Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases.

Journal: EBioMedicine
Published Date:

Abstract

BACKGROUND: Recent advances in digital pathology have enabled accurate and standardised enumeration of tumour-infiltrating lymphocytes (TILs). Here, we aim to evaluate TILs as a percentage electronic TIL score (eTILs) and investigate its prognostic and predictive relevance in cutaneous melanoma.

Authors

  • Eftychia Chatziioannou
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Tübingen, Germany.
  • Jana Roßner
    Department of Dermatology, University of Heidelberg, Im Neuenheimer Feld 440, 69120 Heidelberg, Germany.
  • Thazin New Aung
    Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
  • David L Rimm
    Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
  • Heike Niessner
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Tübingen, Germany.
  • Ulrike Keim
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany.
  • Lina Maria Serna-Higuita
    Department of Clinical Epidemiology and Applied Biostatistics, Eberhard Karls University of Tübingen, 72076 Tübingen, Germany.
  • Irina Bonzheim
    Institute of Pathology and Neuropathology, Eberhard Karls University of Tübingen, 72076 Tübingen, Germany.
  • Luis Kuhn Cuellar
    Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany.
  • Dana Westphal
    Department of Dermatology, Faculty of Medicine and University Hospital Carl Gustav Carus, Skin Cancer Center at the University Cancer Center and National Center for Tumor Diseases, Technical University Dresden, 01307 Dresden, Germany.
  • Julian Steininger
    Department of Dermatology, Faculty of Medicine and University Hospital Carl Gustav Carus, Skin Cancer Center at the University Cancer Center and National Center for Tumor Diseases, Technical University Dresden, 01307 Dresden, Germany.
  • Friedegund Meier
    Skin Cancer Center at the University Cancer Centre and National Center for Tumor Diseases Dresden, Department of Dermatology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany.
  • Oltin Tiberiu Pop
    Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland.
  • Stephan Forchhammer
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany.
  • Lukas Flatz
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany; Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland.
  • Thomas Eigentler
    Center of Dermatooncology, Department of Dermatology, Eberhard Karls Universitat Tubingen, Tubingen, Germany.
  • Claus Garbe
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany.
  • Martin Röcken
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Tübingen, Germany.
  • Teresa Amaral
    Center of Dermatooncology, Department of Dermatology, Eberhard Karls Universitat Tubingen, Tubingen, Germany.
  • Tobias Sinnberg
    Department of Dermatology, University of Tübingen, Liebermeisterstr. 25, 72076 Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", Tübingen, Germany; Department of Dermatology, Venereology and Allergology, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany. Electronic address: tobias.sinnberg@med.uni-tuebingen.de.