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Dr Dylan Glubb

Honorary Associate Professor

School of Biomedical Sciences
Faculty of Medicine
d.glubb@uq.edu.au

Overview

After completing his BSc and MSc (Hons) at the University of Canterbury (NZ), Dylan worked for five years as a Research Scientist at Antisoma Research Limited (London, UK), developing antibody-enzyme fusion proteins for cancer therapy. He returned to New Zealand to carry out his PhD research into antidepressant pharmacogenomics at the University of Otago. Afterwards, he continued working at the University of Otago as a Research Fellow, studying the biological function of genes involved with inflammatory bowel disease. Dylan moved to the United States in 2009 to perform postdoctoral training, researching the functional genetics of the VEGF-pathway and its relationship with cancer at the University of Chicago and, subsequently, the University of North Carolina, Chapel Hill.

In 2013, Dylan began working at QIMR Berghofer and has undertaken the functional follow-up of large-scale genetic studies of breast, endometrial and ovarian cancer to identify the likely causal variants and genes that mediate associations with cancer risk and survival. He has been awarded both internal and NHMRC grant funding to support these studies. Since 2019, Dylan has held an Honorary Associate Professorship at UQ

As of early 2021, Dylan has authored one conference report, two editorials, two book chapters, six reviews and 31 original research articles. He is first or last author on 20 of these publications and 27 of his publications have been cited at least 10 times. According to CiteScore, since 2010, 53% of his articles have been published in journals ranked in the top 10% and 19% of hispublications are in the 10% most cited publications worldwide.

Research Interests

  • Gynaecological cancer genetics
    Primarily endometrial cancer
  • Functional genomics of gynaecological cancer

Research Impacts

Large numbers of germline genetic variants have been found to associate with disease. A major roadblock in our understanding of how genetics contribute to disease has been a lack of knowledge of the molecular effects of variants. Thus, the aim of my research program is to use genetic analyses to assign function and gene targets to variants associated with disease-related phenotypes. Dylan's knowledge impact is evidenced by 19 articles, with an average of 27 citations per article and 12 articles in journals in top 10% of their field (e.g. Nature, Nat Genet, Am J Hum Genet). Key impacts include:

•Identifying >30 genes with evidence of targeting by disease-related variants (18 articles)

•Providing support for the new paradigm that multiple variants affect target gene expression at disease loci (Corradin et al. Nat Genet 2016)

•Calibrating a functional assay for diagnostic assessment of Lynch syndrome genetic variants of uncertain significance (Drost et al, Genet Med 2018; in top 2% of articles for online attention)

As evidence of significant influence beyond my field, Dylan’s research has:

•Led (in collaboration with Dr McHugh, University of Huddersfield) to screening of ~400,000 compounds by the European Lead Factory (EU public-private partnership; project #ELFSC13_03), identifying candidates that target ADM receptors for pain/depression therapy

•Been cited in 53 research areas (Web of Science)

As evidence of recognition of Dylan's research program across multiple countries/beneficiaries:

•His articles have been cited by researchers from 1912 institutions from 41 countries (Web of Science) and been downloaded 8,510 times (ScienceDirect)

•6 articles have been mentioned in 72 news stories in 11 countries, 7 have online attention scores in the top 10% (Altmetric)

•Dylan has spoken at 8 international meetings and received 6 international awards, including selection as one of 12 finalists (550 applicants) for the ASHG/Charles J. Epstein Award for Excellence in Human Genetics Research

Publications

View all Publications

Supervision

View all Supervision

Available Projects

  • Identifying the regulatory targets of common endometrial cancer risk variants

    We and our international Endometrial Cancer Association Consortium collaborators have identified common genetic variation at 16 genomic regions that associates with endometrial cancer risk. Although we have identified potentially causal risk variants, at most regions we do not know which genes these variants target. However, we have conducted global (HiChIP) analyses of DNA looping to identify physical interactions between genes and regulatory elements at endometrial cancer risk regions in endometrial cancer cell lines. These experiments constitute an essential step for the translation of genetic findings into advances in our knowledge of endometrial cancer biology and the identification of potential targets for therapy.

    Aim: To identify high confidence gene regulatory targets of endometrial cancer risk variants using DNA looping analyses and other functional genomic datasets.

