Early Detection and Diagnosis

Exploiting FOXM1-orchestrated molecular network for early squamous cell carcinoma diagnosis and prognosis†

  1. Muy-Teck Teh1,‡,*,
  2. Iain L. Hutchison2,
  3. Daniela Elena Costea3,
  4. Evelyn Neppelberg4,
  5. Per Gunnar Liavaag5,
  6. Karin Purdie6,
  7. Catherine Harwood6,
  8. Hong Wan1,
  9. Edward W. Odell7,
  10. Allan Hackshaw8,
  11. Ahmad Waseem1

Article first published online: 25 OCT 2012

DOI: 10.1002/ijc.27886

Issue

International Journal of Cancer

International Journal of Cancer

Volume 132, Issue 9, pages 2095–2106, 1 May 2013

Additional Information

How to Cite

Teh, M.-T., Hutchison, I. L., Costea, D. E., Neppelberg, E., Liavaag, P. G., Purdie, K., Harwood, C., Wan, H., Odell, E. W., Hackshaw, A. and Waseem, A. (2013), Exploiting FOXM1-orchestrated molecular network for early squamous cell carcinoma diagnosis and prognosis. Int. J. Cancer, 132: 2095–2106. doi: 10.1002/ijc.27886

Author Information

  1. 1

    Centre for Clinical and Diagnostic Oral Sciences, Institute of Dentistry, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, England, United Kingdom

  2. 2

    Department of Oral & Maxillofacial Surgery, Barts & The London NHS Trust, London, England, United Kingdom

  3. 3

    Section of Pathology, The Gade Institute, University of Bergen, and Dept. of Pathology, Haukeland University Hospital, Bergen, Norway

  4. 4

    Dept. of Oral Surgery, Haukeland University Hospital and Institute of Clinical Dentistry, University of Bergen, Bergen, Norway

  5. 5

    Dept. of Otolaryngology and Head & Neck Surgery, Head and Neck Clinic, Haukeland University Hospital, Bergen, Norway

  6. 6

    Centre for Cutaneous Research, The Blizard Institute, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, England, United Kingdom

  7. 7

    Department of Clinical and Diagnostic Sciences, King's College London, Guy's Hospital Campus, London SE1 9RT, United Kingdom

  8. 8

    Cancer Research UK and University College London Cancer Trials Centre, 90 Tottenham Court Rd, London W1T 4TJ, United Kingdom

  1. ‡

    Tel.: +44 (0) 20 7882 7140, Fax: +44 (0) 20 7882 7137

*Centre for Clinical and Diagnostic Oral Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, The Blizard Building, 4, Newark Street, London E1 2AT, United Kingdom

  1. †

    M.T.T is listed as an inventor on a patent application at the World Intellectual Property Organisation filed by Queen Mary University of London pertaining to the use of the qMIDS technology (biomarkers and algorithm) described in this paper for cancer diagnosis.

  2. ‡

    Tel.: +44 (0) 20 7882 7140, Fax: +44 (0) 20 7882 7137

Publication History

  1. Issue published online: 18 FEB 2013
  2. Article first published online: 25 OCT 2012
  3. Accepted manuscript online: 4 OCT 2012 01:47AM EST
  4. Manuscript Accepted: 5 SEP 2012
  5. Manuscript Received: 4 JUL 2012

Funded by

  • Facial Surgery Research Foundation–Saving Faces
  • Bergen Medical Research Foundation. Grant Number: 20/2009
  • Norwegian Cancer Research Association. Grant Number: 515970/2011
  • British Skin Foundation. Grant Number: S535
  • Cancer Research UK

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Keywords:

  • molecular diagnostics;
  • early cancer biomarkers;
  • qPCR;
  • squamous cell carcinoma;
  • FOXM1 diagnostic biomarkers;
  • prognostic biomarkers;
  • clinical translation;
  • personalised medicine;
  • early detection

Abstract

Histopathological discordance with molecular phenotype of many human cancers poses clinically challenging tasks for accurate cancer diagnosis, which impacts on treatment strategy and patient outcome. Hence, an objective, accurate and quantitative method is needed. A quantitative Malignancy Index Diagnostic System (qMIDS) was developed based on 14 FOXM1 (isoform B)-associated genes implicated in the regulation of the cell cycle, differentiation, ageing, genomic stability, epigenetic and stem cell renewal, and two reference genes. Their mRNA expression levels were translated via a prospectively designed algorithm, into a metric scoring system. Subjects from UK and Norway (n = 299) provided 359 head and neck tissue specimens. Diagnostic test performance was assessed using detection rate (DR) and false-positive rate (FPR). The median qMIDS scores were 1.3, 2.9 and 6.7 in healthy tissue, dysplasia and head and neck squamous cell carcinomas (HNSCC), respectively (UK prospective dataset, p<0.001); 1.4, 2.3 and 7.6 in unaffected, oral lichen planus, or HNSCC, respectively (Norwegian retrospective dataset with up to 19 years survival data, p<0.001). At a qMIDS cut-off of 4.0, DR was 94% and FPR was 3.2% (Norwegian dataset); and DR was 91% and FPR was 1.3% (UK dataset). We further demonstrated the transferability of qMIDS for diagnosing premalignant human vulva (n = 58) and skin (n = 21) SCCs, illustrating its potential clinical use for other cancer types. This study provided evidence that qMIDS was able to quantitatively diagnose and objectively stratify cancer aggressiveness. With further validation, qMIDS could enable early HNSCC detection and guide appropriate treatment. Early treatment intervention can lead to long-term reduction in healthcare costs and improve patient outcome.

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