Medical Research Scotland
PhD Studentship Award
This project is one of 11 four year PhD Studentships funded by Medical Research Scotland (http://www.medicalresearchscotland.org.uk) to be delivered jointly by the named University and Company. The Studentship will provide the first-class academic and commercial training needed to equip the successful candidate for a science career in an increasingly competitive market.
"Spatially‐resolved, highly multiplexed, digital characterisation of protein distribution and abundance in tissue sections using optical barcoding" to be delivered by the University of St Andrews [Supervisors: Professor David Harrison and Dr Peter Caie (School of Medicine)] and Nanostring Technologies Inc (https://www.nanostring.com/) [Company supervisor: Dr Joseph Beecham].
Precise information, derived from the measurement of biomarkers in cancer tissue, helps decide prognosis and prediction of response to new and invariably expensive anti-cancer treatments. Cancers are not uniform; the distribution and interaction of cells and their protein expression profiles within the tumour microenvironment is important. Currently, molecularly profiling cancers either disrupts the tissue giving accurate quantification of many markers, or retains structure but only looks at a few markers giving a subjective description including variability but only guessing quantity.
In this project we will employ cutting-edge image analysis and molecular profiling to ensure we capture spatially resolved, in situ and fully quantified molecular, cellular and morphological data across entire cancer patient tissue sections. The resultant big-data will be analysed through deep machine learning and spatial statistics to identify optimal tissue based features to give an accurate and personalised renal cell carcinoma (RCC) prognosis.
At the University of St Andrews we have developed quantitative approaches to pathological examination of tissue using multiplexed immunofluorescence (up to 5 channels), image analysis and statistical decision tree modelling and, using lessons learned from systems biology, we have shown that the technology can lead to clinically implementable tools in RCC and other cancers.
However, the complexity of RCC requires the co-localised assessment of more molecules than we can currently study through classical immunofluorescence. Nanostring Technologies Inc are developing a 800-plex technology, using optical barcoding as the readout signal, that will dramatically enhance the amount of data available, and which we can analyse and integrate with conventional histopathological findings using our repertoire of quantitative pathology tools.
The successful candidate will join a rapidly expanding team of clinical and scientific specialists in modern pathology. The project will provide training in clinical, digital and molecular pathology while employing industry leading equipment and software. In depth training of automated multi-plexed labelling of tissue and whole slide digital imaging will be provided. The project will employ and develop cutting-edge image analysis algorithms using Definiens Developer software while working closely with our industrial partner (NanoString Technologies Inc) to develop and employ their novel molecular pathology technology. The candidate will receive a unique experience to learn from and work within a medical, academic and commercial setting from university, hospital and industrial settings. Training in PhD research and career development will also be provided.
Informal enquiries should be sent by email to Dr Peter Caie: [email protected]
Candidates must have obtained, or expect to obtain, a first or 2.1 UK honours degree, or equivalent for degrees obtained outside the UK, in an appropriate discipline (an understanding of cancer, molecular biology/pathology or image analysis will be advantageous).
Applications MUST be submitted through the University of St Andrews’ online application system at the following link. Applicants should include a covering letter with their online application, explaining why they wish to carry out this project.
Interviews are expected to take place 2-3 weeks after the closing date for applications.
It is anticipated that the PhD Studentship will start in September 2017.