Literature DB >> 27499953

Role of plasma MicroRNAs in the early diagnosis of non-small-cell lung cancers: a case-control study.

Xin Wang1, Xiuyi Zhi2, Yi Zhang2, Guangyu An3, Guosheng Feng3.   

Abstract

BACKGROUND: Lung cancer is a leading cause of cancer death worldwide. Early diagnosis is essential for improvements of prognosis and survival of the patients. Altered expressions in many cancer types including lung cancer and stable existence in plasma make microRNAs (miRNAs) a group of potentially useful biomarkers for clinical assessments of patients with lung cancer. In this study, we evaluate the potential values of miRNAs as plasma biomarkers for early diagnosis in non-small-cell lung cancers (NSCLC) by comparing with other typical plasma biomarkers.
METHODS: We analyzed the clinical and laboratory characteristics of 59 early-staged NSCLC (I-IIIA) patients and non-cancer controls by 1:1 matching age and gender from January 2012 to February 2014 in Xuanwu Hospital, Beijing, China. Peripheral blood samples from patients and controls before surgery were collected, and plasma was separated. Expression of ten miRNAs in the plasma of the patients and controls was detected by quantitative real-time polymerase chain reaction. Other typical markers, such as SCC, CEA, and CYFRA21-1 in plasma were also detected. The early diagnostic ability of miRNAs and other markers were evaluated by receiver-operating-characteristic (ROC) curve analysis. The sensitivity, specificity, and area under the curve were calculated for the cut-off value.
RESULTS: Plasma CYFRA21-1, miRNA-486 and miRNA-210 levels were significantly different in patients with NSCLC than those in controls (CYFRA21-1: 8.896±7.681 vs. 5.892±6.028, P=0.020; miR-486: 2.778±0.778 vs. 1.746±0.892, P<0.001; miR-210: 4.836±3.374 vs. 2.829±2.503, P<0.001). Area under ROC curve of CYFRA21-1, miR-486 and miR-210 were 0.624 (sensitivity: 0.576, specificity: 0.797), 0.848 (sensitivity: 0.831, specificity: 0.780) and 0.751 (sensitivity: 0.746, specificity: 0.746), respectively. The optimal cut-off value of CYFRA21-1, miRNA-486 and miRNA-210 were 6.595, 1.988 and 3.341, respectively to discriminate patients from controls. Plasma markers combined diagnosis ability had the highest sensitivity: 0.983, but the specificity was low. miR-486, miR-210 and CYFRA21-1 combined diagnosis ability was the highest, and the AUC was 0.924 (sensitivity: 0.847; specificity: 0.728).
CONCLUSIONS: The results suggest that miRNA-486 and miR-210 could be potential blood-based biomarkers for early diagnosis of NSCLC. miRNAs and other lab indexes may be combined to early diagnose NSCLC, which showed better ability of screening patients.

Entities:  

Keywords:  Non-small-cell lung cancers (NSCLC); early diagnosis; microRNAs (miRNAs)

Year:  2016        PMID: 27499953      PMCID: PMC4958809          DOI: 10.21037/jtd.2016.06.21

Source DB:  PubMed          Journal:  J Thorac Dis        ISSN: 2072-1439            Impact factor:   2.895


  41 in total

1.  Correlations of microRNA:microRNA expression patterns reveal insights into microRNA clusters and global microRNA expression patterns.

Authors:  S G Chaulk; H A Ebhardt; R P Fahlman
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2.  MicroRNAs level as an initial screening method for early-stage lung cancer: a bivariate diagnostic random-effects meta-analysis.

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3.  Prognostic and predictive value of CEA and CYFRA 21-1 levels in advanced non-small cell lung cancer patients treated with gefitinib or erlotinib.

Authors:  Minkyu Jung; Se Hyun Kim; Young Joo Lee; Soojung Hong; Young Ae Kang; Se Kyu Kim; Joon Chang; Sun Young Rha; Joo Hang Kim; Dae Joon Kim; Byoung Chul Cho
Journal:  Exp Ther Med       Date:  2011-05-12       Impact factor: 2.447

4.  Clinical utility of haptoglobin in combination with CEA, NSE and CYFRA21-1 for diagnosis of lung cancer.

Authors:  Bing Wang; Yu-Jie He; Ying-Xing Tian; Rui-Ning Yang; Yue-Rong Zhu; Hong Qiu
Journal:  Asian Pac J Cancer Prev       Date:  2014

5.  Serum microRNA signatures identified in a genome-wide serum microRNA expression profiling predict survival of non-small-cell lung cancer.

Authors:  Zhibin Hu; Xi Chen; Yang Zhao; Tian Tian; Guangfu Jin; Yongqian Shu; Yijiang Chen; Lin Xu; Ke Zen; Chenyu Zhang; Hongbing Shen
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6.  The IASLC Lung Cancer Staging Project: proposals for the revision of the TNM stage groupings in the forthcoming (seventh) edition of the TNM Classification of malignant tumours.

