Differences in Tumor-Associated T cell receptor repertoires between Early-Onset and Average-Onset colorectal cancer.

The incidence of colorectal cancer (CRC) among individuals younger than age 50 (early onset CRC; EOCRC) has substantially increased, yet the etiology and molecular mechanisms underlying this alarming rise remain unclear. We compared tumor-associated T cell repertoires between EOCRC and average-onset CRC (AOCRC) to uncover potentially unique immune microenvironment-related features by age of onset. Our discovery cohort included 242 patients who underwent surgical resection at Cleveland Clinic from 2000 to 2020. EOCRC was defined as age < 50 years at diagnosis (N = 126), and AOCRC as age ≥ 60 years (N = 116). T cell receptor (TCR) abundance and clonality were measured by immunosequencing of tumors. Logistic regression models were used to evaluate the associations between TCR repertoire features and age of onset, adjusting for sex, race, tumor location, and stage. Findings were replicated in 152 EOCRC and 1,984 AOCRC cases from the Molecular Epidemiology of Colorectal Cancer Study. EOCRC tumors had significantly higher TCR diversity compared to AOCRC tumors in the discovery cohort (Odds Ratio (OR):0.44, 95% Confidence Interval (CI):0.32-0.61, p < .0001). This association was also observed in the replication cohort (OR : 0.74, 95% CI : 0.62-0.89, p = .0013). No significant differences in TCR abundance were observed between EOCRC and AOCRC in either cohort. Higher TCR diversity, suggesting a more diverse intratumoral T cell response, is more frequently observed in EOCRC than AOCRC. Further studies are warranted to investigate the role of T cell diversity and the adaptive immune response more broadly in the etiology and outcomes of EOCRC.

Germline genetic regulation of the colorectal tumor immune microenvironment.

OBJECTIVE: To evaluate the contribution of germline genetics to regulating the briskness and diversity of T cell responses in CRC, we conducted a genome-wide association study to examine the associations between germline genetic variation and quantitative measures of T cell landscapes in 2,876 colorectal tumors from participants in the Molecular Epidemiology of Colorectal Cancer Study (MECC). METHODS: Germline DNA samples were genotyped and imputed using genome-wide arrays. Tumor DNA samples were extracted from paraffin blocks, and T cell receptor clonality and abundance were quantified by immunoSEQ (Adaptive Biotechnologies, Seattle, WA). Tumor infiltrating lymphocytes per high powered field (TILs/hpf) were scored by a gastrointestinal pathologist. Regression models were used to evaluate the associations between each variant and the three T-cell features, adjusting for sex, age, genotyping platform, and global ancestry. Three independent datasets were used for replication. RESULTS: We identified a SNP (rs4918567) near RBM20 associated with clonality at a genome-wide significant threshold of 5 × 10- 8, with a consistent direction of association in both discovery and replication datasets. Expression quantitative trait (eQTL) analyses and in silico functional annotation for these loci provided insights into potential functional roles, including a statistically significant eQTL between the T allele at rs4918567 and higher expression of ADRA2A (P = 0.012) in healthy colon mucosa. CONCLUSIONS: Our study suggests that germline genetic variation is associated with the quantity and diversity of adaptive immune responses in CRC. Further studies are warranted to replicate these findings in additional samples and to investigate functional genomic mechanisms.

Heterozygote advantage at HLA class I and II loci and reduced risk of colorectal cancer.

