Bioinformatics Seminar
Time: 11AM
Venue: Davis Auditorium and Online
9 December 2025
This is a WEHI only event.Transcriptomic patterns reveal heterogeneous trajectories to metastatic progression in prostate cancer
James FuWEHI Bioinformatics
Prostate cancer (PC) is the second leading cause of cancer-related death in men. While the prognosis of localized PC is generally favourable, patients with distant metastasis face a five-year survival rate of 37%. To better understand the mechanisms that drive metastatic PC and potentially improve prognostication and therapeutic decision making, as part of the Pan-Prostate Cancer Group (PPCG), we have established a large multi-omics cancer dataset, including bulk RNA-Seq, whole genome sequencing, and methylation data from over 1000 patients—the largest prostate cancer multi-omics cohort to date. Using the RNA-Seq data, we identified 40 recurrent transcriptomic patterns, which showed clear association with prostatic cell signatures, genomic driver mutations (including TMPRSS2-ERG fusion and SPOP), changes in biological pathways, and clinical outcomes. Of these, several patterns defined distinct transcriptional subtypes at higher risk of metastasis. Comparisons with marker gene expression and multiomics revealed that one of these patterns was associated with copy number loss of PTEN and genes on chromosome 18q, while another showed elevated expression of genes involved in neuroendocrine differentiation, despite samples being treatment-naïve. Integration with single cell RNA-seq data linked several outcome-associated patterns with different types of cancerous epithelial cells (luminal and neuroendocrine) and metastatic-related stromal cells observed in advanced human PC and mouse models. Together, our analysis highlights the molecular heterogeneity of PC and supports multiple potentially distinct metastatic trajectories.