The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis
Background: A novel category of non-coding circular RNAs (circRNAs) has been found to be dysregulated in colorectal cancer (CRC) and significantly contribute to its progression. However, the feasibility of using circRNA as a diagnostic biomarker for CRC remains to be elucidated. Herein, we aimed to...
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oai:doaj.org-article:211d98ba7f9a46a6be073d44b656cc442021-11-19T05:34:23ZThe Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis2296-858X10.3389/fmed.2021.766208https://doaj.org/article/211d98ba7f9a46a6be073d44b656cc442021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmed.2021.766208/fullhttps://doaj.org/toc/2296-858XBackground: A novel category of non-coding circular RNAs (circRNAs) has been found to be dysregulated in colorectal cancer (CRC) and significantly contribute to its progression. However, the feasibility of using circRNA as a diagnostic biomarker for CRC remains to be elucidated. Herein, we aimed to comprehensively collect and analyze evidence regarding the potential application of circRNAs as diagnostic indicators for CRC.Methods: A comprehensive retrieval of relevant studies dating from January, 2015 to December 2020, was carried out in PubMed, Cochrane Library, and Web of Science. Data regarding the diagnostic accuracy of circRNA for CRC, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC), were obtained from the included studies. Quality assessment of diagnostic accuracy studies (QUADAS-2) was used to assess the methodological quality of each study. Statistical analysis was performed using STAT and RevMan software.Results: Eighteen studies, involving a total of 2021 individuals, were included in the present meta-analysis. The specimens examined included tissue, serum, and plasma. The pooled sensitivity, specificity, DOR, PLR, NLR, and AUC, with a 95% confidence interval (CI), of circRNAs in the diagnosis of CRC were 0.78 (0.71–0.83), 0.73 (0.68–0.78), 9.68 (6.76–13.85), 2.92 (2.45–3.50), 0.30 (0.23–0.39), and 0.81 (0.78–0.85), respectively. Subgroup analysis showed that the upregulated circRNAs in the tissue or plasma possessed relatively higher diagnostic values for CRC than the downregulated circRNAs. There was no significant difference between the tissue-derived and non-tissue-derived circRNA subgroups.Conclusion: circRNA may be used as a diagnostic biomarker for CRC because of its relatively high diagnostic accuracy in distinguishing CRC patients from normal controls. Further prospective studies are needed to identify more representative circRNAs as diagnostic markers for CRC.Ru-Dong LiMin GuanZhe ZhouShu-Xiao DongQian LiuFrontiers Media S.A.articlecircRNAcolorectal cancerbiomarkerdiagnostic powermeta-analysisMedicine (General)R5-920ENFrontiers in Medicine, Vol 8 (2021) |
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circRNA colorectal cancer biomarker diagnostic power meta-analysis Medicine (General) R5-920 |
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circRNA colorectal cancer biomarker diagnostic power meta-analysis Medicine (General) R5-920 Ru-Dong Li Min Guan Zhe Zhou Shu-Xiao Dong Qian Liu The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis |
description |
Background: A novel category of non-coding circular RNAs (circRNAs) has been found to be dysregulated in colorectal cancer (CRC) and significantly contribute to its progression. However, the feasibility of using circRNA as a diagnostic biomarker for CRC remains to be elucidated. Herein, we aimed to comprehensively collect and analyze evidence regarding the potential application of circRNAs as diagnostic indicators for CRC.Methods: A comprehensive retrieval of relevant studies dating from January, 2015 to December 2020, was carried out in PubMed, Cochrane Library, and Web of Science. Data regarding the diagnostic accuracy of circRNA for CRC, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC), were obtained from the included studies. Quality assessment of diagnostic accuracy studies (QUADAS-2) was used to assess the methodological quality of each study. Statistical analysis was performed using STAT and RevMan software.Results: Eighteen studies, involving a total of 2021 individuals, were included in the present meta-analysis. The specimens examined included tissue, serum, and plasma. The pooled sensitivity, specificity, DOR, PLR, NLR, and AUC, with a 95% confidence interval (CI), of circRNAs in the diagnosis of CRC were 0.78 (0.71–0.83), 0.73 (0.68–0.78), 9.68 (6.76–13.85), 2.92 (2.45–3.50), 0.30 (0.23–0.39), and 0.81 (0.78–0.85), respectively. Subgroup analysis showed that the upregulated circRNAs in the tissue or plasma possessed relatively higher diagnostic values for CRC than the downregulated circRNAs. There was no significant difference between the tissue-derived and non-tissue-derived circRNA subgroups.Conclusion: circRNA may be used as a diagnostic biomarker for CRC because of its relatively high diagnostic accuracy in distinguishing CRC patients from normal controls. Further prospective studies are needed to identify more representative circRNAs as diagnostic markers for CRC. |
format |
article |
author |
Ru-Dong Li Min Guan Zhe Zhou Shu-Xiao Dong Qian Liu |
author_facet |
Ru-Dong Li Min Guan Zhe Zhou Shu-Xiao Dong Qian Liu |
author_sort |
Ru-Dong Li |
title |
The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis |
title_short |
The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis |
title_full |
The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis |
title_fullStr |
The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis |
title_full_unstemmed |
The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis |
title_sort |
role of circrnas in the diagnosis of colorectal cancer: a meta-analysis |
publisher |
Frontiers Media S.A. |
publishDate |
2021 |
url |
https://doaj.org/article/211d98ba7f9a46a6be073d44b656cc44 |
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