Identificación de asociaciones clínico-patológicas e hipermetilación de genes supresores de tumores en cáncer gástrico difuso a través de análisis de Hierarchical clustering

• Luis Zavala G ; Víctor Luengo J ; Francisco Ossandón C ; Erick Riquelme S ^[1] ; Claudia Backhouse E ^[3] ; Mariana Palma V ^[3] ; Jorge Argandoña C ^[3] ; Miguel Angel Cumsille ^[2] ; Alejandro Corvalán R ^[1]
  1. [1] Pontificia Universidad Católica de Chile

     Pontificia Universidad Católica de Chile

     Santiago, Chile

     
  2. [2] Universidad de Chile

     Universidad de Chile

     Santiago, Chile

     
  3. [3] Hospital Clínico-San Borja Arriarán Instituto Chileno Japonés de Enfermedades Digestivas

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• Localización: Revista Médica de Chile, ISSN-e 0034-9887, Vol. 135, Nº. 1, 2007, págs. 17-25
• Idioma: español
• Títulos paralelos:
  • Hierarchical clustering analysis to detect associations between clinical and pathological features of gastric tumors and hypermethylation of suppressor genes
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• Resumen

  • Background:Methylation is an inactivation mechanism for tumor suppressor genes, that can have important clinical implications. Aim: To analyze the methylation status of 11 tumor suppressor genes in pathological samples of diffuse gastric cancer. Material and methods: Eighty three patients with diffuse gastric cancer with information about survival and infection with Epstein Barr virus, were studied. DNA was extracted from pathological slides and the methylation status of genes p14, p15, p16, APC, p73, FHIT, E-caderin, SEMA3B, BRCA-1, MINT-2 y MGMT, was studied using sodium bisulphite modification and polymerase chain reaction. Results were grouped according to the methylation index or Hierarchical clustering (TIGR MultiExperiment Viewer). Results: Three genes had a high frequency of methylation (FHIT, BRCA1, APC), four had an intermediate frequency (p15, MGMT, p14, MINT2) and four had a low frequency (p16, p73, E-cadherin, SEMA3B). The methylation index had no association with clinical or pathological features of tumors or patients survival. Hierarchical clustering generated two clusters. One grouped clinical and pathological features with FHIT, BRCA1, and APC and the other grouped the other eight genes and Epstein Barr virus infection. Two significant associations were found, between APC and survival and p16/p14 and Epstein Barr virus infection. Conclusions: Hierarchical clustering is a tool that identifies associations between clinical and pathological features of tumors and methylation of tumor suppressor genes