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World J Gastroenterol. Oct 14, 2014; 20(38): 13648-13657
Published online Oct 14, 2014. doi: 10.3748/wjg.v20.i38.13648
Proteomic and metabolic prediction of response to therapy in gastric cancer
Michaela Aichler, Birgit Luber, Florian Lordick, Axel Walch
Michaela Aichler, Research Unit Analytical Pathology - Institute of Pathology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
Birgit Luber, Institute of Pathology, Technische Universität München, Trogerstraße 18, 81675 München, Germany
Florian Lordick, University Cancer Center Leipzig, University of Leipzig, Liebigstraße 20, 04103 Leipzig, Germany
Axel Walch, Research Unit Analytical Pathology, Institute of Pathology, Helmholtz Zentrum München, German Research Centre for Environmental Health, 85764 Neuherberg, Germany
Author contributions: All authors contributed in writing this review.
Supported by Ministry of Education and Research of the Federal Republic of Germany, Grant No. 0315508A and No. 01IB10004E (to AW), SYS-Stomach to BL, FL and AW); and the Deutsche Forschungsgemeinschaft, Grant No. HO 1258/3-1, No. SFB 824 TP Z02 and No. WA 1656/3-1 (to AW)
Correspondence to: Axel Walch, MD, Professor, Research Unit Analytical Pathology, Institute of Pathology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany. axel.walch@helmholtz-muenchen.de
Telephone: +49-89-31872739 Fax: +49-89-31873349
Received: December 9, 2013
Revised: February 4, 2014
Accepted: June 13, 2014
Published online: October 14, 2014
Core Tip

Core tip: The prognosis of patients diagnosed with gastric cancer is still poor. Cytotoxic treatment and targeted therapies have improved the prognosis of patients. However, patients do not benefit equally from these treatment options. The ability to predict whether patients will respond to specific therapies would be of particular value and would allow for stratifying patients for personalized treatment strategies. In this review, we discuss the status of targeted therapies for gastric cancer, as well as proteomic and metabolic methods for investigating biomarkers for therapy response prediction in gastric cancer.