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Record W4292241648 · doi:10.1136/jitc-2022-004660

Protein kinase inhibitor ceritinib blocks ectonucleotidase CD39 – a promising target for cancer immunotherapy

2022· article· en· W4292241648 on OpenAlexafffund
Laura Schäkel, Salahuddin Mirza, Riekje Winzer, Vittoria Lopez, Riham M. Idris, Haneen Al-Hroub, Julie Pelletier, Jean Sévigny, Eva Tolosa, Christa E. Müller

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
FundersUniversitätsklinikum Hamburg-EppendorfNatural Sciences and Engineering Research Council of CanadaBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftUniversité Laval
KeywordsAdenosineCancer researchCeritinibCancer cellPharmacologyKinaseChemistryAdenosine kinaseCancerMedicineLung cancerBiochemistryAnaplastic lymphoma kinaseAdenosine deaminaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: receptors on immune cells constituting one of the strongest immunosuppressive mediators. In addition, extracellular adenosine promotes angiogenesis, tumor cell proliferation, and metastasis. Cancer cells upregulate ectonucleotidases, most importantly CD39 and CD73, which catalyze the hydrolysis of extracellular ATP to AMP (CD39) and further to adenosine (CD73). Inhibition of CD39 is thus expected to be an effective strategy for the (immuno)therapy of cancer. However, suitable small molecule inhibitors for CD39 are not available. Our aim was to identify drug-like CD39 inhibitors and evaluate them in vitro. METHODS: We pursued a repurposing approach by screening a self-compiled collection of approved, mostly ATP-competitive protein kinase inhibitors, on human CD39. The best hit compound was further characterized and evaluated in various orthogonal assays and enzyme preparations, and on human immune and cancer cells. RESULTS: The tyrosine kinase inhibitor ceritinib, a potent anticancer drug used for the treatment of anaplastic lymphoma kinase (ALK)-positive metastatic non-small cell lung cancer, was found to strongly inhibit CD39 showing selectivity versus other ectonucleotidases. The drug displays a non-competitive, allosteric mechanism of CD39 inhibition exhibiting potency in the low micromolar range, which is independent of substrate (ATP) concentration. We could show that ceritinib inhibits ATP dephosphorylation in peripheral blood mononuclear cells in a dose-dependent manner, resulting in a significant increase in ATP concentrations and preventing adenosine formation from ATP. Importantly, ceritinib (1-10 µM) substantially inhibited ATP hydrolysis in triple negative breast cancer and melanoma cells with high native expression of CD39. CONCLUSIONS: CD39 inhibition might contribute to the effects of the powerful anticancer drug ceritinib. Ceritinib is a novel CD39 inhibitor with high metabolic stability and optimized physicochemical properties; according to our knowledge, it is the first brain-permeant CD39 inhibitor. Our discovery will provide the basis (i) to develop more potent and balanced dual CD39/ALK inhibitors, and (ii) to optimize the ceritinib scaffold towards interaction with CD39 to obtain potent and selective drug-like CD39 inhibitors for future in vivo studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.301
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2022
Admission routes2
Has abstractyes

Explore more

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