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A novel saliva-based microRNA biomarker panel to detect head and neck cancers

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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.

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Acknowledgments

The authors would like to acknowledge the financial support of the Queensland Government Smart Futures Fellowship Programme (QGSFF), Queensland Centre for Head and Neck cancer and University of Queensland Diamantina Institute Central Funds. In addition, the authors wish to acknowledge the on-going clinical support from the ENT Department at the Princess Alexandra Hospital in Woolloongabba, Australia. Special thanks goes to Ms Dana Middleton, A/Prof Chris Perry and A/Prof Ben Panizza.

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Authors and Affiliations

  1. The University of Queensland Diamantina Institute, The University of Queensland, Level 6, TRI, 37 Kent St, Woolloongabba, QLD, 4102, Australia

    Carolina Salazar, Rahul Nagadia, Pratibala Pandit & Chamindie Punyadeera

  2. Australian Institute for BioEngineering and Nanotechnology, St-Lucia, Brisbane, Australia

    Justin Cooper-White

  3. The School of Chemical Engineering, The University of Queensland, Brisbane, Australia

    Justin Cooper-White

  4. Philips Research, 345 Scarborough Road, Briarcliff Manor, NY, 10510-2099, USA

    Nilanjana Banerjee & Nevenka Dimitrova

  5. The School of Medicine, University of Queensland, Brisbane, Australia

    William B Coman

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  1. Carolina Salazar
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Correspondence to Chamindie Punyadeera.

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Salazar, C., Nagadia, R., Pandit, P. et al. A novel saliva-based microRNA biomarker panel to detect head and neck cancers. Cell Oncol. 37, 331–338 (2014). https://doi.org/10.1007/s13402-014-0188-2

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