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Molecular disease stratification of childhood brain tumours (HLS/SE/DRFAPP7P/63593)

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database and may not be available.

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  • Full or part time
    Dr Schwalbe
  • Application Deadline
    Applications accepted all year round

Project Description

Medulloblastoma is the most common central nervous system tumour of childhood. Although advances in treatment have raised survival to ~75%, there are still significant numbers of patients who die of their disease. Moreover, survivors have to contend with long term, life-limiting side-effects of their treatments, due to delivery of radiotherapy to the developing brain.
Molecular sub-classification has revealed that medulloblastoma is a heterogeneous disease, comprising four major subtypes, with different clinical and pathological behaviours. The project would utilise a large, clinically well-annotated cohort of medulloblastoma cases for which molecular data (methylation array, RNA-seq, SNP array, targeted sequencing data) are available.
Using this cohort, the project’s major aims would be:
• The formulation of novel classification schemes that integrate classic clinical prognostic markers, disease subtype and novel molecular markers to refine risk stratification of medulloblastoma, so that patients with a poor prognosis could continue to be aggressively treated, whilst good-prognosis patients could be eligible for reduction in therapy intensity, maintaining cure of their disease, and sparing them from the debilitating late effects of treatment.
• The development of assays suitable for assignment of risk category, to aid clinicians in their treatment decisions. After surgical excision of the tumour, there is a 1 month window before commencement of chemo- and radio-therapy during which time molecular classification of the tumour must be undertaken. Novel, clinically applicable rapid assays which measure the identified markers will be developed using established methodologies.

The project would therefore suit candidates with an interest in performing both bioinformatic and wet-lab experiments, and would provide comprehensive training in state-of-the-art bioinformatic techniques, alongside a rigorous training in genetic analysis that would equip interested applicants for a career in the Life Sciences.

Informal Enquiries
Enquiries regarding this studentship should be made to:
Dr. Ed Schwalbe, [email protected]

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please ensure you quote the advert reference above on your application form.

Eligibility
For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please ensure you quote the advert reference above on your application form.

How to Apply
For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please ensure you quote the advert reference above on your application form.

Funding Notes

This studentship is only open to self-funding candidates. Self-funding candidates are expected to pay University fees and to provide their own living costs. In addition, a ‘bench fee’ will have to be paid to cover project running costs (at a level that will be determined specifically for each project).

References

Combined MYC and TP53 defects emerge at medulloblastoma relapse and define rapidly progressive, therapeutically targetable disease. Hill, R.M., Kujiper, S., Lindsey, J.C., Petrie K., Schwalbe, E.C., Barker, K., Boult, J.K.R., Williamson, D., Ahmad, Z., Hallsworth, A., Ryan, S.L., Poon, E., Robinson, S.P., Ruddle, R., Raynaud, F.I., Howell, L., Kwok, C., Joshi, A., Nicholson, S.L., Crosier, S., Ellison, D.W., Wharton, S.B., Robson, K., Michalski, A., Hargrave, D., Jacques, T.S., Pizer, B., Bailey, S., Swartling, F.J., Weiss, W.A., Chesler, L., Clifford, S.C. 2015. Cancer Cell. 27(1):72-84

DNA methylation profiling of medulloblastoma allows robust subclassification and improved outcome prediction using formalin-fixed biopsies. Schwalbe, E.C., Williamson, D., Lindsey, J.C., Hamilton, D., Ryan, S.L., Megahed, H., Garami, M., Hauser, P., Dembowska-Baginska, B., Perek, D., Northcott, P.A., Taylor, M.D., Taylor, R.E., Ellison, D.W., Bailey, S., Clifford, S.C., 2013. Acta Neuropathologica, 125(3):359-71

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