A resequence analysis of genomic loci on chromosomes 1q32.1, 5p15.33, and 13q22.1 associated with pancreatic cancer risk.

OBJECTIVE: The objective of this study was to fine-map common pancreatic cancer susceptibility regions. METHODS: We conducted targeted Roche-454 resequencing across 428 kb in 3 genomic regions identified in genome-wide association studies (GWAS) of pancreatic cancer, on chromosomes 1q32.1, 5p15.33, and 13q22.1. RESULTS: An analytical pipeline for calling genotypes was developed using HapMap samples sequenced on chr5p15.33. Concordance to 1000 Genomes data for chr5p15.33 was greater than 96%. The concordance for chr1q32.1 and chr13q22.1 with pancreatic cancer GWAS data was greater than 99%. Between 9.2% and 19.0% of variants detected were not present in 1000 Genomes for the respective continental population. The majority of completely novel single-nucleotide polymorphisms (SNPs) were less common (minor allele frequency [MAF], ≤5%) or rare (MAF, ≤2%), illustrating the value of enlarging test sets for discovery of less common variants. Using the data set, we examined haplotype blocks across each region using a tag SNP analysis (r² > 0.8 for MAF of ≥5%) and determined that at least 196, 243, and 63 SNPs are required for fine-mapping chr1q32.1, chr5p15.33, and chr13q22.1, respectively, in European populations. CONCLUSIONS: We have characterized germline variation in 3 regions associated with pancreatic cancer risk and show that targeted resequencing leads to the discovery of novel variants and improves the completeness of germline sequence variants for fine-mapping GWAS susceptibility loci.

Meat-related mutagen exposure, xenobiotic metabolizing gene polymorphisms and the risk of advanced colorectal adenoma and cancer.

Meat mutagens, including heterocyclic amines (HCAs), polycyclic aromatic hydrocarbons (PAHs) and N-nitroso compounds (NOCs), may be involved in colorectal carcinogenesis depending on their activation or detoxification by phase I and II xenobiotic metabolizing enzymes (XME). Using unconditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI), we examined the intake of five meat mutagens and >300 single nucleotide polymorphisms (SNPs) in 18 XME genes in relation to advanced colorectal adenoma (1205 cases and 1387 controls) and colorectal cancer (370 cases and 401 controls) within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Dietary intake of meat mutagens was assessed using a food frequency questionnaire with a detailed meat-cooking module. An interaction was observed between 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) intake and the NAT1 polymorphism rs6586714 in the adenoma study (P(interaction) = 0.001). Among individuals carrying a GG genotype, high MeIQx intake was associated with a 43% increased risk of adenoma (95% CI 1.11-1.85, P(trend) = 0.07), whereas the reverse was observed among carriers of the A variant (OR = 0.50, 95% CI 0.30-0.84, P(trend) = 0.01). In addition, we observed some suggestive (P < 0.05) modifying effects for SNPs in other XME genes (UGT1A, CYP2E1, EPHX1, AHR and GSTM3), but these were not significant after adjustment for multiple testing. This large and comprehensive study of XME genes, meat mutagens and the risk of colorectal tumours found that a NAT1 polymorphism modified the association between MeIQx intake and colorectal adenoma risk.

Fine mapping the KLK3 locus on chromosome 19q13.33 associated with prostate cancer susceptibility and PSA levels.

Measurements of serum prostate-specific antigen (PSA) protein levels form the basis for a widely used test to screen men for prostate cancer. Germline variants in the gene that encodes the PSA protein (KLK3) have been shown to be associated with both serum PSA levels and prostate cancer. Based on a resequencing analysis of a 56 kb region on chromosome 19q13.33, centered on the KLK3 gene, we fine mapped this locus by genotyping tag SNPs in 3,522 prostate cancer cases and 3,338 controls from five case-control studies. We did not observe a strong association with the KLK3 variant, reported in previous studies to confer risk for prostate cancer (rs2735839; P = 0.20) but did observe three highly correlated SNPs (rs17632542, rs62113212 and rs62113214) associated with prostate cancer [P = 3.41 × 10(-4), per-allele trend odds ratio (OR) = 0.77, 95% CI = 0.67-0.89]. The signal was apparent only for nonaggressive prostate cancer cases with Gleason score <7 and disease stage 8 or stage ≥III (P = 0.31, per-allele trend OR = 1.12, 95% CI = 0.90-1.40). One of the three highly correlated SNPs, rs17632542, introduces a non-synonymous amino acid change in the KLK3 protein with a predicted benign or neutral functional impact. Baseline PSA levels were 43.7% higher in control subjects with no minor alleles (1.61 ng/ml, 95% CI = 1.49-1.72) than in those with one or more minor alleles at any one of the three SNPs (1.12 ng/ml, 95% CI = 0.96-1.28) (P = 9.70 × 10(-5)). Together our results suggest that germline KLK3 variants could influence the diagnosis of nonaggressive prostate cancer by influencing the likelihood of biopsy.

