A major focus of our work is cancer heterogeneity and evolution—how the genomes and transcriptomes of tumours and their microenvironments change as they are initiated and progress. This is critical in understanding how tumours metastasise and develop resistance to therapies.
We are also interested in complex genomic rearrangements and the mechanisms underlying extreme amplification events in genomes. We have developed novel methods to identify these rearrangements and use mathematical models to make sense of them. With this approach, we recently discovered the dynamic mechanisms underlying the formation of giant cancer-associated neochromosomes.
Australia, Monash University, BSc (Hons) PhD
Peter MacCallum Cancer Centre
2014 Lorenzo and Pamela Galli Melanoma Research Fellowship, Peter MacCallum Cancer Centre
2014-2018 Program Grant, “Computational and statistical bioinformatics for medical omics”, National Health and Medical Research Council
2015 NHMRC Assigners Academy, National Health and Medical Research Council
2014- President, Australian Bioinformatics and Computational Biology Society Inc
2014- Clinical Genomics Steering Committee, Peter MacCallum Cancer Centre
2014- Editorial board member, Biology Direct
2012-2014 Project Grant Review Panel, National Health and Medical Research Council
Vergara IA, Mintoff CP, Sandhu S, McIntosh L, Young RJ, Wong SQ, Colebatch A, Cameron DL, Kwon JL, Wolfe R, Peng A, Ellul J, Dou X, Fedele C, Boyle S, Arnau GM, Raleigh J, Hatzimihalis A, Szeto P, Mooi J, Widmer DS, Cheng PF, Amann V, Dummer R, Hayward N, Wilmott J, Scolyer RA, Cho RJ, Bowtell D, Thorne H, Alsop K, Cordner S, Woodford N, Leditschke J, O’Brien P, Dawson SJ, McArthur GA, Mann GJ, Levesque MP, Papenfuss AT*, Shackleton M*. Evolution of late-stage metastatic melanoma is dominated by aneuploidy and whole-genome doubling. Nat Commun. 2021 Mar 4;12(1):1434. PMID: 33664264
Colebatch AJ, Di Stefano L, Wong SQ, Hannan RD, Waring PM, Dobrovic A, McArthur GA*, Papenfuss AT*. Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies. Oncotarget. 2016 Oct 11;7(41):66569-66585. PMID: 27611953
Garsed DW*, Marshall OJ*, Corbin VD*, Hsu A*, Di Stefano L, Schröder J, Li J, Feng ZP, Kim BW, Kowarsky M, Lansdell B, Brookwell R, Myklebost O, Meza-Zepeda L, Holloway AJ, Pedeutour F, Choo KH, Damore MA, Deans AJ, Papenfuss AT**, Thomas DM**. The architecture and evolution of cancer neochromosomes. Cancer Cell. 2014 Nov 10;26(5):653-67. PMID: 25517748
Fong CY, Gilan O, Lam EY, Rubin AF, Ftouni S, Tyler D, Stanley K, Sinha D, Yeh P, Morison J, Giotopoulos G, Lugo D, Jeffrey P, Lee SC, Carpenter C, Gregory R, Ramsay RG, Lane SW, Abdel-Wahab O, Kouzarides T, Johnstone RW, Dawson SJ, Huntly BJ, Prinjha RK, Papenfuss AT, Dawson MA. BET inhibitor resistance emerges from leukaemia stem cells. Nature. 2015 Sep 24;525(7570):538-42. PMID: 26367796
Murchison EP, Tovar C, Hsu A, Bender HS, Kheradpour P, Rebbeck CA, Obendorf D, Conlan C, Bahlo M, Blizzard CA, Pyecroft S, Kreiss A, Kellis M, Stark A, Harkins TT, Marshall Graves JA, Woods GM, Hannon GJ, Papenfuss AT. The Tasmanian devil transcriptome reveals Schwann cell origins of a clonally transmissible cancer. Science. 2010 Jan 1;327(5961):84-7. PMID: 20044575
Daniel L Cameron, Nina Jacobs, Paul Roepman, Peter Priestley, Edwin Cuppen, Anthony T Papenfuss, VIRUSBreakend: Viral Integration Recognition Using Single Breakends, Bioinformatics. 2021 May 11;btab343. PMID: 33973999
Cameron DL, Baber J, Shale C, Valle-Inclan JE, Besselink N, van Hoeck A, Janssen R, Cuppen E, Priestley P, Papenfuss AT. GRIDSS2: comprehensive characterisation of somatic structural variation using single breakend variants and structural variant phasing.Genome Biol. 2021 Jul 12;22(1):202. PMID: 34253237
Cameron DL, Di Stefano L, Papenfuss AT. Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software. Nat Commun. 2019 Jul 19;10(1):3240. PMID: 31324872
Cameron DL, Schröder J, Penington JS, Do H, Molania R, Dobrovic A, Speed TP, Papenfuss AT. GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly. Genome Res. 2017 Dec;27(12):2050-2060. PMID: 29097403
Mangiola S, Molania R, Dong R, Doyle MA, Papenfuss AT. tidybulk: an R tidy framework for modular transcriptomic data analysis. Genome Biol. 2021 Jan 22;22(1):42. PMID: 33482892
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