- Close date
- Sunday, 31 December 2023
- Academic background
- Sciences, Health Sciences
- Host campus
- Pathology (Dunedin)
- Dr Nicholas Fleming
Cancer patients vary in their experience with the disease, with some experiencing more aggressive disease than others. Moreover, patients also vary widely in their response to therapeutics, and do better when their treatment is tailored to their individual disease. Recently, a new class of cancer drugs called the immune checkpoint inhibitors (ICIs) has revolutionised cancer treatment, giving improved outcomes for many cancer types not previously seen. However, many patients still do not respond to these drugs and so it's important to be able to predict who will respond and who will do better with other therapeutics.
An important determinant of patient variation are the common natural genetic variations in our genomes such as single nucleotide polymorphisms (SNPs). A particular SNP that is expected to make a large impact on cancers, is one that we know to alter one of our checkpoint inhibitor proteins. The SNP is known to alter a patient's risk of cancer progression and because it alters an ICI target, it is also expected to alter response to these drugs too. However, it is difficult to test this because we do not currently have animal models that mimic its effects.
In this project, you will determine whether this human SNP can be replicated in mouse cells, enabling the subsequent use of mice to test its effects against ICI treatments. People differ from mice subtlety in the region where this SNP alters the encoded protein, therefore it is not clear that change can be mimicked correctly. CRISPR-Cas9 will be used to modify mouse cell lines from the T cell lineage, to make cells expressing the altered protein. Next, the cells will be tested for altered expression of the protein using flow cytometry and western blotting. If that is confirmed, then cell biology experiments will be performed to test whether the altered state impacts on functions of the protein.
Together, these findings will help establish whether it is viable test the effects of the SNP in animal models.
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