A comprehensive resequence analysis of the KLK15-KLK3-KLK2 locus on chromosome 19q13.33.

Single nucleotide polymorphisms (SNPs) in the KLK3 gene on chromosome 19q13.33 are associated with serum prostate-specific antigen (PSA) levels. Recent genome wide association studies of prostate cancer have yielded conflicting results for association of the same SNPs with prostate cancer risk. Since the KLK3 gene encodes the PSA protein that forms the basis for a widely used screening test for prostate cancer, it is critical to fully characterize genetic variation in this region and assess its relationship with the risk of prostate cancer. We have conducted a next-generation sequence analysis in 78 individuals of European ancestry to characterize common (minor allele frequency, MAF >1%) genetic variation in a 56 kb region on chromosome 19q13.33 centered on the KLK3 gene (chr19:56,019,829-56,076,043 bps). We identified 555 polymorphic loci in the process including 116 novel SNPs and 182 novel insertion/deletion polymorphisms (indels). Based on tagging analysis, 144 loci are necessary to tag the region at an r (2) threshold of 0.8 and MAF of 1% or higher, while 86 loci are required to tag the region at an r (2) threshold of 0.8 and MAF >5%. Our sequence data augments coverage by 35 and 78% as compared to variants in dbSNP and HapMap, respectively. We observed six non-synonymous amino acid or frame shift changes in the KLK3 gene and three changes in each of the neighboring genes, KLK15 and KLK2. Our study has generated a detailed map of common genetic variation in the genomic region surrounding the KLK3 gene, which should be useful for fine-mapping the association signal as well as determining the contribution of this locus to prostate cancer risk and/or regulation of PSA expression.

Comprehensive resequence analysis of a 97 kb region of chromosome 10q11.2 containing the MSMB gene associated with prostate cancer.

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 10q11.2, harboring the microseminoprotein-ß (MSMB) gene. Both the gene product of MSMB, the prostate secretory protein 94 (PSP94) and its binding protein (PSPBP), have been previously investigated as serum biomarkers for prostate cancer progression. Recent functional work has shown that different alleles of the significantly associated SNP in the promoter of MSMB found to be associated with prostate cancer risk, rs10993994, can influence its expression in tumors and in vitro studies. Since it is plausible that additional variants in this region contribute to the risk of prostate cancer, we have used next-generation sequencing technology to resequence a ~97-kb region that includes the area surrounding MSMB (chr10: 51,168,025-51,265,101) in 36 prostate cancer cases, 26 controls of European origin, and 8 unrelated CEPH individuals in order to identify additional variants to investigate in functional studies. We identified 241 novel polymorphisms within this region, including 142 in the 51-kb block of linkage disequilibrium (LD) that contains rs10993994 and the proximal promoter of MSMB. No sites were observed to be polymorphic within the exons of MSMB.

Comprehensive resequence analysis of a 136 kb region of human chromosome 8q24 associated with prostate and colon cancers.

Recently, genome-wide association studies have identified loci across a segment of chromosome 8q24 (128,100,000-128,700,000) associated with the risk of breast, colon and prostate cancers. At least three regions of 8q24 have been independently associated with prostate cancer risk; the most centromeric of which appears to be population specific. Haplotypes in two contiguous but independent loci, marked by rs6983267 and rs1447295, have been identified in the Cancer Genetic Markers of Susceptibility project ( http://cgems.cancer.gov ), which genotyped more than 5,000 prostate cancer cases and 5,000 controls of European origin. The rs6983267 locus is also strongly associated with colorectal cancer. To ascertain a comprehensive catalog of common single-nucleotide polymorphisms (SNPs) across the two regions, we conducted a resequence analysis of 136 kb (chr8: 128,473,000-128,609,802) using the Roche/454 next-generation sequencing technology in 39 prostate cancer cases and 40 controls of European origin. We have characterized a comprehensive catalog of common (MAF > 1%) SNPs within this region, including 442 novel SNPs and have determined the pattern of linkage disequilibrium across the region. Our study has generated a detailed map of genetic variation across the region, which should be useful for choosing SNPs for fine mapping of association signals in 8q24 and investigations of the functional consequences of select common variants.

Validation of the performance of a comprehensive genotyping assay panel of single nucleotide polymorphisms in drug metabolism enzyme genes.

