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Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells
Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjus...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359939/ https://www.ncbi.nlm.nih.gov/pubmed/37485377 http://dx.doi.org/10.1016/j.isci.2023.107209 |
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author | Athanasiadis, Paschalis Ravikumar, Balaguru Elliott, Richard J.R. Dawson, John C. Carragher, Neil O. Clemons, Paul A. Johanssen, Timothy Ebner, Daniel Aittokallio, Tero |
author_facet | Athanasiadis, Paschalis Ravikumar, Balaguru Elliott, Richard J.R. Dawson, John C. Carragher, Neil O. Clemons, Paul A. Johanssen, Timothy Ebner, Daniel Aittokallio, Tero |
author_sort | Athanasiadis, Paschalis |
collection | PubMed |
description | Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjusted for library size, cellular activity, chemical diversity and availability, and target selectivity. The resulting compound collections cover a wide range of protein targets and biological pathways implicated in various cancers, making them widely applicable to precision oncology. We characterized the compound and target spaces of the virtual libraries, in comparison with a minimal screening library of 1,211 compounds for targeting 1,386 anticancer proteins. In a pilot screening study, we identified patient-specific vulnerabilities by imaging glioma stem cells from patients with glioblastoma (GBM), using a physical library of 789 compounds that cover 1,320 of the anticancer targets. The cell survival profiling revealed highly heterogeneous phenotypic responses across the patients and GBM subtypes. |
format | Online Article Text |
id | pubmed-10359939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103599392023-07-22 Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells Athanasiadis, Paschalis Ravikumar, Balaguru Elliott, Richard J.R. Dawson, John C. Carragher, Neil O. Clemons, Paul A. Johanssen, Timothy Ebner, Daniel Aittokallio, Tero iScience Article Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjusted for library size, cellular activity, chemical diversity and availability, and target selectivity. The resulting compound collections cover a wide range of protein targets and biological pathways implicated in various cancers, making them widely applicable to precision oncology. We characterized the compound and target spaces of the virtual libraries, in comparison with a minimal screening library of 1,211 compounds for targeting 1,386 anticancer proteins. In a pilot screening study, we identified patient-specific vulnerabilities by imaging glioma stem cells from patients with glioblastoma (GBM), using a physical library of 789 compounds that cover 1,320 of the anticancer targets. The cell survival profiling revealed highly heterogeneous phenotypic responses across the patients and GBM subtypes. Elsevier 2023-06-25 /pmc/articles/PMC10359939/ /pubmed/37485377 http://dx.doi.org/10.1016/j.isci.2023.107209 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Athanasiadis, Paschalis Ravikumar, Balaguru Elliott, Richard J.R. Dawson, John C. Carragher, Neil O. Clemons, Paul A. Johanssen, Timothy Ebner, Daniel Aittokallio, Tero Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
title | Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
title_full | Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
title_fullStr | Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
title_full_unstemmed | Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
title_short | Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
title_sort | chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359939/ https://www.ncbi.nlm.nih.gov/pubmed/37485377 http://dx.doi.org/10.1016/j.isci.2023.107209 |
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