{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T10:18:58Z","timestamp":1785320338199,"version":"3.55.0"},"reference-count":52,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T00:00:00Z","timestamp":1762128000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Gastric cancer (GC) is a highly heterogeneous malignancy with poor prognosis, underscoring the urgent need for reliable biomarkers to guide precise stratification and therapy. Transfer RNA-derived small RNAs (tsRNAs) have emerged as potential key regulators in cancer, yet their systematic role in defining GC subtypes remains unexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We profiled tsRNA expression in GC using transcriptomic data from TCGA and GEO databases. Unsupervised consensus clustering identified tsRNA-based subtypes. A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and\n                      <jats:italic>in vitro<\/jats:italic>\n                      and organoid-based assays.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Three distinct tsRNA-mediated subtypes (Stromal_H, Stromal_L, Stromal_M) were identified, exhibiting significant differences in stromal activity, tumor microenvironment, and clinical outcomes. The Stromal_H subtype demonstrated the poorest prognosis, characterized by an immunosuppressive microenvironment and dysregulated DNA repair pathways. A random survival forest (RSF)-based prognostic signature (GCtsRNAscore) effectively stratified patients into high- and low-risk groups, with high-risk patients showing increased sensitivity to targeted therapies (axitinib, bexarotene, dasatinib) and low-risk patients benefiting more from immunotherapy. Furthermore, tsRNA-Asp-3-0024 was significantly upregulated in GC tissues and cell lines, where it promoted proliferation and inhibited apoptosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Our study establishes tsRNAs as powerful biomarkers for molecular subtyping and prognostic prediction in GC. The tsRNA-defined subtypes and GCtsRNAscore model provide a novel framework for personalized treatment strategies. The functional characterization of tsRNA-Asp-3-0024 highlights its potential as both a therapeutic target and a prognostic indicator, paving the way for tsRNA-based precision medicine in GC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1684113","type":"journal-article","created":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T06:23:05Z","timestamp":1762150985000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric 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