QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.
Found 4 matching student topics
Displaying 1–4 of 4 results
Patient-derived oncology NAMs for preclinical breast cancer research and therapeutic evaluation
New approach methodologies (NAMs), including advanced 3D cultures and microphysiological systems (MPS), are creating new opportunities to develop more human-relevant approaches for preclinical cancer research. However, translating these technologies from established cell lines to patient-derived tumours remains challenging because of limited tissue availability, tumour heterogeneity and variability in model establishment and performance.Building on established QUT expertise in patient-derived bioengineered breast tumour models, this project will develop robust and reproducible patient-derived oncology NAMs for preclinical breast cancer research and therapeutic evaluation.Breast …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
Eribulin effects on epithelial mesenchymal plasticity and therapy response
Epithelial mesenchymal plasticity (EMP) is a highly regulated and powerful cellular process that is fundamental in embryonic development (1), which is hijacked by cancer cells for metastatic progression and therapy resistance in epithelial cancers (2). Eribulin is a microtubule-inhibiting cancer drug discovered in sea sponges and approved for 3rd line therapy in metastatic breast cancer, which was shown to block EMP (3).We hypothesise that eribulin’s reversal of EMT will sensitise breast cancer cells to other therapies and ultimately improve patient …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Development of a machine learning algorithm for high throughput cell response data in drug therapy
High-throughput screening assays are essential for accelerating drug discovery, but current assays often rely on endpoint measurements that do not capture the dynamic response of cells to drug treatment. Machine learning algorithms (MLAs) have the potential to enable real-time, high-throughput monitoring of cell response to drug treatment by analyzing complex datasets generated by multiplexed live-cell assays. This research project aims to develop an MLA for enabling high throughput cell response data in drug treatment. The project will involve three main …
- Study level
- Honours
- Faculty
- Faculty of Engineering
- School
- School of Computer Science
- Research centre(s)
- Centre for Biomedical Technologies
Centre for Biomedical Technologies
Engineering 3D osteocyte–tumour microenvironments to study bone metastasis and therapeutic response
Project Reference: #2MPQC-HuECM1Preferred Project Start: Late 2026/Early 2027How do cancer cells communicate with bone cells, and can we recreate these interactions in the laboratory to improve therapy testing?When cancer spreads to bone, tumour cells enter a highly specialised microenvironment containing multiple cell types and a complex extracellular matrix. Osteocytes are embedded throughout this matrix and form an interconnected cellular network that senses and regulates changes within bone. However, their contribution to cancer progression and treatment response remains poorly understood.Conventional two-dimensional …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
- Centre for Biomedical Technologies
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