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

Author:

Shen Jun,Liu Ziling,Todd Nevins W,Zhang Howard,Liao Jipei,Yu Lei,Guarnera Maria A,Li Ruiyun,Cai Ling,Zhan Min,Jiang Feng

Abstract

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.

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

Reference52 articles.

1. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, Thun MJ: Cancer statistics, 2008. CA Cancer J Clin. 2008, 58: 71-96. 10.3322/CA.2007.0010.

2. Flehinger BJ, Melamed MR, Zaman MB, Heelan RT, Perchick WB, Martini N: Early lung cancer detection: results of the initial (prevalence) radiologic and cytologic screening in the Johns Hopkins study. Am Rev Respir Dis. 1984, 130: 549-554.

3. Hirsch FR, Franklin WA, Gazdar AF, Bunn PA: Early detection of lung cancer: clinical perspectives of recent advances in biology and radiology. Clin Cancer Res. 2001, 7: 5-22.

4. Minna JD, Roth JA, Gazdar AF: Focus on lung cancer. Cancer Cell. 2002, 1: 49-52. 10.1016/S1535-6108(02)00027-2.

5. Henschke CI, Boffetta P, Gorlova O, Yip R, Delancey JO, Foy M: Assessment of lung-cancer mortality reduction from CT Screening. Lung Cancer. 2011, 71: 328-332. 10.1016/j.lungcan.2010.10.025.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3