Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study.

Journal: Cell reports. Medicine
PMID: 36958327

Abstract

Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other biomarkers with high performance and whether DL predictions generalize to external patient populations. Here, we acquire CRC tissue samples from two large multi-centric studies. We systematically compare six different state-of-the-art DL architectures to predict biomarkers from pathology slides, including MSI and mutations in BRAF, KRAS, NRAS, and PIK3CA. Using a large external validation cohort to provide a realistic evaluation setting, we show that models using self-supervised, attention-based multiple-instance learning consistently outperform previous approaches while offering explainable visualizations of the indicative regions and morphologies. While the prediction of MSI and BRAF mutations reaches a clinical-grade performance, mutation prediction of PIK3CA, KRAS, and NRAS was clinically insufficient.

Authors

  • Jan Moritz Niehues
    Else Kroener Fresenius Center for Digital Health, Technical University Dresden, 01307 Dresden, Germany; Department of Medicine III, University Hospital RWTH Aachen, 52074 Aachen, Germany.
  • Philip Quirke
    Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom.
  • Nicholas P West
    Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom.
  • Heike I Grabsch
    Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, Netherlands.
  • Marko van Treeck
    Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
  • Yoni Schirris
    Else Kroener Fresenius Center for Digital Health, Technical University Dresden, 01307 Dresden, Germany; Netherlands Cancer Institute, 1066 CX Amsterdam, the Netherlands; University of Amsterdam, 1012 WP Amsterdam, the Netherlands.
  • Gregory P Veldhuizen
    Else Kroener Fresenius Center for Digital Health, Technical University Dresden, 01307 Dresden, Germany; Department of Medicine III, University Hospital RWTH Aachen, 52074 Aachen, Germany.
  • Gordon G A Hutchins
    Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom.
  • Susan D Richman
    Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, United Kingdom.
  • Sebastian Foersch
    Institute of Pathology, University Medical Center Mainz, Mainz, Germany. Electronic address: sebastian.foersch@unimedizin-mainz.de.
  • Titus J Brinker
    National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Junya Fukuoka
    Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences, Sakamoto, Nagasaki, Japan; Department of Pathology, Kameda Medical Center, Kamogawa, Chiba, Japan. Electronic address: fukuokaj@nagasaki-u.ac.jp.
  • Andrey Bychkov
    Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences, Sakamoto, Nagasaki, Japan; Department of Pathology, Kameda Medical Center, Kamogawa, Chiba, Japan.
  • Wataru Uegami
    Anatomical Pathology, Kameda Medical Center, Chiba, Japan.
  • Daniel Truhn
    Department of Diagnostic and Interventional Radiology, University Hospital Düsseldorf, Düsseldorf, Germany (J.S., D.B.A., S.N.); Institute of Computer Vision and Imaging, RWTH University Aachen, Pauwelsstrasse 30, 52072 Aachen, Germany (J.S., D.M.); Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany (D.T., M.P., F.M., C.K., S.N.); and Faculty of Mathematics and Natural Sciences, Institute of Informatics, Heinrich Heine University Düsseldorf, Düsseldorf, Germany (S.C.).
  • Hermann Brenner
    German Cancer Consortium (DKTK), Heidelberg, Germany.
  • Alexander Brobeil
    Institute of Pathology, University of Heidelberg, Heidelberg, Germany; Tissue Bank of the National Center for Tumor Diseases (NCT), Heidelberg, Germany.
  • Michael Hoffmeister
    Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Jakob Nikolas Kather
    Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.

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