ArticlePloS one2013
Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 25 citations in OpenAlex.
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- Effect of smoking on the recurrence and progression of non-muscle-invasive bladder cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- Sigma-1 Receptor Specific Biological Functions, Protective Role, and Therapeutic Potential in Cardiovascular Diseases.Cardiovascular toxicology · 2025Review
- Genetic Polymorphisms Involved in Bladder Cancer: A Global Review.Oncology reviews · 2023Article
- Computational Functional Genomics-Based AmpliSeq™ Panel for Next-Generation Sequencing of Key Genes of Pain.International journal of molecular sciences · 2021Article
- Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases.Journal of personalized medicine · 2019Article
- Article
- A fast algorithm for Bayesian multi-locus model in genome-wide association studies.Molecular genetics and genomics : MGG · 2017Article
- Impact of smoking status and cumulative smoking exposure on tumor recurrence of non-muscle-invasive bladder cancer.International urology and nephrology · 2017Article
- Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2016Article
- Sparse regressions for predicting and interpreting subcellular localization of multi-label proteins.BMC bioinformatics · 2016Article
- Modeling X Chromosome Data Using Random Forests: Conquering Sex Bias.Genetic epidemiology · 2016Article
- Next generation modeling in GWAS: comparing different genetic architectures.Human genetics · 2014Article
Corrections and comments
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Authors and funding
19 authors at 11 institutions in 2 countries.
Funding
Abstract
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.
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