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Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 7, 2015; 21(41): 11636-11653
Published online Nov 7, 2015. doi: 10.3748/wjg.v21.i41.11636
Emerging blood-based biomarkers for detection of gastric cancer
Zane Kalniņa, Irēna Meistere, Ilze Kikuste, Ivars Tolmanis, Pawel Zayakin, Aija Linē
Zane Kalniņa, Irēna Meistere, Pawel Zayakin, Aija Linē, Latvian Biomedical Research and Study Centre, Riga, 1067 LV, Latvia
Ilze Kikuste, Ivars Tolmanis, Digestive Diseases Centre GASTRO, Riga, 1006 LV, Latvia
Ilze Kikuste, Faculty of Medicine, University of Latvia, Riga, 1586 LV, Latvia
Author contributions: Kalniņa Z and Meistere I equally contributed to the collection of data and writing the manuscript; Kikuste I and Tolmanis I contributed to collection of data and writing individual sections of the manuscript; Zayakin P assisted in collection of data; Linē A supervised the work and revised the manuscript.
Supported by ERDF project, No. 2013/0052/2DP/2.1.1.1.0/13APIA/VIAA/019.
Conflict-of-interest statement: The authors have no conflicts of interest to report.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Aija Linē, PhD, Latvian Biomedical Research and Study Centre, Cancer Biomarker Group, Ratsupites Str 1, k-1, LV-1067, Riga, 1067 LV, Latvia. aija@biomed.lu.lv
Telephone: +371-7808208 Fax: +371-7442407
Received: May 9, 2015
Peer-review started: May 11, 2015
First decision: June 23, 2015
Revised: July 8, 2015
Accepted: September 30, 2015
Article in press: September 30, 2015
Published online: November 7, 2015
Abstract

Early detection and efficient monitoring of tumor dynamics are prerequisites for reducing disease burden and mortality, and for improving the management of patients with gastric cancer (GC). Blood-based biomarker assays for the detection of early-stage GC could be of great relevance both for population-wide or risk group-based screening programs, while circulating biomarkers that reflect the genetic make-up and dynamics of the tumor would allow monitoring of treatment efficacy, predict recurrences and assess the genetic heterogeneity of the tumor. Recent research to identify blood-based biomarkers of GC has resulted in the identification of a wide variety of cancer-associated molecules, including various proteins, autoantibodies against tumor associated antigens, cell-free DNA fragments, mRNAs and various non-coding RNAs, circulating tumor cells and cancer-derived extracellular vesicles. Each type of these biomarkers provides different information on the disease status, has different advantages and disadvantages, and distinct clinical usefulness. In the current review, we summarize the recent developments in blood-based GC biomarker discovery, discuss the origin of various types of biomarkers and their clinical usefulness and the technological challenges in the development of biomarker assays for clinical use.

Keywords: Gastric cancer, Biomarker, Liquid biopsy, Cell-free DNA, Cell-free RNA, Extracellular vesicles, Autoantibodies, Proteomics

Core tip: The identification of blood-based biomarkers that could reliably detect the presence of early-stage gastric cancer or provide means to monitor the tumor dynamics is an unmet clinical need. Recently, considerable effort has been devoted to discovering various types of cancer-associated molecules in the blood of gastric cancer patients, and this has resulted in establishing biomarker models with remarkably high sensitivity and specificity. However, a validation in large-scale studies and a head-to-head comparison of the biomarker models and technologies are required before these biomarkers can be used in routine clinical practice.