Main Menu

Scientific aims and themes

Find out more about the themes and aims of the Centre for Translational Immunotherapy.

Immunogenomics

Integration of genomics and immunology to study the immune response. This involves high throughput interrogation of tumour antigen and T cell repertoires, and the analysis of mutations and gene expression using bulk and single cell sequencing. Using this information, we can interpret the functionality and effectiveness of the immune response.

Theme leads: Dr Ben O’Leary, Kerry Fenwick, Dr Andrew Feber

Single cell analysis 

Immune profiling by flow cytometry and single cell RNA sequencing allows for identification and characterization of specialized and rare immune cell subtypes. Multi-parameter flow cytometry is a form of semi-automated, quantitative fluorescence microscopy with the ability to process large numbers of single cells in a short period of time. Using tailor-made antibody panels assessing up to 28 parameters simultaneously, researchers can perform a detailed and customized analysis of the tumour immune landscape.

Theme leads: Ian Titley, Alan Dunlop 

Proteomics and peptidomics

Quantitative mass spectrometry analysis of tumour samples using global proteomics approaches to study how mutations determine cellular processes and immune resistance mechanisms, as well as identifying biomarkers of disease states including cancers-specific proteins, endogenous peptides presented on MHC Class I and II molecules (the immunopeptidome). These methods are important for precision medicine and development of new treatment strategies.

Theme leads: Professor Jyoti Choudhary, Dr Marco Gerlinger

Bioinformatics

With the increasing size and complexity of genomic, transcriptomic and proteomic data sets generated from patient samples and pre-clinical models, bioinformatic tools have become increasingly important for data analysis and deconvolution. Bioinformatic methods of network modelling and integrative data analysis work towards finding molecular patterns that describe active signalling pathways and identifying antigenic determinants that drive tumour immunogenicity, all of which aid in the design of personalized treatments.

Theme leads: Dr Anguraj Sadanandam, Dr James Campbell

Clinical translation

Development and design of clinical trials involving immunomodulatory treatments, with a particular focus on immune-monitoring of patient samples (eg tumour, blood, urine, ascites).   

Theme leads: Dr Andrew FurnessDr Anna Wilkins

Pre-clinical modelling

Using in vitro assays and animal models that accurately mimic the pathological conditions and therapeutic interventions seen in the clinic, hypothesis-driven pre-clinical modelling is essential for performing mechanistic studies and testing of novel combination strategies. 

Theme leads: Esther Arwert, Dr Astero Klampatsa, Dr Erik Wennerberg, Dr Marco Bezzi

Digital pathology

Digital pathology is the acquisition, interpretation and analysis of pathology information in a digital environment. Novel approaches to view and interpret digitized tissue slides, including AI-based deep-learning neural networks, allows for sophisticated mapping of the tumour microenvironment and for rapid and optimized identification of immune infiltration patterns across many samples. 

Theme leads: Professor Manuel Salto-Tellez, Dr Katharina von LogaDr Yinyin Yuan

In this section

Scientific aims and themes