Job Description:
This project is directly funded by Cancer Research UK for UK/EU students.
Applications and queries should be directed to Dr Matthew Care – M.A.Care@leeds.ac.uk
Co-supervisors – Dr Reuben Tooze, Professor David Westhead
Background: Plasma cell (PC) myeloma is an aggressive blood cancer that remains largely incurable. Precursor states known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smouldering Myeloma precede overt myeloma in almost all patients. The fundamental question is how a ‘terminally differentiated’ cell is oncogenically transformed and if myeloma is maintained from the differentiation of mutated progenitor B-cells or oncogenically transformed PCs.
Objectives: This 4-year CRUK funded PhD project will develop an integrated model of the gene regulatory network of human plasma cell differentiation, and the disruption of this process by oncogenes.
The PhD student will carry out a data-led analysis integrating temporal transcriptomic and epigenetic data (Expression arrays, ChIP-seq, RNA-seq, CpG-Methylation, DNase-Seq) through network/clustering/motif based approaches. The PhD will run as a data-led analysis complementing a parallel hypothesis-led approach. To address this problem we have developed an in vitro model system that allows the generation, maintenance and perturbation of long-lived human PCs, in addition we have access to primary tumour material. Predictions of the data-led approach will be tested in the model system.
Novelty: The combination of local immunology, bioinformatics and clinical expertise, and the generation of a large integrated transcriptomic and epigenetic data-set make this a unique opportunity. The close working relationship between bioinformatics and wet-laboratory teams provides the basis for developing innovative and complimentary approaches to study an important and timely question.
Requirements: Given the large amount of data to be analysed students need to be proficient at programming (preferably Python) and have good analytical and statistical skills. A good working knowledge of genomics, immunology or bioinformatics is also desirable.
References
M. Cocco, S. Stephenson, M. A. Care, D. Newton, N. a Barnes, A. Davison, A. Rawstron, D. R. Westhead, G. M. Doody, and R. M. Tooze, “In vitro generation of long-lived human plasma cells.,” J. Immunol., vol. 189, no. 12, pp. 5773–85, Dec. 2012.
h3. M. A. Care, M. Cocco, J. P. Laye, N. Barnes, Y. Huang, M. Wang, S. Barrans, M. Du, A. Jack, D. R. Westhead, G. M. Doody, and R. M.
Tooze, “SPIB and BATF provide alternate determinants of IRF4 occupancy in diffuse large B-cell lymphoma linked to disease heterogeneity.,” Nucleic Acids Res., vol. 42, no. 12, pp. 7591–610, Aug. 2014.
M. A. Care, S. Barrans, L. Worrillow, A. Jack, D. R. Westhead, and R. M. Tooze, “A microarray platform-independent classification tool for cell of origin class allows comparative analysis of gene expression in diffuse large B-cell lymphoma.,” PLoS One, vol. 8, no. 2, p. e55895, Jan. 2013.
S. L. Barrans, S. Crouch, M. A. Care, L. Worrillow, A. Smith, R. Patmore, D. R. Westhead, R. Tooze, E. Roman, and A. S. Jack, “Whole genome expression profiling based on paraffin embedded tissue can be used to classify diffuse large B-cell lymphoma and predict clinical outcome.,” Br. J. Haematol., vol. 159, no. 4, pp. 441–53, Nov. 2012.
Some useful websites
http://www.bioinformatics.leeds.ac.uk/group.html
http://medhealth.leeds.ac.uk/info/940/experimental_haematology/883/molecular_haematopathology
http://medhealth.leeds.ac.uk/info/940/experimental_haematology
http://www.cancerresearchuk.org/science/research/who-and-what-we-fund/browse-by-location/leeds/university-of-leeds/reuben-tooze-7845 …
Additional Info:
[Click Here to Access the Original Job Post]
This project is directly funded by Cancer Research UK for UK/EU students.
Applications and queries should be directed to Dr Matthew Care – M.A.Care@leeds.ac.uk
Co-supervisors – Dr Reuben Tooze, Professor David Westhead
Background: Plasma cell (PC) myeloma is an aggressive blood cancer that remains largely incurable. Precursor states known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smouldering Myeloma precede overt myeloma in almost all patients. The fundamental question is how a ‘terminally differentiated’ cell is oncogenically transformed and if myeloma is maintained from the differentiation of mutated progenitor B-cells or oncogenically transformed PCs.
Objectives: This 4-year CRUK funded PhD project will develop an integrated model of the gene regulatory network of human plasma cell differentiation, and the disruption of this process by oncogenes.
The PhD student will carry out a data-led analysis integrating temporal transcriptomic and epigenetic data (Expression arrays, ChIP-seq, RNA-seq, CpG-Methylation, DNase-Seq) through network/clustering/motif based approaches. The PhD will run as a data-led analysis complementing a parallel hypothesis-led approach. To address this problem we have developed an in vitro model system that allows the generation, maintenance and perturbation of long-lived human PCs, in addition we have access to primary tumour material. Predictions of the data-led approach will be tested in the model system.
Novelty: The combination of local immunology, bioinformatics and clinical expertise, and the generation of a large integrated transcriptomic and epigenetic data-set make this a unique opportunity. The close working relationship between bioinformatics and wet-laboratory teams provides the basis for developing innovative and complimentary approaches to study an important and timely question.
Requirements: Given the large amount of data to be analysed students need to be proficient at programming (preferably Python) and have good analytical and statistical skills. A good working knowledge of genomics, immunology or bioinformatics is also desirable.
References
M. Cocco, S. Stephenson, M. A. Care, D. Newton, N. a Barnes, A. Davison, A. Rawstron, D. R. Westhead, G. M. Doody, and R. M. Tooze, “In vitro generation of long-lived human plasma cells.,” J. Immunol., vol. 189, no. 12, pp. 5773–85, Dec. 2012.
h3. M. A. Care, M. Cocco, J. P. Laye, N. Barnes, Y. Huang, M. Wang, S. Barrans, M. Du, A. Jack, D. R. Westhead, G. M. Doody, and R. M.
Tooze, “SPIB and BATF provide alternate determinants of IRF4 occupancy in diffuse large B-cell lymphoma linked to disease heterogeneity.,” Nucleic Acids Res., vol. 42, no. 12, pp. 7591–610, Aug. 2014.
M. A. Care, S. Barrans, L. Worrillow, A. Jack, D. R. Westhead, and R. M. Tooze, “A microarray platform-independent classification tool for cell of origin class allows comparative analysis of gene expression in diffuse large B-cell lymphoma.,” PLoS One, vol. 8, no. 2, p. e55895, Jan. 2013.
S. L. Barrans, S. Crouch, M. A. Care, L. Worrillow, A. Smith, R. Patmore, D. R. Westhead, R. Tooze, E. Roman, and A. S. Jack, “Whole genome expression profiling based on paraffin embedded tissue can be used to classify diffuse large B-cell lymphoma and predict clinical outcome.,” Br. J. Haematol., vol. 159, no. 4, pp. 441–53, Nov. 2012.
Some useful websites
http://www.bioinformatics.leeds.ac.uk/group.html
http://medhealth.leeds.ac.uk/info/940/experimental_haematology/883/molecular_haematopathology
http://medhealth.leeds.ac.uk/info/940/experimental_haematology
http://www.cancerresearchuk.org/science/research/who-and-what-we-fund/browse-by-location/leeds/university-of-leeds/reuben-tooze-7845 …
Requeriments :
Skills :
- Bioinformatics
- Biology
- Cancer biology
- Computational Biology
- Programing in Python
- Programing Skills
- Statistics
Areas :
Additional Info:
[Click Here to Access the Original Job Post]