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Advanced colorectal cancer (CRC) is the UK’s second most lethal cancer, with limited treatment options for unresectable metastatic tumours. Therefore, novel therapeutic strategies are needed to improve patient outcomes.
Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are omega-3 polyunsaturated fatty acids, naturally found in cold water oily fish. EPA is licenced for prophylaxis of cardiovascular events in high-risk individuals and shows promise as an anti-cancer agent to prevent and treat CRC (1, 2, 3). The phase II EMT clinical trial (1), led by prof Hull, demonstrated its safety and potential as an anticancer agent against colorectal cancer liver metastasis. EPA’s mechanisms of action are multifaceted and the contribution of each pathway is most likely context dependent. As the larger phase III clinical trial EMT2 is underway, predictive biomarkers of response need to be identified in order to further translate the findings into oncology clinical practice.
Studies in our lab have demonstrated that human CRC cell lines display differential responses to EPA (3). We have applied a newly emerging molecular classification of CRC tumours to identify sub categories of tumours with increased sensitivity or resistance to EPA. We have observed that CRC cell line exhibiting genome hypermethylation (CIMP+) were more sensitive to EPA than those who were not hypermethylated (CIMP-). Exposure to decitabine, an epigenetic drug, led to an increase in EPA resistance in CIMP+ cell lines, but not in CIMP- cell lines.
The successful candidate will validate these findings further in a wider range of cell line models and epigenetic drugs. Using already obtained RNAseq data, the student will perform bioinformatic studies to identify candidate genes that could drive resistance to EPA and serve as predictive biomarkers of response. The students will then establish the signalling pathways or mechanisms involved in promoting resistance to EPA.
Techniques associated with this project:
This project will utilise a range of cell culture techniques to grow different established cell lines, as well MTT assay and growth curve assays. Bioinformatics studies will be performed using Cytoscape and Reactome alongside data mining publicly available database. Gene expression studies will be performed using real-time RT-PCR and immunohistochemistry/immunofluorescence staining, using cell lines and clinical samples for validation studies.
This project is part of the International PhD Academy: Medical Research
Eligibility:
You should hold a first degree equivalent to at least a UK upper second class honours degree in a relevant subject.
Candidates whose first language is not English must provide evidence that their English language is sufficient to meet the specific demands of their study. The Faculty of Medicine and Health minimum requirements are:
How to apply:
Applications can be made at any time. To apply for this project applicants should complete an online application form and attach the following documentation to support their application.
To help us identify that you are applying for this project please ensure you provide the following information on your application form;
Any queries regarding the application process should be directed to fmhpgradmissions@leeds.ac.uk
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