Objective: Reduced diversity at Human Leukocyte Antigen (HLA) loci may adversely affect the host's ability to recognize tumor neoantigens and subsequently increase disease burden. We hypothesized that increased heterozygosity at HLA loci is associated with a reduced risk of developing colorectal cancer (CRC). Methods: We imputed HLA class I and II four-digit alleles using genotype data from a population-based study of 5,406 cases and 4,635 controls from the Molecular Epidemiology of Colorectal Cancer Study (MECC). Heterozygosity at each HLA locus and the number of heterozygous genotypes at HLA class -I (A, B, and C) and HLA class -II loci (DQB1, DRB1, and DPB1) were quantified. Logistic regression analysis was used to estimate the risk of CRC associated with HLA heterozygosity. Individuals with homozygous genotypes for all loci served as the reference category, and the analyses were adjusted for sex, age, genotyping platform, and ancestry. Further, we investigated associations between HLA diversity and tumor-associated T cell repertoire features, as measured by tumor infiltrating lymphocytes (TILs; N=2,839) and immunosequencing (N=2,357). Results: Individuals with all heterozygous genotypes at all three class I genes had a reduced odds of CRC (OR: 0.74; 95% CI: 0.56-0.97, p= 0.031). A similar association was observed for class II loci, with an OR of 0.75 (95% CI: 0.60-0.95, p= 0.016). For class-I and class-II combined, individuals with all heterozygous genotypes had significantly lower odds of developing CRC (OR: 0.66, 95% CI: 0.49-0.87, p= 0.004) than those with 0 or one heterozygous genotype. HLA class I and/or II diversity was associated with higher T cell receptor (TCR) abundance and lower TCR clonality, but results were not statistically significant. Conclusion: Our findings support a heterozygote advantage for the HLA class-I and -II loci, indicating an important role for HLA genetic variability in the etiology of CRC.

Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk.

BACKGROUND: Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk. METHODS: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons. RESULTS: The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4). CONCLUSION: These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.

Safety and chemopreventive effect of Polyphenon E in preventing early and metastatic progression of prostate cancer in TRAMP mice.

Prostate cancer treatment is often accompanied by untoward side effects. Therefore, chemoprevention to reduce the risk and inhibit the progression of prostate cancer may be an effective approach to reducing disease burden. We investigated the safety and efficacy of Polyphenon E, a green tea extract, in reducing the progression of prostate cancer in transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. A total of 119 male TRAMP and 119 C57BL/6J mice were treated orally with one of 3 doses of Polyphenon E (200, 500, and 1,000 mg/kg/day) in drinking water ad libitum replicating human achievable doses. Baseline assessments were performed before treatments. Safety and efficacy assessments during treatments were performed when mice were 12, 22, and 32 weeks old. The number and size of tumors in treated TRAMP mice were significantly decreased compared with untreated animals. In untreated 32 weeks old TRAMP mice, prostate carcinoma metastasis to distant sites was observed in 100% of mice (8/8), compared with 13% of mice (2/16) treated with high-dose Polyphenon E during the same period. Furthermore, Polyphenon E treatment significantly inhibited metastasis in TRAMP mice in a dose-dependent manner (P = 0.0003). Long-term (32 weeks) treatment with Polyphenon E was safe and well tolerated with no evidence of toxicity in C57BL/6J mice. Polyphenon E is an effective chemopreventive agent in preventing the progression of prostate cancer to metastasis in TRAMP mice. Polyphenon E showed no toxicity in these mouse models. Our findings provide additional evidence for the safety and chemopreventive effect of Polyphenon E in preventing metastatic progression of prostate cancer.

Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31.

Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3' untranslated region at putative microRNA (miRNA)-binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA-related single-nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (odds ratio=1.12, P=10(-8)) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10(-10)). Variation at 17q21.31 is associated with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.

GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer.

Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10(-9)) and 10p12 (rs1243180, P = 1.8 × 10(-8)) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10(-10)). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility and implicated CHMP4C in the pathogenesis of ovarian cancer.

ABO blood group and risk of epithelial ovarian cancer within the Ovarian Cancer Association Consortium.

PURPOSE: Previous studies have examined the association between ABO blood group and ovarian cancer risk, with inconclusive results. METHODS: In eight studies participating in the Ovarian Cancer Association Consortium, we determined ABO blood groups and diplotypes by genotyping 3 SNPs in the ABO locus. Odds ratios and 95 % confidence intervals were calculated in each study using logistic regression; individual study results were combined using random effects meta-analysis. RESULTS: Compared to blood group O, the A blood group was associated with a modestly increased ovarian cancer risk: (OR: 1.09; 95 % CI: 1.01-1.18; p = 0.03). In diplotype analysis, the AO, but not the AA diplotype, was associated with increased risk (AO: OR: 1.11; 95 % CI: 1.01-1.22; p = 0.03; AA: OR: 1.03; 95 % CI: 0.87-1.21; p = 0.76). Neither AB nor the B blood groups were associated with risk. Results were similar across ovarian cancer histologic subtypes. CONCLUSION: Consistent with most previous reports, the A blood type was associated modestly with increased ovarian cancer risk in this large analysis of multiple studies of ovarian cancer. Future studies investigating potential biologic mechanisms are warranted.

