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Record W2147598859 · doi:10.1186/bcr2875

Notch signaling as a therapeutic target for breast cancer treatment?

2011· review· en· W2147598859 on OpenAlexafffund
Jianxun Han, Michael J. Hendzel, Joan Allalunis‐Turner

Bibliographic record

VenueBreast Cancer Research · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleAlberta Cancer FoundationCancer Research Institute
KeywordsNotch signaling pathwayBreast cancerCancer researchCarcinogenesisHes3 signaling axisCancerSignal transductionMedicineBiologyBioinformaticsReceptorInternal medicineCell biology

Abstract

fetched live from OpenAlex

Aberrant Notch signaling can induce mammary gland carcinoma in transgenic mice, and high expressions of Notch receptors and ligands have been linked to poor clinical outcomes in human patients with breast cancer. This suggests that inhibition of Notch signaling may be beneficial for breast cancer treatment. In this review, we critically evaluate the evidence that supports or challenges the hypothesis that inhibition of Notch signaling would be advantageous in breast cancer management. We find that there are many remaining uncertainties that must be addressed experimentally if we are to exploit inhibition of Notch signaling as a treatment approach in breast cancer. Nonetheless, Notch inhibition, in combination with other therapies, is a promising avenue for future management of breast cancer. Furthermore, since aberrant Notch4 activity can induce mammary gland carcinoma in the absence of RBPjκ, a better understanding of the components of RBPjκ-independent oncogenic Notch signaling pathways and their contribution to Notch-induced tumorigenesis would facilitate the deployment of Notch inhibition strategies for effective treatment of breast cancer.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.115
GPT teacher head0.441
Teacher spread0.326 · 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 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

Citations71
Published2011
Admission routes2
Has abstractyes

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