Abstract 2812: Prognostic implications of gastric cancer-specific tsRNA subtypes and functional validation

Abstract Background: Gastric cancer is a global malignant disease of the digestive tract. The marked heterogeneity of gastric cancer leads to prognostic and therapeutic challenges. tRNA-derived fragments (tsRNAs), a novel class of small non-coding RNAs closely associated with tumor progression, have an imperfect role in prognostic assessment and treatment of gastric cancer. We aimed to identify specific tsRNA isoforms associated with the tumor microenvironment of gastric cancer, establish a tsRNA-based prognostic model for gastric cancer, and screen-specific factors that may inhibit gastric cancer to guide prognosis and treatment. Methods: We performed matrix score analysis and consensus clustering analysis using tsRNA expression profiles from the tsRFun database and gastric cancer sample information from the TCGA database. Ten machine learning (Lasso, Enet, plsRcox, CoxBoost, StepCox, GBM, Ridge, RSF, survival-SVM, and SuperPC) were used to construct tsRNA-related prognostic models (TRS). In-house development of an R package called ‘GCtsRNAscore’ for calculating tsRNA score (RS) in gastric cancer patients. TMB and IMvigor210 cohorts were evaluated for immunotherapy efficacy. Pandora sequencing screened for gastric cancer-specific tsRNAs for functional validation in cellular, organoid, and animal models for functional validation. Results: We classified 80 gastric cancer-specific tsRNAs into three immunological subtypes, Stromal_L, Stromal_M, and Stromal_H, based on stromal cell infiltration analysis, with Stromal_L having the best prognosis. A multi-omics approach revealed significant differences in biological characteristics, CNVs, and mutation patterns among the subtypes (P < 0.05). The TCGA and GEO gastric cancer cohorts validated that TRS was the best prognostic model for tsRNA-associated tsRNAs in gastric cancer (P < 0.0001, AUC = 0.967). Gastric cancer patients were categorized into high-risk and low-risk based on their respective RS. High-risk patients responded well to axitinib, bexarotene, and dasatinib, while low-risk patients responded well to immunotherapy. In addition, we identified six subtype-specific tsRNAs, which were combined with Pandora sequencing to screen for the gastric cancer-specific suppressor Gly-tsRNA-4. Overexpression of Gly-tsRNA-4 was found to inhibit tumor growth in cellular, organoid, and animal experiments. Conclusion: In this study, tsRNA-related indicators accurately predicted the prognosis of gastric cancer and provided insight into the response of GC patients to therapeutic drugs. Gly-tsRNA-4 may act as a tumor suppressor to inhibit gastric cancer progression. The above study can help to explore new targets for gastric cancer treatment, but further comprehensive validation is needed. Citation Format: Yuan Liu, Xin Hu, Ye Tian, Wei Wang, Kexin Chen, Hongji Dai, Ben Liu, Fengju Song. Prognostic implications of gastric cancer-specific tsRNA subtypes and functional validation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2812.