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Record W4408987622 · doi:10.1038/s41419-025-07547-7

A novel clinically relevant antagonistic interplay between prolactin and oncogenic YAP-CCN2 pathways as a differentiation therapeutic target in breast cancer

2025· article· en· W4408987622 on OpenAlexafffund
Alaa Moamer, R. da Silva, Aidan Shoham-Amizlev, Dana Hamam, Anwar Shams, Jean‐Jacques Lebrun, Suhad Ali

Bibliographic record

VenueCell Death and Disease · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsMcGill University Health Centre
FundersCIHR Skin Research Training CentreGovernment of Canada
KeywordsHippo signaling pathwayBiologyCancer researchCD44Breast cancerCancerCancer stem cellCancer cellCell biologyCellular differentiationStem cell markerStem cellSignal transductionCellGenetics

Abstract

fetched live from OpenAlex

Cellular differentiation limits cellular plasticity allowing cells to attain their specialized functional characteristics and phenotypes, whereas loss of differentiation is a hallmark of cancer. Thus, characterizing mechanisms underlying differentiation is key to discover new cancer therapeutics. We report a novel functional antagonistic relationship between the prolactin (PRL)/prolactin receptor (PRLR) differentiation pathway and YAP-CCN2 oncogenic pathway in normal mammary epithelial cells and breast cancer cells that is essential for establishing/maintaining acinar morphogenesis, cell-cell junctions and the intracellular localization of apical-basal polarity protein complexes (Par, Crumb and Scrib). Importantly, using CRISPR knockout of the PRLR in MCF7, HR+ breast cancer cells, further revealed that the negative relationship between PRL/PRLR pathway and YAP-CCN2 pathway is critical in suppressing luminal-to-basal stem-like lineage plasticity. Furthermore, the clinical relevance of this interplay was evaluated using bioinformatics approaches on several human datasets, including samples from normal breast epithelium, breast cancer, and 33 other cancer types. This analysis revealed a positive correlation between PRLR and the YAP suppressor Hippo pathway and a co-expression gene network driving favourable patients' survival outcomes in breast cancer. The therapeutic potential of this interplay was also evaluated in vitro using MDA-MB-231 cells, a preclinical model of human triple-negative breast cancer, where treatment with PRL and Verteporfin, an FDA-approved pharmacological YAP-inhibitor, alone or their combination suppressed the expression of the mesenchymal marker vimentin and the stem cell marker CD44 as well as reduced their Ki67 proliferative marker expression. Collectively, our results emphasize the pro-differentiation role of PRL/PRLR pathway in mammary and breast cancer cells and highlight that promoting PRL/PRLR signaling while inhibiting the YAP-CCN2 oncogenic pathway can be exploited as a differentiation-based combination therapeutic strategy in 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.288
Teacher spread0.276 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2025
Admission routes2
Has abstractyes

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