    Approach: Depending on the applicant’s expertise, this project could have either a wet-lab and/or a bioinformatics focus. We already have a wealth of endometrial cell DNA looping data that can be coupled with complementary datasets (gene expression, histone modification and transcription factor ChIP-seq) for bioinformatic analyses to prioritise regulatory target genes. To extend our findings from DNA looping analysis of endometrial cell lines, we are also interested in performing analysis of human endometrial organoids from normal, hyperplastic and tumoural endometrium. These organoids should provide experimental systems that better recapitulate the morphological and genomic features of human tissue.

    Outcome: Through the identification of high confidence gene targets at endometrial cancer risk regions, we will gain a deeper understanding of endometrial cancer aetiology and identify potential targets for endometrial cancer therapy.

    TO APPLY FOR THIS PROJECT, PLEASE CONTACT THE PROJECT SUPERVISOR/S

    • A/Professor Tracy O’Mara

      Tracy.OMara@qimrberghofer.edu.au

    • A/Professor Dylan Glubb

      Dylan.Glubb@qimrberghofer.edu.au

  • Genetic epidemiology of endometrial cancer

    Endometrial cancer is the most commonly diagnosed invasive gynaecological cancer in developed countries. In contrast with many cancers, the incidence and mortality of endometrial cancer is steadily increasing, largely due to increasing rates of obesity, the strongest risk factor for this disease. Through leadership of the Endometrial Cancer Association Consortium (ECAC), our lab runs the largest genetic study of endometrial cancer. To date, we have identified 16 genetic regions associated with endometrial cancer predisposition by genome-wide association study (GWAS), which account for ~25% of the genetic heritability attributable to common genetic variants (O’Mara et al, Nat Commun 2018). Incorporation of existing GWAS data with newly acquired GWAS datasets from international collaborators will identify further genetic regions associated with endometrial cancer risk. Additionally, we have approved access to large, well-phenotyped international datasets (e.g. UK Biobank, N = 500,000). This allows us unparalleled ability to examine the genetics of endometrial cancer, as well as explore its relationship with risk factors, such as obesity.

    Aims: To identify new genetic risk regions for endometrial cancer, by performing the largest GWAS meta-analysis for this disease. To use computational approaches to identify and explore risk factors of endometrial cancer. To use genetic data to construct and test risk prediction models for endometrial cancer.

    Approaches: This project will use standard GWAS pipelines to identify genetic variants associated with endometrial cancer risk, including imputation, QC and association testing. Post-GWAS analyses to explore novel regions could also be performed (e.g. eQTL analyses, integration with functional genomic datasets). The relationship between endometrial cancer and potential/known risk factors will be performed using approaches such as genetic correlation (LD Score Regression) and Mendelian randomization. Endometrial cancer risk prediction models will be constructed using polygenic risk scores in combination with endometrial cancer environmental risk factors and tested for efficacy in independent datasets.

    TO APPLY FOR THIS PROJECT, PLEASE CONTACT THE PROJECT SUPERVISOR/S

    • A/Professor Tracy O’Mara

      Tracy.OMara@qimrberghofer.edu.au

    • A/Professor Dylan Glubb

      Dylan.Glubb@qimrberghofer.edu.au

View all Available Projects

Publications

Book Chapter

Journal Article

Conference Publication

  • The XVth World Congress of Psychiatric Genetics, October 7-11, 2007: Rapporteur summaries of oral presentations

    Alkelai, Anna, Baum, Amber, Carless, Melanie, Crowley, James, DasBanerjee, Tania, Dempster, Emma, Docherty, Sophia, Hare, Elizabeth, Galsworthy, Michael J., Grover, Deepak, Glubb, Dylan, Karlsson, Robert, Mill, Jonathan, Sen, Srijan, Quinones, Marlon P., Vallender, Eric J., Verma, Ranjana, Vijayan, Neethan, Villafuerte, Sandra, Voineskos, Aristotle N., Volk, Heather, Yu, Lan, Zimmermann, Petra and DeLisi, Lynn E. (2008). The XVth World Congress of Psychiatric Genetics, October 7-11, 2007: Rapporteur summaries of oral presentations. doi: 10.1002/ajmg.b.30711

PhD and MPhil Supervision

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Identifying the regulatory targets of common endometrial cancer risk variants

    We and our international Endometrial Cancer Association Consortium collaborators have identified common genetic variation at 16 genomic regions that associates with endometrial cancer risk. Although we have identified potentially causal risk variants, at most regions we do not know which genes these variants target. However, we have conducted global (HiChIP) analyses of DNA looping to identify physical interactions between genes and regulatory elements at endometrial cancer risk regions in endometrial cancer cell lines. These experiments constitute an essential step for the translation of genetic findings into advances in our knowledge of endometrial cancer biology and the identification of potential targets for therapy.

