My research spans computational cancer biology and bioinformatics methods development. My team develops novel mathematical, statistical and computational methods and applies these to make sense of cancer “omics” data. We particularly focus on rare cancers, melanoma, prostate cancer and myeloma, but also work on some other diseases.
We are developing methods to detect and classify genomic rearrangements in tumours and normal genomes. We apply these methods to understand the mechanisms underlying genomic instability in cancer. We are particularly interested in complex rearrangements and recently discovered the dynamic mechanisms underlying the formation of highly rearranged neochromosomes, which required mathematical models to make sense of the data.
We have previously developed the Socrates SV caller. Our current method, GRIDSS2, is …
Team members: Daniel Cameron, Justin Bedo, Ruining Dong, Lachlan McIntosh, Moe Zardbani
This project is aimed at developing new strategies for diagnosing and treating patients with rare cancers. It is supported by two Centenary Fellowships:
Stafford Fox Centenary Fellowship in rare cancer research
Stafford Fox Centenary Fellowship in bioinformatics
This project aims to develop new strategies for diagnosing and treating patients with rare cancers and patients with multiple primary tumours.
Team members: Justin Bedo, Matt Wakefield, Jocelyn Penington, Ramyar Molania, Elisa Roesti, Stefano Mangiola, Lachlan Doig
We are involved in an international consortium analysing the genome, transcriptome and methylome of >1000 prostate cancers with high-quality clinical outcome information. This big data project is providing new insights into how prostate cancer evolves and identifying potential prognostic biomarkers.
We co-lead the PPCG Transcriptome and the PPCG Prostate Cancer Subtyping Working Groups.
Team members: Justin Bedo, Ramyar Molania, Stefano Mangiola, Jocelyn Penington, Lachlan McIntosh
Evolution underlies tumour initiation and progression, including metastasis and the development of resistance to treatment. We are investigating the evolution of a variety of cancers using different technologies. This requires developing new statistical tools to identify evolutionary changes between tumour genomes, including changes in subclonal populations.
One aspect of this work is the role of the tumour micro-environment in progression. Deconvolution of bulk RNAseq and direct use of single-cell and spatial transcriptomics make insights into the cellular composition of tumours and its relationship to tumour evolution and patient outcome.
Team members: Justin Bedo, Stefano Mangiola, Jian Wu, Peinan Zhao, Lachlan McIntosh
Neochromosomes are massive, extra chromosomes found in 3 per cent of cancers but are common in some cancer types, such as liposarcomas.
Neochromosomes harbour the oncogenic changes that drive these cancers. We recently mapped the structure of neochromosomes at high resolution. This revealed that punctuated chromothriptic events and hundreds of breakage-fusion-bridge (BFB) cycles underlie their formation (Garsed et al, Cancer Cell 2014).
We are now pursuing the molecular machinery that contributes to this process.
Team member: Daniel Cameron
My lab consists of bioinformaticians, mathematicians, statisticians, computer scientists and computational biologists. Enquiries from people interested in undertaking a PhD in bioinformatics or computational biology are encouraged.
I also hold a joint appointment with the Peter MacCallum Cancer Centre.