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Record W2115163916 · doi:10.1530/erc-15-0137

Regulation of tumor cell plasticity by the androgen receptor in prostate cancer

2015· review· en· W2115163916 on OpenAlexafffund
Jennifer L. Bishop, Alastair Davies, Kirsi Ketola, Amina Zoubeidi

Bibliographic record

VenueEndocrine Related Cancer · 2015
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
FundersProstate Cancer CanadaMovember FoundationProstate Cancer Foundation
KeywordsProstate cancerAndrogen receptorTransdifferentiationAndrogen deprivation therapyCancer researchCancerBiologyAndrogenTumor progressionMedicineBioinformaticsInternal medicineStem cellHormoneCell biology

Abstract

fetched live from OpenAlex

Prostate cancer (PCa) has become the most common form of cancer in men in the developed world, and it ranks second in cancer-related deaths. Men that succumb to PCa have a disease that is resistant to hormonal therapies that suppress androgen receptor (AR) signaling, which plays a central role in tumor development and progression. Although AR continues to be a clinically relevant therapeutic target in PCa, selection pressures imposed by androgen-deprivation therapies promote the emergence of heterogeneous cell populations within tumors that dictate the severity of disease. This cellular plasticity, which is induced by androgen deprivation, is the focus of this review. More specifically, we address the emergence of cancer stem-like cells, epithelial-mesenchymal or myeloid plasticity, and neuroendocrine transdifferentiation as well as evidence that demonstrates how each is regulated by the AR. Importantly, because all of these cell phenotypes are associated with aggressive PCa, we examine novel therapeutic approaches for targeting therapy-induced cellular plasticity as a way of preventing PCa progression.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.037
GPT teacher head0.364
Teacher spread0.327 · 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

Citations55
Published2015
Admission routes2
Has abstractyes

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