title: Genomic investigation of etiologic heterogeneity: methodologic challenges.
abstract: BACKGROUND
  The etiologic heterogeneity of cancer has traditionally been investigated by comparing risk factor frequencies within candidate sub-types, defined for example by histology or by distinct tumor markers of interest. Increasingly tumors are being profiled for molecular features much more extensively. This greatly expands the opportunities for defining distinct sub-types. In this article we describe an exploratory analysis of the etiologic heterogeneity of clear cell kidney cancer. Data are available on the primary known risk factors for kidney cancer, while the tumors are characterized on a genome-wide basis using expression, methylation, copy number and mutational profiles.
  
  
  METHODS
  We use a novel clustering strategy to identify sub-types. This is accomplished independently for the expression, methylation and copy number profiles. The goals are to identify tumor sub-types that are etiologically distinct, to identify the risk factors that define specific sub-types, and to endeavor to characterize the key genes that appear to represent the principal features of the distinct sub-types.
  
  
  RESULTS
  The analysis reveals strong evidence that gender represents an important factor that distinguishes disease sub-types. The sub-types defined using expression data and methylation data demonstrate considerable congruence and are also clearly correlated with mutations in important cancer genes. These sub-types are also strongly correlated with survival. The complexity of the data presents many analytical challenges including, prominently, the risk of false discovery.
  
  
  CONCLUSIONS
  Genomic profiling of tumors offers the opportunity to identify etiologically distinct sub-types, paving the way for a more refined understanding of cancer etiology.
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. beggc@mskcc.org.
authors.forename: Colin B
authors.initials: CB
authors.lastname: Begg
authors.forename: Venkatraman E
authors.initials: VE
authors.lastname: Seshan
authors.forename: Emily C
authors.initials: EC
authors.lastname: Zabor
authors.forename: Helena
authors.initials: H
authors.lastname: Furberg
authors.forename: Arshi
authors.initials: A
authors.lastname: Arora
authors.forename: Ronglai
authors.initials: R
authors.lastname: Shen
authors.forename: Jodi K
authors.initials: JK
authors.lastname: Maranchie
authors.forename: Matthew E
authors.initials: ME
authors.lastname: Nielsen
authors.forename: W Kimryn
authors.initials: WK
authors.lastname: Rathmell
authors.forename: Sabina
authors.initials: S
authors.lastname: Signoretti
authors.forename: Pheroze
authors.initials: P
authors.lastname: Tamboli
authors.forename: Jose A
authors.initials: JA
authors.lastname: Karam
authors.forename: Toni K
authors.initials: TK
authors.lastname: Choueiri
authors.forename: A Ari
authors.initials: AA
authors.lastname: Hakimi
authors.forename: James J
authors.initials: JJ
authors.lastname: Hsieh
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D002292:Carcinoma, Renal Cell / Q000145:classification / Q000209:etiology / Q000235:genetics*; D019175:DNA Methylation / Q000235:genetics; D005260:Female; D018628:Gene Dosage / Q000235:genetics; D020869:Gene Expression Profiling; D020022:Genetic Predisposition to Disease; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D007680:Kidney Neoplasms / Q000145:classification / Q000209:etiology / Q000235:genetics*; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D012737:Sex Factors
chemical_list: D014408:Biomarkers, Tumor