Prognostic modeling of oral cancer by gene profiles and clinicopathological co-variables

Steven W. Mes, Dennis te Beest, Tito Poli, Silvia Rossi, Kathrin Scheckenbach, Wessel N. van Wieringen, Arjen Brink, Nicoletta Bertani, Davide Lanfranco, Enrico M. Silini, Paul J. van Diest, Elisabeth Bloemena, C. René Leemans, Mark A. van de Wiel*, Ruud H. Brakenhoff

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Accurate staging and outcome prediction is a major problem in clinical management of oral cancer patients, hampering high precision treatment and adjuvant therapy planning. Here, we have built and validated multivariable models that integrate gene signatures with clinical and pathological variables to improve staging and survival prediction of patients with oral squamous cell carcinoma (OSCC). Gene expression profiles from 249 human papillomavirus (HPV)-negative OSCCs were explored to identify a 22-gene lymph node metastasis signature (LNMsig) and a 40- gene overall survival signature (OSsig). To facilitate future clinical implementation and increase performance, these signatures were transferred to quantitative polymerase chain reaction (qPCR) assays and validated in an independent cohort of 125 HPVnegative tumors. When applied in the clinically relevant subgroup of early-stage (cT1-2N0) OSCC, the LNMsig could prevent overtreatment in two-third of the patients. Additionally, the integration of RT-qPCR gene signatures with clinical and pathological variables provided accurate prognostic models for oral cancer, strongly outperforming TNM. Finally, the OSsig gene signature identified a subpopulation of patients, currently considered at low-risk for disease-related survival, who showed an unexpected poor prognosis. These well-validated models will assist in personalizing primary treatment with respect to neck dissection and adjuvant therapies.

Original languageEnglish
Pages (from-to)59312-59323
Number of pages12
JournalOncotarget
Volume8
Issue number35
Early online date26 Jul 2017
DOIs
Publication statusPublished - 29 Aug 2017

Funding

This work was supported by grants from the Dutch Cancer Society, KWF (grant number 2008-4201) and European Union’s Seventh Framework Project (grant agreement 224483: NeoMark, and grant agreement 611425: OraMod).

FundersFunder number
Dutch Cancer Society
European Union’s Seventh Framework Project
Seventh Framework Programme224483, 611425
KWF Kankerbestrijding2008-4201

    Keywords

    • Expression profiling
    • Head and neck cancer
    • Lymph node metastasis
    • Oral cancer
    • Prognostic modeling

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