The interaction of four genes in the inflammation pathway significantly predicts prostate cancer risk

Cancer Epidemiol Biomarkers Prev. 2005 Nov;14(11 Pt 1):2563-8. doi: 10.1158/1055-9965.EPI-05-0356.

Abstract

It is widely hypothesized that the interactions of multiple genes influence individual risk to prostate cancer. However, current efforts at identifying prostate cancer risk genes primarily rely on single-gene approaches. In an attempt to fill this gap, we carried out a study to explore the joint effect of multiple genes in the inflammation pathway on prostate cancer risk. We studied 20 genes in the Toll-like receptor signaling pathway as well as several cytokines. For each of these genes, we selected and genotyped haplotype-tagging single nucleotide polymorphisms (SNP) among 1,383 cases and 780 controls from the CAPS (CAncer Prostate in Sweden) study population. A total of 57 SNPs were included in the final analysis. A data mining method, multifactor dimensionality reduction, was used to explore the interaction effects of SNPs on prostate cancer risk. Interaction effects were assessed for all possible n SNP combinations, where n = 2, 3, or 4. For each n SNP combination, the model providing lowest prediction error among 100 cross-validations was chosen. The statistical significance levels of the best models in each n SNP combination were determined using permutation tests. A four-SNP interaction (one SNP each from IL-10, IL-1RN, TIRAP, and TLR5) had the lowest prediction error (43.28%, P = 0.019). Our ability to analyze a large number of SNPs in a large sample size is one of the first efforts in exploring the effect of high-order gene-gene interactions on prostate cancer risk, and this is an important contribution to this new and quickly evolving field.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Case-Control Studies
  • Genetic Predisposition to Disease
  • Genotype
  • Haplotypes
  • Humans
  • Inflammation*
  • Male
  • Polymorphism, Single Nucleotide*
  • Prognosis
  • Prostatic Neoplasms / etiology
  • Prostatic Neoplasms / genetics*
  • Prostatic Neoplasms / immunology*
  • Registries / statistics & numerical data
  • Risk Factors
  • Signal Transduction
  • Toll-Like Receptors / genetics*

Substances

  • Toll-Like Receptors