Southey laboratory - Cancer Genomics
| Contact: | Professor Melissa Southey |
|---|---|
| Phone: | +61 3 8344 4895 |
| Fax: | +61 3 8344 4004 |
| Email: | msouthey@unimelb.edu.au |
Our research programs both currently active and those planned over the next five years are focused on characterizing the genetic and epigenetic factors responsible for cancer predisposition and progression, including familial aggregation of cancers. The team, based at The University of Melbourne is an extremely active research group and we have numerous national and international multidisciplinary collaborations. Significant focus is placed on breast and prostate cancer along with progressive programs in colorectal, B-cell, pediatric, urothelial, lung, kidney cancer and mammographic density. We work productively with clinical colleagues to improve personal cancer risk assessment, and actively translating this new genetic information to improve health outcomes.
Research Team
Head
Professor Melissa C. Southey
Personal Assistant: Amanda Edwards
Senior Research Fellow
Dr Daniel J. Park
Research Fellows
Dr Tu Nguyen-Dumont
Dr EE Ming Wong
Dr Jihoon (Eric) Joo
Helen Tsimiklis
Research Assistants
Catherine Chatfield
Fleur Hammet
Maryam Mahmoodi
Anke Grabosch-Meehan
Mark Fernando
Graduate Students
Melissa Yow
Joyce Teo
Louise Thingholm
Nicole Wong Do
Key research areas are
Genetic variation associated with risk of prostate and breast cancer.
Familial clustering of breast cancer is well recognized with up to 20% of breast cancer cases occurring in the familial setting. Three defined classes of breast cancer susceptibility alleles with different levels of average risk and prevalence in the population have emerged (Stratton & Rahman 2008) but only account for 30-35% of the familial aggregation of breast cancer. Several lines of evidence suggest that no single gene is likely to account for a large fraction of the remaining familial aggregation of breast cancer (Cui et al., 2001; Thompson & Easton 2004; Smith et al., 2006).
Having a family history of prostate cancer is one of the few well-established risk factors for the disease. The increased risk associated with having at least one affected first-degree relative is approximately 2.5-fold. The genetic components of this underlying familial risk have proven to be difficult to identity. Many studies set in several different populations have demonstrated familial clustering of prostate cancer and support an underlying autosomal dominant inheritance of a ‘high risk’ gene (eg Carter et al., 1992; Schaid et al., 1998; Verhage et al., 2001; MacInnis et al., 2010).
Our research: We lead well advanced and funded studies using highly selected multiple-case families and applying massively parallel sequencing (MPS; see below) to identify new “high risk” breast and prostate cancer susceptibility genes. We were the first to report the identification of a new breast cancer susceptibility gene via the application of MPS, and thus demonstration of the capacity of this study design and the value and utility of having large population-based studies and close collaborations that can be mobilized quickly to validate findings from exome sequencing (Park et al., 2012). Recently we have led the formation of an international consortium named COMPLEXO (a name chosen to reflect the complexity of the exome that brings MPS and the power of large sample sets together which is fundamentally important to research examining extremely rare genetic variants (Hilbers, et al., 2012).
Methylation variation as a risk factor for prostate and breast cancer.
Analyses of single and small numbers of genes have shown that aberrant methylation of DNA extracted from peripheral blood can be a marker of prostate and breast cancer risk. Few published studies have measured methylation in DNA from blood to investigate its potential as a diagnostic marker and most of these have used blood samples collected after diagnosis, which limits their usefulness for assessing the utility of methylation for risk prediction and/or early detection. We have previously reported BRCA1 promoter methylation measured in DNA extracted from peripheral blood as a risk factor for early-onset breast cancer, and the tumours of those affected have a specific histological type (Wong et al., 2010). However, the majority of reports in the area involve the analysis of one or few markers by relatively small studies. Larger epidemiologically-based studies of a broad range of epigenetic markers are urgently required to identify the most specific and sensitive markers of prostate and breast cancer risk and markers of the aggressive prostate cancer. Identification and characterization of such key epigenetic alterations for breast and prostate cancer risk may provide new opportunities for cancer screening, cancer detection, diagnostic staging, risk stratification and “epigenetic-marker targeted” drug development.
The potential for using genome-wide measurement (or specific gene) methylation for breast and prostate cancer risk prediction, prevention and management is exciting, but has not yet been at all well investigated. There have been advances in our understanding of epigenetic regulation and great advances in the molecular genetic tools available to measure methylation, both as a global measure and genome-wide at specific genomic regions or nucleotides (now facilitated by new technology).
