J Cancer 2017; 8(1):48-56. doi:10.7150/jca.16644

Research Paper

Identification of A Panel of Serum microRNAs as Biomarkers for Early Detection of Lung Adenocarcinoma

Shaogang Lv*, Jian Xue*, Chuanyong Wu, Lin Wang, Jing Wu, Shujun Xu, Xiaohui Liang, Jiatao Lou

Department of Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China.
* These authors contributed equally to this work.

Abstract

Introduction: Since currently no sensitive and specific biomarkers for early detection of lung adenocarcinoma (AD) exist and the majority of AD patients are diagnosed at late stages of disease, the development of effective screening tests for early-stage lung AD is urgently needed. Serum microRNAs (miRNAs) have been documented as novel noninvasive biomarkers in tumor diagnosis; thus, we studied the profile of serum miRNA in AD patients in order to identify the differentially expressed miRNAs as potential biomarkers for early detection of AD.

Patients and Methods: Serum samples were collected from 180 AD patients and 180 age- and sex-matched healthy controls. Serum miRNA profiling was performed by low-density array (LDA) using RNA extracted from blood samples of 20 patients and 20 controls. To validate the selected miRNAs, a stem-loop based RT-qPCR assay was used and serum samples from 160 patients and 160 controls were examined.

Results: Profiling data showed 11 differentially expressed miRNAs in the serum samples from AD patients compared with the controls. Among them, 6 selected miRNAs in AD patients, including miR-103, miR-146a, miR-151, miR-21, miR-221, miR-222, and miR-223, were validated by RT-qPCR. In particular, the top three, miR-146a, miR-222, and miR-223, were confirmed to be significantly expressed in stage I/II AD patients compared with healthy controls.

Conclusion: A panel of miRNAs with miR-146a, miR-222 and miR-223 could be used as potential noninvasive biomarkers for early detection of AD.

Keywords: Screening - Low-density array - Receiver operating characteristic (ROC) curve - Area under the ROC curve (AUC) - Logistic regression.

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How to cite this article:
Lv S, Xue J, Wu C, Wang L, Wu J, Xu S, Liang X, Lou J. Identification of A Panel of Serum microRNAs as Biomarkers for Early Detection of Lung Adenocarcinoma. J Cancer 2017; 8(1):48-56. doi:10.7150/jca.16644. Available from http://www.jcancer.org/v08p0048.htm