A yeast-based functional assay for the detection of the mutant androgen receptor in prostate cancer

Jocelyn Céraline1, Eva Erdmann, Philippe Erbs

  • 1Laboratoire de Cancerologie Experimentale et de Radiobiologie, EA 3430-ULP, IRCAD, 1, Place de l'Hopital, BP426, F67091 Strasbourg, France. jocelyn.ceraline@ircad.u-strasbg.fr

Abstract

Insights

This study presents a new yeast-based assay to detect mutant androgen receptors (ARs) in prostate cancer (PCa). This method can identify AR mutations that drive cancer growth and assess anti-androgen drug effectiveness.

Area of Science:

  • Molecular biology
  • Cancer research
  • Endocrinology

Background:

  • Mutations in the androgen receptor (AR) ligand-binding domain allow prostate adenocarcinoma (PCa) to evade androgen dependence.
  • These AR mutations can alter hormone specificity and affinity, leading to aberrant receptor activation and impacting treatment efficacy.

Purpose of the Study:

  • To develop and validate a yeast-based functional assay for detecting mutant ARs.
  • To analyze the transactivation capacities of mutant ARs in response to various ligands.
  • To assess the utility of the assay for routine detection and evaluating anti-androgen activity.

Main Methods:

  • Cloning of AR cDNA into a yeast expression vector with an ADE2 reporter gene.
  • Utilizing a yeast strain with an androgen-dependent promoter linked to the ADE2 reporter.
  • Assessing yeast growth in selective media based on AR-ligand specificity.

Main Results:

  • The assay successfully discriminated between wild-type AR and specific mutants (T877A, C685Y, L701H).
  • The assay demonstrated sensitivity, detecting at least 1% mutant ARs in mixed cDNA samples.
  • Transactivation capacities of different AR variants were analyzed across a wide range of ligands.

Conclusions:

  • The developed yeast assay is a simple and convenient tool for routine detection of mutant ARs in PCa.
  • The assay is suitable for evaluating the antagonist activities of anti-androgen compounds.
  • This method aids in understanding AR mutation impact on PCa progression and treatment response.

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