Dr Xiao Fu - Integrative Modelling

Introduction

Complex and dynamic interactions between cancer cells and elements of the tumour microenvironment (TME) underlie tumour development and contribute to therapy resistance. Facilitated by multiplex imaging and spatial omics data, architectural features of the TME organisation associated with clinical outcomes have been characterised in various types of solid tumours. One example is immune exclusion, where T lymphocytes are spatially excluded from tumour nests, limiting the effectiveness of immune checkpoint blockade-based immunotherapy. How clinically relevant TME architecture develops dynamically and how altering cellular properties and behaviours can re-sculpt TME organisation in favour of therapy response is less well established. We aim to gain insight into the dynamic delineation of, and the mechanistic basis for, clinically relevant TME organisation.

We focus on developing computational methods to map spatial features of the TME and deconstruct principles underlying the TME organisation. We are interested in a variety of approaches, including:

  • Mechanistic models and computer simulations to investigate dynamic delineation of the TME organisation, such as sculpting of tumour/stroma architecture and spatial distribution of immune cells
  • Quantitative analysis of molecular and spatial tumour data to characterise architectural features of the TME organisation, such as cell communities and neighbourhoods
  • Machine learning frameworks to infer cellular and molecular mechanisms underpinning characteristic TME architectures.

We collaborate closely with experimental and clinical research groups. In application of our computational methods to spatial and molecular data of various solid tumours, including colorectal and pancreatic cancers, our goals are to discover novel spatial TME features associated with clinical outcomes and to identify cellular and molecular mechanisms for re-sculpting TME organisation in favour of therapy response and tumour elimination.