Semi-Supervised, Attention-Based Deep Learning for Predicting TMPRSS2:ERG Fusion Status in Prostate Cancer Using Whole Slide Images

Mol Cancer Res. 2024 Apr 2;22(4):347-359. doi: 10.1158/1541-7786.MCR-23-0639.

Abstract

Our study illuminates the potential of deep learning in effectively inferring key prostate cancer genetic alterations from the tissue morphology depicted in routinely available histology slides, offering a cost-effective method that could revolutionize diagnostic strategies in oncology.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Deep Learning*
  • Humans
  • Male
  • Oncogene Proteins, Fusion / genetics
  • Prostatectomy
  • Prostatic Neoplasms* / pathology
  • Serine Endopeptidases / genetics
  • Transcriptional Regulator ERG

Substances

  • Oncogene Proteins, Fusion
  • ERG protein, human
  • Transcriptional Regulator ERG
  • TMPRSS2 protein, human
  • Serine Endopeptidases