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Curr Cancer Drug Targets ; 11(7): 849-69, 2011 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-21762077

RESUMO

Gastric cancer is the leading cause of cancer-related death worldwide, and treatment options include surgery and chemotherapy. Because of its prevalence, chemotherapy for gastric cancer treatment represents an active area of pharmacology research, and different small compounds have been used as single treatments or in combination therapy. Unfortunately, chemoresistance is a common phenomenon in gastric cancer cells, and the current arsenal of small compounds used in chemotherapy is not effective for long periods of treatment. Thus, to understand how gastric cancer cells develop chemoresistance and also to find new protein targets and small compounds for gastric cancer treatment, a systems pharmacology-based study was performed using the proteomic and small compounds-protein interaction data available for Homo sapiens. A major physical protein-protein and chemo-protein interaction (PPPI-PCPI) network was obtained, and five subnetworks representing different biological processes were observed. Interestingly, the small compounds currently used to treat gastric cancer converge on the same biological processes, potentially resulting in the development of chemoresistance. This analysis was followed by a network centrality study, which allows for selection of protein targets and/or small compounds, termed bottlenecks, that are defined as central nodes. The bottlenecks control the flow of biological information within the network, and their disruption can break the entire network into small components. From ten major bottlenecks observed within the network, seven bottlenecks represent new protein targets that are suitable for the development of new combinatory drug regimens for gastric cancer treatment.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias Gástricas/tratamento farmacológico , Biologia de Sistemas , Segregação de Cromossomos , Humanos , Mapas de Interação de Proteínas
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