A class of genes, known as drug metabolism enzymes (DMEs) are responsible for the metabolism and transport of drugs and other xenobiotics. Variation in DME genes most likely accounts for a proportion of the variability in drug response in humans, and may contribute to complex diseases such as cancer (Nebert DW, Dieter MZ. Pharmacology 2000;61:124-135). To date, assessing the extent of this variation has proven difficult, especially because of sequence paralogy issues that cause difficulty when attempting to genotype polymorphisms in very closely-related gene families (Murphy MP. Pharmacogenomics 2000;1:115-123; Ingelman-Sundberg M. Drug Metab Rev 1999;31:449-459). We have developed and genotyped a panel of N=2,325 individual TaqMan genotyping assays for polymorphisms in >200 DME genes; many of the variants in the panel are single nucleotide polymorphisms (SNPs) that are of known or putative function (e.g., missense, nonsense or frameshift). Using these assays, we have examined genetic variation among several groups of populations, including: 1) the two SNP500 Cancer population panels (http://snp500cancer.nci.nih.gov; last accessed: 11 December 2007); and 2) the panel used in the International HapMap Project panel (www.hapmap.org; last accessed: 11 December 2007). We have developed a comprehensive validation strategy to ensure reproducibility and accuracy of the assays and estimated minor allele frequencies. Here, we present the results of these analyses, which strongly suggest that this panel of DME assays are of extremely high quality and produce robust, accurate, and reproducible results.

Germ-line genetic variation of TP53 in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) has been well described in individuals with germ-line TP53 mutations (Li-Fraumeni Syndrome) but typically occurs sporadically in adolescents and young adults. Single nucleotide polymorphisms (SNPs), the most common germ-line genetic variation, have been associated with risk for other types of cancer. We hypothesized that genetic variation in TP53 could be associated with OS risk based on its critical role in cell growth and effect of somatic mutations in OS tumors. PROCEDURE: Twelve common SNPs in TP53 were genotyped in a case-control study of sporadic OS. These SNPs spanned the TP53 locus and captured common haplotypes. Genotype data were analyzed using contingency tables for additive, dominant, and recessive genetic models. PHASEv2.1 and HaploStats were used to evaluate haplotypes. RESULTS: The recessive model suggested an increased risk of OS when two copies of TP53-34 C>G variant (IVS2+38, rs1642785) were present, P = 0.041, odds ratio (OR) 6.70 (95% confidence interval [CI] 1.06-41.6). The TP53-01 variant C>G (Pro72Arg, rs1042522) may also be associated with increased risk for OS, P = 0.028, OR 7.5 (95% CI 1.20-46.3). Common TP53 haplotypes as well as the remaining 10 SNPs were not associated with risk for OS. CONCLUSIONS: These data do not indicate a strong link between variation in TP53 and OS risk, although they provide preliminary evidence of an increased risk of OS associated with variants at IVS2+38 and Pro72Arg. The findings warrant replication in further studies.

SNP500Cancer: a public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes.

The SNP500Cancer database provides sequence and genotype assay information for candidate SNPs useful in mapping complex diseases, such as cancer. The database is an integral component of the NCI Cancer Genome Anatomy Project (http://cgap.nci.nih.gov). SNP500Cancer reports sequence analysis of anonymized control DNA samples (n = 102 Coriell samples representing four self-described ethnic groups: African/African-American, Caucasian, Hispanic and Pacific Rim). The website is searchable by gene, chromosome, gene ontology pathway, dbSNP ID and SNP500Cancer SNP ID. As of October 2005, the database contains >13 400 SNPs, 9124 of which have been sequenced in the SNP500Cancer population. For each analysed SNP, gene location and >200 bp of surrounding annotated sequence (including nearby SNPs) are provided, with frequency information in total and per subpopulation as well as calculation of Hardy-Weinberg equilibrium for each subpopulation. The website provides the conditions for validated sequencing and genotyping assays, as well as genotype results for the 102 samples, in both viewable and downloadable formats. A subset of sequence validated SNPs with minor allele frequency >5% are entered into a high-throughput pipeline for genotyping analysis to determine concordance for the same 102 samples. In addition, the results of genotype analysis for select validated SNP assays (defined as 100% concordance between sequence analysis and genotype results) are posted for an additional 280 samples drawn from the Human Diversity Panel (HDP). SNP500Cancer provides an invaluable resource for investigators to select SNPs for analysis, design genotyping assays using validated sequence data, choose selected assays already validated on one or more genotyping platforms, and select reference standards for genotyping assays. The SNP500Cancer database is freely accessible via the web page at http://snp500cancer.nci.nih.gov.