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Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer

Colorectal cancer often presents as a highly variable disease with myriad forms that are at times difficult to detect in early screenings with sufficient accuracy, for which novel diagnostic methods are an attractive and valuable area of improvement. To improve colorectal cancer diagnosis and progno...

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Autores principales: Zhu, Yong, Chen, Shaoqiu, Ling, Zhougui, Winnicki, Andrew, Xu, Lilly, Xu, Shaun, Gong, Ting, Jiang, Bin, Huang, Gang, Deng, Youping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371552/
https://www.ncbi.nlm.nih.gov/pubmed/34422655
http://dx.doi.org/10.3389/fonc.2021.701440
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author Zhu, Yong
Chen, Shaoqiu
Ling, Zhougui
Winnicki, Andrew
Xu, Lilly
Xu, Shaun
Gong, Ting
Jiang, Bin
Huang, Gang
Deng, Youping
author_facet Zhu, Yong
Chen, Shaoqiu
Ling, Zhougui
Winnicki, Andrew
Xu, Lilly
Xu, Shaun
Gong, Ting
Jiang, Bin
Huang, Gang
Deng, Youping
author_sort Zhu, Yong
collection PubMed
description Colorectal cancer often presents as a highly variable disease with myriad forms that are at times difficult to detect in early screenings with sufficient accuracy, for which novel diagnostic methods are an attractive and valuable area of improvement. To improve colorectal cancer diagnosis and prognosis, new biomarkers that can be assembled into a diagnostic panel must be identified, and tRNA-derived small RNAs (tsRNAs) are a particularly interesting and increasingly visible new class of molecules to examine. In this study, small RNA-seq data were profiled for the expression of 104 human tsRNAs in tumor tissue and adjacent normal tissue samples, and a diagnostic model was built based on four differentially expressed tsRNAs: tRF-22-WB86Q3P92, tRF-22-WE8SPOX52, tRF-22-WE8S68L52, tRF-18-8R1546D2. Furthermore, the diagnostic model was validated by two independent validation datasets (AUC was 0.97 and 0.99), and a LASSO model was applied to develop a seven-tsRNA-based risk score model for colorectal cancer prognosis. Finally, a tsRNA-mRNA interaction network was established according to potential mRNA targets predicted by bioinformatic methods. In conclusion, the results suggest that abnormal expression of tsRNA in colorectal cancer may have a functional effect on tumor action and moreover, that some of the tsRNAs identified in this study with diagnostic and prognostic potential could be of clinical significance.
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spelling pubmed-83715522021-08-19 Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer Zhu, Yong Chen, Shaoqiu Ling, Zhougui Winnicki, Andrew Xu, Lilly Xu, Shaun Gong, Ting Jiang, Bin Huang, Gang Deng, Youping Front Oncol Oncology Colorectal cancer often presents as a highly variable disease with myriad forms that are at times difficult to detect in early screenings with sufficient accuracy, for which novel diagnostic methods are an attractive and valuable area of improvement. To improve colorectal cancer diagnosis and prognosis, new biomarkers that can be assembled into a diagnostic panel must be identified, and tRNA-derived small RNAs (tsRNAs) are a particularly interesting and increasingly visible new class of molecules to examine. In this study, small RNA-seq data were profiled for the expression of 104 human tsRNAs in tumor tissue and adjacent normal tissue samples, and a diagnostic model was built based on four differentially expressed tsRNAs: tRF-22-WB86Q3P92, tRF-22-WE8SPOX52, tRF-22-WE8S68L52, tRF-18-8R1546D2. Furthermore, the diagnostic model was validated by two independent validation datasets (AUC was 0.97 and 0.99), and a LASSO model was applied to develop a seven-tsRNA-based risk score model for colorectal cancer prognosis. Finally, a tsRNA-mRNA interaction network was established according to potential mRNA targets predicted by bioinformatic methods. In conclusion, the results suggest that abnormal expression of tsRNA in colorectal cancer may have a functional effect on tumor action and moreover, that some of the tsRNAs identified in this study with diagnostic and prognostic potential could be of clinical significance. Frontiers Media S.A. 2021-08-04 /pmc/articles/PMC8371552/ /pubmed/34422655 http://dx.doi.org/10.3389/fonc.2021.701440 Text en Copyright © 2021 Zhu, Chen, Ling, Winnicki, Xu, Xu, Gong, Jiang, Huang and Deng https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Zhu, Yong
Chen, Shaoqiu
Ling, Zhougui
Winnicki, Andrew
Xu, Lilly
Xu, Shaun
Gong, Ting
Jiang, Bin
Huang, Gang
Deng, Youping
Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer
title Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer
title_full Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer
title_fullStr Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer
title_full_unstemmed Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer
title_short Comprehensive Analysis of a tRNA-Derived Small RNA in Colorectal Cancer
title_sort comprehensive analysis of a trna-derived small rna in colorectal cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371552/
https://www.ncbi.nlm.nih.gov/pubmed/34422655
http://dx.doi.org/10.3389/fonc.2021.701440
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