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

Authors

  • Muy-Teck Teh,

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

  • Iain L. Hutchison,

    1. Department of Oral & Maxillofacial Surgery, Barts & The London NHS Trust, London, England, United Kingdom
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  • Daniela Elena Costea,

    1. Section of Pathology, The Gade Institute, University of Bergen, and Dept. of Pathology, Haukeland University Hospital, Bergen, Norway
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  • Evelyn Neppelberg,

    1. Dept. of Oral Surgery, Haukeland University Hospital and Institute of Clinical Dentistry, University of Bergen, Bergen, Norway
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  • Per Gunnar Liavaag,

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

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

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

    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
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  • Edward W. Odell,

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

    1. Cancer Research UK and University College London Cancer Trials Centre, 90 Tottenham Court Rd, London W1T 4TJ, United Kingdom
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  • Ahmad Waseem

    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
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  • 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.

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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