Oncotarget

Research Papers:

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

A. Marcell Szász, András Lánczky, Ádám Nagy, Susann Förster, Kim Hark, Jeffrey E. Green, Alex Boussioutas, Rita Busuttil, András Szabó, Balázs Győrffy _

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Oncotarget. 2016; 7:49322-49333. https://doi.org/10.18632/oncotarget.10337

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Abstract

A. Marcell Szász1,2, András Lánczky1, Ádám Nagy1, Susann Förster3, Kim Hark4, Jeffrey E. Green4, Alex Boussioutas5,6,7, Rita Busuttil5,6,7, András Szabó8, Balázs Győrffy1,8

1MTA-TTK Lendület Cancer Biomarker Research Group, Budapest, Hungary

22nd Department of Pathology, Semmelweis University, Budapest, Hungary

3Max Delbrück Center for Molecular Medicine, Berlin, Germany

4Transgenic Oncogenesis and Genomics Section, Laboratory of Cancer Biology and Genetics, National Cancer Institute, Bethesda, Maryland, USA

5Cancer Genetics and Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Australia

6Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia

7Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia

82nd Department of Pediatrics, Semmelweis University, Budapest, Hungary

Correspondence to:

Balázs Győrffy, email: gyorffy.balazs@ttk.mta.hu

Keywords: gastric cancer, survival, meta-analysis

Received: April 07, 2016     Accepted: June 13, 2016     Published: June 30, 2016

ABSTRACT

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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