A validation and extended description of the Lund taxonomy for urothelial carcinoma using the TCGA cohort

Research output: Contribution to journalArticle

Abstract

Global gene expression analysis has been a major tool for urothelial carcinoma subtype discovery. This approach has revealed extensive complexity both in intrinsic features of the tumor cells and in the microenvironment. However, global gene expression cannot distinguish between gene expression signals originating from the tumor cells proper and from normal cells in the biopsy. Here, we use a large cohort of advanced urothelial carcinomas for which both gene expression data and extensive immunohistochemistry are available to create a supervised mRNA expression centroid classifier. This classifier identifies the major Lund taxonomy tumor cell phenotypes as defined by IHC. We apply this classifier to the independent TCGA dataset and show excellent associations between identified subtypes and genomic features. We validate a progressed version of Urothelial-like A (UroA-Prog) that shows FGFR3 mutations and CDKN2A deletions, and we show that the variant Urothelial-like C is almost devoid of FGFR3 mutations. We show that Genomically Unstable tumors are very distinct from Urothelial-like tumors at the genomic level, and that tumors classified as Basal/SCC-like all complied with the established definition for Basal/SCC-like tumors. We identify the Mesenchymal-like and Small-cell/Neuroendocrine-like subtypes, and demonstrate that patients with UroB and Sc/NE-like tumors show the worst overall survival.

Details

Authors
Organisations
External organisations
  • Skåne University Hospital
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Cancer and Oncology
Original languageEnglish
Article number3737
JournalScientific Reports
Volume8
Issue number1
StatePublished - 2018 Dec 1
Publication categoryResearch
Peer-reviewedYes

Related research output

Pontus Eriksson, 2018, Lund: Lund University, Faculty of Medicine. 104 p.

Research output: ThesisDoctoral Thesis (compilation)

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