Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer.
<h4>Background</h4>To investigate the potential of serum miRNAs as biomarkers for early detection of gastric cancer (GC), a population-based study was conducted in Linqu, a high-risk area of GC in China.<h4>Methodology/principal findings</h4>All subjects were selected from tw...
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Format: | Article |
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Public Library of Science (PLoS)
2012-01-01
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Series: | PLoS ONE |
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22432036/pdf/?tool=EBI |
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author | Ming-yang Song Kai-feng Pan Hui-juan Su Lian Zhang Jun-ling Ma Ji-you Li Yasuhito Yuasa Daehee Kang Yong Sung Kim Wei-cheng You |
author_facet | Ming-yang Song Kai-feng Pan Hui-juan Su Lian Zhang Jun-ling Ma Ji-you Li Yasuhito Yuasa Daehee Kang Yong Sung Kim Wei-cheng You |
author_sort | Ming-yang Song |
collection | DOAJ |
description | <h4>Background</h4>To investigate the potential of serum miRNAs as biomarkers for early detection of gastric cancer (GC), a population-based study was conducted in Linqu, a high-risk area of GC in China.<h4>Methodology/principal findings</h4>All subjects were selected from two large cohort studies. Differential miRNAs were identified in serum pools of GC and control using TaqMan low density array, and validated in individual from 82 pairs of GC and control, and 46 pairs of dysplasia and control by real-time quantitative reverse transcription-polymerase chain reaction. The temporal trends of identified serum miRNA expression were further explored in a retrospective study on 58 GC patients who had at least one pre-GC diagnosis serum sample based on the long-term follow-up population. The miRNA profiling results demonstrated that 16 miRNAs were markedly upregulated in GC patients compared to controls. Further validation identified a panel of three serum miRNAs (miR-221, miR-744, and miR-376c) as potential biomarkers for GC detection, and receiver operating characteristic (ROC) curve-based risk assessment analysis revealed that this panel could distinguish GCs from controls with 82.4% sensitivity and 58.8% specificity. MiR-221 and miR-376c demonstrated significantly positive correlation with poor differentiation of GC, and miR-221 displayed higher level in dysplasia than in control. Furthermore, the retrospective study revealed an increasing trend of these three miRNA levels during GC development (P for trend<0.05), and this panel could classify serum samples collected up to 5 years ahead of clinical GC diagnosis with 79.3% overall accuracy.<h4>Conclusions/significance</h4>These data suggest that serum miR-221, miR-376c and miR-744 have strong potential as novel non-invasive biomarkers for early detection of GC. |
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language | English |
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spelling | doaj.art-1acedf37d5794d9f873919ffa3f99ee82022-12-21T20:31:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0173e3360810.1371/journal.pone.0033608Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer.Ming-yang SongKai-feng PanHui-juan SuLian ZhangJun-ling MaJi-you LiYasuhito YuasaDaehee KangYong Sung KimWei-cheng You<h4>Background</h4>To investigate the potential of serum miRNAs as biomarkers for early detection of gastric cancer (GC), a population-based study was conducted in Linqu, a high-risk area of GC in China.<h4>Methodology/principal findings</h4>All subjects were selected from two large cohort studies. Differential miRNAs were identified in serum pools of GC and control using TaqMan low density array, and validated in individual from 82 pairs of GC and control, and 46 pairs of dysplasia and control by real-time quantitative reverse transcription-polymerase chain reaction. The temporal trends of identified serum miRNA expression were further explored in a retrospective study on 58 GC patients who had at least one pre-GC diagnosis serum sample based on the long-term follow-up population. The miRNA profiling results demonstrated that 16 miRNAs were markedly upregulated in GC patients compared to controls. Further validation identified a panel of three serum miRNAs (miR-221, miR-744, and miR-376c) as potential biomarkers for GC detection, and receiver operating characteristic (ROC) curve-based risk assessment analysis revealed that this panel could distinguish GCs from controls with 82.4% sensitivity and 58.8% specificity. MiR-221 and miR-376c demonstrated significantly positive correlation with poor differentiation of GC, and miR-221 displayed higher level in dysplasia than in control. Furthermore, the retrospective study revealed an increasing trend of these three miRNA levels during GC development (P for trend<0.05), and this panel could classify serum samples collected up to 5 years ahead of clinical GC diagnosis with 79.3% overall accuracy.<h4>Conclusions/significance</h4>These data suggest that serum miR-221, miR-376c and miR-744 have strong potential as novel non-invasive biomarkers for early detection of GC.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22432036/pdf/?tool=EBI |
spellingShingle | Ming-yang Song Kai-feng Pan Hui-juan Su Lian Zhang Jun-ling Ma Ji-you Li Yasuhito Yuasa Daehee Kang Yong Sung Kim Wei-cheng You Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. PLoS ONE |
title | Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. |
title_full | Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. |
title_fullStr | Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. |
title_full_unstemmed | Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. |
title_short | Identification of serum microRNAs as novel non-invasive biomarkers for early detection of gastric cancer. |
title_sort | identification of serum micrornas as novel non invasive biomarkers for early detection of gastric cancer |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22432036/pdf/?tool=EBI |
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