Immune activation-related risk score: A new tool to predict prognosis and immunotherapy applicability in colorectal cancer

e15534 Background: In colorectal cancer (CRC), the therapeutic potential of immune checkpoint inhibitors (ICIs) is limited to the patients with mismatch repair deficient (dMMR)/high microsatellite instable (MSI-H) tumors, which accounts for less than 5% of CRC patients. While, patients with mismatch repair proficient (pMMR)/microsatellite stable (MSS) tumors represent the vast majority (≈ 95%), particularly those with similar inflammatory tumour microenvironment characteristics to dMMR/MSI-H patients are at risk of losing the opportunity to receive appropriate treatment. Thus, there is an urgent clinical need for biomarkers that can accurately predict prognosis of CRC patients, and assist in selection of patients who may benefit from immunotherapy. Methods: A public database, GEO (GSE39582, n = 502), was used as a training cohort to assess the characteristics associated with immune activation. Individuals with immune characteristics similar to dMMR/MSI-H were identified through GSVA and unsupervised clustering analysis, and defined as MSI-Like. Limma analysis identified MSI-Like immune activation characteristic, and immune activation-related prognostic models were developed by LASSO and COX regression. In addition, the applicability of immunotherapy for immune activation-related prognostic score was estimated in an external validation cohort (n = 96) from an Asian institution. Results: 113 differentially expressed genes between MSI-Like and non-MSI-Like pMMR/MSS samples were defined as immune activation- related characteristics of MSI-Like. After stepwise regression analysis, the characteristics were reduced to 6 key genes, and combined with their regression coefficients to construct a model. Overall survival was significantly shorter in high-risk [Immune Activation-related Risk Score (IARS) ≥ 0] group than in low-risk (IARS < 0) group (p < 0.0001). The area under the ROC curve (AUC) values at 1, 5 and 10 years were 0.683, 0.708 and 0.765, respectively. Furthermore, in multiple CRC data sets, the IARS can screen out the low-risk group with significantly better prognosis (p < 0.05). Additionally, low-risk group showed more expression of immune activation-related genes compared to high-risk group. IARS did not shown significant correlations with clinically characteristic factors (e.g., gender, age, stage, etc.) or gene mutations (including TP53, KRAS and BRAF). Conclusions: For a subset of pMMR/MSS patients with immune activation characteristics similar to those of dMMR/MSI-H patients, an immune activation-related risk score model was constructed based on 6 genes associated with immune activation characteristics. This model can effectively predict the prognosis of patients and also help to assess the adaptability of patients to immunotherapy. These findings have the potential to provide new insights into the immunotherapy of patients with pMMR/MSS CRC.