A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Published Date:

Abstract

Multiplexed immunofluorescence provides an un-precedented opportunity for studying specific cell-to-cell and cell microenvironment interactions. We employ graph neural networks to combine features obtained from tissue morphology with measurements of protein expression to profile the tumour microenvironment associated with different tumour stages. Our framework presents a new approach to analysing and processing these complex multi-dimensional datasets that overcomes some of the key challenges in analysing these data and opens up the opportunity to abstract biologically meaningful interactions.

Authors

  • Natalia Garcia Martin
  • Stefano Malacrino
    Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK.
  • Marta Wojciechowska
  • Leticia Campo
  • Helen Jones
  • David C Wedge
  • Chris Holmes
    Department of Statistics, University of Oxford, Oxford, UK.
  • Korsuk Sirinukunwattana
  • Heba Sailem
    Institute of Biomedical Engineering, Department of Engineering Science, Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, United Kingdom.
  • Clare Verrill
    Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK; Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK; NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK. Electronic address: Clare.Verrill@ouh.nhs.uk.
  • Jens Rittscher
    Department of Engineering Science, University of Oxford, Oxford, United Kingdom.