Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis
Guozheng Yu,1,2 Wei Zhang,2,3 Linyan Zhu,1,2 Lin Xia2,4 1Department of General Surgery, Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, 2Hubei Key Laboratory of Kidney Disease Pathogenesis and Intervention, 3Department of Clinical Laboratory...
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doaj-8785cb9cea674af499b85b9c8ed3a8442020-11-25T00:10:00ZengDove Medical PressOncoTargets and Therapy1178-69302018-03-01Volume 111491149937300Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysisYu GZhang WZhu LXia LGuozheng Yu,1,2 Wei Zhang,2,3 Linyan Zhu,1,2 Lin Xia2,4 1Department of General Surgery, Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, 2Hubei Key Laboratory of Kidney Disease Pathogenesis and Intervention, 3Department of Clinical Laboratory, 4Department of Medical Oncology, Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, Huangshi, China Purpose: Focusing on the latest literature, dysregulated long non-coding RNAs (lncRNAs) have been extensively explored in breast cancer (BC) research. The purpose of this meta-analysis is to synthesize the evidence on the diagnostic performance of abnormally expressed lncRNAs for BC.Materials and methods: Relevant studies were searched in multiple electronic databases. The Quality Assessment of Diagnosis Accuracy Studies II criteria were applied to assess the quality of included studies. The bivariate meta-analysis model was applied to synthesize the diagnostic parameters using Stata 12.0 software. Publication bias was judged in terms of the Deek’s funnel plot asymmetry test.Results: We included 10 eligible studies, which comprised 835 BC patients and 725 paired controls for this meta-analysis. The pooled sensitivity, specificity, diagnostic odds ratio, likelihood ratio positive, likelihood ratio negative, and area under the curve (AUC) of upregulated lncRNA expression signature in confirming BC were 0.79 (95% CI: 0.70–0.85), 0.80 (95% CI: 0.73–0.85), 14.61 (95% CI: 10.91–19.55), 3.90 (95% CI: 3.03–5.02), 0.27 (95% CI: 0.20–0.36), and 0.86, respectively. Stratified analyses yielded a sensitivity of 0.83 (95% CI: 0.80–0.86) for serum-based analysis, which was higher than plasma-based analysis, whereas plasma-based analysis revealed a greater specificity of 0.88 (95% CI: 0.85–0.91). Moreover, lncRNA-homeotic genes (HOX) transcript antisense RNA showed a pooled specificity of 0.89 (95% CI: 0.84–0.93) and AUC of 0.86, which were superior to performances by lncRNA-metastasis-associated lung adenocarcinoma transcript-1 and -H19 in diagnosing BC. Notably, the analysis based on cancer subtypes demonstrated that lncRNA expression signature could distinguish triple-negative BC (lacks estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 expression) from non-triple-negative BC, with an AUC of 0.85.Conclusion: Upregulated lncRNAs reveal an immense potential as novel non-invasive biomarker(s) that could complement BC diagnosis. Keywords: lncRNA, breast cancer, diagnosis, meta-analysishttps://www.dovepress.com/upregulated-long-non-coding-rnas-demonstrate-promising-efficacy-for-br-peer-reviewed-article-OTTlncRNAbreast cancerdiagnosismeta-analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yu G Zhang W Zhu L Xia L |
spellingShingle |
Yu G Zhang W Zhu L Xia L Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis OncoTargets and Therapy lncRNA breast cancer diagnosis meta-analysis |
author_facet |
Yu G Zhang W Zhu L Xia L |
author_sort |
Yu G |
title |
Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis |
title_short |
Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis |
title_full |
Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis |
title_fullStr |
Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis |
title_full_unstemmed |
Upregulated long non-coding RNAs demonstrate promising efficacy for breast cancer detection: a meta-analysis |
title_sort |
upregulated long non-coding rnas demonstrate promising efficacy for breast cancer detection: a meta-analysis |
publisher |
Dove Medical Press |
series |
OncoTargets and Therapy |
issn |
1178-6930 |
publishDate |
2018-03-01 |
description |
Guozheng Yu,1,2 Wei Zhang,2,3 Linyan Zhu,1,2 Lin Xia2,4 1Department of General Surgery, Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, 2Hubei Key Laboratory of Kidney Disease Pathogenesis and Intervention, 3Department of Clinical Laboratory, 4Department of Medical Oncology, Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, Huangshi, China Purpose: Focusing on the latest literature, dysregulated long non-coding RNAs (lncRNAs) have been extensively explored in breast cancer (BC) research. The purpose of this meta-analysis is to synthesize the evidence on the diagnostic performance of abnormally expressed lncRNAs for BC.Materials and methods: Relevant studies were searched in multiple electronic databases. The Quality Assessment of Diagnosis Accuracy Studies II criteria were applied to assess the quality of included studies. The bivariate meta-analysis model was applied to synthesize the diagnostic parameters using Stata 12.0 software. Publication bias was judged in terms of the Deek’s funnel plot asymmetry test.Results: We included 10 eligible studies, which comprised 835 BC patients and 725 paired controls for this meta-analysis. The pooled sensitivity, specificity, diagnostic odds ratio, likelihood ratio positive, likelihood ratio negative, and area under the curve (AUC) of upregulated lncRNA expression signature in confirming BC were 0.79 (95% CI: 0.70–0.85), 0.80 (95% CI: 0.73–0.85), 14.61 (95% CI: 10.91–19.55), 3.90 (95% CI: 3.03–5.02), 0.27 (95% CI: 0.20–0.36), and 0.86, respectively. Stratified analyses yielded a sensitivity of 0.83 (95% CI: 0.80–0.86) for serum-based analysis, which was higher than plasma-based analysis, whereas plasma-based analysis revealed a greater specificity of 0.88 (95% CI: 0.85–0.91). Moreover, lncRNA-homeotic genes (HOX) transcript antisense RNA showed a pooled specificity of 0.89 (95% CI: 0.84–0.93) and AUC of 0.86, which were superior to performances by lncRNA-metastasis-associated lung adenocarcinoma transcript-1 and -H19 in diagnosing BC. Notably, the analysis based on cancer subtypes demonstrated that lncRNA expression signature could distinguish triple-negative BC (lacks estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 expression) from non-triple-negative BC, with an AUC of 0.85.Conclusion: Upregulated lncRNAs reveal an immense potential as novel non-invasive biomarker(s) that could complement BC diagnosis. Keywords: lncRNA, breast cancer, diagnosis, meta-analysis |
topic |
lncRNA breast cancer diagnosis meta-analysis |
url |
https://www.dovepress.com/upregulated-long-non-coding-rnas-demonstrate-promising-efficacy-for-br-peer-reviewed-article-OTT |
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