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Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data.

Natalie C FisherRyan M ByrneHolly LeslieColin WoodAssya LegriniAndrew J CameronBaharak AhmaderaghiShania M CorrySudhir B MallaRaheleh AmirkhahAoife J McCooeyEmily RoganKeara L RedmondSvetlana SakhnevychEnric DomingoJames JacksonMaurice B LoughreySimon J LeedhamTimothy S MaughanMark LawlerOwen James SansomFelicity LamrockViktor Hendrik KoelzerNigel B JamiesonPhilip D Dunne
Published in: Clinical cancer research : an official journal of the American Association for Cancer Research (2022)
Efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples.
Keyphrases
  • genome wide
  • cell therapy
  • gene expression
  • electronic health record
  • transcription factor
  • big data
  • cross sectional
  • quality improvement
  • stem cells
  • dna methylation
  • machine learning
  • oxidative stress
  • bone marrow