Chu Chen1, Pawadee Lohavanichbutr2, Yuzheng Zhang2, John R Houck2, Melissa P Upton3, Behnoush Abedi-Ardekani4, Antonio Agudo5, Wolfgang Ahrens6, Laia Alemany7, Devasena Anantharaman8, David I Conway9, Neal D Futran10, Ivana Holcatova11, Kathrin Günther12, Bo T Hansen13, Claire M Healy14, Doha Itani15, Kristina Kjaerheim13, Marcus M Monroe16, Peter J Thomson17, Benjamin L Witt16, Steven Nakoneshny15, Lisa A Peterson18, Stephen M Schwartz19, Katie R Zarins18, Mia Hashibe16, Paul Brennan4, Laura S Rozek18, Gregory Wolf18, Joseph C Dort15, Pei Wang20. 1. Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA; Department of Epidemiology, University of Washington, 1959 NE Pacific St, Seattle, WA, USA; Department of Otolaryngology -- Head and Neck Surgery, University of Washington, 1959, NE Pacific St, Seattle, WA, USA. Electronic address: cchen@fredhutch.org. 2. Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA. 3. Department of Pathology, University of Washington, 1959 NE Pacific St, Seattle, WA, USA. 4. International Agency of Research on Cancer, 150 Cours Albert Thomas, Lyon, France. 5. Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, Avinguda de la Granvia, 199, 08908, L'Hospitalet de Llobregat, Barcelona, Spain. 6. Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Institute of Statistics, Bremen University, Achterstraße 30, 28359 Bremen, Germany. 7. Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, Avinguda de la Granvia, 199, 08908, L'Hospitalet de Llobregat, Barcelona, Spain; Epidemiology and Public Health, Centro de Investigación Biomédica en Red: Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain. 8. Rajiv Gandhi Centre for Biotechnology, Melarannoor Road, Thycaud, Thiruvananthapuram, India. 9. School of Medicine, Dentistry, and Nursing, University of Glasgow, University Avenue, Glasgow, UK. 10. Department of Otolaryngology -- Head and Neck Surgery, University of Washington, 1959, NE Pacific St, Seattle, WA, USA. 11. Institute of Hygiene and Epidemiology, 1st Faculty of Medicine, Opletalova 38, 110 00 Staré Město, Charles University, Prague, Czech Republic. 12. Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany. 13. Cancer Registry of Norway, Ullernchausseen 64, 0379 Oslo, Norway. 14. Dublin Dental University Hospital, Trinity College Dublin, Lincoln Pl, Dublin, Ireland. 15. Section of Otolaryngology -- Head & Neck Surgery, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary Alberta, Canada. 16. University of Utah, 201 Presidents Cir, Salt Lake City, UT, USA. 17. Oral & Maxillofacial Surgery, The University of Hong Kong, Pok Fu Lam, Hong Kong. 18. University of Michigan, 500 S State St, Ann Arbor, MI, USA. 19. Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA; Department of Epidemiology, University of Washington, 1959 NE Pacific St, Seattle, WA, USA. 20. Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, USA.
Abstract
OBJECTIVES: To test the performance of an oral cancer prognostic 13-gene signature for the prediction of survival of patients diagnosed with HPV-negative and p16-negative oral cavity cancer. MATERIALS AND METHODS: Diagnostic formalin-fixed paraffin-embedded oral cavity cancer tumor samples were obtained from the Fred Hutchinson Cancer Research Center/University of Washington, University of Calgary, University of Michigan, University of Utah, and seven ARCAGE study centers coordinated by the International Agency of Research on Cancer. RNA from 638 Human Papillomavirus (HPV)-negative and p16-negative samples was analyzed for the 13 genes using a NanoString assay. Ridge-penalized Cox regressions were applied to samples randomly split into discovery and validation sets to build models and evaluate the performance of the 13-gene signature in predicting 2-year oral cavity cancer-specific survival overall and separately for patients with early and late stage disease. RESULTS: Among AJCC stage I/II patients, including the 13-gene signature in the model resulted in substantial improvement in the prediction of 2-year oral cavity cancer-specific survival. For models containing age and sex with and without the 13-gene signature score, the areas under the Receiver Operating Characteristic Curve (AUC) and partial AUC were 0.700 vs. 0.537 (p < 0.001), and 0.046 vs. 0.018 (p < 0.001), respectively. Improvement in predicting prognosis for AJCC stage III/IV disease also was observed, but to a lesser extent. CONCLUSIONS: If confirmed using tumor samples from a larger number of early stage oral cavity cancer patients, the 13-gene signature may inform personalized treatment of early stage HPV-negative and p16-negative oral cavity cancer patients.
OBJECTIVES: To test the performance of an oral cancer prognostic 13-gene signature for the prediction of survival of patients diagnosed with HPV-negative and p16-negative oral cavity cancer. MATERIALS AND METHODS: Diagnostic formalin-fixed paraffin-embedded oral cavity cancer tumor samples were obtained from the Fred Hutchinson Cancer Research Center/University of Washington, University of Calgary, University of Michigan, University of Utah, and seven ARCAGE study centers coordinated by the International Agency of Research on Cancer. RNA from 638 Human Papillomavirus (HPV)-negative and p16-negative samples was analyzed for the 13 genes using a NanoString assay. Ridge-penalized Cox regressions were applied to samples randomly split into discovery and validation sets to build models and evaluate the performance of the 13-gene signature in predicting 2-year oral cavity cancer-specific survival overall and separately for patients with early and late stage disease. RESULTS: Among AJCC stage I/II patients, including the 13-gene signature in the model resulted in substantial improvement in the prediction of 2-year oral cavity cancer-specific survival. For models containing age and sex with and without the 13-gene signature score, the areas under the Receiver Operating Characteristic Curve (AUC) and partial AUC were 0.700 vs. 0.537 (p < 0.001), and 0.046 vs. 0.018 (p < 0.001), respectively. Improvement in predicting prognosis for AJCC stage III/IV disease also was observed, but to a lesser extent. CONCLUSIONS: If confirmed using tumor samples from a larger number of early stage oral cavity cancerpatients, the 13-gene signature may inform personalized treatment of early stage HPV-negative and p16-negative oral cavity cancerpatients.
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