As the most abundant noncoding RNA in cells, tRNA plays an important role in tumorigenesis and development. The report of tRNA on the pathogenesis of lung adenocarcinoma is rare. It is of great clinical significance to explore the relationship between tRNA expression and prognosis of lung adenocarcinoma. The expression level of tRNAs in lung adenocarcinoma tissues and paracarcinoma tissues was detected using a tRNA RT-qPCR array. A total of 104 lung adenocarcinomas were included in the analysis of the correlation between candidate tRNAs expression and prognosis. A tRNA-based prognostic model was constructed and validated using Cox proportional hazards regression. A nomogram was built to help clinicians develop treatment strategies. We screened a series of differentially expressed tRNAs between lung adenocarcinoma tissues and paracarcinoma tissues. Among these tRNAs, tRNAAsnATT , tRNAIleAAT , tRNALeuTAA , mt-tRNATrpTCA , mt-tRNALeuTAA , tRNAProAGG , tRNALysCTT-1 and tRNALeuAAG were associated with the clinicopathological characteristics of lung adenocarcinoma. tRNALysCTT-1 , mt-tRNASerGCT and tRNATyrATA were associated with cancer-specific survival. We constructed a prognostic model for lung adenocarcinoma using specific tRNA expression levels as reference factors. Multivariate analyses showed that tRNA-based prognostic score was a significant and important prognostic factor. The prognostic model based on the tRNAs expression signatures can help predict the prognosis of patients with lung adenocarcinoma.
Keywords: lung adenocarcinoma; nomogram; prognostic model; tRNA.
© 2019 UICC.