Prediction of recurrence free survival for esophageal cancer patients using a protein signature based risk model
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Raghibul Hasan1, Gunjan Srivastava2, Akram Alyass2,3, Rinu Sharma4, Anoop Saraya5, Tushar K. Chattopadhyay6, Siddartha DattaGupta7, Paul G. Walfish2,8,9,10, Shyam S. Chauhan1 and Ranju Ralhan1,2,9,10,11
1 Department of Biochemistry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
2 Alex and Simona Shnaider Research Laboratory in Molecular Oncology, Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada
3 Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
4 University School of Biotechnology, Guru Gobind Singh Indraprastha Univesity, Dwarka, New Delhi, India
5 Department of Gastroenterology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
6 Department of Gastrointestinal Surgery, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
7 Department of Pathology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
8 Department of Medicine, Endocrine Division, Mount Sinai Hospital and University of Toronto, Toronto, Ontario, Canada
9 Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada
10 Joseph and Mildred Sonshine Family Centre for Head and Neck Diseases, Department of Otolaryngology – Head and Neck Surgery, Mount Sinai Hospital, Toronto, Ontario, Canada
11 Department of Otolaryngology – Head and Neck Surgery, University of Toronto, Toronto, Ontario, Canada
|Ranju Ralhan,||email:||[email protected]|
|Shyam S. Chauhan,||email:||[email protected]|
Keywords: esophageal cancer; wnt proteins; dishevelled; molecular markers; prognosis
Received: January 15, 2016 Accepted: May 16, 2016 Published: September 14, 2022
Background: Biomarkers to predict the risk of disease recurrence in Esophageal squamous cell carcinoma (ESCC) patients are urgently needed to improve treatment. We developed proteins expression-based risk model to predict recurrence free survival for ESCC patients.
Methods: Alterations in Wnt pathway components expression and subcellular localization were analyzed by immunohistochemistry in 80 ESCCs, 61 esophageal dysplastic and 47 normal tissues; correlated with clinicopathological parameters and clinical outcome over 86 months by survival analysis. Significant prognostic factors were identified by multivariable Cox regression analysis.
Results: Biomarker signature score based on cytoplasmic β-catenin, nuclear c-Myc, nuclear DVL and membrane α-catenin was associated with recurrence free survival [Hazard ratio = 1.11 (95% CI = 1.05, 1.17), p < 0.001, C-index = 0.68] and added significant prognostic value over clinical parameters (p < 0.001). The inclusion of Slug further improved prognostic utility (p < 0.001, C-index = 0.71). Biomarker Signature Scoreslug improved risk classification abilities for clinical outcomes at 3 years, accurately predicting recurrence in 79% patients in 1 year and 97% in 3 years in high risk group; 73% patients within low risk group did not have recurrence in 1 year, with AUC of 0.76.
Conclusions: Our comprehensive risk model predictive for recurrence allowed us to determine the robustness of our biomarker panel in stratification of ESCC patients at high or low risk of disease recurrence; high risk patients are stratified for more rigorous personalized treatment while the low risk patients may be spared from harmful side effects of toxic therapy.
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