151P - Development of a predictive model for response to neoadjuvant chemoradiation therapy of rectal cancer using the immunologic profile

Background

Response to neoadjuvant chemoradiation therapy (nCRT) in rectal cancer is variable. Prediction for response to nCRT will allow to select rectal cancer patients who would or would not benefit from nCRT, providing adequate treatment options for locally advanced rectal cancer patients. Recent studies have indicated immunomicroenvironment has relevance to tumor behavior including response to radio- or chemo-treatment. In the present study, we aimed to examine the putative role of the immunomicroenvironment in mediating differential nCRT response in rectal cancer patients and to develop a biomarker model for predicting response to nCRT using immune-related gene expression.

Methods

Expression profiling of 770 immune-related genes was performed in 47 rectal cancer tissues before nCRT. Tumors were screened for predictive biomarkers using the NanoString nCounter platform for digital gene expression analysis with the PanCancer Immune Profiling panel. A genetic model was generated for the prediction of response to nCRT.

Results

Genes associated with the function of T-cell, NK cell, and macrophage were significantly differentially expressed between good and poor responders. Complement pathway components and chemokines were also associated with response to nCRT. Higher expression of FOXJ1, IL7RB, LGALS3, MAP2K2, SH2D1B, and ZC3H14 was significantly associated with pathologic complete response. To discriminate between good and poor responders, we developed a predictive model composed of TNFRSR10B, TCF7, TLR4, SH2D1B, AGK, TBX21, CCL25, IL17RB, ZNF346, and CREB5 using machine learning methods. This model predicted treatment response with good performance in internal validation test (accuracy: 0.8182).

Conclusions

Our results suggest that response to nCRT in rectal cancer is associated with gene expression patterns related to the immunomicroenvironment. We developed a predictive model composed of immune-related genes that allowed the prediction of rectal cancer response to nCRT.

Editorial acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government. (No. 2020R1F1A1076367)

Clinical trial identification

Legal entity responsible for the study

The authors.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government. (No. 2020R1F1A1076367).

Disclosure

All authors have declared no conflicts of interest.