Researching the development and application of molecular based methods, including mass spectrometry, to improve the identification, characterisation and responses to viruses that cause infectious disease and cancer.
Genetic and epigenetic abnormalities enable cancer stem cells to hijack normal stem cell self-renewal mechanisms that multiply out of control, causing cancer. The major goal of the Cancer and Stem Cell Biology Group is to understand the mechanisms that regulate aberrant self-renewal and drug resistance of malignant stem cells, and to develop cancer stem cell-targeted therapies that are more effective and less toxic for patients with tumours
Cellular immortality is a hallmark of cancer and provides a cancer-specific target for creating anti-cancer drugs with minimal side-effects. The Cancer Cell Immortality Group has developed the only specific biomarker and quantitative assay for the ALT (Alternative Lengthening of Telomeres) immortality mechanism, which now makes it possible to generate novel ALT-targeted therapeutics and diagnostics, as well as furthering our understanding of the ALT cellular immortality mechanism.
Pancreatic cancer claims five Australian lives every day and is one of the nation’s most lethal diseases. Despite aggressive treatment regimes, there has been no improvement in patient survival in the last decade. Evidence suggests that targeting cancer cells alone is not enough. The overall aim of the Pancreatic Cancer Translational Research group is to therapeutically target tumour cells and stromal pancreatic stellate cells (PSCs) which both contribute to chemoresistance in pancreatic cancer.
With the proliferation of biological data over the past decade, bioinformatics has become an indispensable tool in understanding biological processes. The major focus of our research is to contribute to the understanding of the functional aspects of the human genome in health and disease through integrative analysis of the different levels of information encoded by the genome. Our research involves the application of methods in data mining and machine learning to a broad range of problems in genomics, proteomics and molecular evolution with particular focus on cancer biology.