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Germline variants in  TP63  have been consistently associated with several tumors, including bladder cancer, indicating the importance of  TP53  pathway in cancer genetic susceptibility. However, variants in other related genes, including  TP53  rs1042522 (Arg72Pro), still present controversial results. We carried out an in depth assessment of associations between common germline variants in the  TP53  pathway and bladder cancer risk.    Material and Methods  We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998–2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized logistic regression analysis to assess multiple SNPs simultaneously.    Results  Based on classical analyses, SNPs in  BAK1  (1),  IGF1R  (5),  P53AIP1  (1),  PMAIP1  (2),  SERINPB5  (3),  TP63  (3), and  TP73  (1) showed significant associations at p-value≤0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value≥0.8). LASSO selected the SNP rs6567355 in  SERPINB5  with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05–1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation.    Discussion  We found no strong evidence that common variants in the  TP53  pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that  TP53  Arg72Pro is implicated in the UCB in white Europeans.  SERPINB5  and  TP63  variation deserve further exploration in extended studies.

Genetic Variation in the TP53 Pathway and Bladder Cancer Risk. A Comprehensive Analysis