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Record W3083638783 · doi:10.1158/1538-7445.am2020-4361

Abstract 4361: A systematic study of the impact of estrogens and selective estrogen receptor modulators on prostate cancer cell proliferation

2020· article· en· W3083638783 on OpenAlexaff
Camille Lafront, Lucas Germain, Cindy Weidmann, Étienne Audet‐Walsh

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEstrogen receptorLNCaPCancer researchDU145Prostate cancerEstrogenSelective estrogen receptor modulatorAndrogen receptorCell growthOncogeneReceptorEstrogen receptor alphaCancerCellBiologyInternal medicineEndocrinologyCell cycleBreast cancerMedicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract The estrogen receptors ERα and ERβ are expressed in prostate cancer (PCa) cells and are believed to act as an oncogene and a tumor suppressor, respectively, and thus to be attractive therapeutic targets. Indeed, compounds modulating the activity of these receptors already exist and are currently used to treat ERα-positive breast tumors. However, there is a lot of discrepancies regarding the efficacy of anti-estrogen treatments for the management of PCa. Several factors explain these discrepancies, including unspecific antibodies against ERβ, lack of proper estrogenic positive controls, and usage of estrogens and anti-estrogens molecules at high dosages were off-target effects are observed. Our objective was to conduct a systematic study on the impact of estrogenic and anti-estrogenic ligands on PCa cell proliferation and survival. After optimization of our cellular assay using the human breast cancer cell line MCF7, we used five of the most commonly studied human PCa cell models, namely LNCaP, 22Rv1, LAPC4, DU145, and PC3 cells. These cells were treated with nine estrogenic/anti-estrogenic compounds, including five selective estrogen receptor modulators (SERMs), with and without co-treatment with androgens for androgen receptor (AR)-positive cells. In both AR-positive and AR-negative cells, we observed no significant modulation of proliferation following modulation of ERs activity. Using both RNA-seq and Western Blots, ERs expression was mostly undetectable in these models. Our study indicate that commonly used PCa models in vitro are not appropriate models to study the estrogen signaling pathway in PCa. Yet, expression data from PCa tissues indicate a significant expression of both receptors, and indicate that usage of new PCa models or of in vivo models are required to properly study drug repurposing of anti-estrogens and SERMs for PCa treatment. Citation Format: Camille Lafront, Lucas Germain, Cindy Weidmann, Etienne Audet-Walsh. A systematic study of the impact of estrogens and selective estrogen receptor modulators on prostate cancer cell proliferation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4361.

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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.073
GPT teacher head0.414
Teacher spread0.342 · 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 designMeta-analysis
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

Citations1
Published2020
Admission routes1
Has abstractyes

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