A drug screen that only rewards killing sleeping cancer cells
Nearly all cancer drugs are found by killing fast-growing cells. Sleeping cells survive them. A screen designed around dormant cells would find a different class of drug.
Dormant disseminated tumour cells are non-cycling, so proliferation-based screens are blind to them. Induced-dormancy models exist — serum-starved and matrix-confined cells, bone-marrow-niche co-cultures, three-dimensional dormancy assays — and small screens have already flagged cardiac glycosides, autophagy inhibitors and specific metabolic dependencies. Nobody has run a million-compound campaign with dormancy-selective killing as the primary readout.
- Dormant cells and minimal residual disease · After a 'successful' treatment, cells can sleep for years then relapse. We can barely detect them and cannot target them.
- Preclinical models that do not predict people · Nine in ten cancer drugs that work in mice fail in humans. Our models are the reason.
- The undruggable drivers · The proteins that drive most cancers, such as MYC, mutant p53 and most RAS variants, still have no good drug.
Pages like this
not linked directly; found by shared links- IdeaAn open engine that ranks every drug pair by predicted synergy before anyone runs a trial
Shares DrugBank & ChEMBL, DepMap (Cancer Dependency Map), CRISPR functional genomics, Patient-derived organoids.
- IdeaA bone marrow niche on a chip to study human dormancy
Shares Functional (ex vivo) drug testing, Patient-derived organoids, Dormant cells and minimal residual disease, Preclinical models that do not predict people.
- IdeaMake in vivo metastasis screens a required step in drug discovery
Shares DepMap (Cancer Dependency Map), CRISPR functional genomics, Patient-derived organoids, Preclinical models that do not predict people.
- IdeaEvery drug screen includes standard reference compounds whose performance is published
Shares DepMap (Cancer Dependency Map), Functional (ex vivo) drug testing, CRISPR functional genomics, Preclinical models that do not predict people.
- IdeaEvery resistance mechanism found in a patient must be rebuilt in the laboratory
Shares Functional (ex vivo) drug testing, CRISPR functional genomics, Preclinical models that do not predict people.
- Key paperDefining a Cancer Dependency Map: which genes each cancer cell line cannot live without
Shares DepMap (Cancer Dependency Map), Functional (ex vivo) drug testing, CRISPR functional genomics, Preclinical models that do not predict people.
- IdeaA public atlas of drug-pair responses across a thousand patient-derived organoids
Shares DepMap (Cancer Dependency Map), Functional (ex vivo) drug testing, Patient-derived organoids, Preclinical models that do not predict people.
- IdeaAn open model bank for the rare tumours nobody has models for
Shares DepMap (Cancer Dependency Map), Functional (ex vivo) drug testing, Patient-derived organoids, Preclinical models that do not predict people.