Functional Cancer Genomics

To identify and characterise new drug targets for breast and ovarian cancers

Professor Stacey Edwards

Senior Group Leader

Research Focus

The Functional Cancer Genomics Group is focused on identifying new therapeutic targets for breast and ovarian cancer.

We are particularly interested in those targets that have genetic evidence linking a DNA variant to risk of the cancers. Most risk variants fall in noncoding regions of the genome and are enriched in DNA regulatory elements such as enhancers, which can be located hundreds of kilobases away from their target genes.

The noncoding genome also serves as a template for the transcription of long noncoding RNAs (lncRNAs), which often show cell-type-specific expression and function, making them exceptional drug targets.

We integrate genetic information with a diverse range of sophisticated molecular approaches to identify and evaluate protein-coding genes and lncRNAs that are driving cancer development.

Gallery

Research Projects

Current Research Projects

Connecting the noncoding genome to breast cancer development

Combining genetics and genomics to tackle ovarian cancer

Leveraging genomics to overcome drug resistance in ovarian cancer

Past Research Projects

Connecting the genome to gene function in cutaneous melanoma (NHMRC; GNT1182775)

Can a recurrent enhancer mutation drive Luminal B breast cancer development? (National Breast Cancer Foundation; IIRS-18-053)

High-throughput identification of new breast cancer genes from GWAS (NHMRC; GNT1120563)


Research Team

Larissa Cassiano

Shenyu Chen

Lucy Su-Hyun Ock

Chun Guo


Funding

  • National Health and Medical Research Council of Australia (NHMRC)
  • US Army Department of Defense
  • National Breast Cancer Foundation
  • Ovarian Cancer Research Foundation
  • Australia Cancer Research Foundation
  • Cancer Council Queensland
  • Perpetual IMPACT Philanthropy Program


Publications

Wang L et al (2023). CRISPR-Cas13d screens identify KILR, a lncRNA tumor suppressor associated with breast cancer risk. bioRxiv: 10.1101/2023.11.16.567471

Bitar M et al (2023). Redefining normal breast cell populations using long noncoding RNAs. Nucleic Acids Res. 51:6389-6410.

Beesley J et al (2020). eQTL colocalization analyses identify NTN4 as a candidate breast cancer risk gene. Am J Hum Genet. 107:778-787.

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Further Information



External Collaborations
  • Breast Cancer Association Consortium (BCAC)
  • Professor Douglas Easton, Cambridge University, UK
  • Professor Alison Dunning, Cambridge University, UK
  • Professor John Hooper, The University of Queensland, TRI, AUS
  • Professor Sunil Lakhani, The University of Queensland, UQCCR, AUS
  • Associate Professor Joseph Rosenbluh, Monash University, AUS
  • Associate Professor Rakesh Veedu, Murdoch University, AUS
  • Dr Kevin Brown, National Cancer Institute, USA