OBJECTIVE: This update reviews the epidemiology and surgical management, and the controversies of gastric adenocarcinoma. We provide the relevance of outcome data to surgical decision-making and discuss the application of gene-expression analysis to clinical practice. SUMMARY BACKGROUND DATA: Gastric cancer mortality rates have remained relatively unchanged over the past 30 years, and gastric cancer continues to be one of the leading causes of cancer-related death. Well-conducted studies have stimulated changes to surgical decision-making and technique. Microarray studies linked to predictive outcome models are poised to advance our understanding of the biologic behavior of gastric cancer and improve surgical management and outcome. METHODS: We performed a review of the English gastric adenocarcinoma medical literature (1980-2003). This review included epidemiology, pathology and staging, surgical management, issues and controversies in management, prognostic variables, and the application of outcome models to gastric cancer. The results of DNA microarray analysis in various cancers and its predictive abilities in gastric cancer are considered. RESULTS: Prognostic studies have provided valuable data to better the understanding of gastric cancer. These studies have contributed to improved surgical technique, more accurate pathologic characterization, and the identification of clinically useful prognostic markers. The application of microarray analysis linked to predictive models will provide a molecular understanding of the biology driving gastric cancer. CONCLUSIONS: Predictive models generate important information allowing a logical evolution in the surgical and pathologic understanding and therapy for gastric cancer. However, a greater understanding of the molecular changes associated with gastric cancer is needed to guide surgical and medical therapy.
OBJECTIVE: This update reviews the epidemiology and surgical management, and the controversies of gastric adenocarcinoma. We provide the relevance of outcome data to surgical decision-making and discuss the application of gene-expression analysis to clinical practice. SUMMARY BACKGROUND DATA: Gastric cancer mortality rates have remained relatively unchanged over the past 30 years, and gastric cancer continues to be one of the leading causes of cancer-related death. Well-conducted studies have stimulated changes to surgical decision-making and technique. Microarray studies linked to predictive outcome models are poised to advance our understanding of the biologic behavior of gastric cancer and improve surgical management and outcome. METHODS: We performed a review of the English gastric adenocarcinoma medical literature (1980-2003). This review included epidemiology, pathology and staging, surgical management, issues and controversies in management, prognostic variables, and the application of outcome models to gastric cancer. The results of DNA microarray analysis in various cancers and its predictive abilities in gastric cancer are considered. RESULTS: Prognostic studies have provided valuable data to better the understanding of gastric cancer. These studies have contributed to improved surgical technique, more accurate pathologic characterization, and the identification of clinically useful prognostic markers. The application of microarray analysis linked to predictive models will provide a molecular understanding of the biology driving gastric cancer. CONCLUSIONS: Predictive models generate important information allowing a logical evolution in the surgical and pathologic understanding and therapy for gastric cancer. However, a greater understanding of the molecular changes associated with gastric cancer is needed to guide surgical and medical therapy.
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Authors: Sureyya Ozcan; Donald A Barkauskas; L Renee Ruhaak; Javier Torres; Cara L Cooke; Hyun Joo An; Serenus Hua; Cynthia C Williams; Lauren M Dimapasoc; Jae Han Kim; Margarita Camorlinga-Ponce; David Rocke; Carlito B Lebrilla; Jay V Solnick Journal: Cancer Prev Res (Phila) Date: 2013-12-10