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This study aimed to develop a combinatorial model based on serum cell\u2010free tsRNA signatures and evaluated its diagnostic performance for NSCLC detection. Through systematic screening from the tsRFun database, we identified 32 NSCLC\u2010related differentially expressed tsRNAs, whose predicted target genes were significantly enriched in the MAPK pathway. Four MAPK pathway\u2010associated tsRNAs were selected for further validation due to their robust discriminatory power in distinguishing NSCLC patients from healthy control. Subsequent validation via quantitative RT\u2010PCR confirmed significantly elevated serum levels of tsRNA\u2010Thr\u20105\u20100039, tsRNA\u2010Thr\u20105\u20100044, and tsRNA\u2010Cys\u20105\u20100011 in NSCLC patients compared to healthy controls. The final combinatorial diagnostic model incorporating these three tsRNAs achieved an AUC of 0.83 (95% CI: 0.70\u20130.95), with 71.8% accuracy, 52.6% sensitivity, and 90.0% specificity. The three\u2010tsRNA model outperformed individual tsRNAs in diagnostic efficiency. In conclusion, these findings highlight the diagnostic potential of circulating tsRNA signatures as a minimally invasive liquid biopsy approach, offering new perspectives for early diagnosis of NSCLC.<\/jats:p>","DOI":"10.1002\/mc.70124","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T13:24:36Z","timestamp":1778851476000},"page":"938-947","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Combinatorial Model of Serum tsRNAs as a Diagnostic Biomarker for Non\u2010Small Cell Lung Cancer"],"prefix":"10.1002","volume":"65","author":[{"given":"Xiaolu","family":"Hu","sequence":"first","affiliation":[{"name":"The First Clinical College Chongqing Medical University Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyu","family":"Yang","sequence":"additional","affiliation":[{"name":"The First Clinical College Chongqing Medical University Chongqing 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