Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC

Background/Aims: Circulating long non coding RNAs (lncRNAs) have emerged recently as major players in tumor biology and may be used for cancer diagnosis, prognosis, and as potential therapeutic targets. We explored circulating lncRNA as a predictor for the tumorigenesis of non-small-cell lung cancer...

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Main Authors: Qingfeng Tang, Zhenhua Ni, Zhuoan Cheng, Jianhua Xu, Hui Yu, Peihao Yin
Format: Article
Language:English
Published: Cell Physiol Biochem Press GmbH & Co KG 2015-09-01
Series:Cellular Physiology and Biochemistry
Subjects:
Online Access:http://www.karger.com/Article/FullText/430226
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spelling doaj-76c4685287814ab89862a079c16451402020-11-24T22:09:34ZengCell Physiol Biochem Press GmbH & Co KGCellular Physiology and Biochemistry1015-89871421-97782015-09-013731002100910.1159/000430226430226Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLCQingfeng TangZhenhua NiZhuoan ChengJianhua XuHui YuPeihao YinBackground/Aims: Circulating long non coding RNAs (lncRNAs) have emerged recently as major players in tumor biology and may be used for cancer diagnosis, prognosis, and as potential therapeutic targets. We explored circulating lncRNA as a predictor for the tumorigenesis of non-small-cell lung cancer (NSCLC). Methods: In this study, we applied a lncRNA microarray to screen for a potential biomarker for NSCLC, utilizing RT-PCR (ABI 7900HT). A multi-stage validation and risk score formula detection analysis was used. Results: We discovered that three lncRNAs (RP11-397D12.4, AC007403.1, and ERICH1-AS1) were up regulated in NSCLC, compared with cancer-free controls, with the merged area under the curve in the training and validation sets of 0.986 and 0.861. Furthermore, the positive predictive value and negative predictive value of the three merged factors were 0.72 and 0.87. We confirmed stable detection of the three lncRNAs by three cycles of freezing and thawing. Conclusions: RP11-397D12.4, AC007403.1, and ERICH1-AS1 may be potential biomarkers for predicting the tumorigenesis of NSCLC in the future.http://www.karger.com/Article/FullText/430226CirculationROC curveRisk score analysisNSCLC
collection DOAJ
language English
format Article
sources DOAJ
author Qingfeng Tang
Zhenhua Ni
Zhuoan Cheng
Jianhua Xu
Hui Yu
Peihao Yin
spellingShingle Qingfeng Tang
Zhenhua Ni
Zhuoan Cheng
Jianhua Xu
Hui Yu
Peihao Yin
Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC
Cellular Physiology and Biochemistry
Circulation
ROC curve
Risk score analysis
NSCLC
author_facet Qingfeng Tang
Zhenhua Ni
Zhuoan Cheng
Jianhua Xu
Hui Yu
Peihao Yin
author_sort Qingfeng Tang
title Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC
title_short Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC
title_full Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC
title_fullStr Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC
title_full_unstemmed Three Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting NSCLC
title_sort three circulating long non-coding rnas act as biomarkers for predicting nsclc
publisher Cell Physiol Biochem Press GmbH & Co KG
series Cellular Physiology and Biochemistry
issn 1015-8987
1421-9778
publishDate 2015-09-01
description Background/Aims: Circulating long non coding RNAs (lncRNAs) have emerged recently as major players in tumor biology and may be used for cancer diagnosis, prognosis, and as potential therapeutic targets. We explored circulating lncRNA as a predictor for the tumorigenesis of non-small-cell lung cancer (NSCLC). Methods: In this study, we applied a lncRNA microarray to screen for a potential biomarker for NSCLC, utilizing RT-PCR (ABI 7900HT). A multi-stage validation and risk score formula detection analysis was used. Results: We discovered that three lncRNAs (RP11-397D12.4, AC007403.1, and ERICH1-AS1) were up regulated in NSCLC, compared with cancer-free controls, with the merged area under the curve in the training and validation sets of 0.986 and 0.861. Furthermore, the positive predictive value and negative predictive value of the three merged factors were 0.72 and 0.87. We confirmed stable detection of the three lncRNAs by three cycles of freezing and thawing. Conclusions: RP11-397D12.4, AC007403.1, and ERICH1-AS1 may be potential biomarkers for predicting the tumorigenesis of NSCLC in the future.
topic Circulation
ROC curve
Risk score analysis
NSCLC
url http://www.karger.com/Article/FullText/430226
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