ImmunoScore Signature: A Prognostic and Predictive Tool in Gastric Cancer.

Abstract

We postulated that the ImmunoScore (IS) could markedly improve the prediction of postsurgical survival and chemotherapeutic benefits in gastric cancer (GC). A prediction model for GC patients was developed using data from 879 consecutive patients. 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. 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. 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.