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Gene expression profile and cancer-associated pathways linked to progesterone receptor isoform a (PRA) predominance in transgenic mouse mammary glands

Overview of attention for article published in BMC Cancer, June 2018
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Title
Gene expression profile and cancer-associated pathways linked to progesterone receptor isoform a (PRA) predominance in transgenic mouse mammary glands
Published in
BMC Cancer, June 2018
DOI 10.1186/s12885-018-4550-z
Pubmed ID
Authors

María José Carlini, María Sol Recouvreux, Marina Simian, Maria Aparecida Nagai

Abstract

Progesterone 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. The 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. We 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. The transcriptional targets identified in this study should facilitate the formulation or refinement of useful molecular descriptors for diagnosis, prognosis, and therapy of breast cancer.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 19%
Student > Master 3 19%
Researcher 3 19%
Student > Bachelor 2 13%
Librarian 1 6%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Agricultural and Biological Sciences 3 19%
Computer Science 1 6%
Nursing and Health Professions 1 6%
Immunology and Microbiology 1 6%
Other 3 19%
Unknown 3 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 June 2018.
All research outputs
#10,476,765
of 13,145,206 outputs
Outputs from BMC Cancer
#3,252
of 4,913 outputs
Outputs of similar age
#200,907
of 268,718 outputs
Outputs of similar age from BMC Cancer
#1
of 1 outputs
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