Identifying common transcriptome signatures of cancer by interpreting deep learning models.

Journal: Genome biology
Published Date: May 17, 2022

Abstract

BACKGROUND: Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types.

Authors

  • Anupama Jha
    Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, USA.
  • Mathieu Quesnel-Vallières
    Department of Genetics, Philadelphia, USA. mathieu.quesnel-vallieres@pennmedicine.upenn.edu.
  • David Wang
    Imaging Biomarkers and Computer-aided Diagnosis Laboratory and Clinical Image Processing Service, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
  • Andrei Thomas-Tikhonenko
    Department of Pathology and Laboratory Medicine, Philadelphia, USA.
  • Kristen W Lynch
    Department of Biochemistry and Biophysics, Philadelphia, USA.
  • Yoseph Barash
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario M5S 3G4, Canada. Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada. School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

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