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 IS GC 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 IS GC classifier based on 5 features: CD3 invasive margin (IM), CD3 center of tumor (CT), CD8 IM, CD45RO CT, and CD66b IM. Significant differences were found between the high-IS GC and low-IS GC 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 IS GC classifier was an independent prognostic factor. A combination of IS GC 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-IS GC 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 IS GC classifier could effectively predict recurrence and survival of GC, and complemented the prognostic value of the TNM staging system. Moreover, the IS GC might be a useful predictive tool to identify stage II and III GC patients who would benefit from adjuvant chemotherapy.