AI-based prediction of androgen receptor expression and its prognostic significance in prostate cancer

Sci Rep. 2025 Feb 1;15(1):3985. doi: 10.1038/s41598-025-88199-7.

Abstract

Biochemical recurrence (BCR) of prostate cancer (PCa) negatively impacts patients' post-surgery quality of life, and the traditional predictive models have shown limited accuracy. This study develops an AI-based prognostic model using deep learning that incorporates androgen receptor (AR) regional features from whole-slide images (WSIs). Data from 545 patients across two centres are used for training and validation. The model showed strong performances, with high accuracy in identifying regions with high AR expression and BCR prediction. This AI model may help identify high-risk patients, aiding in better treatment strategies, particularly in underdeveloped areas.

MeSH terms

  • Aged
  • Biomarkers, Tumor / metabolism
  • Deep Learning
  • Humans
  • Male
  • Middle Aged
  • Neoplasm Recurrence, Local / metabolism
  • Prognosis
  • Prostatic Neoplasms* / diagnosis
  • Prostatic Neoplasms* / genetics
  • Prostatic Neoplasms* / metabolism
  • Prostatic Neoplasms* / pathology
  • Receptors, Androgen* / metabolism

Substances

  • Receptors, Androgen
  • AR protein, human
  • Biomarkers, Tumor