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Research Fellow in Cancer Research

4 months ago


Brighton, United Kingdom University of Sussex Full time

Applications are invited for the post of Research Fellow in Cancer Research (non-clinical) at Brighton and Sussex Medical School (BSMS). We are looking to recruit a scientist with a background in the field of cancer research, or a related discipline to work on a recently awarded Blood Cancer UK project grant.

**Project title: Using NF-κB ‘fingerprints’ to identify therapeutic vulnerabilities within subsets of B cell malignancies.**

Although there have been major advances in treatments for B cell malignancies, heterogeneity both between and within diseases contribute to the variable responses to current therapies. Therefore, there is an urgent need for personalised strategies to accurately predict the optimal drug/drug combination for an individual patient. Aberrant NF-κB transcription is a major player in B cell malignancies and is activated by numerous signalling pathways within the tumour microenvironment (BCR, TLR9, CD40L etc) resulting in proliferation and upregulation of anti-apoptotic proteins. The NF-κB signalling network is comprised of multiple components, which can be activated by different stimuli, giving rise to distinct NF-κB states. We have developed a novel flow cytometry-based NF-κB fingerprinting assay and demonstrated distinct expression patterns between and within different CLL patient samples and DLBCL cell lines. We propose that these different NF-κB fingerprints, coupled with nuclear NF-κB subunit activity, and global gene transcription states, are the key to identifying therapeutic vulnerabilities in individual tumours. The project will generate experimental data, using primary CLL cells and DLBCL cell lines, to create a library of NF-κB signalling states, and then use this library to inform mechanistic mathematical modelling/simulations. The ultimate goal of this interdisciplinary project is to exploit computational models to accurately identify the ‘right drug(s) for the right patient’ and then experimentally test these predictions in the laboratory using patient-derived tumour samples.
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