Germline copy number variation and ovarian cancer survival.

Copy number variants (CNVs) have been implicated in many complex diseases. We examined whether inherited CNVs were associated with overall survival among women with invasive epithelial ovarian cancer. Germline DNA from 1,056 cases (494 deceased, average of 3.7 years follow-up) was interrogated with the Illumina 610 quad genome-wide array containing, after quality control exclusions, 581,903 single nucleotide polymorphisms (SNPs) and 17,917 CNV probes. Comprehensive analysis capitalized upon the strengths of three complementary approaches to CNV classification. First, to identify small CNVs, single markers were evaluated and, where associated with survival, consecutive markers were combined. Two chromosomal regions were associated with survival using this approach (14q31.3 rs2274736 p = 1.59 × 10(-6), p = 0.001; 22q13.31 rs2285164 p = 4.01 × 10(-5), p = 0.009), but were not significant after multiple testing correction. Second, to identify large CNVs, genome-wide segmentation was conducted to characterize chromosomal gains and losses, and association with survival was evaluated by segment. Four regions were associated with survival (1q21.3 loss p = 0.005, 5p14.1 loss p = 0.004, 9p23 loss p = 0.002, and 15q22.31 gain p = 0.002); however, again, after correcting for multiple testing, no regions were statistically significant, and none were in common with the single marker approach. Finally, to evaluate associations with general amounts of copy number changes across the genome, we estimated CNV burden based on genome-wide numbers of gains and losses; no associations with survival were observed (p > 0.40). Although CNVs that were not well-covered by the Illumina 610 quad array merit investigation, these data suggest no association between inherited CNVs and survival after ovarian cancer.

European American stratification in ovarian cancer case control data: the utility of genome-wide data for inferring ancestry.

We investigated the ability of several principal components analysis (PCA)-based strategies to detect and control for population stratification using data from a multi-center study of epithelial ovarian cancer among women of European-American ethnicity. These include a correction based on an ancestry informative markers (AIMs) panel designed to capture European ancestral variation and corrections utilizing un-thinned genome-wide SNP data; case-control samples were drawn from four geographically distinct North-American sites. The AIMs-only and genome-wide first principal components (PC1) both corresponded to the previously described North or Northwest-Southeast axis of European variation. We found that the genome-wide PCA captured this primary dimension of variation more precisely and identified additional axes of genome-wide variation of relevance to epithelial ovarian cancer. Associations evident between the genome-wide PCs and study site corroborate North American immigration history and suggest that undiscovered dimensions of variation lie within Northern Europe. The structure captured by the genome-wide PCA was also found within control individuals and did not reflect the case-control variation present in the data. The genome-wide PCA highlighted three regions of local LD, corresponding to the lactase (LCT) gene on chromosome 2, the human leukocyte antigen system (HLA) on chromosome 6 and to a common inversion polymorphism on chromosome 8. These features did not compromise the efficacy of PCs from this analysis for ancestry control. This study concludes that although AIMs panels are a cost-effective way of capturing population structure, genome-wide data should preferably be used when available.

Regular Multivitamin Supplement Use, Single Nucleotide Polymorphisms in ATIC, SHMT2, and SLC46A1, and Risk of Ovarian Carcinoma.

ATIC, SHMT2, and SLC46A1 have essential roles in one-carbon (1-C) transfer. The authors examined whether associations between ovarian carcinoma and 15 variants in these genes are modified by regular multivitamin use, a source of 1-C donors, among Caucasian participants from two US case-control studies. Using a phased study design, variant-by-multivitamin interactions were tested, and associations between variants and ovarian carcinoma were reported stratified by multivitamin supplement use. Per-allele risk associations were modified by multivitamin use at six variants among 655 cases and 920 controls (Phase 1). In a larger sample of 968 cases and 1,265 controls (Phases 1 and 2), interactions were significant (P ≤ 0.03) for two variants, particularly among regular multivitamin users: ATIC rs7586969 [odds ratio (OR) = 0.7, 95% confidence interval (CI) = 0.6-0.9] and ATIC rs16853834 (OR = 1.5, 95% CI = 1.1-2.0). The two ATIC single nucleotide polymorphisms (SNPs) did not share the same haplotype; however, the haplotypes they comprised mirrored their SNP risk associations among regular multivitamin supplement users. A multi-variant analysis was also performed by comparing the observed likelihood ratio test statistic from adjusted models with and without the two ATIC variant-by-multivitamin interaction terms with a null distribution of test statistics generated by permuting case status 10,000 times. The corresponding observed P value of 0.001 was more extreme than the permutation-derived P value of 0.009, suggesting rejection of the null hypothesis of no association. In summary, there is little statistical evidence that the 15 variants are independently associated with risk of ovarian carcinoma. However, the statistical interaction of ATIC variants with regular multivitamin intake, when evaluated at both the SNP and gene level, may support these findings as relevant to ovarian health and disease processes.