Our research: We lead well-advanced and funded Epigenome-Wide Association Studies (EWASs) utilizing the resources of the Melbourne Collaborative Cohort Study (MCCS see below) in breast and prostate cancer. We have completed the analysis of the breast cancer study (1200 cases and controls) and are progressing with the bench work of the prostate study (3,000 cases and controls) and anticipate a 2013 completion date. We have optimized protocols to include the corresponding FFPE material and initiated work to develop targeted capture bisulfite sequencing strategies anticipated for follow-up activities.
Broad objectives
1. To identify more of the ‘missing heritability’ of breast and prostate cancers.
2. To investigate DNA methylation as a risk factor for breast and prostate cancers.
3. To incorporate relevant new genetic and epigenetic information into new risk prediction models and to translate relevant findings into clinical practice to improve health outcomes.
Methodologies
Massively parallel sequencing (MPS) offers a powerful approach to try to identify more of the as yet unidentified breast and prostate cancer susceptibility genes though its ability to sequence substantial portions of multiple human exomes during a single instrument run. This methodology is transforming the way genetic research is conducted in genomic facilities around the world, including ours. We have established in-house MPS and bioinformatic analysis pipelines that have been verified via traditional Sanger-based follow-up sequencing (Park et al., 2011; Park et al 2012; Pope et al., 2013). These have been established to accommodate analyses involving large sample sets and within family studies utilizing our mature population-based family study resources (see PEDIGREE below).
It is anticipated that the first phase of the genome-wide methylation studies will identify genomic regions associated with cancer risk that we will want to further characterize in terms of their methylation patterns and regulation. We are developing the expertise in-house to conduct targeted bisulfite sequencing and associated analytical pipelines to characterize these new associations.
Exome sequencing Vs whole genome sequencing: Until very recently there has been compelling justification for undertaking exome sequencing rather than whole genome sequencing (WGS) for cancer gene discovery projects. This justification has centered around the ability to better interpret genetic variation in the exome and flanking intronic regions, and lower cost. The cost differential is now minimal and after a phase of pilot work we have moved to favouring WGS in some study designs.
Genome-wide methylation profiling: We are utilizing the Illumina methylation Infinium HumanMethylation450 BeadChip that interrogates >480,000 methylation sites per sample at single-nucleotide resolution. Recent NHMRC project funding has allowed us to take the lead this area of epigenetic research and utilise the resources of the Melbourne Collaborative Cohort Study that collected blood samples from participants prior to diagnosis. We have confirmed that the samples in our biorepository are adequate for this new technology (2). We have established a laboratory system involving robotics and the illumina iScan to enable the analysis of 10,000 DNAs from this resource during 2013 all associated with projects funded by the NHMRC (see also Genomics Facility below).
Validation of all findings: We are members of many cancer research consortia which can be used for discovery and validation studies and to increase the precision of estimates and examine interactions, especially methylation/gene/environment interactions.
Translation
Translation of this new genetic knowledge into clinical practice will greatly benefit the very large proportion of families who have tested negative for known cancer predisposition gene mutations. Knowledge about the mutation status of other cancer susceptibility genes will allow us to develop new statistical models that will more precisely estimate risk and provide evidence upon which to base clinical advice and genetic counseling. This is also important in the management of unaffected family members, who have the option of surveillance based upon predictive testing. Our recent research in the area of PALB2 and breast cancer has demonstrated what research data, publications, presentations and collaborations are required to move basic research data onto agendas that enable nationally coordinated changes to clinical practice. Our work in population-based case-control-family studies has demonstrated that for some PALB2 mutations the breast cancer risks are comparable to the risks associated with mutations in BRCA2 (Southey et al., 2010). Further work has demonstrated that 1-1.5% of Australian multiple-case breast cancer families carry a mutation in PALB2 that is of clinical significance (3, 4) and that one morphological feature of the breast cancers arising in PALB2 mutation carriers is highly predictive of PALB2 mutation status (5), similar to our work that has shown morphological features to be predicted of BRCA1 mutation status (Southey et al., 2011).
