title: Molecular classification of gastric adenocarcinoma: translating new insights from the cancer genome atlas research network.
abstract: Gastric cancer is a heterogenous cancer, which may be classified into several distinct subtypes based on pathology and epidemiology, each with different initiating pathological processes and each possibly having different tumor biology. A classification of gastric cancer should be important to select patients who can benefit from the targeted therapies or to precisely predict prognosis. The Cancer Genome Atlas (TCGA) study collaborated with previous reports regarding subtyping gastric cancer but also proposed a refined classification based on molecular characteristics. The addition of the new molecular classification strategy to a current classical subtyping may be a promising option, particularly stratification by Epstein-Barr virus (EBV) and microsatellite instability (MSI) statuses. According to TCGA study, EBV gastric cancer patients may benefit the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) antibodies or phosphoinositide 3-kinase (PI3K) inhibitors which are now being developed. The discoveries of predictive biomarkers should improve patient care and individualized medicine in the management since the targeted therapies may have the potential to change the landscape of gastric cancer treatment, moreover leading to both better understanding of the heterogeneity and better outcomes. Patient enrichment by predictive biomarkers for new treatment strategies will be critical to improve clinical outcomes. Additionally, liquid biopsies will be able to enable us to monitor in real-time molecular escape mechanism, resulting in better treatment strategies.
authors: Division of Medical Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, 1441 Eastlake Ave, Suite 5410, Los Angeles, CA, 90033, USA, y.suna0825@gmail.com.
authors: Yu
authors: Y
authors: Sunakawa
authors: Heinz-Josef
authors: HJ
authors: Lenz
mesh_terms: D000230:Adenocarcinoma / Q000145:classification* / Q000235:genetics / Q000473:pathology; D023281:Genomics; D006801:Humans; D013274:Stomach Neoplasms / Q000145:classification* / Q000235:genetics / Q000473:pathology