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A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve

Gene expression data before and after treatment with an individual drug and the IC(20) of dose–response data were utilized to predict two drugs' interaction effects on a diffuse large B-cell lymphoma (DLBCL) cancer cell. A novel drug interaction scoring algorithm was developed to account for ei...

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Autores principales: Goswami, C Pankaj, Cheng, L, Alexander, PS, Singal, A, Li, L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4360667/
https://www.ncbi.nlm.nih.gov/pubmed/26225234
http://dx.doi.org/10.1002/psp4.9
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author Goswami, C Pankaj
Cheng, L
Alexander, PS
Singal, A
Li, L
author_facet Goswami, C Pankaj
Cheng, L
Alexander, PS
Singal, A
Li, L
author_sort Goswami, C Pankaj
collection PubMed
description Gene expression data before and after treatment with an individual drug and the IC(20) of dose–response data were utilized to predict two drugs' interaction effects on a diffuse large B-cell lymphoma (DLBCL) cancer cell. A novel drug interaction scoring algorithm was developed to account for either synergistic or antagonistic effects between drug combinations. Different core gene selection schemes were investigated, which included the whole gene set, the drug-sensitive gene set, the drug-sensitive minus drug-resistant gene set, and the known drug target gene set. The prediction scores were compared with the observed drug interaction data at 6, 12, and 24 hours with a probability concordance (PC) index. The test result shows the concordance between observed and predicted drug interaction ranking reaches a PC index of 0.605. The scoring reliability and efficiency was further confirmed in five drug interaction studies published in the GEO database.
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spelling pubmed-43606672015-03-23 A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve Goswami, C Pankaj Cheng, L Alexander, PS Singal, A Li, L CPT Pharmacometrics Syst Pharmacol Original Articles Gene expression data before and after treatment with an individual drug and the IC(20) of dose–response data were utilized to predict two drugs' interaction effects on a diffuse large B-cell lymphoma (DLBCL) cancer cell. A novel drug interaction scoring algorithm was developed to account for either synergistic or antagonistic effects between drug combinations. Different core gene selection schemes were investigated, which included the whole gene set, the drug-sensitive gene set, the drug-sensitive minus drug-resistant gene set, and the known drug target gene set. The prediction scores were compared with the observed drug interaction data at 6, 12, and 24 hours with a probability concordance (PC) index. The test result shows the concordance between observed and predicted drug interaction ranking reaches a PC index of 0.605. The scoring reliability and efficiency was further confirmed in five drug interaction studies published in the GEO database. BlackWell Publishing Ltd 2015-02 2015-02-19 /pmc/articles/PMC4360667/ /pubmed/26225234 http://dx.doi.org/10.1002/psp4.9 Text en © The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Articles
Goswami, C Pankaj
Cheng, L
Alexander, PS
Singal, A
Li, L
A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve
title A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve
title_full A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve
title_fullStr A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve
title_full_unstemmed A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve
title_short A New Drug Combinatory Effect Prediction Algorithm on the Cancer Cell Based on Gene Expression and Dose–Response Curve
title_sort new drug combinatory effect prediction algorithm on the cancer cell based on gene expression and dose–response curve
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4360667/
https://www.ncbi.nlm.nih.gov/pubmed/26225234
http://dx.doi.org/10.1002/psp4.9
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