Current and future molecular diagnostics of gastric cancer

Expert Rev Mol Diagn. 2019 Oct;19(10):863-874. doi: 10.1080/14737159.2019.1660645. Epub 2019 Aug 29.

Abstract

Introduction: Gastric cancer (GC) is the fifth most common cancer and confers the second-highest mortality among other cancers. Improving the survival rates of GC patients requires prompt and accurate diagnosis and effective treatment which is often preceded by the poorly understood pathogenic mechanisms. Area covered: This literature review aims to summarize current understanding of genetic and molecular alterations that promote carcinogenesis including (1) activation of oncogenes, (2) overexpression of growth factors, receptors and matrix metalloproteinases, (3) inactivation of tumor suppressor genes, DNA repair genes, and cell adhesion molecules and (4) alterations of cell-cycle regulators that regulate biological characteristics of cancer cells. Moreover, the significance of molecular biomarkers such as micro-RNAs (miRNAs) and long non-coding RNAs (lncRNAs) and advanced molecular techniques including droplet digital polymerase chain reaction (ddPCR), quantitative PCR (qPCR) and next-generation sequencing (NGS) are also discussed. Expert opinion: A GC-specific panel of biomarkers based on the NGS or ddPCR has the potential for diagnosis, prognosis, and monitoring treatment response in GC patients. Despite the requirements for validation in larger population in clinical studies, race-specific differences in the gene panel have also to be examined by performing the clinical trials in subjects with different races.

Keywords: Stomach cancer; circulating tumor DNA; gastric cancer; molecular diagnostics; non-invasive biomarkers; personalized medicine.

Publication types

  • Review

MeSH terms

  • Biomarkers, Tumor / genetics
  • Carcinogenesis / genetics
  • Humans
  • MicroRNAs / genetics
  • Pathology, Molecular / methods
  • Prognosis
  • RNA, Long Noncoding / genetics
  • Stomach Neoplasms / diagnosis*
  • Stomach Neoplasms / genetics*

Substances

  • Biomarkers, Tumor
  • MicroRNAs
  • RNA, Long Noncoding