Exploring expression patterns of uninvolved and involved lymph nodes metastases with regards to disease progression in breast cancers using genomic and transcriptomic analyses

Positive lymph node status is a major prognostic factor in breast cancer. Nodal deposits early in breast cancer can act as a source for seeding and then metastasis to other sites in the body. So far, our knowledge of how the healthy lymph node response to cancer cells, and then influences organ-specific metastatic spread is limited. The aim of this bioinformatics PhD project is to explore changes in lymph nodes and relate them to breast cancer progression, organ-specific metastasis and overall outcome, by analysing whole exome sequencing and RNA-sequencing data of uninvolved and involved lymph nodes and primary breast tumours. Optimal features from these high dimensional data will be extracted and used in Bayesian proportional hazard models.
The student on this project will engage in two complementary activities: bioinformatics analyses on next generation sequencing data and translational immune-oncology research. Prior programming skills in R, python or perl as well as an aptitude for mathematical analyses are essential for this PhD.

For full details, please visit http://www.kcl.ac.uk/health/study/studentships/div-studentships/cancer/grigoriadis-purushotham.aspx