Cargando…

Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer

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 fi...

Descripción completa

Detalles Bibliográficos
Autores principales: Chauhan, S S, Kaur, J, Kumar, M, Matta, A, Srivastava, G, Alyass, A, Assi, J, Leong, I, MacMillan, C, Witterick, I, Colgan, T J, Shukla, N K, Thakar, A, Sharma, M C, Siu, K W M, Walfish, P G, Ralhan, R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491610/
https://www.ncbi.nlm.nih.gov/pubmed/25893634
http://dx.doi.org/10.1038/oncsis.2015.7
_version_ 1782379668663435264
author Chauhan, S S
Kaur, J
Kumar, M
Matta, A
Srivastava, G
Alyass, A
Assi, J
Leong, I
MacMillan, C
Witterick, I
Colgan, T J
Shukla, N K
Thakar, A
Sharma, M C
Siu, K W M
Walfish, P G
Ralhan, R
author_facet Chauhan, S S
Kaur, J
Kumar, M
Matta, A
Srivastava, G
Alyass, A
Assi, J
Leong, I
MacMillan, C
Witterick, I
Colgan, T J
Shukla, N K
Thakar, A
Sharma, M C
Siu, K W M
Walfish, P G
Ralhan, R
author_sort Chauhan, S S
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4491610
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-44916102015-07-14 Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer Chauhan, S S Kaur, J Kumar, M Matta, A Srivastava, G Alyass, A Assi, J Leong, I MacMillan, C Witterick, I Colgan, T J Shukla, N K Thakar, A Sharma, M C Siu, K W M Walfish, P G Ralhan, R Oncogenesis Original Article 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. Nature Publishing Group 2015-04 2015-04-20 /pmc/articles/PMC4491610/ /pubmed/25893634 http://dx.doi.org/10.1038/oncsis.2015.7 Text en Copyright © 2015 Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ Oncogenesis is an open-access journal published by Nature Publishing Group. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Original Article
Chauhan, S S
Kaur, J
Kumar, M
Matta, A
Srivastava, G
Alyass, A
Assi, J
Leong, I
MacMillan, C
Witterick, I
Colgan, T J
Shukla, N K
Thakar, A
Sharma, M C
Siu, K W M
Walfish, P G
Ralhan, R
Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
title Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
title_full Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
title_fullStr Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
title_full_unstemmed Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
title_short Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
title_sort prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491610/
https://www.ncbi.nlm.nih.gov/pubmed/25893634
http://dx.doi.org/10.1038/oncsis.2015.7
work_keys_str_mv AT chauhanss predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT kaurj predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT kumarm predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT mattaa predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT srivastavag predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT alyassa predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT assij predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT leongi predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT macmillanc predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT wittericki predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT colgantj predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT shuklank predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT thakara predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT sharmamc predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT siukwm predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT walfishpg predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer
AT ralhanr predictionofrecurrencefreesurvivalusingaproteinexpressionbasedriskclassifierforheadandneckcancer