Abstract / Description of output
We identified a number of phenotypic clusters enriched with similar pharmacological classes e.g. Methotrexate and three other antimetabolites which are highly selective for OAC cell lines. We further identify a small number of hits from our diverse chemical library which show potent and selective activity for OAC cell lines and which do not cluster with the reference library of compounds, indicating they may be selectively targeting novel oesophageal cancer biology. Overall our results demonstrate that our OAC phenotypic screening platform can identify existing pharmacological classes and novel compounds with selective activity for OAC cell phenotypes.
Keywords / Materials (for Non-textual outputs)
- esophageal adenocarcinoma
- high content
- mechanism of action
- machine learning
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Deanery of Molecular, Genetic and Population Health Sciences
Alison Munro (Manager) & Kenneth Macleod (Other)Deanery of Molecular, Genetic and Population Health Sciences