Brain metastases are the most common brain tumours in adults and are associated with poor outcomes. We are performing whole genome sequencing and assaying methylation genome-wide in matched primary and brain metastases across different tumour types to identify molecular predictors of brain metastasis.

Papenfuss Lab

Q: Tumour evolution, heterogeneity and the micro-environment

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.

Q: Pan-Prostate Cancer genome (PPCG) project

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.

Q: Stafford Fox Rare Cancer Program

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 researchStafford Fox Centenary Fellowship in bioinformaticsThis project aims to develop new strategies for diagnosing and treating patients with rare cancers and patients with multiple primary tumours.

Q: Mechanistic and functional drivers of neochromosome evolution

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.

Q: Multi-omics data integration

We are testing and developing statistical and machine learning methods for multi-omics data integration. The purpose of this research is to improve the identification of biomarkers that identify the state of a tumour or the cancer subtype and predict the patient outcome.

Q: Good to bad melanomas

Thin primary melanomas (T1a) typically have good outcomes following surgery alone, but sometimes recur and can progress rapidly. We are applying novel computational approaches to multi-omics data (WES, single cell, spatial transcriptomics) to identify the molecular and cellular determinants of low risk primary melanomas that go bad. This will lead to new biomarkers or therapeutic targets and help to refine patient risk stratification, identifying patients who might benefit from a higher level of surveillance.

Q: PPCG CombiMets - Pan-Prostate Cancer Metastasis Working Group

International collaboration researching the genomic changes associated with prostate cancer metastasis.

Papenfuss Lab

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About the lab

Lab research projects

Student research projects

Lab team

About the lab

Our laboratory develops and applies bioinformatics methods to drive discoveries in cancer and translate these into improved outcome for patients.

We use mathematics, statistics and computing to analyse and interpret omics data, especially related to cancer evolution, spanning cancer initiation, progression and patient outcome. We work extensively on rare cancers, melanoma and prostate cancer, but also work on other cancers and other diseases. We have strong research interests in chromosomal instability and extensive experience in the analysis of whole genome sequencing data. A major focus of the lab is now cancer multiomics, predictive biomarker and subtype discovery.

Lab research projects

Tumour evolution, heterogeneity and the micro-environment

Pan-Prostate Cancer genome (PPCG) project

Stafford Fox Rare Cancer Program

Mechanistic and functional drivers of neochromosome evolution

Algorithms for structural variant detection

Brain metastasis

Multi-omics data integration

Good to bad melanomas

PPCG CombiMets – Pan-Prostate Cancer Metastasis Working Group

Student research projects

Integration of multi-resolution and multi-omics data

PhD

More information

Integration of multi-resolution and multi-omics data

PhD

More information

Lab team

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.

20 members

Prof Tony Papenfuss

Lab head