Oncotarget

Research Papers:

A plasma miRNA signature for lung cancer early detection

Qixin Leng, Yanli Lin, Fangran Jiang, Cheng-Ju Lee, Min Zhan, HongBin Fang, Yue Wang and Feng Jiang _

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Oncotarget. 2017; 8:111902-111911. https://doi.org/10.18632/oncotarget.22950

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Abstract

Qixin Leng1,*, Yanli Lin1,*, Fangran Jiang2, Cheng-Ju Lee2, Min Zhan3, HongBin Fang4, Yue Wang5 and Feng Jiang1

1Department of Pathology, University of Maryland School of Medicine, Baltimore, MD 21201, USA

2Departments of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA

3Departments of Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA

4Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Washington, DC 20057, USA

5Department of Mathematics & Statistics, University of Maryland, Baltimore County, Baltimore, MD 21250, USA

*The authors have contributed equally to this work

Correspondence to:

Feng Jiang, email: fjiang@som.umaryland.edu

Keywords: diagnosis; lung cancer; plasma; microRNA; biomarkers

Received: November 08, 2017     Accepted: November 19, 2017     Published: December 05, 2017

ABSTRACT

The early detection of lung cancer continues to be a major clinical challenge. Using whole-transcriptome next-generation sequencing to analyze lung tumor and the matched noncancerous tissues, we previously identified 54 lung cancer-associated microRNAs (miRNAs). The objective of this study was to investigate whether the miRNAs could be used as plasma biomarkers for lung cancer. We determined expressions of the lung tumor-miRNAs in plasma of a development cohort of 180 subjects by using reverse transcription PCR to develop biomarkers. The development cohort included 92 lung cancer patients and 88 cancer-free smokers. We validated the biomarkers in a validation cohort of 64 individuals comprising 34 lung cancer patients and 30 cancer-free smokers. Of the 54 miRNAs, 30 displayed a significant different expression level in plasma of the lung cancer patients vs. cancer-free controls (all P < 0.05). A plasma miRNA signature (miRs-126, 145, 210, and 205-5p) with the best prediction was developed, producing 91.5% sensitivity and 96.2% specificity for lung cancer detection. Diagnostic performance of the plasma miRNA signature had no association with stage and histological type of lung tumor, and patients’ age, sex, and ethnicity (all p > 0.05). The plasma miRNA signature was reproducibly confirmed in the validation cohort. The plasma miRNA signature may provide a blood-based assay for diagnosing lung cancer at the early stage, and thereby reduce the associated mortality and cost.


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