Cell-in-cell associated lncRNA signature predicts prognosis and immunotherapy response in gastric cancer.

INTRODUCTION

Gastric cancer (GC) remains a leading cause of cancer mortality, necessitating robust prognostic biomarkers and personalized therapeutic strategies.

MATERIALS AND METHODS

We developed a risk model integrating three cell-in-cell-associated lncRNAs (CICRlncRNAs: AP003392.1, AP000695.2, AL161785.1) using transcriptomic data from 367 TCGA-GC patients. The cohort was randomly split into training (n = 184) and test sets (n = 183) for model construction and external validation. Statistical rigor included LASSO-Cox regression, Kaplan-Meier analysis, and ROC curves assessing 1/3/5-year AUC.

RESULTS

The model stratified patients into low- and high-risk groups with distinct overall survival (OS, HR = 2.62, 0.001) and progression-free survival (PFS, HR = 1.94, 0.001). High-risk patients exhibited an immunosuppressive tumor microenvironment (TME), characterized by elevated Tregs (0.05) and M2 macrophages (0.05), correlating with poor response to immune checkpoint inhibitors (TIDE score, 0.001). Drug sensitivity analysis revealed low-risk patients responded better to gefitinib/entinostat, while high-risk patients benefited from dasatinib/foretinib. Experimental validation confirmed AP000695.2 promoted proliferation and invasion in GC cells (0.01).

CONCLUSION

This study establishes CICRlncRNAs as prognostic biomarkers and provides insights for precision therapy, though clinical applicability requires prospective validation.