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- Title
Genomic investigation of etiologic heterogeneity: methodologic challenges.
- Authors
Begg, Colin B.; Seshan, Venkatraman E.; Zabor, Emily C.; Furberg, Helena; Arora, Arshi; Shen, Ronglai; Maranchie, Jodi K.; Nielsen, Matthew E.; Rathmell, W. Kimryn; Signoretti, Sabina; Tamboli, Pheroze; Karam, Jose A.; Choueiri, Toni K.; Hakimi, A. Ari; Hsieh, James J.
- 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 subtypes, 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 subtypes, paving the way for a more refined understanding of cancer etiology.
- Subjects
GENOMICS; CANCER risk factors; ETIOLOGY of cancer; RENAL cancer; DATA analysis; TUMOR markers
- Publication
BMC Medical Research Methodology, 2014, Vol 14, Issue 1, p1
- ISSN
1471-2288
- Publication type
Article
- DOI
10.1186/1471-2288-14-138