Gene set analysis of survival following ovarian cancer implicates macrolide binding and intracellular signaling genes.

BACKGROUND: Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes. METHODS: To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype. RESULTS: Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10(-5)) and macrolide binding (P = 6.2 × 10(-4)) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10(-4)) and macrolide binding (P = 1.0 × 10(-3)). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS. CONCLUSION: This research detected novel gene sets associated with EOC survival. IMPACT: Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies.

Common variation in Nemo-like kinase is associated with risk of ovarian cancer.

BACKGROUND: Overexpression of mitotic kinases has been associated with prognosis, histologic grade, and clinical stage in ovarian cancer, but the relationship between inherited variation in these genes and ovarian cancer risk has not been well defined. METHODS: We measured associations between 397 single nucleotide polymorphisms (SNPs) from 67 mitotic kinases and invasive epithelial ovarian cancer risk in two case-control studies (n = 671 cases; n = 939 controls). Thirty-six candidate SNPs (P < 0.05) were assessed in a replication analysis consisting of three additional studies (n = 1,094 cases; n = 829 controls). RESULTS: In initial analysis, thirty-six SNPs were suggestive of association with risk of serous ovarian cancer, all subtypes of ovarian cancer, or both (P < 0.05). Replication analyses suggested an association between rs2125846 in the Nemo-like kinase (NLK) gene and ovarian cancer (serous OR = 1.36, 95% CI: 1.11-1.67, P = 1.77 × 10(-3); all subtypes OR = 1.30, 95% CI: 1.08-1.56, P = 2.97 × 10(-3)). Furthermore, rs2125846 was associated with risk in the combined discovery and replication sets (serous OR = 1.33, 95% CI: 1.15-1.54; all subtypes OR = 1.27, 95% CI: 1.12-1.45). CONCLUSIONS: Variation in NLK may be associated with risk of invasive epithelial ovarian cancer. Further studies are needed to confirm and understand the biologic relationship between this mitotic kinase and ovarian cancer risk. IMPACT: An association between SNPs in NLK and ovarian cancer may provide biologic insight into the development of this disease.

Phase I trial of vorinostat combined with bevacizumab and CPT-11 in recurrent glioblastoma.

A phase I study was conducted to determine the dose-limiting toxicities (DLT) and maximum tolerated dose (MTD) for the combination of vorinostat with bevacizumab and CPT-11 in recurrent glioblastoma. Vorinostat was combined with bevacizumab and CPT-11 and was escalated using a standard 3 + 3 design. Vorinostat was escalated up to 2 actively investigated doses of this compound or until the MTD was identified on the basis of DLTs. Correlative science involving proteomic profiling of serial patient plasma samples was performed. Nineteen patients were treated. The MTD of vorinostat was established at 400 mg on days 1-7 and 15-21 every 28 days when combined with bevacizumab and CPT-11. Common toxicities were fatigue and diarrhea. DLTs included fatigue, hypertension/hypotension, and central nervous system ischemia. Although the MTD was established, CPT-11 dose reductions were common early in therapy. High-dose vorinostat had an improved progression-free survival and overall survival when compared with low-dose vorinostat. Serum proteomic profiling identified IGFBP-5 and PDGF-AA as markers for improved PFS and recurrence, respectively. A MTD for the combination of vorinostat with bevacizumab and CPT-11 has been established, although it has poor long-term tolerability. With the increased toxicities associated with CPT-11 coupled with its unclear clinical significance, investigating the efficacy of vorinostat combined with bevacizumab alone may represent a more promising strategy to evaluate in the context of a phase II clinical trial.

TRM: a powerful two-stage machine learning approach for identifying SNP-SNP interactions.

