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Record W4396514128 · doi:10.3389/fcell.2024.1343938

The role of the master cancer regulator Pin1 in the development and treatment of cancer

2024· article· en· W4396514128 on OpenAlexafffund
Robert Stewart, Shaunik Sharma, Timothy Wu, Sho Okuda, George Xie, Xiao Zhen Zhou, Brian H. Shilton, Kun Ping Lu

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsRobarts Clinical TrialsLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health Research
KeywordsCancerRegulatorMaster regulatorPIN1Cancer treatmentCancer researchMedicineBiologyInternal medicineTranscription factorGenetics

Abstract

fetched live from OpenAlex

This review examines the complex role of Pin1 in the development and treatment of cancer. Pin1 is the only peptidyl-prolyl isomerase (PPIase) that can recognize and isomerize phosphorylated Ser/Thr-Pro peptide bonds. Pin1 catalyzes a structural change in phosphorylated Ser/Thr-Pro motifs that can modulate protein function and thereby impact cell cycle regulation and tumorigenesis. The molecular mechanisms by which Pin1 contributes to oncogenesis are reviewed, including Pin1 overexpression and its correlation with poor cancer prognosis, and the contribution of Pin1 to aggressive tumor phenotypes involved in therapeutic resistance is discussed, with an emphasis on cancer stem cells, the epithelial-to-mesenchymal transition (EMT), and immunosuppression. The therapeutic potential of Pin1 inhibition in cancer is discussed, along with the promise and the difficulties in identifying potent, drug-like, small-molecule Pin1 inhibitors. The available evidence supports the efficacy of targeting Pin1 as a novel cancer therapeutic by analyzing the role of Pin1 in a complex network of cancer-driving pathways and illustrating the potential of synergistic drug combinations with Pin1 inhibitors for treating aggressive and drug-resistant tumors.

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 categoriesnone
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 score0.713
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.233
Teacher spread0.223 · 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.

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

Citations5
Published2024
Admission routes2
Has abstractyes

Explore more

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