The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We
performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988
controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration ...»»»»
The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We
performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988
controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate
logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two
more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold
LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches
explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with
bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the
total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed.
The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the
effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was
detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer
risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.^^^^
Tipus:
Article
Indexació:
Indexat a SCOPUS
Indexat a WOS/JCR
Citació Bibliogràfica:
de Maturana EL, Ye Y, Calle ML, Rothman N, Urrea V, et al. (2013) Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main
Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk. PLoS ONE 8(12): e83745. doi:10.1371/journal.pone.0083745