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Meta-Analysis
. 2018 Sep 5;8(1):13281.
doi: 10.1038/s41598-018-31548-6.

A systematic review and meta-analysis of prognostic biomarkers in resectable esophageal adenocarcinomas

Aafke Creemers  1   2 , Eva A Ebbing  3   4 , Thomas C Pelgrim  4 , Sjoerd M Lagarde  5 , Faridi S van Etten-Jamaludin  6 , Mark I van Berge Henegouwen  7 , Maarten C C M Hulshof  8 , Kausilia K Krishnadath  3   9 , Sybren L Meijer  10 , Maarten F Bijlsma  3 , Martijn G H van Oijen  4 , Hanneke W M van Laarhoven  3   4
Affiliations
Meta-Analysis

A systematic review and meta-analysis of prognostic biomarkers in resectable esophageal adenocarcinomas

Aafke Creemers et al. Sci Rep. .

Abstract

Targeted therapy is lagging behind in esophageal adenocarcinoma (EAC). To guide the development of new treatment strategies, we provide an overview of the prognostic biomarkers in resectable EAC treated with curative intent. The Medline, Cochrane and EMBASE databases were systematically searched, focusing on overall survival (OS). The quality of the studies was assessed using a scoring system ranging from 0-7 points based on modified REMARK criteria. To evaluate all identified prognostic biomarkers, the hallmarks of cancer were adapted to fit all biomarkers based on their biological function in EAC, resulting in the features angiogenesis, cell adhesion and extra-cellular matrix remodeling, cell cycle, immune, invasion and metastasis, proliferation, and self-renewal. Pooled hazard ratios (HR) and 95% confidence intervals (CI) were derived by random effects meta-analyses performed on each hallmarks of cancer feature. Of the 3298 unique articles identified, 84 were included, with a mean quality of 5.9 points (range 3.5-7). The hallmarks of cancer feature 'immune' was most significantly associated with worse OS (HR 1.88, (95%CI 1.20-2.93)). Of the 82 unique prognostic biomarkers identified, meta-analyses showed prominent biomarkers, including COX-2, PAK-1, p14ARF, PD-L1, MET, LC3B, IGFBP7 and LGR5, associated to each hallmark of cancer.

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Conflict of interest statement

Dr. Maarten F. Bijlsma has received research funding from Celgene. Dr. Martijn G. H. van Oijen has received unrestricted research grants from Bayer, Lilly, Merck Serono, and Roche. Prof. dr. Hanneke W. M. van Laarhoven has served as a consultant for Celgene, BMS, Lilly, and Nordic, and has received unrestricted research funding from Bayer, BMS, Celgene, Lilly, Merck Serono, MSD, Nordic, Philips and Roche. None of these parties was involved in drafting this review. All remaining authors have declared no conflicts of interest.

Figures

Figure 1
Figure 1
Flow-chart of included articles.
Figure 2
Figure 2
Random-effect Forest plot of prognostic biomarkers included in the adapted hallmark of cancer ‘proliferation’. EGFR, Cyclin D1, mTOR and HER2 were pooled as subgroup.
Figure 3
Figure 3
All identified biomarkers and adapted hallmarks of cancer are summarized in the Ferris Wheel Plot. The area of each adapted hallmark of cancer represents the amount of articles with data on the corresponding hallmark of cancer. The most promising prognostic biomarkers according to our meta-analysis are highlighted. In the inner circle the hazard ratios (HR) and 95% Confidence Intervals (95%CI) are reported for each adapted hallmark of cancer.
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