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mRNA ratios of AR to ESR1 and PGR distinguish breast cancer subtypes based on public datasets and experimental models

  • Diego Prieto
  • , Milena Rondón-Lagos
  • , Paola Cruz-Tapias
  • , Andrés Rincón-Riveros
  • , Wilson Rubiano
  • , Jairo De la Peña
  • , Elizabeth Vargas
  • , Victoria E. Villegas
  • , Nelson Rangel
  • Universidad Pedagógica y Tecnológica de Colombia
  • University Clinic
  • Universidad Colegio Mayor de Cundinamarca
  • Hospital Universitario Mayor Méderi
  • Universidad del Rosario

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The role of the androgen receptor (AR) in breast cancer (BC) remains incompletely understood. Here, we conducted a meta-analysis of large-scale microarray transcriptomic datasets to evaluate whether the mRNA expression levels of the androgen receptor gene, relative to those of the estrogen receptor gene (AR/ESR1 ratio) and the progesterone receptor gene (AR/PGR ratio), can help differentiate BC tumor subtypes. Additionally, we used qRT-PCR assays to assess the mRNA levels of the AR/ESR1 and AR/PGR ratios in four cell lines representative of different BC subtypes (MCF7, BT474, MDA-MB453, and MDA-MB231), as well as in breast tissue from a small group of patients (11 cases) stratified by estrogen receptor (ER) status. Our results showed that higher AR gene expression relative to ESR1 and PGR (≥ 2.0 and ≥ 1.54, respectively) were associated with BC patients classified under the Luminal B and HER2-enriched subtypes. Positive values of AR/ESR1 and AR/PGR ratios were also observed in the ER-negative (ER-) cell line MDA-MB453, as well as in tumor tissue from ER- BC patients. Our findings confirm that higher or even positive AR/ESR1 and AR/PGR ratios may be associated with BC cases exhibiting more aggressive clinical and biological features, leading to a worse prognosis.

Original languageEnglish
Article number21793
Pages (from-to)21793
JournalScientific Reports
Volume15
Issue number1
DOIs
StatePublished - 01 Jul 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Breast Neoplasms/genetics
  • Cell Line, Tumor
  • Estrogen Receptor alpha/genetics
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Humans
  • MCF-7 Cells
  • RNA, Messenger/genetics
  • Receptors, Androgen/genetics
  • Receptors, Progesterone/genetics

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