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Subclassification, survival prediction and drug target analyses of chemotherapy-naïve muscle-invasive bladder cancer with a molecular screening

  • Sebastien Rinaldetti*
  • , Eugen Rempel
  • , Thomas Stefan Worst
  • , Markus Eckstein
  • , Annette Steidler
  • , Cleo Aaron Weiss
  • , Christian Bolenz
  • , Arndt Hartmann
  • , Philipp Erben
  • *Corresponding author for this work

Research output: Contribution to journal › Article › Research › peer-review

24 Citations (Scopus)

Abstract

Background: Transcriptome expression studies identified distinct muscle invasive bladder cancer (MIBC) subtypes closely related with breast cancer subclasses. Here we developed a sensitive quantification method for MIBC subclassification (luminal, basal, p53-like). In addition, the subtype specific expression of drug targets has been investigated. Methods: Absolute quantification (nCounter) of a 64-gene panel was performed on MIBC patients (n=47) treated exclusively with radical cystectomy (RC). In conjunction of 170 MIBCs from 3 independent cohorts, a minimal set of consensus genes has been established. Survival of the consensus subtypes has been assessed by multivariate analysis. Relevant drug targets were tested for their subtype specificity in a clustering independent assessment. Results: A reduced 36-gene panel stably clustered into 3 subtypes throughout the cohorts (luminal, basal, infiltrated). Patients treated by RC only, showed worst 8-year disease specific survival (DSS) for the luminal subtype in contrast to the infiltrated subtype (17% vs. 73%, p=0.011). In multivariate analyses, the risk stratification based on luminal versus not-luminal MIBC proved to be an independent predictor for DSS superior to the TNM system in patients with RC. Drug targets (e.g. ERBB2, FGFR, AR, PDGFRB) showed a distinct subtype attribution. The subtypes based on this nCounter screening could further be validated by the TCGA cohort. Conclusion: This MIBC subtype screening predicted survival and allowed an analysis of subtype specific drug targets, thus being a powerful tool for the translation of personalized MIBC treatment concepts.

Original languageEnglish
Pages (from-to)25935-25945
Number of pages11
JournalOncotarget
Volume9
Issue number40
DOIs
Publication statusPublished - 2018
Externally publishedYes

Keywords

  • Biomarkers
  • Bladder cancer subtypes
  • Drug targets
  • Gene expression
  • Survival prediction

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