Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

• Published in: PloS one Vol. 8; no. 12; p. e83745
• Main Authors: de Maturana, Evangelina López, Ye, Yuanqing, Calle, M. Luz, Rothman, Nathaniel, Urrea, Víctor, Kogevinas, Manolis, Petrus, Sandra, Chanock, Stephen J., Tardón, Adonina, García-Closas, Montserrat, González-Neira, Anna, Vellalta, Gemma, Carrato, Alfredo, Navarro, Arcadi, Lorente-Galdós, Belén, Silverman, Debra T., Real, Francisco X., Wu, Xifeng, Malats, Núria
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 31.12.2013; Public Library of Science (PLoS)
• Subjects: Adult; Aged; Aged, 80 and over; Algorithms; Artificial Intelligence; Bayes Theorem; Bayesian analysis; Bioinformatics; Biology; Biomarkers, Tumor - genetics; Bladder; Bladder cancer; Bufeta; Cancer; Cancer genetics; Cancer research; Case-Control Studies; Cell cycle; Complexity; Càncer; Data mining; Disease susceptibility; Efectes fisiològics; Environmental risk; Epidemiology; Female; Follow-Up Studies; Gene expression; Genes; Genetic Predisposition to Disease; Genetics; Genomes; Health aspects; Health risks; Hospitals; Humans; Identification methods; Inflammation; Inflammation - genetics; Inflammation Mediators - analysis; Learning algorithms; Machine learning; Male; Mathematics; Medical research; Medicine; Methods; Middle Aged; Polymorphism, Single Nucleotide - genetics; Prognosis; Regression analysis; Risk Factors; Single nucleotide polymorphisms; Single-nucleotide polymorphism; Smoking; Smoking - adverse effects; Smoking - genetics; Studies; Tabac; Texas; Tobacco; Tumors; Urinary bladder; Urinary Bladder Neoplasms - etiology; Young Adult; Texas; United States > US; Maryland; Spain
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0083745

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.