Heterogeneity in Gastric Cancer: From Pure Morphology to Molecular Classifications

Pathobiology. 2018;85(1-2):50-63. doi: 10.1159/000473881. Epub 2017 Jun 16.

Abstract

Gastric cancer (GC) represents a global health concern. Despite advances in prevention, diagnosis, and therapy, GC is still the third leading cause of cancer mortality worldwide, with more than 720,000 estimated deaths in 2012. Overall survival for advanced disease is about 1 year, a dismal prognosis that is partly due to the high levels of biological heterogeneity found in GC. Indeed, GC is a highly heterogeneous disease from morphological and molecular standpoints. The numerous histological and molecular classifications currently available reflect such heterogeneity. Although recent high-throughput studies cluster the molecular data obtained into subgroups with clinical relevance, we still need a practical, prognostic, and predictive classification system, integrating morphological and molecular features, towards the identification of novel therapeutic targets. It is noteworthy that GC heterogeneity encompasses not only interpatient variability (intertumour heterogeneity), but also variations within the same tumour (intratumour heterogeneity). The latter encompasses spatial heterogeneity (in different tumour areas) and temporal heterogeneity (along progression from primary to recurrent and/or metastatic disease). In this review, we analyse the morphological, immunophenotypic, and molecular heterogeneity in GC as the basis for a better understanding of the disease, and discuss the practical implications for diagnostic pathology, prognostic evaluation, and precision therapy.

Keywords: Gastric cancer; Intratumour heterogeneity; Molecular heterogeneity; Morphological heterogeneity; Stomach.

MeSH terms

  • Biomarkers, Tumor / genetics*
  • Disease Progression
  • Genetic Heterogeneity*
  • Humans
  • Precision Medicine
  • Prognosis
  • Stomach Neoplasms / classification*
  • Stomach Neoplasms / diagnosis
  • Stomach Neoplasms / genetics
  • Stomach Neoplasms / pathology

Substances

  • Biomarkers, Tumor