title: Systematic evaluation of the prognostic impact and intratumour heterogeneity of clear cell renal cell carcinoma biomarkers.
abstract: BACKGROUND
  Candidate biomarkers have been identified for clear cell renal cell carcinoma (ccRCC) patients, but most have not been validated.
  
  
  OBJECTIVE
  To validate published ccRCC prognostic biomarkers in an independent patient cohort and to assess intratumour heterogeneity (ITH) of the most promising markers to guide biomarker optimisation.
  
  
  METHODS
  Cancer-specific survival (CSS) for each of 28 identified genetic or transcriptomic biomarkers was assessed in 350 ccRCC patients. ITH was interrogated in a multiregion biopsy data set of 10 ccRCCs.
  
  
  METHODS
  Biomarker association with CSS was analysed by univariate and multivariate analyses.
  
  
  CONCLUSIONS
  A total of 17 of 28 biomarkers (TP53 mutations; amplifications of chromosomes 8q, 12, 20q11.21q13.32, and 20 and deletions of 4p, 9p, 9p21.3p24.1, and 22q; low EDNRB and TSPAN7 expression and six gene expression signatures) were validated as predictors of poor CSS in univariate analysis. Tumour stage and the ccB expression signature were the only independent predictors in multivariate analysis. ITH of the ccB signature was identified in 8 of 10 tumours. Several genetic alterations that were significant in univariate analysis were enriched, and chromosomal instability indices were increased in samples expressing the ccB signature. The study may be underpowered to validate low-prevalence biomarkers.
  
  
  CONCLUSIONS
  The ccB signature was the only independent prognostic biomarker. Enrichment of multiple poor prognosis genetic alterations in ccB samples indicated that several events may be required to establish this aggressive phenotype, catalysed in some tumours by chromosomal instability. Multiregion assessment may improve the precision of this biomarker.
  
  
  RESULTS
  We evaluated the ability of published biomarkers to predict the survival of patients with clear cell kidney cancer in an independent patient cohort. Only one molecular test adds prognostic information to routine clinical assessments. This marker showed good and poor prognosis results within most individual cancers. Future biomarkers need to consider variation within tumours to improve accuracy.
authors.affiliation: Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, UK.
authors.forename: Sakshi
authors.initials: S
authors.lastname: Gulati
authors.affiliation: Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, UK.
authors.forename: Pierre
authors.initials: P
authors.lastname: Martinez
authors.affiliation: Centre for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark.
authors.forename: Tejal
authors.initials: T
authors.lastname: Joshi
authors.affiliation: Centre for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark.
authors.forename: Nicolai Juul
authors.initials: NJ
authors.lastname: Birkbak
authors.affiliation: Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, UK.
authors.forename: Claudio R
authors.initials: CR
authors.lastname: Santos
authors.affiliation: Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, UK.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Rowan
authors.affiliation: The Royal Marsden Hospital, London, UK.
authors.forename: Lisa
authors.initials: L
authors.lastname: Pickering
authors.affiliation: The Royal Marsden Hospital, London, UK.
authors.forename: Martin
authors.initials: M
authors.lastname: Gore
authors.affiliation: The Royal Marsden Hospital, London, UK.
authors.forename: James
authors.initials: J
authors.lastname: Larkin
authors.affiliation: Centre for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark; Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA, USA.
authors.forename: Zoltan
authors.initials: Z
authors.lastname: Szallasi
authors.affiliation: Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, UK. Electronic address: paul.batest@cancer.org.uk.
authors.forename: Paul A
authors.initials: PA
authors.lastname: Bates
authors.affiliation: Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, UK; UCL Cancer Institute, London, UK. Electronic address: charles.swanton@cancer.org.uk.
authors.forename: Charles
authors.initials: C
authors.lastname: Swanton
authors.affiliation: Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, UK; Present address: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
authors.forename: Marco
authors.initials: M
authors.lastname: Gerlinger
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D001706:Biopsy; D002292:Carcinoma, Renal Cell / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D004252:DNA Mutational Analysis; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D020022:Genetic Predisposition to Disease; D006801:Humans; D053208:Kaplan-Meier Estimate; D007680:Kidney Neoplasms / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009154:Mutation; D009367:Neoplasm Staging; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012307:Risk Factors; D013997:Time Factors; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor
keywords: Biomarker; Intratumour heterogeneity; Kidney cancer; Personalised medicine; Prognostic marker