Discovering The Cell Of Origin For Rare Ovarian Cancers
Funder
National Health and Medical Research Council
Funding Amount
$599,438.00
Summary
Ovarian cancer has many different varieties, and even though they all grow at the ovary, for some types we don't know the cell where the cancer starts. Using novel sequencing methods, this study will find the tissue of origin for two rare subtypes. This finding will help us to develop appropriate pre-clinical models that we can use to test emerging cancer therapies. Identifying the cell of origin will provide key insights into early detection or even prevention of these rare but deadly diseases.
Identification Of Therapy-resistant Cells Driving Relapse In Medulloblastoma From Integrated Spatial Transcriptomics And Tissue Imaging
Funder
National Health and Medical Research Council
Funding Amount
$749,272.00
Summary
Medulloblastoma (MB) is the most common cause of cancer related mortality in children, with relapsed MB nearly a universally fatal event. Relapsed MB can be caused by pre-existing rare cells that escape treatment and continue to evolve. This project will identify the organisation of all cell types within patient derived xenograft models of MB, monitoring how this changes throughout tumour progression and drug treatment. We will identify rare cells responsible for driving recurrence.
Modulating COVID-19 Disease By Targeting Virus And Virus-induced Responses Through Pharmaceutical And Mechanical Ventilation Strategies: SARS-CoV-2 S-protein, ACE2 And TMPRSS2
Funder
National Health and Medical Research Council
Funding Amount
$628,856.00
Summary
COVID-19 is a current global pandemic that is likely to be an on-going threat. We need a multipronged strategy to combat COVID-19, including therapeutic anti-virals and clinical practice management strategy. We will address both these points to define the mechanisms triggering disease, test existing drugs targeting androgens and modify the way doctors use ventilators to treat COVID-19 disease in the intensive care unit. Outcomes will have impact beyond COVID-19 for managing viral lung disease.
The Role Of LINE Encoded Natural Antisense Transcripts In Immune Regulation
Funder
National Health and Medical Research Council
Funding Amount
$934,853.00
Summary
Genetic information underpins all life on earth and is processed to make proteins, which determine the characteristics of an organism. However, only about 2% of our whole genome is made up of genes that encode proteins; the other 98% is non-coding and its function remains poorly understood. This proposal aims to utilize cutting edge genomic technologies to generate new knowledge about how the non-coding genome regulates the expression of protein coding genes in human autoimmune disease.
About one in eight known genetic disorders involve DNA alteration that activates a cellular quality control mechanism that disables the affected gene. This mechanism is more efficient in some individuals than others. It can influence disease outcomes and severity. We will engineer and apply tools and models to measure and manipulate this crucial cellular mechanism. This will allow us to predict disease severity as well as to intervene where a manipulation of this mechanism will be beneficial.
Advancing The Spatial Analysis Of Cells In Tissues To Profile The Tumour Microenvironment
Funder
National Health and Medical Research Council
Funding Amount
$187,918.00
Summary
Tumours are composed of a mix of different cells, including cancer cells, immune cells and other cells supporting tumour growth. These cells are not organised randomly, but rather are distributed in specific patterns. Here we will develop computational methods to detect these patterns and determine what statistical tests should be used to compare samples. This project will give us the tools to investigate how the location of cells in tissues relates to treatment response and survival.
Identifying Unintentional Effects Of Medication Using Statistical Genetics Analyses Of Large-scale Genetic And Genomic Data
Funder
National Health and Medical Research Council
Funding Amount
$251,441.00
Summary
An increasing number of studies have highlighted unknown adverse effects of medication, for example, use of statins to lower cholesterol with increased risk of type 2 diabetes. The gold standard approach to confirm these effects is randomised control trials, which may not always be feasible or ethical, and are very expensive. This project aims to apply innovative statistical genetics approaches to (genetic and genomic) 'big-data' to predict unknown effects of commonly prescribed medications.
Sudden cardiac death (SCD) is a devastating consequence of a number of heart diseases. Underlying causes include inherited heart muscle problems (cardiomyopathies), with no cause found in 40%. Our study will investigate the role of 'concealed cardiomyopathy' cases, i.e. those with a SCD event with no evidence of heart disease, but carry errors in heart genes. Our findings will translate rapidly into more targeted clinical and genetic evaluation of families with the ultimate goal to prevent SCD.
Biomechanics Meets Phenomics: Towards Understanding And Predicting Abdominal Aortic Aneurysm (AAA) Disease Progression
Funder
National Health and Medical Research Council
Funding Amount
$1,324,897.00
Summary
The criterion used to decide whether to operate on an abdominal aortic aneurysm (AAA), based on the maximum diameter, does not take into consideration the rupture risk for a given patient. By combining imaging, computational biomechanics and metabolic phenotyping, we will assess the structural integrity of an AAA and local structural changes of systemic response. These will allow improved differentiation of rupture risk, leading to better outcomes for patients and savings for the health system.
ARX- A Hub Gene For A Common Biological Pathway In Schizophrenia
Funder
National Health and Medical Research Council
Funding Amount
$707,974.00
Summary
Schizophrenia is a severe psychiatric disorder with no cure. I have identified that some people with schizophrenia show variations to a gene called ARX. This project will use preclinical mouse models to explore how variations to the Arx gene affect brain molecules, networks of cells and behavioural outcomes. This biological pathway will provide the framework for the identification of new molecules to target therapeutically to modify the biological course of schizophrenia and improve outcomes.