title: A novel saliva-based microRNA biomarker panel to detect head and neck cancers.
abstract: BACKGROUND
  MicroRNAs (miRNAs) are known to play an important role in cancer development by post-transcriptionally affecting the expression of critical genes. The aims of this study were two-fold: (i) to develop a robust method to isolate miRNAs from small volumes of saliva and (ii) to develop a panel of saliva-based diagnostic biomarkers for the detection of head and neck squamous cell carcinoma (HNSCC).
  
  
  METHODS
  Five differentially expressed miRNAs were selected from miScript™ miRNA microarray data generated using saliva from five HNSCC patients and five healthy controls. Their differential expression was subsequently confirmed by RT-qPCR using saliva samples from healthy controls (n = 56) and HNSCC patients (n = 56). These samples were divided into two different cohorts, i.e., a first confirmatory cohort (n = 21) and a second independent validation cohort (n = 35), to narrow down the miRNA diagnostic panel to three miRNAs: miR-9, miR-134 and miR-191. This diagnostic panel was independently validated using HNSCC miRNA expression data from The Cancer Genome Atlas (TCGA), encompassing 334 tumours and 39 adjacent normal tissues. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic capacity of the panel.
  
  
  RESULTS
  On average 60 ng/μL miRNA was isolated from 200 μL of saliva. Overall a good correlation was observed between the microarray data and the RT-qPCR data. We found that miR-9 (P <0.0001), miR-134 (P <0.0001) and miR-191 (P <0.001) were differentially expressed between saliva from HNSCC patients and healthy controls, and that these miRNAs provided a good discriminative capacity with area under the curve (AUC) values of 0.85 (P <0.0001), 0.74 (P < 0.001) and 0.98 (P < 0.0001), respectively. In addition, we found that the salivary miRNA data showed a good correlation with the TCGA miRNA data, thereby providing an independent validation.
  
  
  CONCLUSIONS
  We show that we have developed a reliable method to isolate miRNAs from small volumes of saliva, and that the saliva-derived miRNAs miR-9, miR-134 and miR-191 may serve as novel biomarkers to reliably detect HNSCC.
authors.affiliation: The University of Queensland Diamantina Institute, The University of Queensland, Level 6, TRI, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
authors.forename: Carolina
authors.initials: C
authors.lastname: Salazar
authors.forename: Rahul
authors.initials: R
authors.lastname: Nagadia
authors.forename: Pratibala
authors.initials: P
authors.lastname: Pandit
authors.forename: Justin
authors.initials: J
authors.lastname: Cooper-White
authors.forename: Nilanjana
authors.initials: N
authors.lastname: Banerjee
authors.forename: Nevenka
authors.initials: N
authors.lastname: Dimitrova
authors.forename: William B
authors.initials: WB
authors.lastname: Coman
authors.forename: Chamindie
authors.initials: C
authors.lastname: Punyadeera
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis / Q000235:genetics*; D016000:Cluster Analysis; D015331:Cohort Studies; D003937:Diagnosis, Differential; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006258:Head and Neck Neoplasms / Q000175:diagnosis / Q000235:genetics*; D006801:Humans; D008297:Male; D035683:MicroRNAs / Q000235:genetics*; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D012372:ROC Curve; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012463:Saliva / Q000378:metabolism*
chemical_list: D014408:Biomarkers, Tumor; C569273:MIRN134 microRNA, human; C546177:MIRN191 microRNA, human; C541874:MIRN92 microRNA, human; D035683:MicroRNAs