Cancer Research Resources:
PEDIGREE: We are key members of the Executive Committee of PEDIGREE that has recently brought a number of large epidemiological studies together for effective governance and utilization. PEDIGREE is a resource of 100,000 people, 20,000 cancer families, 1,000,000 bio-specimens, data, researchers and community representatives established to conduct collaborative research on cancer (www.pedigree.org.au). The biological material associated with the PEDIGREE studies are curated in my biorepository (see above). Included in PEDIGREE and key to the proposed research are;
The Breast Cancer Family Registry (BCFR) is a collaboration of six institutes in the USA, Canada, and Australia, who developed core family history and epidemiology questionnaires, data dictionaries and common protocols for biospecimen collection, processing and pathology review. This resource includes of over 14,000 families (John et al., 2004).
The Melbourne Collaborative Cohort Study (MCCS) is a prospective study of 41,514 people (17,045 men) recruited between 1990 and 1994 (Giles et al., 2002). Data on family history of prostate and breast cancer has been collected from all subjects.
Australian Risk Factors for Prostate Cancer Study (ARFPCS) is a multi-centre, population-based case–control study. Cases were recruited via population cancer registers and eligible controls were identified through the electoral rolls. A total of 1,475 cases and 1,405 controls have been recruited.
The Australian Prostate Cancer Family Study (APCFS) has collected blood samples from 740 controls (71% of those approached) and 836 cases (83% of those approached) including 105 who were 55 years or younger at diagnosis. Blood was also sampled from the relatives of cases and controls with a first-degree family history of prostate cancer.
The Early Onset Prostate Cancer Study (EOPCS)currently involves 1450 additional probands in this age group (as well as any available parents, brothers and uncles) who have been recruited and given blood samples.
The Aggressive Prostate Cancer Study (APCS) has, since 2010, invited every new case of aggressive prostate cancer diagnosed in Victoria to participate. We are expecting to recruit more than 1,000 cases and 1,000 controls by the end of 2014.
Other resources that will be utilized in the proposed research include,
Outcomes
We expect to identify additional new cancer susceptibility genes and characterize mutations in these genes in terms of population prevalence and penetrance in order to provide the evidence base from which clinical genetics can adopt mutation screening.
We expect to identify methylation markers from genome-wide methylation studies that are associated with cancer risk. With newly developed methodologies, we will characterize the genomic regions that contain these markers to further understand the underlying biological mechanisms giving rise to the cancer risk. Some methylation markers might have associated prevalence and cancer risk of a magnitude that means they will be clinically relevant. Our resources can characterize these prevalences and risks for the Australian population and provide important evidence to inform translation.
Our data will create a paradigm shift in the way that clinical genetic services and cancer screening programs are conducted in Australia. Current and new data (including data from our studies of mammographic density) could allow the identification of people at the highest risk of developing cancer, people at highest risk of carrying a mutation in a specific gene and people most likely to benefit from alternate screening approaches (as described for colorectal cancer in Southey et al., 2005). In this way, screening and genetic testing can be tailored to a personal risk estimate rather than an average population risk measure and improve resource usage.
References
Carter BS, et al., 1992 Proc. Natl. Acad. Sci USA 89:3367-3371.
Christensen GB, et al., 2010 The Prostate 70:735-744.
Cui J, et al 2001 Am J. Hum. Genet 68:1207-1218.
Dite GS et al., 2012 Breast Cancer Res. 14(4):R122
Giles GG, English DR. IARC Sci Publ. 2002;156:69-70
Hilbers FS, et al., 2012 J Med Genet 49(10):618-20
John EM, et al., 2004 Breast Cancer Res, 6(4): R375-R389.
Joo J-HE, et al BMC biotechnology November 2012
Le Calvez-Kelm F, et al., 2011 Breast Cancer Res. Jan 18;13(1):R6
MacInnis RJ, et al., 2010 Genet Epidemiol. Jan;34(1):42-50.
Mann GJ, et al., 2006 Breast Cancer Res, 8(1): R12.
Park DJ, et al., 2011, Breast Cancer Res Treat Dec;130(3):1043-9.
Park DJ et al., 2012, AJHG, 90:4:734-739.
Pope BJ, et al BMC BMC Bioinformatics. 2013 Feb 25;14:65
Schaid DJ, et al., 1998 AJHG, 62:1425-1438.
Singh R, et al., 2000 EU Biomed. Br J Cancer. Dec;83(12):1654-8
Smith P, et al., 2006 Genes Chromosomes Cancer, 45(7): 646-55.
Southey MC, et al., 2005 J Clin Oncol. Sep 20;23(27):6524-32.
Southey MC, et al., 2003 Hum Mutat, 22(1): 86-91.
Southey MC, et al., 2010 Breast Cancer Res. 12(6):R109.
