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PLoS One ; 9(11): e111813, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25368990

RESUMO

Identification of conserved co-expression networks is a useful tool for clustering groups of genes enriched for common molecular or cellular functions [1]. The relative importance of genes within networks can frequently be inferred by the degree of connectivity, with those displaying high connectivity being significantly more likely to be associated with specific molecular functions [2]. Previously we utilized cross-species network analysis to identify two network modules that were significantly associated with distant metastasis free survival in breast cancer. Here, we validate one of the highly connected genes as a metastasis associated gene. Tpx2, the most highly connected gene within a proliferation network specifically prognostic for estrogen receptor positive (ER+) breast cancers, enhances metastatic disease, but in a tumor autonomous, proliferation-independent manner. Histologic analysis suggests instead that variation of TPX2 levels within disseminated tumor cells may influence the transition between dormant to actively proliferating cells in the secondary site. These results support the co-expression network approach for identification of new metastasis-associated genes to provide new information regarding the etiology of breast cancer progression and metastatic disease.


Assuntos
Neoplasias da Mama/genética , Redes Reguladoras de Genes , Neoplasias Pulmonares/genética , Animais , Apoptose , Neoplasias da Mama/metabolismo , Neoplasias da Mama/patologia , Proteínas de Ciclo Celular/genética , Proteínas de Ciclo Celular/metabolismo , Linhagem Celular Tumoral , Movimento Celular , Proliferação de Células , Transição Epitelial-Mesenquimal , Feminino , Técnicas de Silenciamento de Genes , Células HEK293 , Humanos , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/secundário , Camundongos , Proteínas Associadas aos Microtúbulos/genética , Proteínas Associadas aos Microtúbulos/metabolismo , Transplante de Neoplasias , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Prognóstico , Transcriptoma , Carga Tumoral
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