Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells

Paschalis Athanasiadis; Balaguru Ravikumar; Richard J R Elliott; John C Dawson; Neil O Carragher; Paul A Clemons; Timothy Johanssen; Daniel Ebner; Tero Aittokallio

doi:10.1016/j.isci.2023.107209

Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells

iScience. 2023 Jun 25;26(7):107209. doi: 10.1016/j.isci.2023.107209. eCollection 2023 Jul 21.

Authors

Paschalis Athanasiadis^{1

2}, Balaguru Ravikumar³, Richard J R Elliott⁴, John C Dawson⁴, Neil O Carragher⁴, Paul A Clemons⁵, Timothy Johanssen⁶, Daniel Ebner⁶, Tero Aittokallio^{1

2

3}

Affiliations

¹ Institute for Cancer Research, Department of Cancer Genetics, Oslo University Hospital, 0310 Oslo, Norway.
² Centre for Biostatistics and Epidemiology (OCBE), Faculty of Medicine, University of Oslo, 0317 Oslo, Norway.
³ Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, 20520 00290 Helsinki, Finland.
⁴ Cancer Research UK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XR, UK.
⁵ Chemical Biology and Therapeutics Science Program, Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, United States.
⁶ Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7FZ, UK.

Abstract

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.

Keywords: Cancer; Genetics.

Grants and funding

28596/CRUK_/Cancer Research UK/United Kingdom