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Identification of serum miRNAs by nano-quantum dots microarray as diagnostic biomarkers for early detection of non-small cell lung cancer

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Tumor Biology

Abstract

Circulating microRNAs (miRNAs) are potential noninvasive biomarkers for cancer detection. We used preoperative serum samples from non-small cell lung cancer (NSCLC) patients and healthy controls to investigate whether serum levels of candidate miRNAs could be used as diagnostic biomarkers in patients with resectable NSCLC and whether they were associated with clinicopathologic characteristics. We initially detected expression of 12 miRNAs using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in preoperative serum samples of 94 NSCLC patients and 58 healthy controls. We further validated our results using the fluorescence quantum dots liquid bead array for differentially expressed miRNAs in serum samples of 70 NSCLC patients and 54 healthy controls. Receiver operating characteristic (ROC) analysis was performed to select the best diagnostic miRNA cutoff value. A predictive model of miRNAs for NSCLC was derived by multivariate logistic regression. We found that five serum miRNAs (miR-16-5p, miR-17b-5p, miR-19-3p, miR-20a-5p, and miR-92-3p) were significantly downregulated in NSCLC, while miR-15b-5p was significantly upregulated (p < 0.05). Multivariate logistic regression analysis revealed that miR-15b-5p, miR-16-5p, and miR-20a-5p expression were independent diagnostic factors for the identification of patients with NSCLC after adjustment for patient’s age and sex. In addition, the expression of serum miR-106-5p was higher in stage I than in stages IIa–IIIb, and no significant association was observed between expression of miRNAs and other variables including pathological type, tumor size, and lymph nodes status. Six serum miRNAs could potentially serve as noninvasive diagnostic biomarkers for resectable NSCLC. The predictive model combining miR-15b-5p, miR-16-5p, and miR-20a-5p was the best diagnostic approach.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant No. 81473469).

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    Authors and Affiliations

    1. Department of Respiration, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China

      Lihong Fan & Changhui Wang

    2. Department of Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Road, Shanghai, 200433, China

      Huiwei Qi

    3. School of information management and engineering, Shanghai University of Finance and Economics, Shanghai, China

      Junliang Teng

    4. Central laboratory, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

      Bo Su

    5. Department of Oncology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China

      Hao Chen

    6. Department of Respiration, Shanghai Tenth People’s Hospital, Nanjing medical University, Jiangsu, China

      Qing Xia

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    Correspondence to Huiwei Qi.

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    The study protocols were approved by the Ethics Committee of Shanghai Pulmonary Hospital, and written informed consent was obtained from each patient.

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    This work was supported by National Natural Science Foundation of China (Grant No. 81473469).

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    Lihong Fan and Huiwei Qi contributed equally to this work.

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    Fan, L., Qi, H., Teng, J. et al. Identification of serum miRNAs by nano-quantum dots microarray as diagnostic biomarkers for early detection of non-small cell lung cancer. Tumor Biol. 37, 7777–7784 (2016). https://doi.org/10.1007/s13277-015-4608-3

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