ImmunoScore Signature

Abstract

OBJECTIVE: We postulated that the ImmunoScore (IS) could markedly improve the prediction of postsurgical survival and chemotherapeutic benefits in gastric cancer (GC). SUMMARY BACKGROUND DATA: A prediction model for GC patients was developed using data from 879 consecutive patients. METHODS: The expression of 27 immune features was detected in 251 specimens by using immunohistochemistry, and a 5-feature-based ISGC was then constructed using the LASSO Cox regression model. Testing and validation cohorts were included to validate the model. RESULTS: Using the LASSO model, we established an ISGC classifier based on 5 features: CD3invasive margin (IM), CD3center of tumor (CT), CD8IM, CD45ROCT, and CD66bIM. Significant differences were found between the high-ISGC and low-ISGC patients in the training cohort in 5-year disease-free survival (45.0% vs. 4.4%, respectively; P <0.001) and 5-year overall survival (48.8% vs. 6.7%, respectively; P <0.001). Multivariate analysis revealed that the ISGC classifier was an independent prognostic factor. A combination of ISGC and tumor, node, and metastasis (TNM) had better prognostic value than TNM stage alone. Further analysis revealed that stage II and III GC patients with high-ISGC exhibited a favorable response to adjuvant chemotherapy. Finally, we constructed 2 nomograms to predict which patients with stages II and III GC might benefit from adjuvant chemotherapy after surgery. CONCLUSIONS: The ISGC classifier could effectively predict recurrence and survival of GC, and complemented the prognostic value of the TNM staging system. Moreover, the ISGC might be a useful predictive tool to identify stage II and III GC patients who would benefit from adjuvant chemotherapy.