Original Article

Citation: Oncogenesis (2015) 4, e147; doi:10.1038/oncsis.2015.7
Published online 20 April 2015

Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
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S S Chauhan1, J Kaur1,2,13, M Kumar1,13, A Matta2,13, G Srivastava2, A Alyass2,3, J Assi2, I Leong4,5, C MacMillan4, I Witterick6,7, T J Colgan4,5, N K Shukla8, A Thakar9, M C Sharma10, K W M Siu11, P G Walfish2,4,5,6,7,12 and R Ralhan2,4,5,6,7

  1. 1Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, India
  2. 2Alex and Simona Shnaider Laboratory in Molecular Oncology, Mount Sinai Hospital, Toronto, Ontario, Canada
  3. 3Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
  4. 4Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Joseph & Wolf Lebovic Health Complex, Toronto, Ontario, Canada
  5. 5Department of Oral Pathology and Oral Medicine, Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada
  6. 6Department of Otolaryngology – Head and Neck Surgery, Joseph and Mildred Sonshine Family Centre for Head and Neck Diseases, Mount Sinai Hospital, Toronto, Ontario, Canada
  7. 7Department of Otolaryngology – Head and Neck Surgery, University of Toronto, Toronto, Ontario, Canada
  8. 8Department of Surgery, Dr. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences, New Delhi, India
  9. 9Department of Otorhinolaryngology, All India Institute of Medical Sciences, New Delhi, India
  10. 10Department of Pathology, All India Institute of Medical Sciences, New Delhi, India
  11. 11Department of Chemistry and Biochemistry, University of Windsor, Windsor, Ontario, Canada
  12. 12Endocrine Division, Department of Medicine, Mount Sinai Hospital and University of Toronto, Toronto, Ontario, Canada

Correspondence: Dr R Ralhan, Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, 6-500, 600 University Avenue, Toronto, Ontario, Canada M5G 1X5. E-mail: ralhanr@gmail.com

13These authors contributed equally to this work.

Received 26 November 2014; Revised 28 January 2015; Accepted 9 February 2015

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Abstract

Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heterogeneous nuclear ribonucleoproteinK (hnRNPK), prothymosin α (PTMA), 14-3-3ζ and 14-3-3σ was analyzed by immunohistochemistry in test set (282 Indian OSCCs and 209 normal tissues), correlated with clinic–pathological parameters and clinical outcome over 12 years to develop a risk model for prediction of recurrence-free survival. This risk classifier was externally validated in 135 Canadian OSCC and 96 normal tissues. Biomarker signature score based on PTMA, S100A7 and hnRNPK was associated with recurrence free survival of OSCC patients (hazard ratio=1.11; 95% confidence interval 1.08, 1.13, P<0.001, optimism-corrected c-statistic=0.69) independent of clinical parameters. Biomarker signature score stratified OSCC patients into high- and low-risk groups with significant difference for disease recurrence. The high-risk group had median survival 14 months, and 3-year survival rate of 30%, whereas low-risk group survival probability did not reach 50%, and had 3-year survival rate of 71%. As a powerful predictor of 3-year recurrence-free survival in OSCC patients, the newly developed biomarkers panel risk classifier will facilitate patient counseling for personalized treatment.