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Updated: Aug 4, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Tumor Immunophenotyping-Derived Signature Identifies Prognosis and Neoadjuvant Immunotherapeutic Responsiveness in
Jia-Bin Wang1,2,3, Qing-Zhu Qiu1,2,3, Qiao-Ling Zheng4
1Department of Gastric Surgery, Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, P. R. China.
Abstract:
The effectiveness of neoadjuvant immune checkpoint inhibitor (ICI) therapy is confirmed in clinical trials; however, the patients suitable for receiving this therapy remain unspecified. Previous studies have demonstrated that the tumor microenvironment (TME) dominates immunotherapy; therefore, an effective TME classification strategy is required. In this study, five crucial immunophenotype-related molecules (WARS, UBE2L6, GZMB, BATF2, and LAG-3) in the TME are determined in five public gastric cancer (GC) datasets (n = 1426) and an in-house sequencing dataset (n = 79). Based on this, a GC immunophenotypic score (IPS) is constructed using the least absolute shrinkage and selection operator (LASSO) Cox, and randomSurvivalForest. IPSLow is characterized as immune-activated, and IPSHigh is immune-silenced. Data from seven centers (n = 1144) indicate that the IPS is a robust and independent biomarker for GC and superior to the AJCC stage. Furthermore, patients with an IPSLow and a combined positive score of ≥5 are likely to benefit from neoadjuvant anti-PD-1 therapy. In summary, the IPS can be a useful quantitative tool for immunophenotyping to improve clinical outcomes and provide a practical reference for implementing neoadjuvant ICI therapy for patients with GC.
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