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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2016
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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. |
format | Online Article Text |
id | pubmed-5226511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
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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