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Official Journal of the Society to Improve Diagnosis in Medicine (SIDM)

Editor-in-Chief: Graber, Mark L. / Plebani, Mario

Ed. by Argy, Nicolas / Epner, Paul L. / Lippi, Giuseppe / McDonald, Kathryn / Singh, Hardeep

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Histo-genomics: digital pathology at the forefront of precision medicine

Ivraym Barsoum
  • Department of Pathology and Molecular Medicine, Faculty of Health Sciences, Queen’s University, Kingston, Ontario, Canada
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/ Eriny Tawedrous
  • Department of Laboratory Medicine, and the Keenan Research Centre for Biomedical Science at the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada
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/ Hala Faragalla / George M. Yousef
  • Corresponding author
  • Department of Laboratory Medicine, and the Keenan Research Centre for Biomedical Science at the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada
  • Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
  • Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada
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  • Other articles by this author:
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Published Online: 2018-12-20 | DOI: https://doi.org/10.1515/dx-2018-0064


The toughest challenge OMICs face is that they provide extremely high molecular resolution but poor spatial information. Understanding the cellular/histological context of the overwhelming genetic data is critical for a full understanding of the clinical behavior of a malignant tumor. Digital pathology can add an extra layer of information to help visualize in a spatial and microenvironmental context the molecular information of cancer. Thus, histo-genomics provide a unique chance for data integration. In the era of a precision medicine, a four-dimensional (4D) (temporal/spatial) analysis of cancer aided by digital pathology can be a critical step to understand the evolution/progression of different cancers and consequently tailor individual treatment plans. For instance, the integration of molecular biomarkers expression into a three-dimensional (3D) image of a digitally scanned tumor can offer a better understanding of its subtype, behavior, host immune response and prognosis. Using advanced digital image analysis, a larger spectrum of parameters can be analyzed as potential predictors of clinical behavior. Correlation between morphological features and host immune response can be also performed with therapeutic implications. Radio-histomics, or the interface of radiological images and histology is another emerging exciting field which encompasses the integration of radiological imaging with digital pathological images, genomics, and clinical data to portray a more holistic approach to understating and treating disease. These advances in digital slide scanning are not without technical challenges, which will be addressed carefully in this review with quick peek at its future.

Keywords: digital pathology; image analysis; omics; pathology informatics; precision medicine; virtual slides


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About the article

Corresponding author: George M. Yousef, MD, PhD, FRCPC (Path), MSc, MBBCh, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada; Department of Laboratory Medicine, and the Keenan Research Centre for Biomedical Science at the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada; and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada, Phone: +416-813-5990, Fax: +416-813-8674

Received: 2018-07-25

Accepted: 2018-09-28

Published Online: 2018-12-20

Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: This work was supported by grants from the Kidney Cancer Research Network of Canada and the Canadian Urology Oncology group (KCRNC/CUOG) research trainee award, the Ontario Institute of Cancer Research (Transformative Pathology Fellowship award RFTP-004), and Ontario Molecular Pathology Research Network (OMPRN stream 1 grant #CPTRG-004).

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

Citation Information: Diagnosis, 20180064, ISSN (Online) 2194-802X, ISSN (Print) 2194-8011, DOI: https://doi.org/10.1515/dx-2018-0064.

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