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

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...

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Autores principales: Wang, Jun, Liu, Xianyu, Cui, Weifang, Xie, Qun, Peng, Wei, Zhang, Heng, Gao, Yang, Zhang, Chunfang, Duan, Chaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812260/
https://www.ncbi.nlm.nih.gov/pubmed/35115004
http://dx.doi.org/10.1186/s12935-022-02481-6
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author Wang, Jun
Liu, Xianyu
Cui, Weifang
Xie, Qun
Peng, Wei
Zhang, Heng
Gao, Yang
Zhang, Chunfang
Duan, Chaojun
author_facet Wang, Jun
Liu, Xianyu
Cui, Weifang
Xie, Qun
Peng, Wei
Zhang, Heng
Gao, Yang
Zhang, Chunfang
Duan, Chaojun
author_sort Wang, Jun
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-022-02481-6.
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spelling pubmed-88122602022-02-07 Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma Wang, Jun Liu, Xianyu Cui, Weifang Xie, Qun Peng, Wei Zhang, Heng Gao, Yang Zhang, Chunfang Duan, Chaojun Cancer Cell Int Primary Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-022-02481-6. BioMed Central 2022-02-03 /pmc/articles/PMC8812260/ /pubmed/35115004 http://dx.doi.org/10.1186/s12935-022-02481-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Primary Research
Wang, Jun
Liu, Xianyu
Cui, Weifang
Xie, Qun
Peng, Wei
Zhang, Heng
Gao, Yang
Zhang, Chunfang
Duan, Chaojun
Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma
title Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma
title_full Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma
title_fullStr Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma
title_full_unstemmed Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma
title_short Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma
title_sort plasma trna-derived small rnas signature as a predictive and prognostic biomarker in lung adenocarcinoma
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812260/
https://www.ncbi.nlm.nih.gov/pubmed/35115004
http://dx.doi.org/10.1186/s12935-022-02481-6
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