Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

Nat Med. 2019 Jul;25(7):1054-1056. doi: 10.1038/s41591-019-0462-y. Epub 2019 Jun 3.


Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohistochemical tests. Here we show that deep residual learning can predict MSI directly from H&E histology, which is ubiquitously available. This approach has the potential to provide immunotherapy to a much broader subset of patients with gastrointestinal cancer.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Deep Learning*
  • Gastrointestinal Neoplasms / diagnosis
  • Gastrointestinal Neoplasms / genetics
  • Gastrointestinal Neoplasms / pathology*
  • Humans
  • Immunotherapy
  • Microsatellite Instability*