Nature Communications (May 2022)

Automated next-generation profiling of genomic alterations in human cancers

  • Laurel A. Keefer,
  • James R. White,
  • Derrick E. Wood,
  • Kelly M. R. Gerding,
  • Kenneth C. Valkenburg,
  • David Riley,
  • Christopher Gault,
  • Eniko Papp,
  • Christine M. Vollmer,
  • Amy Greer,
  • James Hernandez,
  • Paul M. McGregor,
  • Adriana Zingone,
  • Bríd M. Ryan,
  • Kristen Deak,
  • Shannon J. McCall,
  • Michael B. Datto,
  • James L. Prescott,
  • John F. Thompson,
  • Gustavo C. Cerqueira,
  • Siân Jones,
  • John K. Simmons,
  • Abigail McElhinny,
  • Jennifer Dickey,
  • Samuel V. Angiuoli,
  • Luis A. Diaz,
  • Victor E. Velculescu,
  • Mark Sausen

DOI
https://doi.org/10.1038/s41467-022-30380-x
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 15

Abstract

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The genomic profiling of tumours has not been widely adopted in the clinic due to technical and practical hurdles. Here, the authors develop PGDx elio tissue complete, a scalable, standardised and FDA-cleared test comprising a targeted gene panel and automated machine-learning analysis, which detects clinically relevant sequence biomarkers in cancer samples.