4.6 Article

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

Journal

BMC CANCER
Volume 18, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s12885-018-4550-z

Keywords

Progesterone receptor; Isoforms; Transgenic mice; Mammary gland; Hyperplasia; Breast cancer; Gene expression profiling; Gene set enrichment analysis; Biomarker

Categories

Funding

  1. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2015/10208-3]
  2. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [303134/2013-5]
  3. FAPESP [2014/13470-8]
  4. Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) [PIP 11220150100155CO]
  5. CONICET

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Background: 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. Methods: 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. Results: 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 LAMBS. Conclusion: 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.

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