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Record W4393095905 · doi:10.1158/1538-7445.am2024-1955

Abstract 1955: Novel long-acting covalent PI3Kα inhibitors boost potential action in cancer

2024· article· en· W4393095905 on OpenAlexaff
Theodora A. Constantin, Lukas Bissegger, Erhan Keleş, Luka Raguž, Clara Orbegozo, Thorsten Schaefer, Isobel Barlow-Busch, John E. Burke, Chiara Borsari, Matthias P. Wymann

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsCancerAction (physics)MedicinePI3K/AKT/mTOR pathwayPharmacologyCancer researchChemistryInternal medicineBiochemistrySignal transductionPhysics

Abstract

fetched live from OpenAlex

Abstract Phosphoinositide 3-kinase (PI3K) is a key regulator of cell proliferation, survival, and metabolism. Hotspot mutations in the PIK3CA gene constitutively activate the catalytic subunit of the PI3Kα isoform and are found in 10-30% of solid tumors. The development of PI3K pathway inhibitors has been hampered by poor drug tolerance and release of negative feedback loops, leading to rapid reactivation of signaling in response to reversible inhibitors. To remedy these challenges, we developed highly selective covalent PI3Kα inhibitors that irreversibly bind to a non-conserved cysteine (C862) located 11 Å outside the ATP-binding site. Here we present the properties of an optimized drug-like covalent lead, dubbed compound 9, and describe the generation of a biotinylated probe developed to be used in conjunction with compound 9 to monitor PI3Kα target occupancy in relation to downstream PI3K signaling outputs. Biochemical investigations of compound 9 using TR-FRET assays showed high affinity binding (Ki), high reaction rates (kinact) for covalent bond formation with PI3Kα, and negligible off-target reactivity. Cellular NanoBRET assays revealed that compound 9 diffuses three times more rapidly into cells as compared to BYL719 (alpelisib), and leads to rapid and potent on-target engagement. Covalent bond formation to residue C862 of PI3Kα was further confirmed by X-ray crystallography. In PIK3CA mutant cancer cell lines, covalent binding of PI3Kα occurred at low nanomolar concentrations and led to persistent inhibition of Akt/PKB phosphorylation for more than 72 hours after drug removal. Notably, investigation of PI3Kα re-synthesis after labeling with compound 9 showed a negligible reappearance in cancer cell lines, which indicates that persistent suppression of PI3Kα signaling by compound 9 results in a much longer half-life for PI3Kα than previously reported. The irreversible inactivation of PI3Kα by compound 9 provides a marked gain in growth inhibition potency (10-600-fold) in PIK3CA mutant cancer cell lines in comparison to clinical reversible PI3Kα inhibitors and allows for intermittent dosing without compromising efficacy. These data collectively demonstrate that compound 9 enables precise and selective targeting of PI3Kα with high potency and long-lasting efficacy in cancer models. The new class of irreversible PI3Kα inhibitors have a unique pharmacology among PI3K inhibitors characterized by strong decoupling of drug exposure from efficacy which may provide opportunities to lower treatment burden in patients. Citation Format: Theodora A. Constantin, Lukas Bissegger, Erhan Keleş, Luka Raguž, Clara Orbegozo, Thorsten Schaefer, Isobel Barlow-Busch, John E. Burke, Chiara Borsari, Matthias P. Wymann. Novel long-acting covalent PI3Kα inhibitors boost potential action in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1955.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.110
GPT teacher head0.446
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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