A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Journal: Nature cancer
Published Date: Jul 3, 2024

Abstract

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts.

Authors

  • Danh-Tai Hoang
    Biological Data Science Institute, College of Science, Australian National University, Canberra, Australian Capital Territory, Australia.
  • Gal Dinstag
    Pangea Biomed Ltd., Tel Aviv, Israel.
  • Eldad D Shulman
    Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Leandro C Hermida
    Department of Immunology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Doreen S Ben-Zvi
    Pangea Biomed Ltd., Tel Aviv, Israel.
  • Efrat Elis
    Pangea Biomed Ltd., Tel Aviv, Israel.
  • Katherine Caley
    Biological Data Science Institute, College of Science, Australian National University, Canberra, Australian Capital Territory, Australia.
  • Stephen-John Sammut
    Breast Cancer Now Toby Robins Research Centre, Institute of Cancer Research, London, UK.
  • Sanju Sinha
    Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Neelam Sinha
    Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Christopher H Dampier
    Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Chani Stossel
    Oncology Institute, Sheba Medical Center at Tel-Hashomer, Tel Aviv University, Tel Aviv, Israel.
  • Tejas Patil
    Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Arun Rajan
    Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Wiem Lassoued
    Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Julius Strauss
    Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Shania Bailey
    Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Clint Allen
    Surgical Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Jason Redman
    Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Tuvik Beker
    Pangea Biomed Ltd., Tel Aviv, Israel.
  • Peng Jiang
    Department of Joint Surgery, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, China.
  • Talia Golan
    Oncology Institute, Sheba Medical Center at Tel-Hashomer, Tel Aviv University, Tel Aviv, Israel.
  • Scott Wilkinson
    Laboratory of Genitourinary Cancer Pathogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Adam G Sowalsky
    Laboratory of Genitourinary Cancer Pathogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
  • Sharon R Pine
    Division of Medical Oncology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Carlos Caldas
    Cancer Research UK Cambridge Centre, University of Cambridge, CB2 0RE Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, CB2 0RE Cambridge, United Kingdom; Department of Oncology, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service (NHS) Foundation Trust, CB2 0QQ Cambridge, United Kingdom.
  • James L Gulley
    Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
  • Kenneth Aldape
    Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA. kenneth.aldape@nih.gov.
  • Ranit Aharonov
    IBM Research AI, Haifa, Israel.
  • Eric A Stone
    Biological Data Science Institute, College of Science, Australian National University, Canberra, Australian Capital Territory, Australia.
  • Eytan Ruppin
    Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA. eytan.ruppin@nih.gov.

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