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Open Access Highly Accessed Research article

Diagnosis of lung cancer in individuals with solitary pulmonary nodules by plasma microRNA biomarkers

Jun Shen1, Ziling Liu2, Nevins W Todd3, Howard Zhang3, Jipei Liao1, Lei Yu1, Maria A Guarnera1, Ruiyun Li4, Ling Cai5, Min Zhan5 and Feng Jiang1*

Author Affiliations

1 Department of Pathology, University of Maryland School of Medicine, 10 S. Pine St. Baltimore, MD 21201, USA

2 Department of Oncology, The First Hospital of Jilin University, 1 Xinmin St. Changchun, Jilin 130021, China

3 Department of Medicine, University of Maryland School of Medicine, 22 S. Greene St. Baltimore, MD 21201, USA

4 Department of Surgery, University of Maryland School of Medicine, 22 S. Greene St. Baltimore, MD 21201, USA

5 Department of Epidemiology & Public Health, University of Maryland School of Medicine, 660 W. Redwood St. Baltimore, MD 21201, USA

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BMC Cancer 2011, 11:374  doi:10.1186/1471-2407-11-374

Published: 24 August 2011

Abstract

Background

Making a definitive preoperative diagnosis of solitary pulmonary nodules (SPNs) found by CT has been a clinical challenge. We previously demonstrated that microRNAs (miRNAs) could be used as biomarkers for lung cancer diagnosis. Here we investigate whether plasma microRNAs are useful in identifying lung cancer among individuals with CT-detected SPNs.

Methods

By using quantitative reverse transcriptase PCR analysis, we first determine plasma expressions of five miRNAs in a training set of 32 patients with malignant SPNs, 33 subjects with benign SPNs, and 29 healthy smokers to define a panel of miRNAs that has high diagnostic efficiency for lung cancer. We then validate the miRNA panel in a testing set of 76 patients with malignant SPNs and 80 patients with benign SPNs.

Results

In the training set, miR-21 and miR-210 display higher plasma expression levels, whereas miR-486-5p has lower expression level in patients with malignant SPNs, as compared to subjects with benign SPNs and healthy controls (all P ≤ 0.001). A logistic regression model with the best prediction was built on the basis of miR-21, miR-210, and miR-486-5p. The three miRNAs used in combination produced the area under receiver operating characteristic curve at 0.86 in distinguishing lung tumors from benign SPNs with 75.00% sensitivity and 84.95% specificity. Validation of the miRNA panel in the testing set confirms their diagnostic value that yields significant improvement over any single one.

Conclusions

The plasma miRNAs provide potential circulating biomarkers for noninvasively diagnosing lung cancer among individuals with SPNs, and could be further evaluated in clinical trials.