Developing a non-coding RNA predictive biomarker in bladder cancer

About the Project

Muscle invasive bladder cancer can be classified into gene expression subtypes that can help guide chemo- and immunotherapy choices. The GUSTO clinical trial is currently exploring this personalised approach to bladder cancer treatment.

Conventionally, gene expression subtypes are derived from the combined measurement of a selection of coding RNAusing RNA-seq or gene expression microarrays. The aim of this PhD project is to understand how a classnon-coding RNA regulates gene expression signatures and whether non-coding RNA can be used as a biomarker of subtypes of bladder cancer that have differing response to treatment.

Specifically this project aims to:

1. Map non-coding RNA species of the different subtypes of bladder cancer using cell culture models
2. Develop a non-coding RNA biomarker and test this on samples from clinical trials
3. Understand the functional and mechanistic roles of non-coding RNA in specifying gene expression subtypes in bladder cancer

In this project you will use bioinformatics approaches to integrate in-house data with publicly available data and develop candidate biomarkers. You will then use molecular biology techniques to develop a biomarker that can be used clinically. This will be tested on samples from clinical trials including GUSTO. You will also use techniques such as CRISPR and antisense olignucleotides to deplete non-coding RNA species and study the functional effect of this disruption on the phenotype and behaviour of bladder cancer cell lines representing different molecular subtypes.

This project offers the opportunity to work in translational cancer research in a world-leading and interdisciplinary institution.

The supervisory team includes primary supervisor Dr Jon Griffin, Pathologist and Senior Clinical Lecturer, Dr Dan Bose, Senior Lecturer and Dr Ian Sudbery, Senior Lecturer.

Proposed start date: 01 October 2026

Entry Requirements: Candidates must have a first or upper second class honours degree or significant research experience. Experience of molecular biology techniques (nucleic acid extraction, qPCR, biomarker development and evaluation) and/or bioinformatics is desirable. Master's level research experience is desirable.