Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors.

Journal: EBioMedicine
PMID:

Abstract

BACKGROUND: It is uncertain which biological features underpin the response of rectal cancer (RC) to radiotherapy. No biomarker is currently in clinical use to select patients for treatment modifications.

Authors

  • Enric Domingo
    Department of Oncology, University of Oxford, Oxford, UK.
  • Sanjay Rathee
    Department of Oncology, Medical Sciences Division, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK.
  • Andrew Blake
    Department of Oncology, University of Oxford, Oxford, UK.
  • Leslie Samuel
    Department of Clinical Oncology, Aberdeen Royal Infirmary, Aberdeen, UK.
  • Graeme Murray
    School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK.
  • David Sebag-Montefiore
    Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, United Kingdom; Radiotherapy Research Group, Leeds Institute of Medical Research, University of Leeds, United Kingdom.
  • Simon Gollins
    North Wales Cancer Treatment Centre, Besti Cadwaladr University Health Board, Bodelwyddan, Denbighshire, LL18 5UJ, UK.
  • Nicholas West
    Leeds Institute of Medical Research, University of Leeds, LS9 7TF, UK.
  • Rubina Begum
    Cancer Research & University College London Clinica Trial Unit, London, United Kingdom.
  • Susan Richman
    Leeds Institute of Medical Research, University of Leeds, LS9 7TF, UK.
  • Phil Quirke
    Department of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, Leeds, UK.
  • Keara Redmond
    The Patrick G Johnston Centre for Cancer Research, Queens University Belfast, Belfast, BT7 9AE, UK.
  • Aikaterini Chatzipli
    Wellcome Trust Sanger Institute, Hinxton, UK.
  • Alessandro Barberis
    Nuffield Department of Surgical Sciences, Medical Sciences Division, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK. dr.alessandro.barberis@gmail.com.
  • Sylvana Hassanieh
    Department of Oncology, Medical Sciences Division, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK.
  • Umair Mahmood
    Department of Oncology, Medical Sciences Division, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK.
  • Michael Youdell
    Department of Oncology, Medical Sciences Division, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK.
  • Ultan McDermott
    Wellcome Trust Sanger Institute, Hinxton, UK.
  • Viktor Koelzer
    Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Oncology and Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
  • Simon Leedham
    Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, UK.
  • Ian Tomlinson
    Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway; Edinburgh Cancer Research Centre, University of Edinburgh, Edinburgh, UK.
  • Philip Dunne
    The Patrick G Johnston Centre for Cancer Research, Queens University Belfast, Belfast, BT7 9AE, UK.
  • Francesca M Buffa
    Computational Biology and Integrative Genomics Lab, Department of Oncology, Medical Sciences Division, University of Oxford, Oxford, OX3 7DQ, UK. francesca.buffa@unibocconi.it.
  • Timothy S Maughan
    Department of Oncology, Medical Sciences Division, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK; Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK. Electronic address: tim.maughan@oncology.ox.ac.uk.