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Record W3005361124 · doi:10.3390/cancers12020374

Autotaxin and Breast Cancer: Towards Overcoming Treatment Barriers and Sequelae

2020· review· en· W3005361124 on OpenAlexaff
Matthew G.K. Benesch, Xiaoyun Tang, David N. Brindley

Bibliographic record

VenueCancers · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversity of AlbertaMemorial University of Newfoundland
Fundersnot available
KeywordsAutotaxinBreast cancerMedicineCancerClinical trialAdjuvantTumor microenvironmentCancer researchOncologyInternal medicineBioinformaticsLysophosphatidic acidBiologyReceptor

Abstract

fetched live from OpenAlex

After a decade of intense preclinical investigations, the first in-class autotaxin inhibitor, GLPG1690, has entered Phase III clinical trials for idiopathic pulmonary fibrosis. In the intervening time, a deeper understanding of the role of the autotaxin-lysophosphatidate (LPA)-lipid phosphate phosphatase axis in breast cancer progression and treatment resistance has emerged. Concordantly, appreciation of the tumor microenvironment and chronic inflammation in cancer biology has matured. The role of LPA as a central mediator behind these concepts has been exemplified within the breast cancer field. In this review, we will summarize current challenges in breast cancer therapy and delineate how blocking LPA signaling could provide novel adjuvant therapeutic options for overcoming therapy resistance and adverse side effects, including radiation-induced fibrosis. The advent of autotaxin inhibitors in clinical practice could herald their applications as adjuvant therapies to improve the therapeutic indexes of existing treatments for breast and other 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 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 score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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

Citations33
Published2020
Admission routes1
Has abstractyes

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