Integrated High-Throughput Screening and Large-Scale Isobolographic Analysis to Accelerate the Discovery of Radiosensitizers With Greater Selectivity for Cancer Cells.


Journal

International journal of radiation oncology, biology, physics
ISSN: 1879-355X
Titre abrégé: Int J Radiat Oncol Biol Phys
Pays: United States
ID NLM: 7603616

Informations de publication

Date de publication:
01 Apr 2024
Historique:
received: 05 04 2023
revised: 15 09 2023
accepted: 19 09 2023
medline: 18 3 2024
pubmed: 2 10 2023
entrez: 1 10 2023
Statut: ppublish

Résumé

High-throughput screening (HTS) platforms have been widely used to identify candidate anticancer drugs and drug-drug combinations; however, HTS-based identification of new drug-ionizing radiation (IR) combinations has rarely been reported. Herein, we developed an integrated approach including cell-based HTS and computational large-scale isobolographic analysis to accelerate the identification of radiosensitizing compounds acting strongly and more specifically on cancer cells. In a 384-well plate format, 160 compounds likely to interfere with the cell response to radiation were screened on human glioblastoma (U251-MG) and cervix carcinoma (ME-180) cell lines, as well as on normal fibroblasts (CCD-19Lu). After drug exposure, cells were irradiated or not and short-term cell survival was assessed by high-throughput cell microscopy. Computational large-scale dose-response and isobolographic approach were used to identify promising synergistic drugs radiosensitizing cancer cells rather than normal cells. Synergy of a promising compound was confirmed on ME-180 cells by an independent 96-well assay protocol, and finally, by the gold-standard colony forming assay. We retained 4 compounds synergistic at 2 isoeffects in U251-MG and ME-180 cell lines and 11 compounds synergistically effective in only one cancer cell line. Among these 15 promising radiosensitizers, 5 compounds showed limited toxicity combined or not with IR on normal fibroblasts. Overall, this study demonstrated that HTS chemoradiation screening together with large-scale computational analysis is an efficient tool to identify synergistic drug-IR combinations, with concomitant assessment of unwanted toxicity on normal fibroblasts. It sparks expectations to accelerate the discovery of highly desired agents improving the therapeutic index of radiation therapy.

Identifiants

pubmed: 37778425
pii: S0360-3016(23)07958-0
doi: 10.1016/j.ijrobp.2023.09.044
pii:
doi:

Substances chimiques

Radiation-Sensitizing Agents 0
Antineoplastic Agents 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1294-1307

Informations de copyright

Copyright © 2023 Elsevier Inc. All rights reserved.

Auteurs

Pierre Verrelle (P)

Radiation Oncology Department, Institut Curie Hospital, Paris, France; Chemistry and Modelisation for the Biology of Cancer, CNRS UMR9187, INSERM U1196, Institut Curie, Université Paris Saclay, 91405 Orsay, France. Electronic address: pierre.verrelle@curie.fr.

Pierre Gestraud (P)

Chemistry and Modelisation for the Biology of Cancer, CNRS UMR9187, INSERM U1196, Institut Curie, Université Paris Saclay, 91405 Orsay, France.

Florent Poyer (F)

Chemistry and Modelisation for the Biology of Cancer, CNRS UMR9187, INSERM U1196, Institut Curie, Université Paris Saclay, 91405 Orsay, France.

Adèle Soria (A)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France.

Sarah Tessier (S)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France.

Aurianne Lescure (A)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France.

Elodie Anthony (E)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France.

Maxime Corbé (M)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France.

Sophie Heinrich (S)

Experimental Radiotherapy Platform (RadeXp), Translational Research Department, Institut Curie, Orsay, France; Inserm U1021-CNRS UMR 3347, Institut Curie, Paris Saclay University.

Claire Beauvineau (C)

Bioinformatics and Computational Systems Biology of Cancer, PSL Research University, Mines Paris Tech, INSERM U900, Paris, France.

Ludovic Chaput (L)

Bioinformatics and Computational Systems Biology of Cancer, PSL Research University, Mines Paris Tech, INSERM U900, Paris, France.

Anton Granzhan (A)

Bioinformatics and Computational Systems Biology of Cancer, PSL Research University, Mines Paris Tech, INSERM U900, Paris, France.

Sandrine Piguel (S)

Bioinformatics and Computational Systems Biology of Cancer, PSL Research University, Mines Paris Tech, INSERM U900, Paris, France; BioCIS UMR8076, Université Paris-Saclay, Faculté de Pharmacie, Orsay, France.

Franck Perez (F)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France; Cell Biology and Cancer UMR144, Institut Curie, PSL Research University, Paris, France.

Marie-Paule Teulade-Fichou (MP)

Chemistry and Modelisation for the Biology of Cancer, CNRS UMR9187, INSERM U1196, Institut Curie, Université Paris Saclay, 91405 Orsay, France.

Frédérique Megnin-Chanet (F)

Bioinformatics and Computational Systems Biology of Cancer, PSL Research University, Mines Paris Tech, INSERM U900, Paris, France.

Elaine Del Nery (E)

Biophenics High-Content Screening Laboratory, Department of Translational Research, PSL Research University, PICT-IBiSa, Institut Curie Research Center, Paris, France. Electronic address: elaine.del.nery@curie.fr.

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Classifications MeSH