    Aim: To identify high confidence gene regulatory targets of endometrial cancer risk variants using DNA looping analyses and other functional genomic datasets.

    Approach: Depending on the applicant’s expertise, this project could have either a wet-lab and/or a bioinformatics focus. We already have a wealth of endometrial cell DNA looping data that can be coupled with complementary datasets (gene expression, histone modification and transcription factor ChIP-seq) for bioinformatic analyses to prioritise regulatory target genes. To extend our findings from DNA looping analysis of endometrial cell lines, we are also interested in performing analysis of human endometrial organoids from normal, hyperplastic and tumoural endometrium. These organoids should provide experimental systems that better recapitulate the morphological and genomic features of human tissue.

    Outcome: Through the identification of high confidence gene targets at endometrial cancer risk regions, we will gain a deeper understanding of endometrial cancer aetiology and identify potential targets for endometrial cancer therapy.

    TO APPLY FOR THIS PROJECT, PLEASE CONTACT THE PROJECT SUPERVISOR/S

    • A/Professor Tracy O’Mara

      Tracy.OMara@qimrberghofer.edu.au

    • A/Professor Dylan Glubb

      Dylan.Glubb@qimrberghofer.edu.au

  • Genetic epidemiology of endometrial cancer

    Endometrial cancer is the most commonly diagnosed invasive gynaecological cancer in developed countries. In contrast with many cancers, the incidence and mortality of endometrial cancer is steadily increasing, largely due to increasing rates of obesity, the strongest risk factor for this disease. Through leadership of the Endometrial Cancer Association Consortium (ECAC), our lab runs the largest genetic study of endometrial cancer. To date, we have identified 16 genetic regions associated with endometrial cancer predisposition by genome-wide association study (GWAS), which account for ~25% of the genetic heritability attributable to common genetic variants (O’Mara et al, Nat Commun 2018). Incorporation of existing GWAS data with newly acquired GWAS datasets from international collaborators will identify further genetic regions associated with endometrial cancer risk. Additionally, we have approved access to large, well-phenotyped international datasets (e.g. UK Biobank, N = 500,000). This allows us unparalleled ability to examine the genetics of endometrial cancer, as well as explore its relationship with risk factors, such as obesity.

    Aims: To identify new genetic risk regions for endometrial cancer, by performing the largest GWAS meta-analysis for this disease. To use computational approaches to identify and explore risk factors of endometrial cancer. To use genetic data to construct and test risk prediction models for endometrial cancer.

    Approaches: This project will use standard GWAS pipelines to identify genetic variants associated with endometrial cancer risk, including imputation, QC and association testing. Post-GWAS analyses to explore novel regions could also be performed (e.g. eQTL analyses, integration with functional genomic datasets). The relationship between endometrial cancer and potential/known risk factors will be performed using approaches such as genetic correlation (LD Score Regression) and Mendelian randomization. Endometrial cancer risk prediction models will be constructed using polygenic risk scores in combination with endometrial cancer environmental risk factors and tested for efficacy in independent datasets.

    TO APPLY FOR THIS PROJECT, PLEASE CONTACT THE PROJECT SUPERVISOR/S

    • A/Professor Tracy O’Mara

      Tracy.OMara@qimrberghofer.edu.au

    • A/Professor Dylan Glubb

      Dylan.Glubb@qimrberghofer.edu.au

This staff member is a UQ Expert for media in the following fields:

Gene regulation, Gynaecological cancer genetics

They are happy to lend their expertise to your articles or broadcasts and share their research discoveries and insights with the community via media channels.

For additional assistance with story ideas, general advice and information or help with seeking further experts, please email the UQ Media Team or telephone (07) 3365 1120.

Links

ResearcherID: M-7514-2016

ORCID: 0000-0002-2184-7708

Scopus ID: 23970679000

Google Scholar ID: gZPuM1oAAAAJ

Personal Profile: Link

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