Prediction of Recurrence Free Survival for Esophageal Cancer Patients | Oncotarget
Channel: Oncotarget
Date: 2022-09-21

Oncotarget published this trending research paper in Volume 13, entitled, "Prediction of recurrence free survival for esophageal cancer patients using a protein signature based risk model" by researchers from the Department of Biochemistry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India, Alex and Simona Shnaider Research Laboratory in Molecular Oncology, Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada, University School of Biotechnology, Guru Gobind Singh Indraprastha University, Dwarka, New Delhi, India, Department of Gastroenterology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India, Department of Gastrointestinal Surgery, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India, Department of Pathology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India, Department of Medicine, Endocrine Division, Mount Sinai Hospital and University of Toronto, Toronto, Ontario, Canada, Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada, Joseph and Mildred Sonshine Family Centre for Head and Neck Diseases, Department of Otolaryngology – Head and Neck Surgery, Mount Sinai Hospital, Toronto, Ontario, Canada, Department of Otolaryngology – Head and Neck Surgery, University of Toronto, Toronto, Ontario, Canada
#openaccess #esophagealcancer #researchpaper #peerreview #cancer #meded #oncology

DOI - https://doi.org/10.18632/oncotarget.10656

Correspondence to - Ranju Ralhan - rralhan@mtsinai.on.ca, Shyam S. Chauhan - s_s_chauhan@hotmail.com 

Abstract

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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Keywords - esophageal cancer, wnt proteins, disheveled, molecular markers, prognosis

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