Classifying Gastric Cancers by Subtype May Provide Tailored Treatment Options
Gastric cancer is the third leading cause of cancer death in both men and women worldwide. In 2014, The Cancer Genome Atlas (TCGA) project discovered there are four molecular subtypes of gastric cancer: Epstein-Barr virus (EBV), microsatellite instability (MSI), genomically stable (GS), and chromosomal instability (CIN). However, their clinical significance is unknown.
Now, a study by Sohn et al investigating the relationship between subtypes and prognosis of patients with gastric cancer has found the molecular classification of the four distinct subtypes of gastric cancer may potentially provide tailored treatment options by helping physicians to predict survival outcomes and patients’ response to chemotherapy. Further development of the prediction model is necessary before it can be implemented into clinical practice, noted the study authors. The study was published in Clinical Cancer Research.
Study Methodology
The researchers analyzed gene-expression data of the four subtypes of gastric cancer using genomic data from the TCGA project gastric cancer cohort (n = 262) to develop a subtype prediction model. The association of each subtype with survival and benefit from adjuvant chemotherapy was tested in two other cohorts (n = 267 and 432). An integrated risk-assessment model (TCGA risk score) was also developed.
Study Results
The researchers found that the EBV subtype was associated with the best prognosis, and the GS subtype was associated with the worst prognosis. Patients with MSI and CIN subtypes had poorer overall survival than those with the EBV subtype but better overall survival than those with the GS subtype (P = .004 and .03 in the two cohorts, respectively).
In multivariate Cox regression analysis, the TCGA risk score was an independent prognostic factor (hazard ratio [HR] = 1.5; 95% confidence interval [CI] = 1.2–1.9; P = .001). Patients with the CIN subtype experienced the greatest benefit from adjuvant chemotherapy (HR = 0.39; 95% CI = 0.16–0.94; P = .03), and those with the GS subtype had the least benefit from adjuvant chemotherapy (HR = 0.83; 95% CI = 0.36–1.89; P = .65.
Clinical Significance
“The validation of our prediction model in two independent patient cohorts and the fact that the model reflects the biological characteristics associated with each subtype indicate this prediction model could be used to develop rational therapy recommendations. If confirmed in prospective studies, the association between subtype and adjuvant chemotherapy outcomes might improve patient selection for treatment,” concluded the study authors.
“These findings, if confirmed, could provide some information for personalized medicine,” said Ju-Seog Lee, PhD, Associate Professor in the Department of Systems Biology at The University of Texas MD Anderson Cancer Center in Houston, and a coauthor of the study, in a statement. “As we learn more about the biological characteristics associated with each subtype, it will help determine which patients will benefit from immunotherapy, chemotherapy, or other treatment options.”
Funding for this study was provided by the National Institutes of Health, The University of Texas MD Anderson Cancer Center, the Korea National Research Foundation, the Scientific Research Center Program, and the Korean Research Institute of Bioscience and Biotechnology.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
