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The low effectiveness of common biomarkers for the detection of early GC makes it essential to seek new biomarkers to improve diagnostic efficacy. tsRNAs (transfer RNA-derived small RNAs) are related to the growth of malignant tumors. In this article, we focused on whether tsRNAs may be employed as biomarkers for GC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      tRF-17-18VBY9M was screened in the tsRFun database as a research object. The methodological efficacy of tRF-17-18VBY9M was evaluated using Sanger sequencing, agarose gel electrophoresis assays, and gradient dilution. The \u03c7\n                      <jats:sup>2<\/jats:sup>\n                      test was applied to assess the interaction between tRF-17-18VBY9M expression and clinicopathologic characteristics. The receiver operating characteristic (ROC) curve was utilized to investigate the clinical\u00a0efficiency of tRF-17-18VBY9M in GC.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The Chi-square test demonstrated that high-expressed tRF-17-18VBY9M was closely associated with the T stage, tumor node metastasis stage (TNM), lymph node metastasis, and neurological\/vascular invasion. ROC curve analysis revealed that the diagnostic value of tRF-17-18VBY9M in GC was superior to carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), and carbohydrate antigen 724 (CA724).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>tRF-17-18VBY9M is up-regulated in both GC sera and tissues. Differential tRF-17-18VBY9M expression distinguishes GC patients from healthy donors and gastritis patients, which suggests tRF-17-18VBY9M could act as a diagnostic biomarker in GC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00432-024-05792-5","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T09:01:30Z","timestamp":1716195690000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A novel tRNA-derived fragment tRF-17-18VBY9M works as a potential diagnostic biomarker for gastric cancer"],"prefix":"10.1007","volume":"150","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9633-597X","authenticated-orcid":false,"given":"Chunyan","family":"Mao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0947-5469","authenticated-orcid":false,"given":"Zhihan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4273-0218","authenticated-orcid":false,"given":"Ronghua","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8625-0796","authenticated-orcid":false,"given":"Wentao","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0421-2628","authenticated-orcid":false,"given":"Yi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3660-4557","authenticated-orcid":false,"given":"Hui","family":"Cong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,20]]},"reference":[{"issue":"10125","key":"5792_CR1","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1016\/S0140-6736(17)33326-3","volume":"391","author":"C Allemani","year":"2018","unstructured":"Allemani C et al (2018) Global surveillance of trends in cancer survival 2000\u201314 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. 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