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Record W3178993652 · doi:10.1158/1538-7445.am2021-291

Abstract 291: Development of optimized chemical probes targeting PI3Ka to deconvolute the role of class I PI3Ks isoforms in insulin signaling

2021· article· en· W3178993652 on OpenAlexaff
Martina De Pascale, Chiara Borsari, Erhan Keleş, Jacob A. McPhail, Alexander Schäfer, Rohitha Sriramaratnam, Matthias Gstaiger, John E. Burke, Matthias P. Wymann

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPI3K/AKT/mTOR pathwayGene isoformProtein kinase BChemistryKinaseChemical biologyInsulin receptorComputational biologyBiochemistryCancerBiologyCancer researchSignal transductionInsulinGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Phosphatidylinositol-3-kinase (PI3K) activity is aberrant in tumors, and PI3K inhibitors are investigated as cancer therapeutics.[1-5] The major obstacles to the successful implementation of PI3K-targeted cancer therapy are on-target adverse effects on insulin signaling. Isotype selective PI3K inhibitors have been exploited to answer fundamental questions regarding the role of PI3K isoforms in cell biology. However, the availability of claimed isoform-selective PI3Kα inhibitors is limited to BYL719 (Alpelisib)[6] and GDC0032 (Taselisib)[7], which do not maintain PI3Kα selectivity at a concentration required in cellular experimental settings and clinical applications. Highly selective PI3Kα inhibitors are expected to represent ideal tools to elucidate the role of PI3Kα isoform in tumor development and insulin signaling. As the systemic inactivation of PI3Kα is embryonic lethal, genetic approaches are currently limited to organ-specific targeting, and a specific inactivation of PI3Kα in an adult organism has not been achieved up-to-date. Herein, we generate high-quality PI3Kα chemical probes to dissect the role of PI3Kα in cancer and metabolism. We exploit covalent inhibitors, permanently blocking target functions, as a strategy to enhance the ligand binding selectivity for proteins in the same family. The non-conserved nucleophilic amino acid Cys862 in PI3Kα represents a promising target for covalent modifiers. We converted the reversible scaffold of PQR514[5] into irreversible compounds. An extensive Structure Activity Relationship (SAR) study was performed using CNX-1351[8] reacting group and introducing different heteroaliphatic rings in the linker. X-ray crystallography and bottom-up LC-MS/MS based proteomics validated the covalent modification of Cys862. Our pilot chemical probes exceeded in vitro and cellular potency over CNX-1351. The generation of a novel class of covalent PI3Kα-specific inhibitors with improved selectivity and persistency of PI3Kα-inhibition will shed light on the role of PI3Kα in cancer and metabolism. Our results will pave the way for the dissociation of PI3Ki antitumor activity from adverse effects on insulin action. [1] Beaufils F et al. J Med Chem. 2017, 60 (17), 7524-7538. [2] Rageot R et al. J Med Chem. 2019, 62 (13), 6241-6261. [3] Wymann MP et al. Nat Rev Mol Cell Biol. 2008, 9 (2), 62-176. [4] Marone R et al. Biochim Biophys Acta. 2008, 1784 (1), 159-185. [5] Borsari C et al. ACS Med Chem Lett. 2019, 10 (10), 1473-1479. [6] Markham A Drugs 2019, 79 (11), 1249-1253. [7] Zumsteg ZS et al. Clin Cancer Res. 2019, 22 (8), 2009-2019. [8] Nacht M et al. J Med Chem. 2013, 56 (3), 712-721. Citation Format: Martina De Pascale, Chiara Borsari, Erhan Keles, Jacob McPhail, Alexander Schäfer, Rohitha Sriramaratnam, Matthias Gstaiger, John Burke, Matthias Wymann. Development of optimized chemical probes targeting PI3Ka to deconvolute the role of class I PI3Ks isoforms in insulin signaling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 291.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.366
Teacher spread0.317 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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