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

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.

miR-16 mimics inhibit TGF-β1-induced epithelial-to-mesenchymal transition via activation of autophagy in non-small cell lung carcinoma cells

“…Abnormalities in miR-16 levels have been reported in various types of cancers, suggesting that miR-16 is involved in tumor formation and progression. The miRNA microarray analysis of lung cancer and adjacent normal lung tissues showed that miR-16 was downregulated in lung cancer tissues (16)(17)(18). miR-16 plays a different role in the proliferation of different types of tumor cells by regulating a variety of mRNA target genes.…”

“…miR-16 plays important roles in regulating the development of organisms and cell self-renewal, differentiation and many other physiological activities. The miRNA microarray analysis of lung cancer and adjacent normal lung tissues showed the miR-16 is downregulated in lung cancer tissues (16)(17)(18). miR-16 was found to be downregulated in lung squamous cell carcinomas and adenocarcinomas, which was correlated with the expression of cyclin D1 (19).…”

Liquid biopsy - emergence of a new era in personalized cancer care

“…Fan and coworkers found five serum miRNAs (miR-16-5p, miR-17b-5p, miR-19-3p, miR-20a-5p, and miR-92-3p) that were significantly downregulated while miR-15b-5p was significantly upregulated in NSCLC [41]. Treatment procedures also affect the levels of circulating miRNA.…”

Circulating Plasma MicroRNAs As Diagnostic Markers for NSCLC

“…Since circulating miRNAs were first identified in human plasma in 2008, a great many of studies have been aiming at identifying a reliable diagnostic tool by investigating the differential expression of circulating miRNAs between NSCLC patients and healthy controls or patients harboring benign tumors. For instance, Lihong Fan et al have demonstrated that a predictive model combining serum miR-15b-5p, miR-16-5p, miR-20a-5p can be used to discriminate the early stage of NSCLC cases from healthy subjects (Fan et al, 2015). Reassuringly, the fact that this study applied two different methods (RT-qPCR and Nano-quantum dots microarray) to identify the same differential expression of serum miRNAs, which may have improved the sensitivity and reproducibility of the results.…”