Bioinformatics Seminar
Time: 11AM
Venue: Davis Auditorium and Online
1 October 2024
NAIdentifying transcriptional subtypes of prostate cancer using non-negative matrix factorization
James FuWEHI Bioinformatics
Prostate cancer is the most common cancer in men (after skin cancer) and the second leading cause of cancer-related death among men. While a large number of molecular drivers of prostate cancer have been identified, there is a lack of molecular markers or molecularly defined subtypes that can accurately predict the prognosis of the cancer, and paucity of clinical decision support tools to guide clinicians in escalating or de-escalating treatment. The Pan-prostate Cancer Group (PPCG) have established a large multi-omics cancer dataset with over 2000 patients. The PPCG Transcriptomic Working Group is undertaking a comprehensive analysis of the transcriptomic data, and as part of this, we have utilized non-negative matrix factorization (NMF) to identify transcriptional patterns in the RNA-seq data and annotated the results with other omics and clinical data. This analysis allowed us to identify and validate molecular markers that define subtypes of prostate cancer and revealing patterns of transcription that are associated with poor outcome. In this talk, I will introduce the PPCG and discuss our journey using non-negative matrix factorisation to explore and identify interesting transcriptional features in this data set.