T. L. Lotan

This paper develops a deep learning model to predict ERG:TMPRSS2 fusion status in prostate cancer from whole slide images and identifies associated morphological features.

This study examines the origin and dynamics of cellular heterogeneity in different subtypes of castrate-resistant prostate cancer using patient-derived organoids and single-cell analyses, identifying distinct lineage plasticity patterns and therapeutic targets.

This study assesses batch effects in TMA-based cancer biomarker studies and shows mitigation methods reduce variance and alter clinical associations.

This study identifies P2X4 purinergic receptors as a driver of aggressive prostate cancer and a potential therapeutic target through in vitro and in vivo experiments.

The paper investigates differential mast cell phenotypes in benign and cancerous prostate tissues and links higher numbers of tryptase-only mast cells to worse oncologic outcomes.