Molecular Oncology

Our mission is to advance precision oncology by identifying the most effective cancer treatment strategies and biomarkers

Dr Olga Kondrashova

Team Head

Research Focus

We utilise advanced bioinformatic and machine learning methodologies to analyse a variety of cancer data types, including genomic, transcriptomic and DNA methylation data. This analysis allows us to understand how different cancers respond to treatments and influence patient outcomes.

A large part of our work involves studying pre-clinical cancer models to ensure their accurate representation of human disease, thereby enabling the discovery of treatment strategies and biomarkers that can be translated into clinic.

Our research spans multiple solid cancer types, including ovarian, endometrial, breast and lung cancer. Our work is highly collaborative; we partner with several clinical and molecular cancer laboratories to facilitate the most translatable research.

Gallery

Research Projects

Current Research Projects

Overcoming PARP inhibitor resistance in ovarian and breast cancer

Predicting pathogenicity of BRCA1 and BRCA2 genetic variants

Overcoming treatment resistance in KRAS-mutant lung cancer

Past Research Projects

Using machine learning and tumour microenvironment profiling in breast cancer treatment and prognosis predictions. Metro North Health and Hospital Service (MNHHS) Collaborative Research Grant 2020-2022


Research Team

Lijun Xu

Brett Liddell

Siddharth Pruthi

Binny Jaradi


Funding

  • NHMRC Investigator Grant “Improving outcomes for patients with homologous recombination deficient cancer” 2022-2026
  • NHMRC Synergy Grant “Improving outcomes for lung cancer patients: Discovering targetable vulnerabilities in lung cancer” 2022-2026
  • OCRF-ACRF collaborative funding for ovarian cancer research 2024-2026

Publications

Xu, L. et al. "High-level tumour methylation of BRCA1 and RAD51C is required for homologous recombination deficiency in solid cancers." NAR Cancer 6.3 (2024): zcae033.

Tran, KA. et al. "Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures." Nature Communications 14.1 (2023): 5758.

Zeissig, MN. et al. "Next batter up! Targeting cancers with KRAS-G12D mutations." Trends in Cancer (2023).

Google Scholar


Further Information



External Collaborations
  • Professor Clare Scott, WEHI
  • Associate Professor Kate Sutherland, WEHI
  • Professor Andreas Strasser, WEHI
  • Professor Marco Herold, ONJCRI
  • Associate Professor Marian Burr, ANU
  • Dr Garrett Frampton, Foundation Medicine
  • Dr Amy McCart Reed, UQCCR
  • Professor Andreas Obermair, UQCCR
  • Dr Po-Ling Inglis, RBWH
  • Professor Rik Thompson, QUT