MétaCan
Menu
Back to cohort
Record W2968994994 · doi:10.1016/j.scr.2019.101538

Prolactin hormone exerts anti-tumorigenic effects in HER-2 overexpressing breast cancer cells through regulation of stemness

2019· article· en· W2968994994 on OpenAlexafffund
Ibrahim Y. Hachim, Vanessa M. López‐Ozuna, Mahmood Yaseen Hachim, Jean‐Jacques Lebrun, Suhad Ali

Bibliographic record

VenueStem Cell Research · 2019
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéIran Nanotechnology Initiative CouncilConsejo Nacional de Ciencia y Tecnología
KeywordsBiologyProlactinHormoneCancer researchBreast cancerCancerMammary glandInternal medicineEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Background Breast cancers characterized by HER2 overexpression, belong to HER-2 enriched or luminal B subtypes, are frequently associated with higher incidence of tumor recurrence and therapeutic failure. These aggressive features have been attributed to the presence of cancer stem-like cell subpopulations known to have high tumor initiation, self -renewal capacities and high metastatic potential. Depleting these stem-like cells in these tumors therefore might help in improving therapeutic response and patient outcome. Methods Here we used human breast cancer cells representative of HER2- enriched and luminal B subtypes as well as purified ALDH-positive stem-like cell subpopulation for in vitro cell viability, proliferation, tumorshpere formation analyses and gene expression studies. In addition, we used a pre-clinical xenograft HER2 mouse model (NOD/SCID mice) for in vivo tumorigenesis assessment. Furthermore, patient survival outcomes were evaluated using in silico bioinformatics analyses of publicly available datasets. Results Our results indicate that prolactin (PRL) exerts anti-tumorigenic effects in HER-2 positive breast cancer cells. Importantly, PRL caused a significant reduction in ALDH hi stem-like subpopulation, as well as their viability and tumorsphere formation capacity. Molecularly we found PRL to suppress gene expression of markers involved in stemness, tumor initiation, drug resistance and poor patient outcome found to be enriched in the ALDH hi stem-like subpopulation. Furthermore, we show PRL to impede tumor growth of HER-2 xenografts and to suppress expression of Ki67 proliferative marker. Finally, we found PRL pathway gene signature to correlate with favorable patient outcomes in HER-2 and luminal B breast cancer patients. Conclusion Together these results emphasize an anti-tumorigenic role with a potential therapeutic value for PRL in HER-2 and luminal B breast cancer subtypes targeting the cancer stem-like cells.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.050
GPT teacher head0.385
Teacher spread0.335 · 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 designBench or experimental
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

Citations25
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueStem Cell ResearchSame topicHER2/EGFR in Cancer ResearchFrench-language works237,207