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.
EmailLab Report
Key Publications
Fu^ X, Sahai E, Wilkins^ A. Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response. The Journal of Pathology.2023;
Fu X*, Zhao Y,* Lopez JI, Rowan A, Au L, Fendler A, Hazell S, Xu H, Horswell S, Shepherd STC, Spencer CE, Spain L, Byrne F, Stamp G, O'Brien T, Nicol D, Augustine M, Chandra A, Rudman S, Toncheva A, Furness AJS, Pickering L, Kumar S, Koh DM, Messiou C, Dafydd DA, Orton MR, Doran SJ, Larkin J, Swanton C, Sahai E, Litchfield K, Turajlic S, Bates PA. Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study. Nat Ecol Evol. 2022;6:88-102.
Zhao Y*, Fu X*, Lopez JI*, Rowan A, Au L, Fendler A, Hazell S, Xu H, Horswell S, Shepherd STC, Spain L, Byrne F, Stamp G, O'Brien T, Nicol D, Augustine M, Chandra A, Rudman S, Toncheva A, Pickering L, Sahai E, Larkin J, Bates PA, Swanton C, Turajlic S, Litchfield K. Selection of metastasis competent subclones in the tumour interior. Nat Ecol Evol. 2021;5:1033-1045.
*co-first authorship
^co-corresponding authorship
Biography
Education and Qualifications
2017: PhD, Biological Physics, Indiana University, Bloomington, USA
2012: BSc, Physics, Nanjing University, Jiangsu, China
Appointments
2023-present: Beatson Research Fellow, CRUK Beatson Institute, Glasgow, UK
2017-2023: Postdoctoral Researcher, Francis Crick Institute, UK
Awards and Fellowships
2022 Prostate Cancer Research grant, co-led by Erik Sahai and Anna Wilkins
2012 Eli Lilly Fellowships in Biocomplexity, Indiana University Bloomington, Indiana, USA
2008 People’s Scholarship, Nanjing University, Nanjing, China
Recent Publications
2023
Clarence T, Robert NSM, Sarigol F, Fu X, Bates PA, Simakov O. Robust 3D modeling reveals spatiosyntenic properties of animal genomes. iScience. 2023;26:106136.
Kato T, Jenkins RP, Derzsi S, Tozluoglu M, Rullan A, Hooper S, Chaleil RAG, Joyce H, Fu X, Thavaraj S, Bates PA, Sahai E. Interplay of adherens junctions and matrix proteolysis determines the invasive pattern and growth of squamous cell carcinoma. Elife. 2023;12.
Fu X, Sahai E, Wilkins A. Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response. The Journal of Pathology.2023;
2022
Schmidbaur H, Kawaguchi A, Clarence T, Fu X, Hoang OP, Zimmermann B, Ritschard EA, Weissenbacher A, Foster JS, Nyholm SV, Bates PA, Albertin CB, Tanaka E, Simakov O. Emergence of novel cephalopod gene regulation and expression through large-scale genome reorganization. Nat Commun. 2022;13:2172.
Fu X, Zhao Y, Lopez JI, Rowan A, Au L, Fendler A, Hazell S, Xu H, Horswell S, Shepherd STC, Spencer CE, Spain L, Byrne F, Stamp G, O'Brien T, Nicol D, Augustine M, Chandra A, Rudman S, Toncheva A, Furness AJS, Pickering L, Kumar S, Koh DM, Messiou C, Dafydd DA, Orton MR, Doran SJ, Larkin J, Swanton C, Sahai E, Litchfield K, Turajlic S, Bates PA. Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study. Nat Ecol Evol. 2022;6:88-102.
Fu X, Bates PA. Application of deep learning methods: From molecular modelling to patient classification. Exp Cell Res. 2022;418:113278.
