Peripheral blood non-canonical small non-coding RNAs as novel biomarkers in lung cancer
Zhou, Jin J
Knox, Kenneth S
AffiliationUniv Arizona, Dept Epidemiol & Biostat
Univ Arizona, Coll Med Phoenix, Dept Internal Med
MetadataShow full item record
CitationGu, W., Shi, J., Liu, H., Zhang, X., Zhou, J. J., Li, M., ... & Zhou, T. (2020). Peripheral blood non-canonical small non-coding RNAs as novel biomarkers in lung cancer. Molecular Cancer, 19(1), 1-6.
Rights© The Author(s). 2020 Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License. The Creative Commons Public Domain Dedication waiver (http://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.
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AbstractOne unmet challenge in lung cancer diagnosis is to accurately differentiate lung cancer from other lung diseases with similar clinical symptoms and radiological features, such as pulmonary tuberculosis (TB). To identify reliable biomarkers for lung cancer screening, we leverage the recently discovered non-canonical small non-coding RNAs (i.e., tRNA-derived small RNAs [tsRNAs], rRNA-derived small RNAs [rsRNAs], and YRNA-derived small RNAs [ysRNAs]) in human peripheral blood mononuclear cells and develop a molecular signature composed of distinct ts/rs/ysRNAs (TRY-RNA). Our TRY-RNA signature precisely discriminates between control, lung cancer, and pulmonary TB subjects in both the discovery and validation cohorts and outperforms microRNA-based biomarkers, which bears the diagnostic potential for lung cancer screening.
NoteOpen access journal
VersionFinal published version
Except where otherwise noted, this item's license is described as © The Author(s). 2020 Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License. The Creative Commons Public Domain Dedication waiver (http://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.
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