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01.12.2019 | Research article | Ausgabe 1/2019 Open Access

BMC Cancer 1/2019

Genome-wide study of salivary microRNAs as potential noninvasive biomarkers for detection of nasopharyngeal carcinoma

Zeitschrift:
BMC Cancer > Ausgabe 1/2019
Autoren:
Lirong Wu, Kexiao Zheng, Cheng Yan, Xuan Pan, Yatian Liu, Juying Liu, Feijiang Wang, Wenjie Guo, Xia He, Jiong Li, Ye Shen
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12885-019-6037-y) contains supplementary material, which is available to authorized users.
Lirong Wu and Kexiao Zheng contributed equally to this work.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

Background

Recent studies reported that blood-based microRNAs (miRNAs) could detect cancers and predict prognosis have opened a new field of utilizing circulating miRNAs as cancer biomarkers. In this pilot study, we conducted for the first time, to our knowledge, the evaluation of the applicability of salivary miRNAs as novel biomarkers for nasopharyngeal carcinoma (NPC) detection.

Methods

Microarray miRNA expression profiling was performed on saliva samples from 22 newly diagnosed NPC patients and 25 healthy controls, and 12 significantly down-regulated miRNAs were selected for quantitative real-time-PCR (qRT-PCR) validation and further analysis. Their target genes enriched by gene ontology and pathway analysis were used to construct regulatory and interaction networks. The receiver operating characteristic analyses (ROC) and logistic regression were calculated to assess discriminatory accuracy.

Results

Twelve dysregulated miRNAs screened by microarray that showed the same expression patterns with qRT-PCR analysis. Through bioinformatics analysis, the most prominent hub gene probably regulated by the 12 down-regulated miRNAs is found to be TP53. The ROC including the 12 miRNAs separated NPC patients from healthy controls with very high accuracy (areas under the receiver operating characteristic curve [AUC] = 0.999, sensitivity = 100.00%, specificity = 96.00%). Furthermore, if only six significantly dysregulated miRNAs were selected for the ROC analysis, the accuracy is still impressive (AUC = 0.941, sensitivity = 95.45%, specificity = 80.00%).

Conclusions

This study highlights the potential for salivary miRNAs as biomarkers for the detection of NPC. Meanwhile, differentially expressed miRNAs in saliva might play critical roles in NPC by regulating their target genes, which associated with some significant pathways, such as p53 signaling pathway.
Zusatzmaterial
Additional file 1: Table S1. The dysregulated (down-regulated) miRNAs in the NPC samples with the cutoff criteria of P < 0.01 and |fold change| > 2. Table S2. Putative target genes of the dysregulated miRNAs in the saliva samples of NPC patients. Table S3. The enriched Gene Ontology (GO) terms in molecular function (MF), biological process (BP) and cellular component (CC) categories for target genes of all the 12 differentially expressed miRNAs. FDR: false discovery rate. Table S4. The top ten enriched pathways for target genes of all the 12 differentially expressed miRNAs. Table S5. The target genes with degrees not less than five in the protein-protein interaction network. Table S6. Sequences of RT primer, and PCR primers used for quantitative real-time PCR (qRT-PCR). Table S7. Detail information of protein-protein interactions from the Search Tool for the Retrieval of interacting Genes database (STRING) online. Figure S1. Validation of the miRNA expression (miR-937-5p, miR-650, miR-3612, miR-4478, miR-4259, miR-3714, miR-4730, miR-1203, miR-30b-3p, miR-1321, miR-1202, and miR-575) by qRT-PCR in 22 patients and 25 healthy controls. Figure S2. ROC curves of the diagnostic potential of the 12 individual salivary miRNAs (has-miR-30b-3p, has-miR-575, has-miR-650, has-miR-937-5p, has-miR-1202, has-miR-1203, has-miR-1321, has-miR-3612, has-miR-3714, has-miR-4259, has-miR-4478, and has-miR-4730) in discrimination between NPC patients and healthy controls. The AUC values ranged from 0.764 to 0.883, respectively. Figure S3. Diagnostic miRNA expressions were classified into 3 different patterns based on various clinical stages. (DOCX 1214 kb)
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