ArticleBMC cancer2018
Gene expression profile and cancer-associated pathways linked to progesterone receptor isoform a (PRA) predominance in transgenic mouse mammary glands.
Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Progress in the research of cuproptosis and possible targets for cancer therapy.World journal of clinical oncology · 2023Review
- The Impact of Modifying Sunitinib Treatment Scheduling on Renal Cancer Tumor Biology and Resistance.Journal of clinical medicine · 2022Article
- A novel cuproptosis-related prognostic 2-lncRNAs signature in breast cancer.Frontiers in pharmacology · 2022Article
- Article
- EO771, the first luminal B mammary cancer cell line from C57BL/6 mice.Cancer cell international · 2020Article
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Authors and funding
4 authors at 3 institutions in 4 countries.
Funding
Abstract
backgroundProgesterone receptor (PR) is expressed from a single gene as two isoforms, PRA and PRB. In normal breast human tissue, PRA and PRB are expressed in equimolar ratios, but isoform ratio is altered during malignant progression, usually leading to high PRA:PRB ratios. We took advantage of a transgenic mouse model where PRA isoform is predominant (PRA transgenics) and identified the key transcriptional events and associated pathways underlying the preneoplastic phenotype in mammary glands of PRA transgenics as compared with normal wild-type littermates.
methodsThe transcriptomic profiles of PRA transgenics and wild-type mammary glands were generated using microarray technology. We identified differentially expressed genes and analyzed clustering, gene ontology (GO), gene set enrichment analysis (GSEA), and pathway profiles. We also performed comparisons with publicly available gene expression data sets of human breast cancer.
resultsWe identified a large number of differentially expressed genes which were mainly associated with metabolic pathways for the PRA transgenics phenotype while inflammation- related pathways were negatively correlated. Further, we determined a significant overlap of the pathways characterizing PRA transgenics and those in breast cancer subtypes Luminal A and Luminal B and identified novel putative biomarkers, such as PDHB and LAMB3.
conclusionThe transcriptional targets identified in this study should facilitate the formulation or refinement of useful molecular descriptors for diagnosis, prognosis, and therapy of breast cancer.
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