Title:Characterizing the Relationship Between the Chemical Structures of Drugs and their Activities on Primary Cultures of Pediatric Solid Tumors
Volume: 28
Issue: 38
Author(s): Saw Simeon, Ghita Ghislat and Pedro Ballester*
Affiliation:
- Centre de Recherche en Cancerologie de Marseille (CRCM), Inserm, U1068, Marseille, F-13009, France. CNRS, UMR7258, Marseille, F-13009, France. Institut Paoli-Calmettes, Marseille, F-13009, France. Aix-- Marseille University, UM 105, F-13284, Marseille,France
Keywords:
Chemoinformatics, Data mining, pediatric cancers, patient-derived xenografts, machine learning,
QSAR.
Abstract:
Background: Despite continued efforts to develop new treatments, there is an
urgent need to discover new drug leads to treat tumors exhibiting primary or secondary
resistance to existing drugs. Cell cultures derived from patient-derived orthotopic xenografts
are promising pre-clinical models to better predict drug response in cancer recurrence.
Objective: The aim of the study was to investigate the relationship between the physiochemical
properties of drugs and their in vitro potency as well as identifying chemical
scaffolds biasedtowards selectivity or promiscuity of such drugs.
Methods: The bioactivities of 158 drugs screened against cell cultures derived from 30
cancer orthotopic patient-derived xenograft (O-PDX) models were considered. Drugs
were represented by physicochemical descriptors and chemical structure fingerprints. Supervised
learning was employed to model the relationship between features and in vitro
potency.
Results: Drugs with in vitro potency for alveolar rhabdomyosarcoma and osteosarcoma
tend to have a higher number of rings, two carbon-hetero bonds and halogens. Selective
and promiscuous scaffolds for these phenotypic targets were identified. Highly-predictive
models of in vitro potency were obtained across these 30 targets, which can be applied
to unseen molecules via a webserver (https://rnewbie.shinyapps.io/Shobek-master).
Conclusion: It is possible to identify privileged chemical scaffolds and predict the in vitro
potency of unseen molecules across these 30 targets This information and models
should be helpful to select which molecules to screen against these primary cultures of pediatric
solid tumors.
