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The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies.
Diaz, Jennifer El; Ahsen, Mehmet Eren; Schaffter, Thomas; Chen, Xintong; Realubit, Ronald B; Karan, Charles; Califano, Andrea; Losic, Bojan; Stolovitzky, Gustavo.
Afiliação
  • Diaz JE; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, United States.
  • Ahsen ME; Department of Cell, Developmental, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, United States.
  • Schaffter T; IBM Computational Biology Center, IBM Research, Yorktown Heights, United States.
  • Chen X; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, United States.
  • Realubit RB; IBM Computational Biology Center, IBM Research, Yorktown Heights, United States.
  • Karan C; Department of Business Administration, University of Illinois at Urbana-Champaign, Champaign, United States.
  • Califano A; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, United States.
  • Losic B; IBM Computational Biology Center, IBM Research, Yorktown Heights, United States.
  • Stolovitzky G; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, United States.
Elife ; 92020 09 18.
Article em En | MEDLINE | ID: mdl-32945258
ABSTRACT
Our ability to discover effective drug combinations is limited, in part by insufficient understanding of how the transcriptional response of two monotherapies results in that of their combination. We analyzed matched time course RNAseq profiling of cells treated with single drugs and their combinations and found that the transcriptional signature of the synergistic combination was unique relative to that of either constituent monotherapy. The sequential activation of transcription factors in time in the gene regulatory network was implicated. The nature of this transcriptional cascade suggests that drug synergy may ensue when the transcriptional responses elicited by two unrelated individual drugs are correlated. We used these results as the basis of a simple prediction algorithm attaining an AUROC of 0.77 in the prediction of synergistic drug combinations in an independent dataset.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Expressão Gênica / Combinação de Medicamentos / Sinergismo Farmacológico / Redes Reguladoras de Genes / Transcriptoma Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Elife Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Expressão Gênica / Combinação de Medicamentos / Sinergismo Farmacológico / Redes Reguladoras de Genes / Transcriptoma Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Elife Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos