The candidate-gene approach in association studies of polygenic diseases has often yielded conflicting results. In this hospital-based case-control study with 696 white patients newly diagnosed with bladder cancer and 629 unaffected white controls, we applied a multigenic approach to examine the associations with bladder cancer risk of a comprehensive panel of 44 selected polymorphisms in two pathways, DNA repair and cell-cycle control, and to evaluate higher-order gene-gene interactions, using classification and regression tree (CART) analysis. Individually, only XPD Asp312Asn, RAG1 Lys820Arg, and a p53 intronic SNP exhibited statistically significant main effects. However, we found a significant gene-dosage effect for increasing numbers of potential high-risk alleles in DNA-repair and cell-cycle pathways separately and combined. For the nucleotide-excision repair pathway, compared with the referent group (fewer than four adverse alleles), individuals with four (odds ratio [OR] = 1.52, 95% CI 1.05-2.20), five to six (OR = 1.81, 95% CI 1.31-2.50), and seven or more adverse alleles (OR = 2.50, 95% CI 1.69-3.70) had increasingly elevated risks of bladder cancer (P for trend <.001). Each additional adverse allele was associated with a 1.21-fold increase in risk (95% CI 1.12-1.29). For the combined analysis of DNA-repair and cell-cycle SNPs, compared with the referent group (<13 adverse alleles), the ORs for individuals with 13-15, 16-17, and >or=18 adverse alleles were 1.22 (95% CI 0.84-1.76), 1.57 (95% CI 1.05-2.35), and 1.77 (95% CI 1.19-2.63), respectively (P for trend = .002). Each additional high-risk allele was associated with a 1.07-fold significant increase in risk. In addition, we found that smoking had a significant multiplicative interaction with SNPs in the combined DNA-repair and cell-cycle-control pathways (P<.01). All genetic effects were evident only in "ever smokers" (persons who had smoked >or=100 cigarettes) and not in "never smokers." A cross-validation statistical method developed in this study confirmed the above observations. CART analysis revealed potential higher-order gene-gene and gene-smoking interactions and categorized a few higher-risk subgroups for bladder cancer. Moreover, subgroups identified with higher cancer risk also exhibited higher levels of induced genetic damage than did subgroups with lower risk. There was a significant trend of higher numbers of bleomycin- and benzo[a]pyrene diol-epoxide (BPDE)-induced chromatid breaks (by mutagen-sensitivity assay) and DNA damage (by comet assay) for individuals in higher-risk subgroups among cases of bladder cancer in smokers. The P for the trend was .0348 for bleomycin-induced chromosome breaks, .0036 for BPDE-induced chromosome breaks, and .0397 for BPDE-induced DNA damage, indicating that these higher-order gene-gene and gene-smoking interactions included SNPs that modulated repair and resulted in diminished DNA-repair capacity. Thus, genotype/phenotype analyses support findings from CART analyses. This is the first comprehensive stud...

Specific chromosome aberrations in peripheral blood lymphocytes (PBLs) in chromosomes 9 and 11 may be associated with bladder cancer. To investigate this hypothesis, in this study, we used a whole-chromosome painting technique to detect chromosomal aberrations in PBLs from 100 patients with bladder cancer and 100 matched controls. We also used a locus-specific fluorescence in situ hybridization technique to study 9p21 and cyclin D1 gene (CCND1) aberrations in PBLs of 10 patients and 10 controls and in tumor tissues of 38 additional cases. The chromosome-painting analysis showed that there were more aberrations of chromosomes 9 and 11 in bladder cancer patients than in controls. When categorized by type, the number of deletions of 9p and of translocations of chromosome 11 was significantly higher in patients than in controls (P < 0.05). Stratified analysis showed a larger odds ratio (OR) for bladder cancer in individuals with either a 9p deletion or a chromosome 11 translocation/amplification and an even larger OR in individuals with both aberrations. Using locus-specific analysis, we found that 9p21 aberrations occurred more frequently in bladder cancer patients (12.1 per 1,000 interphase cells) than in controls (6.4 per 1,000 interphase cells, P < 0.05); CCND1 translocation and amplification were observed only in bladder cancer patients. Tumor tissue analysis showed that aberrations of 9p21 (40.0 per 100 interphase cells) and CCND1 (43.8 per 100 interphase cells) were very common. Thus, we concluded that 9p deletions and translocations of chromosome 11, especially at 9p21 and CCND1, are associated with bladder cancer.

Objective: Mouse Patient-Derived Xenograft (PDX) models are essential tools for evaluating experimental therapeutics. Baylor College of Medicine (BCM) established a PDX Core to provide technical support and infrastructure for PDX-based research. To manage PDX collections effectively, de-identified patient clinical and omics data, as well as PDX-related information and omics data, must be curated and stored. Data must then be analyzed and visualized for each case. To enhance PDX collection management and data dissemination, the BCM Biomedical Informatics Core created the BCM PDX Portal (https://pdxportal.research.bcm.edu/). Materials and Methods: Patient clinical data are abstracted from medical records for each PDX and stored in a central database. Annotations are reviewed by a clinician and de-identified. PDX development method and biomarker expression are annotated. DNAseq, RNAseq, and proteomics data are processed through standardized pipelines and stored. PDX gene expression (mRNA/protein), copy number alterations, and mutations can be searched in combination with clinical markers to identify models potentially useful as a PDX cohort. Results: PDX collection management and PDX selection of models for drug evaluation are facilitated using the PDX Portal. Discussion: To improve the translational effectiveness of PDX models, it is beneficial to use a tool that captures and displays multiple features of the patient clinical and molecular data. Selection of models for studies should be representative of the patient cohort from which they originated. Conclusion: The BCM PDX Portal is a highly effective PDX collection management tool allowing data access in a visual, intuitive manner thereby enhancing the utility of PDX collections.

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