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Quantification of sensitivity and resistance of breast cancer cell lines to anti-cancer drugs using GR metrics.
Hafner, Marc; Heiser, Laura M; Williams, Elizabeth H; Niepel, Mario; Wang, Nicholas J; Korkola, James E; Gray, Joe W; Sorger, Peter K.
Afiliação
  • Hafner M; HMS LINCS Center, Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA.
  • Heiser LM; MEP LINCS Center, Department of Biomedical Engineering and Oregon Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR 97239 USA.
  • Williams EH; HMS LINCS Center, Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA.
  • Niepel M; HMS LINCS Center, Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA.
  • Wang NJ; MEP LINCS Center, Department of Biomedical Engineering and Oregon Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR 97239 USA.
  • Korkola JE; MEP LINCS Center, Department of Biomedical Engineering and Oregon Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR 97239 USA.
  • Gray JW; MEP LINCS Center, Department of Biomedical Engineering and Oregon Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR 97239 USA.
  • Sorger PK; HMS LINCS Center, Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA.
Sci Data ; 4: 170166, 2017 11 07.
Article em En | MEDLINE | ID: mdl-29112189
Traditional means for scoring the effects of anti-cancer drugs on the growth and survival of cell lines is based on relative cell number in drug-treated and control samples and is seriously confounded by unequal division rates arising from natural biological variation and differences in culture conditions. This problem can be overcome by computing drug sensitivity on a per-division basis. The normalized growth rate inhibition (GR) approach yields per-division metrics for drug potency (GR50) and efficacy (GRmax) that are analogous to the more familiar IC50 and Emax values. In this work, we report GR-based, proliferation-corrected, drug sensitivity metrics for ~4,700 pairs of breast cancer cell lines and perturbagens. Such data are broadly useful in understanding the molecular basis of therapeutic response and resistance. Here, we use them to investigate the relationship between different measures of drug sensitivity and conclude that drug potency and efficacy exhibit high variation that is only weakly correlated. To facilitate further use of these data, computed GR curves and metrics can be browsed interactively at http://www.GRbrowser.org/.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Antineoplásicos Tipo de estudo: Diagnostic_studies Limite: Female / Humans Idioma: En Revista: Sci Data Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Antineoplásicos Tipo de estudo: Diagnostic_studies Limite: Female / Humans Idioma: En Revista: Sci Data Ano de publicação: 2017 Tipo de documento: Article