A novel microRNA miR-4433a-3p as a potential diagnostic biomarker for lung adenocarcinoma

Abstract

Background: Lung adenocarcinoma is one of the leading causes of cancer-related deaths because of the lack of early specific clinical indicators. MicroRNAs (miRNAs) have become the focus in lung cancer diagnosis. Further studies are required to explore miRNA expression in the serum of lung adenocarcinoma patients and their correlation with therapy and analyse specific messenger RNA targets to improve the specificity and sensitivity of early diagnosis.

Methods: The Toray 3D-Gene miRNA array was used to compare the expression levels of various miRNAs in the sera of patients with lung adenocarcinoma and healthy volunteers. Highly expressed miRNAs were selected for further analysis. To verify the screening results, serum and pleural fluid samples were analysed using qRT-PCR. Serum levels of the miRNAs and their correlation with the clinical information of patients with lung adenocarcinoma were analysed. The functions of miRNAs were further analysed using the Kyoto Encyclopedia of Gene and Genomes and Gene Ontology databases.

Results: Microarray analysis identified 60 and 50 miRNAs with upregulated and downregulated expressions, respectively, in the serum of patients with lung adenocarcinoma compared to those in healthy individuals. Using qRT-qPCR to detection of miRNAs expression in the serum or pleural effusion of patients with early and advanced lung adenocarcinoma, we found that miR-4433a-3p could be used as a diagnostic marker and therapeutic evaluation indicator for lung adenocarcinoma. Serum of miR-4433a-3p levels significantly correlated with the clinical stage. miR-4433a-3p may be more suitable than other tumour markers for the early diagnosis and evaluation of therapeutic effects in lung adenocarcinoma. miR-4433a-3p may affect tumour growth and metastasis by acting on target genes (PIK3CD, UBE2J2, ICMT, PRDM16 and others) and regulating tumour-related signalling pathways (MAPK signal pathway, Ras signalling pathway and others).

Conclusion: miR-4433a-3p may serve as a biomarker for the early diagnosis of lung adenocarcinoma and monitoring of therapeutic effects.

Keywords: Biomarker; Early diagnosis; Lung adenocarcinoma; Treatment; microRNAs.

Fig. 1

The flow chart of the study design. LUAD, lung adenocarcinoma; miRNA, microRNA; BPN, Benign pulmonary nodules; MPN, Malignant pulmonary nodules; BPE, Benign pleural effusion; MPE, Malignant pleural effusion; RT–qPCR, quantitative reverse transcription–polymerase chain reaction; ROC, receiver operating characteristic.

Fig. 2

Identification of tumour-associated miRNAs in the serum of healthy volunteers and patients with lung adenocarcinoma. (A–B) Heatmap of miRNA microarray expression between LUAD group and healthy control group. 60 upregulated and 50 downregulated microRNAs were identified. (C) Multiple micrornas with change values greater than 10 and p value less than 0.05 were screened based on differential expression gene analysis.

Fig. 3

Verification of microRNA expression in the serum of lung adenocarcinoma patients using quantitative qRT-PCR analysis. (A) The expression of miR-6721-5p in serum was measured by qRT-PCR. (B) The expression of miR-10527-5p in serum was measured by qRT-PCR. (C) The expression of miR-4433a-3p in serum was measured by qRT-PCR. (D) The expression of miR-3184-3p in serum was measured by qRT-PCR. (E) The expression of miR-181a-2-3p in serum was measured by qRT-PCR. ***, P < 0.001.

Fig. 4

Diagnostic values of microRNA in the serum of lung adenocarcinoma patients using quantitative RT-PCR analysis. (A) The ROC curve analysis of miR-6721-5p in serum produced an AUC value of 0.8002. (B) The ROC curve analysis of miR-10527-5p in serum produced an AUC value of 0.7469. (C) The ROC curve analysis of miR-4433a-3p in serum produced an AUC value of 0.7824. (D) The ROC curve analysis of miR-3184-3p in serum produced an AUC value of 0.7785. (E) The ROC curve analysis of miR-181a-2-3p in serum produced an AUC value of 0.7384.

Fig. 5

Verification of microRNA expression in the pleural effusion of lung adenocarcinoma patients using quantitative qRT-PCR analysis. (A) The expression of miR-6721-5p in pleural effusion was measured by qRT-PCR. (B) The expression of miR-10527-5p in pleural effusion was measured by qRT-PCR. (C) The expression of miR-4433a-3p in pleural effusion was measured by qRT-PCR. (D) The expression of miR-3184-3p in pleural effusion was measured by qRT-PCR. (E) The expression of miR-181a-2-3p in pleural effusion was measured by qRT-PCR. **, P < 0.01; ***,P < 0.001.

Fig. 6

Diagnostic values of microRNA in the pleural effusion of lung adenocarcinoma patients using quantitative qRT-PCR analysis. (A) The ROC curve analysis of miR-6721-5p in pleural effusion produced an AUC value of 0.8125. (B) The ROC curve analysis of miR-10527-5p in pleural effusion produced an AUC value of 0.8889. (C) The ROC curve analysis of miR-4433a-3p in pleural effusion produced an AUC value of 0.9375. (D) The ROC curve analysis of miR-3184-3p in pleural effusion produced an AUC value of 0.8681. (E) The ROC curve analysis of miR-181a-2-3p in pleural effusion produced an AUC value of 0.9306.

Fig. 7

miR-4433a-3p can be used for the diagnosis of early-stage lung cancer. (A) The expression of miR-4433a-3p in serum was measured by qRT-PCR. (B) The ROC curve analysis of miR-4433a-3p in serum produced an AUC value of 0.9750.

Fig. 8

Related miRNAs as indicators for evaluating the efficacy of surgical treatment for early lung cancer. (A) The expression of miR-6721-5p in serum was measured by qRT-PCR. (B) The expression of miR-10527-5p in serum was measured by qRT-PCR. (C) The expression of miR-4433a-3p in serum was measured by qRT-PCR. (D) The expression of miR-3184-3p in serum was measured by qRT-PCR. (E) The expression of miR-181a-2-3p in serum was measured by qRT-PCR. *P < 0.05; **P < 0.01.

Fig. 9

The microRNA–mRNA regulatory network. Red represents the upregulated expression of microRNA; Green represents the downregulated expression of microRNA.

Fig. 10

The selected microRNAs and their targets were analysed by bioinformatics. (A) GO enrichment analysis of related cell components. (B) GO enrichment analysis of related biological processes. (C) GO enrichment analysis of related molecular functions. (D) KEGG analysis of correlated signal pathways.