2021
Zhao Y, Fu X, Lopez JI, Rowan A, Au L, Fendler A, Hazell S, Xu H, Horswell S, Shepherd STC, Spain L, Byrne F, Stamp G, O'Brien T, Nicol D, Augustine M, Chandra A, Rudman S, Toncheva A, Pickering L, Sahai E, Larkin J, Bates PA, Swanton C, Turajlic S, Litchfield K. Selection of metastasis competent subclones in the tumour interior. Nat Ecol Evol. 2021;5:1033-1045.
Muffoletto M, Qureshi A, Zeidan A, Muizniece L, Fu X, Zhao J, Roy A, Bates PA, Aslanidi O. Toward Patient-Specific Prediction of Ablation Strategies for Atrial Fibrillation Using Deep Learning. Front Physiol. 2021;12:674106.
Gerguri T, Fu X, Kakui Y, Khatri BS, Barrington C, Bates PA, Uhlmann F. Comparison of loop extrusion and diffusion capture as mitotic chromosome formation pathways in fission yeast. Nucleic Acids Res. 2021;49:1294-1312.
2020
Kakui Y, Barrington C, Barry DJ, Gerguri T, Fu X, Bates PA, Khatri BS, Uhlmann F. Fission yeast condensin contributes to interphase chromatin organization and prevents transcription-coupled DNA damage. Genome Biol. 2020;21:272.
Adhyapok P, Fu X, Sluka JP, Clendenon SG, Sluka VD, Wang Z, Dunn K, Klaunig JE, Glazier JA. A computational model of liver tissue damage and repair. PLoS One. 2020;15:e0243451.
2019
Muffoletto M, Fu X, Roy A, Varela M, Bates PA, Aslanidi OV. Development of a Deep Learning Method to Predict Optimal Ablation Patterns for Atrial Fibrillation. Paper presented at: 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB); 9-11 July 2019, 2019.
Clendenon SG, Fu X, Von Hoene RA, Clendenon JL, Sluka JP, Winfree S, Mang H, Martinez M, Filson AJ, Klaunig JE, Glazier JA, Dunn KW. A simple automated method for continuous fieldwise measurement of microvascular hemodynamics. Microvasc Res. 2019;123:7-13.
Clendenon SG, Fu X, Von Hoene RA, Clendenon JL, Sluka JP, Winfree S, Mang H, Martinez M, Filson A, Klaunig JE, Glazier JA, Dunn KW. Spatial Temporal Analysis of Fieldwise Flow in Microvasculature. J Vis Exp. 2019;10.3791/60493.
2018
Fu X, Sluka JP, Clendenon SG, Dunn KW, Wang Z, Klaunig JE, Glazier JA. Modeling of xenobiotic transport and metabolism in virtual hepatic lobule models. PLoS One. 2018;13:e0198060.
2016
Fu X, Gens JS, Glazier JA, Burns S, Gast TJ. An Explanatory Computational Simulation of Contiguous Capillary Occlusion in Diabetic Retinopathy based on Patient-derived Vasculature. The FASEB Journal. 2016;30:555.551-555.551
Fu X, Sluka JP, Clendenon S, Glazier JA, Wang Z, Klaunig J, Ryan J, Dunn K. An in-Silico Model of Xenobiotic Distribution and Metabolism in a Simulated Mouse Hepatic Lobule. The FASEB Journal. 2016;30:1036.1038-1036.1038.
Sluka JP, Fu X, Swat M, Belmonte JM, Cosmanescu A, Clendenon SG, Wambaugh JF, Glazier JA. A Liver-Centric Multiscale Modeling Framework for Xenobiotics. PLoS One. 2016;11:e0162428.
Gast TJ, Fu X, Gens JS, Glazier JA. A Computational Model of Peripheral Photocoagulation for the Prevention of Progressive Diabetic Capillary Occlusion. J Diabetes Res. 2016;2016:2508381.
Fu X, Gens JS, Glazier JA, Burns SA, Gast TJ. Progression of Diabetic Capillary Occlusion: A Model. PLoS Comput Biol. 2016;12:e1004932.
