Cross validated serum small extracellular vesicle microRNAs for the detection of oropharyngeal squamous cell carcinoma

G. C. Mayne, C. M. Woods, N. Dharmawardana, T. Wang, S. Krishnan, J. C. Hodge, A. Foreman, S. Boase, A. S. Carney, E. A.W. Sigston, D. I. Watson, E. H. Ooi, D. J. Hussey

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Background: Oropharyngeal squamous cell carcinoma (OPSCC) is often diagnosed at an advanced stage because the disease often causes minimal symptoms other than metastasis to neck lymph nodes. Better tools are required to assist with the early detection of OPSCC. MicroRNAs (miRNAs, miRs) are potential biomarkers for early head and neck squamous cell cancer diagnosis, prognosis, recurrence, and presence of metastatic disease. However, there is no widespread agreement on a panel of miRNAs with clinically meaningful utility for head and neck squamous cell cancers. This could be due to variations in the collection, storage, pre-processing, and isolation of RNA, but several reports have indicated that the selection and reproducibility of biomarkers has been widely affected by the methods used for data analysis. The primary analysis issues appear to be model overfitting and the incorrect application of statistical techniques. The purpose of this study was to develop a robust statistical approach to identify a miRNA signature that can distinguish controls and patients with inflammatory disease from patients with human papilloma virus positive (HPV +) OPSCC. Methods: Small extracellular vesicles were harvested from the serum of 20 control patients, 20 patients with gastroesophageal reflux disease (GORD), and 40 patients with locally advanced HPV + OPSCC. MicroRNAs were purified, and expression profiled on OpenArray™. A novel cross validation method, using lasso regression, was developed to stabilise selection of miRNAs for inclusion in a prediction model. The method, named StaVarSel (for Stable Variable Selection), was used to derive a diagnostic biomarker signature. Results: A standard cross validation approach was unable to produce a biomarker signature with good cross validated predictive capacity. In contrast, StaVarSel produced a regression model containing 11 miRNA ratios with potential clinical utility. Sample permutations indicated that the estimated cross validated prediction accuracy of the 11-miR-ratio model was not due to chance alone. Conclusions: We developed a novel method, StaVarSel, that was able to identify a panel of miRNAs, present in small extracellular vesicles derived from blood serum, that robustly cross validated as a biomarker for the detection of HPV + OPSCC. This approach could be used to derive diagnostic biomarkers of other head and neck cancers.

Original languageEnglish
Article number280
Number of pages12
JournalJournal of Translational Medicine
Issue number1
Publication statusPublished - 10 Jul 2020

Bibliographical note

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons .org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco applies to the data made available in this article, unless otherwise stated in a credit line to the data


  • Biomarkers
  • Data analysis
  • microRNAs
  • Oropharyngeal squamous cell carcinoma
  • Serum


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