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Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients

INTRODUCTION: Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma. However, without confirmation in an independent validation study, their clinical utility is limited. Our goal was to establish a robust database enabling the swift validation of p...

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Autores principales: Szász, A. Marcell, Lánczky, András, Nagy, Ádám, Förster, Susann, Hark, Kim, Green, Jeffrey E., Boussioutas, Alex, Busuttil, Rita, Szabó, András, Győrffy, Balázs
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226511/
https://www.ncbi.nlm.nih.gov/pubmed/27384994
http://dx.doi.org/10.18632/oncotarget.10337
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author Szász, A. Marcell
Lánczky, András
Nagy, Ádám
Förster, Susann
Hark, Kim
Green, Jeffrey E.
Boussioutas, Alex
Busuttil, Rita
Szabó, András
Győrffy, Balázs
author_facet Szász, A. Marcell
Lánczky, András
Nagy, Ádám
Förster, Susann
Hark, Kim
Green, Jeffrey E.
Boussioutas, Alex
Busuttil, Rita
Szabó, András
Győrffy, Balázs
author_sort Szász, A. Marcell
collection PubMed
description INTRODUCTION: Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma. However, without confirmation in an independent validation study, their clinical utility is limited. Our goal was to establish a robust database enabling the swift validation of previous and future gastric cancer survival biomarker candidates. RESULTS: The entire database incorporates 1,065 gastric carcinoma samples, gene expression data. Out of 29 established markers, higher expression of BECN1 (HR = 0.68, p = 1.5E-05), CASP3 (HR = 0.5, p = 6E-14), COX2 (HR = 0.72, p = 0.0013), CTGF (HR = 0.72, p = 0.00051), CTNNB1 (HR = 0.47, p = 4.3E-15), MET (HR = 0.63, p = 1.3E-05), and SIRT1 (HR = 0.64, p = 2.2E-07) correlated to longer OS. Higher expression of BIRC5 (HR = 1.45, p = 1E-04), CNTN1 (HR = 1.44, p = 3.5E- 05), EGFR (HR = 1.86, p = 8.5E-11), ERCC1 (HR = 1.36, p = 0.0012), HER2 (HR = 1.41, p = 0.00011), MMP2 (HR = 1.78, p = 2.6E-09), PFKB4 (HR = 1.56, p = 3.2E-07), SPHK1 (HR = 1.61, p = 3.1E-06), SP1 (HR = 1.45, p = 1.6E-05), TIMP1 (HR = 1.92, p = 2.2E- 10) and VEGF (HR = 1.53, p = 5.7E-06) were predictive for poor OS. MATERIALS AND METHODS: We integrated samples of three major cancer research centers (Berlin, Bethesda and Melbourne datasets) and publicly available datasets with available follow-up data to form a single integrated database. Subsequently, we performed a literature search for prognostic markers in gastric carcinomas (PubMed, 2012–2015) and re-validated their findings predicting first progression (FP) and overall survival (OS) using uni- and multivariate Cox proportional hazards regression analysis. CONCLUSIONS: The major advantage of our analysis is that we evaluated all genes in the same set of patients thereby making direct comparison of the markers feasible. The best performing genes include BIRC5, CASP3, CTNNB1, TIMP-1, MMP-2, SIRT, and VEGF.
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spelling pubmed-52265112017-01-18 Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients Szász, A. Marcell Lánczky, András Nagy, Ádám Förster, Susann Hark, Kim Green, Jeffrey E. Boussioutas, Alex Busuttil, Rita Szabó, András Győrffy, Balázs Oncotarget Research Paper INTRODUCTION: Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma. However, without confirmation in an independent validation study, their clinical utility is limited. Our goal was to establish a robust database enabling the swift validation of previous and future gastric cancer survival biomarker candidates. RESULTS: The entire database incorporates 1,065 gastric carcinoma samples, gene expression data. Out of 29 established markers, higher expression of BECN1 (HR = 0.68, p = 1.5E-05), CASP3 (HR = 0.5, p = 6E-14), COX2 (HR = 0.72, p = 0.0013), CTGF (HR = 0.72, p = 0.00051), CTNNB1 (HR = 0.47, p = 4.3E-15), MET (HR = 0.63, p = 1.3E-05), and SIRT1 (HR = 0.64, p = 2.2E-07) correlated to longer OS. Higher expression of BIRC5 (HR = 1.45, p = 1E-04), CNTN1 (HR = 1.44, p = 3.5E- 05), EGFR (HR = 1.86, p = 8.5E-11), ERCC1 (HR = 1.36, p = 0.0012), HER2 (HR = 1.41, p = 0.00011), MMP2 (HR = 1.78, p = 2.6E-09), PFKB4 (HR = 1.56, p = 3.2E-07), SPHK1 (HR = 1.61, p = 3.1E-06), SP1 (HR = 1.45, p = 1.6E-05), TIMP1 (HR = 1.92, p = 2.2E- 10) and VEGF (HR = 1.53, p = 5.7E-06) were predictive for poor OS. MATERIALS AND METHODS: We integrated samples of three major cancer research centers (Berlin, Bethesda and Melbourne datasets) and publicly available datasets with available follow-up data to form a single integrated database. Subsequently, we performed a literature search for prognostic markers in gastric carcinomas (PubMed, 2012–2015) and re-validated their findings predicting first progression (FP) and overall survival (OS) using uni- and multivariate Cox proportional hazards regression analysis. CONCLUSIONS: The major advantage of our analysis is that we evaluated all genes in the same set of patients thereby making direct comparison of the markers feasible. The best performing genes include BIRC5, CASP3, CTNNB1, TIMP-1, MMP-2, SIRT, and VEGF. Impact Journals LLC 2016-06-30 /pmc/articles/PMC5226511/ /pubmed/27384994 http://dx.doi.org/10.18632/oncotarget.10337 Text en Copyright: © 2016 Szász et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Szász, A. Marcell
Lánczky, András
Nagy, Ádám
Förster, Susann
Hark, Kim
Green, Jeffrey E.
Boussioutas, Alex
Busuttil, Rita
Szabó, András
Győrffy, Balázs
Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
title Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
title_full Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
title_fullStr Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
title_full_unstemmed Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
title_short Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
title_sort cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226511/
https://www.ncbi.nlm.nih.gov/pubmed/27384994
http://dx.doi.org/10.18632/oncotarget.10337
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