Structure, dynamics and impact of extra-chromosomal DNA in cancer

Structure, dynamics and impact of extra-chromosomal DNA in cancer

Project details

Extra-chromosomal DNA (ecDNA) are small circular fragments of DNA that can harbor oncogenes and drive certain cancers, and are associated with poorer outcomes. 

EcDNAs behave very differently to normal chromosomes. EcDNAs lack centromeres and circulate randomly during cell division (Turner, Nature 2017). Selective oncogene amplification can lead to very high ecDNA copy number. They can re-integrate into chromosomes and act as promiscuous enhancers. Extending our lab’s work on neochromosomes (Garsed, cancer Cell 2016), ecDNA can recombine, leading to the phenomena of seismic amplification (Rosswog, Nature Gen 2021).

Using the short- and long-read sequencing, this project will make use of the amazing biobanks and data we have generated from patient cohorts to examine the structure, evolution, dynamics and impact of ecDNA in selected cancers, especially rare cancers, prostate cancer and melanoma.

The project will involve the development of new algorithms to understand ecDNA structure and evolution, integration of multi-omics data, and modelling to understanding the dynamics.

About our research group

The Papenfuss lab undertakes computational biology and bioinformatics research in the Bioinformatics division at WEHI. We develop and apply mathematical, statistical and computational approaches to make sense of different types of omics data from cancer in order to drive discoveries. A key focus of the lab includes understanding the molecular changes in cancers as they develop and progress. 

The lab has extensive expertise in structural variation analysis (Cameron, Genome Research, 2017), circular chromosomes (Garsed, Cancer Cell, 2014) and is co-leading the development cancer cohorts where we observe enrichment for ecDNAs in poor outcome cases.


Email supervisors



Professor Tony Papenfuss

Tony Papenfuss
Laboratory Head; Leader, Computational Biology Theme
Dr Justin Bedo
Bioinformatics division

Project Type: