Evidence mapPaperPMID 39692941Full record

ArticleDiscover oncology2024

Impact of prolactin treatment on enhancing the cellular responses of MCF7 breast cancer cells to tamoxifen treatment.

Anwar Shams

Abstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Anwar ShamsDepartment of Pharmacology, College of Medicine, Taif University, P.O. Box 11099, Taif 21944, Taif, Saudi Arabia. a.shams@tu.edu.sa.

Funding

Taif University 1-442-65
6 · The paper itself

Abstract

Breast cancer remains one of the most challenging diseases to treat due to its heterogeneity, propensity to recur, capacity to spread to distant vital organs, and, ultimately, patient death. Estrogen receptor-positive illness comprises the most common breast cancer subtype. Preclinical progress is hampered by the scarcity of medication-naïve estrogen receptor-positive tumour models that recapitulate metastatic development and treatment resistance. It is becoming increasingly clear that loss of differentiation and increased cellular stemness and plasticity are important causes of cancer evolution, heterogeneity, recurrence, metastasis, and treatment failure. Therefore, it has been suggested that reprogramming cancer cell differentiation could offer an effective method of reversing cancer through terminal differentiation and maturation. In this context, the hormone prolactin is well recognized for its pivotal involvement in the development of the mammary glands lobuloalveolar tissue and the terminal differentiation that drives the production of the milk protein gene and lactation. Additionally, numerous studies have examined the engagement of prolactin in breast cancer as a differentiation player that resulted in the ablation of tumour growth and progression. Here, we showed that a pre-treatment of the estrogen-positive breast cancer cell line with prolactin led to a considerable improvement in the sensitivity of this cancer cell to Tamoxifen endocrine therapy. We also showed a favourable prognostic value of prolactin receptors/estrogen receptors 1 (or alpha) co-expression on breast cancer patients outcomes, and this co-expression is highly correlated with the well-differentiated breast tumour type. Our results revealed a fruitful aspect of the effects of prolactin in improving the responses of breast cancer cells to conventional endocrine therapy. Moreover, these findings further validated the ability of prolactin as a persuader of a more differentiated and less aggressive breast cancer phenotype. Hence, it suggested a potential implication of prolactin as a therapeutic candidate.

Indexed as

Breast cancerDifferentiationEpithelial markersProlactinSensitivityTamoxifen

Identifiers

PMID39692941
PMCPMC11655925

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.