Multi-layer stratified oncology platform utilizing transcriptomics, prostate cancer organoids, and modeling of drug response.

ABSTRACT: The high intra-patient heterogeneity in multifocal primary prostate cancer (PCa) has curtailed the efficacy of current treatment options. By employing twin biopsies from multiple lesions with matched patient-derived organoids (PDO) models, the PCa molecular heterogeneity was investigated. We utilized genomics, transcriptomics and machine learning (ML) approaches to elucidate and predict the underlying mechanisms of pharmacological heterogeneity. Our data indicate a vulnerability of primary PCa organoids for small molecule inhibitors targeting receptor tyrosine kinases (MET, ALK, SRC). By exploring gene expression data from matched parental tissue in an unsupervised manner, we identified two distinct clusters of samples. Interestingly, the PDO drug responses were significantly different bet

SUBMITTER: Kang J 

PROVIDER: S-EPMC12529805 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature