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Record W7114929990 · doi:10.3390/biomedicines13123061

Targeting the JAK/STAT Signaling Pathway in Breast Cancer: Leaps and Hurdles

2025· article· en· W7114929990 on OpenAlexafffund

Bibliographic record

VenueBiomedicines · 2025
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversité de Sherbrooke
FundersLigue Contre le CancerDirection Générale de l’offre de SoinsInstitut National de la Santé et de la Recherche MédicaleInstitut National Du CancerCancer Research Society
KeywordsSignal transductionLEAPSClinical trialBreast cancerCellEndocrine system

Abstract

fetched live from OpenAlex

The JAK/STAT (Janus kinase/signal transducer and activator of transcription) signaling pathway transfers signals at the surface of cell membranes to the nucleus, triggering the expression of a myriad of factors implicated in immunity, cell proliferation, and apoptosis. Owing to this central role in cell homeostasis, its dysregulation is extensively reported in tumorigenesis, particularly in hematological cancers, justifying the development of specific inhibitors. It has more recently also been implicated in the development of solid cancers, including breast cancer. However, so far, clinical trials testing drugs targeting actors of JAK/STAT signaling yielded disappointing results, advocating in favor of a better understanding of this pathway in breast cancer. Herein, we exhaustively reviewed the current tools available to target this pathway in clinical trials and we offer several perspectives to gain further insight into the role of JAK2 in breast cancer and more particularly in the resistance to endocrine therapy in hormone-dependent breast cancers.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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 designNot applicable
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

Citations1
Published2025
Admission routes2
Has abstractyes

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