Published online Nov 7, 2015. doi: 10.3748/wjg.v21.i41.11636
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
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.
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.