Southey MC, et al., 2011 Br J Cancer 15:104(6):903-9.
Stratton MR, & Rahman N. 2008 Nat Genet, 40(1): 17-22.
Teo ZL, et al Breast Cancer Research, 2013 Feb 28;15(1):R17.
Teo ZL, et al Familial Cancer 2013 Mar 8
Teo ZL, et al British Journal of Cancer, (under review).
Tesoriero A, et al., 2005 Hum Mutat, 26(5): 495.
Thompson D, & Easton D. 2004 J Mammary Gland Biol Neoplasia, 9(3): 221-236.
Verhage BA, et al., 2001 Urology. 57:97-101.
Wong EM, et al., 2011 Cancer Prev Res Jan;4(1):23-33.
Recent Achievements
UP CLOSE
Episode 95 32 min 16 sec
Personalized Medicine: Treatments Tailored to Your Unique Genetic Profile
Assoc Prof Melissa Southey and Prof Dan Roden discuss how advances in genetics research are making it possible to develop customized medications and treatments -- in particular for cancer and cardiac arrhythmia -- based on one's own genetic profile. With science host Dr Shane Huntington.
# 190 27 min 26 sec
Germline confidential: Hunting down genes linked to breast cancer
Genetics researchers Prof Melissa Southey and Prof David Goldgar discuss the enterprise of tracking down genes that make one susceptible to breast cancer. With science host Dr Shane Huntington.
VISIONS
Video Pod cast
3 min 22 sec,
Breast Cancer Gene Discovery
http://visions.unimelb.edu.au/episode/136
Resources
The Genetic Epidemiology Laboratory houses a secure Biorepository suitable for the reception, storage and mobilising of biospecimens necessary for large scale molecular genetic studies of populations. The biorespository currently houses 650,000 biospecimens provided by research particpants of a large number of national and international studies and is equipped with liquid handling CAS robots, a MagnaPURE (Roche) for DNA extraction, class II biological cabinets, 25 Forma freezers (-80), 6 MVE LN2 storage tanks with 24 hour monitoring and alarm systems and a dedicated tissue culture facility.
The histopathology section accommodates a catalogue of pathology material including parafin blocks and slides and is equipped with two microtomes and a DAKO Autostainer.
The molecular biology section of the laboratory accommodates a large spectrum of molecular biological activities, including Next Generation Sequencing Platforms (5500xl SOLiD (Life Technologies) and HiSeq2500 (Illumina), Ion Torrent (Life Technologies), Covaris ultrasonicator, iScan (Illumina) and Tcan Freedom EVO robot, three RotoGene 6000s and a LightCycler480.
Collaborations
University:
Professor John Hopper, Centre for Molecular, Environmental, Genetic and Analytic Epidemiology.
Professor Ingrid Winship, Chair in Adult Clinical Genetics.
Professor Mark Jenkins, Centre for Molecular, Environmental, Genetic and Analytic Epidemiology.
Professor Dallas English, Centre for Molecular, Environmental, Genetic and Analytic Epidemiology.
A/Professor Andrew Lonie, Head Life Science Computational Centre, The University of Melbourne.
Dr Bernie Pope, Victorian Life Sciences Computation Initiative.
External:
National Collaborators:
Professor Graham Giles, Cancer Council Victoria.
A/Professor Gianluca Severi, Cancer Council Victoria.
A/Professor Laura Baglietto, Cancer Council Victoria.
kConFab: http://www.kconfab.org/Index.shtml
International Collaborators:
Professor David Goldgar, Huntsman Cancer Center, University of Utah, USA.
Dr Susan Ramus, University College London, UK.
A/Professor Sean Tavtigian, Huntsman Cancer Center, University of Utah, USA.
COMPLEXO: http://www.path.unimelb.edu.au/research/labs/southey/Complexo.dwt
PRACTICAL: http://ccge.medschl.cam.ac.uk/consortia/practical/
BCAC: http://ccge.medschl.cam.ac.uk/consortia/bcac/links/links.html
OCAC: http://ccge.medschl.cam.ac.uk/consortia/ocac/
ENIGMA: http://enigmaconsortium.org/
The Breast Cancer Family Registry (BCFR), NCI, USA.
Funding
- NHMRC
- Cancer Council Victoria
- Cancer Australia
- Komen Foundation (USA)
- National Institute of Health (USA)
- The University of Melbourne
- Victorian Breast Cancer Research Consortuim
- Prostate Cancer Foundation of Australia
- National Breast Cancer Foundation (Australia)