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Bioinformatic framework for analysis of transcription factor changes as the molecular link between replicative cellular senescence signaling pathways and carcinogenesis.
Binenbaum, Ilona; Lefaki, Maria; Chondrogianni, Niki; Chatziioannou, Aristotelis.
Afiliação
  • Binenbaum I; Department of Biology, University of Patras, 26504, Patras, Greece.
  • Lefaki M; Institute of Chemical Biology, National Hellenic Research Foundation, 11635, Athens, Greece.
  • Chondrogianni N; Institute of Chemical Biology, National Hellenic Research Foundation, 11635, Athens, Greece.
  • Chatziioannou A; Institute of Chemical Biology, National Hellenic Research Foundation, 11635, Athens, Greece. nikichon@eie.gr.
Biogerontology ; 21(3): 357-366, 2020 06.
Article em En | MEDLINE | ID: mdl-32100207
ABSTRACT
Cellular senescence is a natural condition of irreversible cell cycle arrest and apoptotic resistance that occurs in cells exposed to various stress factors, such as replicative stress or overexpression of oncogenes. Unraveling the complex regulation of senescence in cells is essential to strengthen senescence-related therapeutic approaches in cancer, as cellular senescence plays a dual role in tumorigenesis, having both anti- and pro-tumorigenic effects. In our study we created a model of replicative cellular senescence, based on transcriptomic data, including an extra intermediate time-point prior to cells entering senescence, to elucidate the interplay of networks governing cellular senescence with networks involved in tumorigenesis. We reveal specific changes that occur in transcription factor activity at different timepoints before and after cells entering senescence and model the signaling networks that govern these changes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Biologia Computacional / Carcinogênese Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Biologia Computacional / Carcinogênese Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article