Abstract

IntroductionMultiple 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.ResultsThe 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 METHODSWe 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.ConclusionsThe 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.

Highlights

  • Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma

  • 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

  • There are no solid biomarkers besides human epidermal growth factor receptor 2 (HER2) [3] and regular clinicopathological parameters predicting prognosis and response to therapy, and there are no efficient therapeutic options available which prove to change the outcome of patients in a groundbreaking manner

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Summary

Introduction

Multiple gene expression based prognostic biomarkers have been repeatedly identified in gastric carcinoma. Our goal was to establish a robust database enabling the swift validation of previous and future gastric cancer survival biomarker candidates. Gastric cancer is one of the most common malignancies and displays variable incidence around the globe. The 5-year survival rate for R0 surgical resection ranges from 30 to 50% for patients with stage II and from 10 to 25% for patients with stage III disease [4]. As these patients have a high likelihood of local and systemic relapse, most centers offer them systemic therapy forming the other cornerstone of the treatment. Radiation therapy has proved to improve 5-year survival in resectable tumors [5]

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