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About the Project

Background and goals:

Breast cancer is the major cause of death among women and 90% of deaths are caused by incurable metastasis. Patients need more therapeutic options. Therefore, a better understanding of the molecular mechanisms underlying breast cancer development and metastasis formation is becoming urgent to uncover novel drug targets. Recent developments in omics technologies including quantitative mass spectrometry-based proteomics and phosphoproteomics offer almost global coverage and a system-wide analysis of changes in protein abundance or signalling pathways using cell lines or patient samples. The project aims at defining phosphoprotein signatures which change during cancer progression, interpreting them using integrative computational modelling approaches, and uncovering novel targets to be experimentally validated.

This project will exploit how quantitative proteomics and bioinformatics enable advancements in our understanding of cancer cell biology and disease mechanisms. Interdisciplinary training will be provided in emerging disciplines (proteomics, bioinformatics).

Training/techniques to be provided:
This project will integrate cutting-edge mass spectrometry-based quantitative proteomics and phosphoproteomics with advanced methods in bioinformatics and mathematical modelling for a comprehensive analysis of signaling signatures in breast cancer.

Entry Requirements:
Candidates are expected to hold a first class honours degree (or equivalent) in a related area / subject (Biology, Biotechnology, Bioinformatics, Biomedicine).

Candidates with experience in mass spectrometry, bioinformatics, and system biology are particularly encouraged to apply. Extremely good communication skills and ability to work in an international and interdisciplinary team are required.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit

Funding Notes

Applications are invited from self-funded students. This project has a Band 3 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.


1. Del Carratore, Schmidt, Vinaixa, Hollywood, Greenland-Bews, Takano, Rogers, Breitling*. Integrated Probabilistic Annotation (IPA): A Bayesian-based annotation method for metabolomic profiles integrating biochemical connections, isotope patterns and adduct relationships. Analytical Chemistry (2019)
2. Tsigkinopoulou, Hawari, Uttley, Breitling. Defining informative priors for ensemble modelling in systems biology. Nature Protocols (2018)
3. Emdal, Pedersen, Bekker-Jensen, Lundby, Claeys, De Preter, Speleman, Francavilla*, Olsen*. Integrated proximal proteomics reveals IRS2 as a determinant of cell survival in ALK-driven neuroblastoma. Sci Signal. (2018)
4. Watson and Francavilla*, Regulation of FGF10 signaling in Development and Disease. Frontiers Genetics (2018)
5. Francavilla* et al., Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer. Cell Reports (2017)

*, corresponding author

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