Overview
Topic status: We're looking for students to study this topic.
Breast cancer is the most commonly diagnosed form of cancer in Australian women. The primary tumour itself is rarely the cause for the high mortality which, rather, arises from metastasis of malignant cells. We have identified novel candidate biomarkers that may be associated with the metastasis of breast cancer and the goal of this project is to conduct a study using archived historical tissue samples to determine whether these markers correlate with disease progression and outcome.
Aim 1: Identify the expression of candidate biomarkers related to the IGF family, their receptors, associated intracellular pathways and extracellular molecular interactions in clinical breast cancer samples using high through-put tissue microarrays
Aim 2: Correlate these candidate biomarkers specifically with standard clinical prognostic and predictive markers, disease history and patient outcomes
a) Modelling of the strength of associations between candidate biomarkers and disease history.
b) Classification of patient outcomes based on these biomarkers, taking into account disease history: Semi- and non-parametric classification of outcomes based on biomarkers and disease history using mathematical modelling.
Note - Training can be provided in the mathematical tools, however, some experience with these would be preferred, although intense interest and desire to learn would be sufficient.
Outcomes and Benefits: This project will identify new prognostic indicators for breast cancer patients with different responses to clinical therapeutic interventions. This will provide, for the first time, important evidence informing the clinical management of women with breast cancer.
Methods and techniques that will be developed in the course of this project:
- Development of tissue microarrays
- Immunhistochemistry
- Pathological analysis of breast cancer tissue
- Higher level mathematical modelling
- Study level
- PhD
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
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Please contact the supervisor.
Dr Kerry Manton
Associate Professor David Leavesley
