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Record W4206466297 · doi:10.1158/2159-8290.cd-21-1411

Precision Targeting of Mutant PI3Kα in Cancer by Selective Degradation

2022· article· en· W4206466297 on OpenAlexafffund

Bibliographic record

VenueCancer Discovery · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersCIHR Skin Research Training CentreNatural Sciences and Engineering Research Council of CanadaMichael Smith Health Research BCCancer Research UKPTEN ResearchWellcome TrustCanadian Institutes of Health ResearchCancer Research Society
KeywordsMutantCancerKinaseProtein subunitTyrosine kinaseReceptor tyrosine kinaseCancer cellPhosphorylationMutationProtein-Tyrosine Kinases

Abstract

fetched live from OpenAlex

Abstract Summary: PIK3CA, which encodes the p110α catalytic subunit of PI3Kα, is one of the most frequently genetically activated kinases in solid tumors. In this issue of Cancer Discovery, Song and colleagues report that the related PI3Kα inhibitors taselisib and inavolisib trigger receptor tyrosine kinase (RTK)–dependent degradation of the mutant p110α protein in breast cancer cells that are positive for HER2 RTK, limiting feedback-mediated drug resistance and potentially widening the therapeutic index of PI3Kα inhibition. See related article by Song et al., p. 204.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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

Citations24
Published2022
Admission routes2
Has abstractyes

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