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Record W3082777808 · doi:10.1039/d0cs00163e

A balancing act: using small molecules for therapeutic intervention of the p53 pathway in cancer

2020· review· en· W3082777808 on OpenAlexafffund
Jessica J. Miller, Christian Gaiddon, Tim Storr

Bibliographic record

VenueChemical Society Reviews · 2020
Typereview
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsBurnaby HospitalSimon Fraser University
FundersCentre National de la Recherche ScientifiqueMichael Smith Health Research BCLigue Contre le CancerInstitut National de la Santé et de la Recherche MédicaleSimon Fraser UniversityNatural Sciences and Engineering Research Council of CanadaAssociation pour la Recherche sur le Cancer
KeywordsSmall moleculeCancerP53 proteinIntervention (counseling)ChemistryCancer researchMedicineInternal medicineBiochemistryApoptosisPsychiatry

Abstract

fetched live from OpenAlex

Referred to as the "guardian of the genome", p53 is the most frequently mutated protein in cancer and almost all cancers exhibit malfunction along the p53 pathway. As an overexpressed and tumour-specific target, the past two decades have seen considerable dedication to the development of small molecules that aim to restore wild-type function in mutant p53. In this review we collect and communicate the chemical principles involved in small molecule drug design for misfolded proteins in anticancer therapy. While this approach has met with significant challenges including off-target mechanisms that induce cytotoxicity independent of p53 status, major technological advancements in gene sequencing capability and a shift towards personalized medicine holds significant promise for p53 reactivating compounds and could have widespread benefits for the field of cancer therapy.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.121
GPT teacher head0.376
Teacher spread0.254 · 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 designOther design
Domainnot available
GenreReview

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

Citations45
Published2020
Admission routes2
Has abstractyes

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