Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma

Abstract

Background The prevalence of lung adenocarcinoma (LUAD) has increased, thus novel biomarkers for its early diagnosis is becoming more important than ever. tRNA-derived small RNA (tsRNA) is a new class of non-coding RNA which has important regulatory roles in cancer biology. This study was designed to identify novel predictive and prognostic tsRNA biomarkers. Methods tsRNAs were identified and performed differential expression analysis from 10 plasma samples (6 LUAD and 4 normal, SRP266333) and 96 tissue samples (48 LUAD and 48 normal, SRP133217). Then a tsRNA-mRNA regulatory network was constructed to find hub tsRNAs. Functional enrichment analysis was performed to infer the potential pathways associated with tsRNAs. Afterwards, a Support Vector Machine (SVM) algorithm was used to explore the potential biomarkers for diagnosing LUAD. Lastly, the function of tRF-21-RK9P4P9L0 was explored in A549 and H1299 cell lines. Results A significant difference of read distribution was observed between normal people and LUAD patients whether in plasma or tissue. A tsRNA-mRNA regulatory network consisting of 155 DEtsRNAs (differential expression tsRNAs) and 406 DEmRNAs (differential expression mRNAs) was established. Three tsRNAs (tRF-16-L85J3KE, tRF-21-RK9P4P9L0 and tRF-16-PSQP4PE) were identified as hub genes with degree > 100. We found Co-DEmRNAs (intersection of DEtsRNAs target mRNAs and differentially expressed mRNAs in LUAD) were engaged in a number of cancer pathways. The AUC of the three hub tsRNAs’ expression for diagnosing LUAD reached 0.92. Furthermore, the qPCR validation of the three hub tsRNAs in 37 paired normal and LUAD tissues was consistent with the RNA-Seq results. In addition, tRF-21-RK9P4P9L0 was negatively associated with LUAD prognosis. Inhibition of tRF-21-RK9P4P9L0 expression reduced the proliferation, migration and invasion ability of A549 and H1299 cell lines. Conclusion These findings will help us further understand the molecular mechanisms of LUAD and contribute to novel diagnostic biomarkers and therapeutic target discovery.

Emerging roles of tRNA-derived fragments in cancer

“…Nowadays, machine learning has been increasingly applied for combined analysis of multiple molecules to achieve higher prediction accuracy. Wang et al established a model by support vector machine, combining three hub tRFs (tRF-16-L85J3KE, tRF-21-RK9P4P9L0 and tRF-16-PSQP4PE) to predict lung adenocarcinoma with an AUC 0.99 in plasma and 0.92 in tissues [ 140 ]. By contrast, the performance of these single tRF to distinguish lung adenocarcinoma in both plasma and tissue was very poor [ 140 ].…”

“…Wang et al established a model by support vector machine, combining three hub tRFs (tRF-16-L85J3KE, tRF-21-RK9P4P9L0 and tRF-16-PSQP4PE) to predict lung adenocarcinoma with an AUC 0.99 in plasma and 0.92 in tissues [ 140 ]. By contrast, the performance of these single tRF to distinguish lung adenocarcinoma in both plasma and tissue was very poor [ 140 ]. Another recent study also demonstrated that machine learning diagnostic models constructed with serum RNAs including tRFs, microRNAs, miscellaneous RNAs, and isomiRs could predict lung cancer up to 10 years prior to diagnosis, with a top AUC up to 0.9 [ 186 ].…”

Transfer RNAs-derived small RNAs and their application potential in multiple diseases

“…Some tsRNAs can be prognostic biomarkers because of their elevated expression in patients ( Tang et al, 2021 ). Such overexpressed tsRNAs can be knocked down by specific siRNAs which are regarded as therapeutic targets ( Wang et al, 2022b ). Some other tsRNAs are downregulated in patients, so the restoration of their intracellular levels may inhibit the disease progression ( Xiao et al, 2022 ).…”

Transfer RNA-derived small RNA: an emerging small non-coding RNA with key roles in cancer

“…The Area Under Curve (AUC) of these three tsRNAs reached 0.92 when they were combined to diagnose LUAD, suggesting good diagnostic efficacy. Additionally, tRF-21-RK9P4P9L0 was negatively correlated with LUAD prognosis, and inhibition of tRF-21-RK9P4P9L0 expression diminished the proliferation, migration, and invasive ability of LC cell lines [ 97 ]. In the plasma of CRC patients, the expression level of 5-tRF-GlyGCC was significantly elevated with an AUC of 0.882 and was further increased to 0.926 after combined with carcinoembryonic antigen and Carbohydrate antigen199, suggesting its good diagnostic efficacy for CRC [ 98 ].…”