Pleural Mesothelioma is an asbestos-related cancer, and is one of the deadliest cancer types. Current methods of treatment and early diagnostics are ineffective. Improved early diagnostics and a deeper understanding of the mechanisms driving the disease are thus needed. Recent insights have revealed the detailed mutational landscape underlying mesothelioma (1). These mutations are believed to rewire the cell and cause cancer onset and metastasis through distinct mechanisms. One pathway of particular interest is the Hippo pathway, which is frequently mutated in a substantial subset of mesothelioma cases. Without functional Hippo pathway activity, the co-transcriptional activators YAP/TAZ become hyperactivated and drive mesothelioma onset and progression (2,3). Using advanced cellular model systems and cutting-edge techniques pioneered by the supervisors’ laboratories, we will directly compare mesothelioma cancers originating from the diverse sets of driver mutations. We have formed a team of dedicated scientists in the UK and Sweden to work closely together to generate and integrate new data on genome and proteome levels. Techniques employed include advanced high content imaging assays, cancer cell biology, modeling and innovative proteomics approaches with the aim to obtain in depth functional cellular insights that will lead to real progress for cancer patients.
The project aims to provide in depth pathway analysis and molecular details of mesothelioma and thereby reveal cancer vulnerabilities that can be therapeutically exploited. Through multilayer bioinformatics analyses, we will examine how cancer genome alterations impact proteome level (4), develop testable models, which will be functionally validated in cancer cells. This innovative project will take advantage of isogenic genome edited cells and patient derived material, with the aim of determining how distinct mutations drive mesothelioma initiation and progression. This approach will provide detailed insights into precisely how driver mutations change the proteome in mesothelioma and will provide a new framework to understand cancer biology. We ultimately seek to explore vulnerabilities that might be used as personalized treatment options for mesothelioma. Our insights will also likely provide a benchmark for other types of cancers. In later stages of the project, this will be directly examined in appropriate cellular models. We have formed an international multi-disciplinary team with leading complimentary and synergistic skillsets, that will allow us to obtain detailed pictures of the molecular phenotype of cancer cells by using innovative study designs and taking advantage of recent technological advances including high content imaging, computer modeling, and newly developed mass spectrometry based omics methods (4). We will build network models that can be functionally examined and validated in our cellular models. Overall, this project will take advantage of cutting edge technologies and model systems to understand driver pathways in mesothelioma. This will enable development of new innovative cancer treatments and personalized therapeutic strategies. This PhD project therefore has the potential to uncover fundamental mechanisms, directly inform future stratified therapeutic strategies and deliver real patient benefits.
The successful candidate will gain expertise in the use of the latest technologies in high-content imaging, genome editing, cell biology, computer modeling and mass spectometry, including proteogenomics. The candidate will therefore learn diverse skills at the interface of biomedical and computational systems. These interdisciplinary and quantitative competencies will ensure that the candidate obtains unique interdisciplinary skill sets, becomes an adaptable researcher, who is well prepared for the changing scientific landscape. We are looking for a motivated candidate with an analytical mindset that finds it stimulating to work with large data sets, state of the art equipment, and who will fit into our dedicated, international and friendly teams formed by members with various background from computational science, cell biology to clinical cancer research. The project will be based in Edinburgh but includes stays at Karolinska. As a PhD student, you will benefit from access to cutting-edge research specialties, outstanding scientific facilities and a supportive community to develop and learn.
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow. http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.
For more information about Precision Medicine visit: http://www.ed.ac.uk/usher/precision-medicine
Start: September 2020
Qualifications criteria: Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area.
Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,009 (RCUK rate 2019/20) for UK and EU nationals that meet all required eligibility criteria.
Full eligibility details are available: View Website
Enquiries regarding programme: [email protected]
1. Bueno, R. et al. Comprehensive genomic analysis of malignant pleural mesothelioma identifies recurrent mutations, gene fusions and splicing alterations. Nat Genet 48, 407-16 (2016).
2. Moroishi, T., Hansen, C.G. & Guan, K.L. The emerging roles of YAP and TAZ in cancer. Nat Rev Cancer 15, 73-9 (2015).
3. Hansen, C.G., Moroishi, T. & Guan, K.L. YAP and TAZ: a nexus for Hippo signaling and beyond. Trends Cell Biol 25, 499-513 (2015).
4. Zhu, Y. Orre, L.M. .... & Lehtiö J. Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow. Nat Commun. Mar 2;9(1):903 (2018). Johansson HJ ......, Lehtiö J., Breast cancer quantitative proteome and proteogenomic landscape. Nature Comm, 10, 1600 (2019).