Authors:  Peter Goldstraw; John Crowley; Kari Chansky; Dorothy J Giroux; Patti A Groome; Ramon Rami-Porta; Pieter E Postmus; Valerie Rusch; Leslie Sobin
Journal:  J Thorac Oncol       Date:  2007-08       Impact factor: 15.609

7.  MicroRNA profiling in lung cancer reveals new molecular markers for diagnosis.

Authors:  Charalambos C Solomides; Barry J Evans; Jean-Marc Navenot; Rajanikanth Vadigepalli; Stephen C Peiper; Zi-xuan Wang
Journal:  Acta Cytol       Date:  2012-11-24       Impact factor: 2.319

8.  Insulin growth factor signaling is regulated by microRNA-486, an underexpressed microRNA in lung cancer.

Authors:  Yong Peng; Yuntao Dai; Charles Hitchcock; Xiaojuan Yang; Edmund S Kassis; Lunxu Liu; Zhenghua Luo; Hui-Lung Sun; Ri Cui; Huijun Wei; Taewan Kim; Tae Jin Lee; Young-Jun Jeon; Gerard J Nuovo; Stefano Volinia; Qianchuan He; Jianhua Yu; Patrick Nana-Sinkam; Carlo M Croce
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-26       Impact factor: 11.205

9.  Prognostic significance of serum microRNA-210 levels in nonsmall-cell lung cancer.

Authors:  Zhi-Hong Li; Hong Zhang; Zhi-Guang Yang; Guo-Qiang Wen; You-Bing Cui; Guo-Guang Shao
Journal:  J Int Med Res       Date:  2013-09-24       Impact factor: 1.671

10.  Diagnostic and prognostic value of the new tumour marker CYFRA 21-1 in patients with squamous cell lung cancer.

Authors:  J Niklinski; M Furman; E Chyczewska; L Chyczewski; F Rogowski; J Laudanski
Journal:  Eur Respir J       Date:  1995-02       Impact factor: 16.671

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  11 in total

1.  Changes in plasma miR-9, miR-16, miR-205 and miR-486 levels after non-small cell lung cancer resection.

Authors:  Maria Sromek; Maciej Glogowski; Magdalena Chechlinska; Mariusz Kulinczak; Lukasz Szafron; Klara Zakrzewska; Joanna Owczarek; Piotr Wisniewski; Robert Wlodarczyk; Lukasz Talarek; Maciej Turski; Jan Konrad Siwicki
Journal:  Cell Oncol (Dordr)       Date:  2017-06-20       Impact factor: 6.730

Review 2.  Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Common Solid Tumors: Focus on Lung, Breast, Prostate Cancers, and Osteosarcoma.

Authors:  Michela Bottani; Giuseppe Banfi; Giovanni Lombardi
Journal:  J Clin Med       Date:  2019-10-11       Impact factor: 4.241

3.  Diagnostic role of Wnt pathway gene promoter methylation in non small cell lung cancer.

Authors:  Shunlin Liu; Xiaoying Chen; Ruhua Chen; Jinzhi Wang; Guoliang Zhu; Jianzhong Jiang; Hongwei Wang; Shiwei Duan; Jianan Huang
Journal:  Oncotarget       Date:  2017-05-30

4.  MiR-486 as an effective biomarker in cancer diagnosis and prognosis: a systematic review and meta-analysis.

Authors:  Min Jiang; Xuelian Li; Xiaowei Quan; Xianglin Yang; Chang Zheng; Xia Hao; Ruoyi Qu; Baosen Zhou
Journal:  Oncotarget       Date:  2018-01-12

5.  The clinical use of circulating microRNAs as non-invasive diagnostic biomarkers for lung cancers.

Authors:  Yanlong Yang; Zaoxiu Hu; Yongchun Zhou; Guangqiang Zhao; Yujie Lei; Guangjian Li; Shuai Chen; Kai Chen; Zhenghai Shen; Xiao Chen; Peilin Dai; Yunchao Huang
Journal:  Oncotarget       Date:  2017-10-04

6.  Clinically Correlated MicroRNAs in the Diagnosis of Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.

Authors:  Min Jiang; Xuelian Li; Xiaowei Quan; Xiaoying Li; Baosen Zhou
Journal:  Biomed Res Int       Date:  2018-06-28       Impact factor: 3.411

7.  High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer.

Authors:  Minhan Yi; Zexi Liao; Langmei Deng; Li Xu; Yun Tan; Kun Liu; Ziliang Chen; Yuan Zhang
Journal:  Ann Med       Date:  2021-12       Impact factor: 4.709

Review 8.  Blood Circulating Non-Coding RNAs for the Clinical Management of Triple-Negative Breast Cancer.

Authors:  Tomasz Powrózek; Michael Ochieng Otieno
Journal:  Cancers (Basel)       Date:  2022-02-04       Impact factor: 6.639

9.  MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer.

Authors:  Xiao-Liang Xing; Zhi-Yong Yao; Ti Zhang; Ning Zhu; Yuan-Wu Liu; Jing Peng
Journal:  Biomed Res Int       Date:  2020-09-09       Impact factor: 3.411

10.  miR-486 as an unfavorable prognostic biomarker for patients with non-small cell lung cancer.

Authors:  Zhao-Jia Gao; Wei-Dong Yuan; Jun-Qiang Yuan; Kai Yuan; Yong Wang
Journal:  Transl Cancer Res       Date:  2020-01       Impact factor: 1.241

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