Development and Validation of an Easy-to-Implement, Practical Algorithm for the Identification of Molecular Subtypes of Gastric Cancer: Prognostic and Therapeutic Implications

Abstract

Background Gastric cancer (GC) is a heterogeneous disease, and substantial efforts have been made to develop a molecular biology-based classification system for GC. Analysis of the genomic signature is not always feasible, and thus, we aimed to (i) develop and validate a practical immunohistochemistry (IHC)- and polymerase chain reaction (PCR)-based molecular classification of GC and (ii) to assess HER2 status according to this classification. Materials and Methods A total of 894 consecutive patients with GC from two individual cohorts (training, n = 507; validation, n = 387) were classified using Epstein-Barr virus (EBV) in situ hybridization, microsatellite instability (MSI) testing, and IHC for E-cadherin and p53. Results We were able to classify patients into five groups in the training cohort: group 1 (MSI+), group 2 (EBV-, MSI-, non-epithelial-mesenchymal transition [non-EMT]-like, p53(-)), group 3 (EBV+), group 4 (EBV-, MSI-, non-EMT-like, p53(+)), and group 5 (EBV-, MSI-, EMT-like). In the training cohort, each group showed different overall survival (OS) after gastrectomy (p < .001); group 1 had the best prognosis, and group 5 showed the worst survival outcome. The significant impact of the classification system on OS was also verified in the validation cohort (p = .004). HER2 positivity was observed in 6.5% of total population, and most of HER2-positive cases (93.1%) were included in groups 2 and 4. Conclusion We developed and validated a modified IHC- and PCR-based molecular classification system in GC, which showed significant impact on survival, irrespective of stage or other clinical variables. We also found close association between HER2 status and non-EMT phenotype in our classification system. Implications for Practice Molecular classification of gastric cancer suggested by previous studies mostly relies on extensive genomic data analysis, which is not always available in daily practice. The authors developed a simplified immunohistochemistry- and polymerase chain reaction-based molecular classification of gastric cancer and proved the prognostic significance of this classification, as well as the close association between HER2 status and certain groups of the classification, in the largest consecutive cohort of gastric cancer. Results of this study suggest that this scheme is a cost-effective, easy-to-implement, and feasible way of classifying gastric cancer in daily clinical practice, also serving as a practical tool for aiding therapeutic decisions and predicting prognosis.