclusion:
Immune-related gene expression patterns are associated with response to nCRT in rectal cancer. High expression levels of S100A8, SPINK5, ANXA1, FOXJ1, and CLEC7A were indicative of favorable treatment response, and S100A8 and SPINK5 were associated with prognosis. A machine learning-based model composed of immune-related genes showed strong predictive potential. Our results support the use of immune gene signatures to guide personalized therapy in rectal cancer.
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