Studies have shown that interactions of single nucleotide polymorphisms (SNPs) may play an important role in understanding the causes of complex disease. We have proposed an integrated machine learning method that combines two machine-learning methods-Random Forests (RF) and Multivariate Adaptive Regression Splines (MARS)-to identify a subset of important SNPs and detect interaction patterns more effectively and efficiently. In this two-stage RF-MARS (TRM) approach, RF is first applied to detect a predictive subset of SNPs, and then MARS is used to identify the interaction patterns. We evaluated the TRM performances in four models. RF variable selection was based on out-of-bag classification error rate (OOB) and variable important spectrum (IS). Our results support that RF(OOB) had better performance than MARS and RF(IS) in detecting important variables. This study demonstrates that TRM(OOB) , which is RF(OOB) plus MARS, has combined the strengths of RF and MARS in identifying SNP-SNP interactions in a scenario of 100 candidate SNPs. TRM(OOB) had greater true positive rate and lower false positive rate compared with MARS, particularly for searching interactions with a strong association with the outcome. Therefore, the use of TRM(OOB) is favored for exploring SNP-SNP interactions in a large-scale genetic variation study.

Meta-analysis of 8q24 for seven cancers reveals a locus between NOV and ENPP2 associated with cancer development.

BACKGROUND: Human chromosomal region 8q24 contains several genes which could be functionally related to cancer, including the proto-oncogene c-MYC. However, the abundance of associations around 128 Mb on chromosome 8 could mask the appearance of a weaker, but important, association elsewhere on 8q24. METHODS: In this study, we completed a meta-analysis of results from nine genome-wide association studies for seven types of solid-tumor cancers (breast, prostate, pancreatic, lung, ovarian, colon, and glioma) to identify additional associations that were not apparent in any individual study. RESULTS: Fifteen SNPs in the 8q24 region had meta-analysis p-values < 1E-04. In particular, the region consisting of 120,576,000-120,627,000 bp contained 7 SNPs with p-values < 1.0E-4, including rs6993464 (p = 1.25E-07). This association lies in the region between two genes, NOV and ENPP2, which have been shown to play a role in tumor development and motility. An additional region consisting of 5 markers from 128,478,000 bp - 128,524,000 (around gene POU5F1B) had p-values < 1E-04, including rs6983267, which had the smallest p-value (p = 6.34E-08). This result replicates previous reports of association between rs6983267 and prostate and colon cancer. CONCLUSIONS: Further research in this area is warranted as these results demonstrate that the chromosomal region 8q24 may contain a locus that influences general cancer susceptibility between 120,576 and 120,630 kb.

Assessment of hepatocyte growth factor in ovarian cancer mortality.

BACKGROUND: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality. METHODS: We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue microarrays (TMA, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths). RESULTS: The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR = 1.7, 95% CI = 1.3-2.2, P = 2.0 × 10(-5)) and with overall variation in HGF (gene-level test, P = 3.7 × 10(-4)). Analysis of TCGA data revealed consistent associations [e.g., rs5745709 (r(2) = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4-4.1, P = 2.2 × 10(-3); Mayo Clinic + TCGA HR = 1.6, CI = 1.3-1.9, P = 7.0 × 10(-5)] and suggested genotype correlation with reduced HGF mRNA levels (P = 0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET (C-MET), and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (P = 0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (HR = 1.0, CI = 0.9-1.1, P = 0.87). CONCLUSIONS: We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression. IMPACT: Our study shows the utility of multiple data types and multiple data sets in observational studies.

A latent model for prioritization of SNPs for functional studies.

One difficult question facing researchers is how to prioritize SNPs detected from genetic association studies for functional studies. Often a list of the top M SNPs is determined based on solely the p-value from an association analysis, where M is determined by financial/time constraints. For many studies of complex diseases, multiple analyses have been completed and integrating these multiple sets of results may be difficult. One may also wish to incorporate biological knowledge, such as whether the SNP is in the exon of a gene or a regulatory region, into the selection of markers to follow-up. In this manuscript, we propose a Bayesian latent variable model (BLVM) for incorporating "features" about a SNP to estimate a latent "quality score", with SNPs prioritized based on the posterior probability distribution of the rankings of these quality scores. We illustrate the method using data from an ovarian cancer genome-wide association study (GWAS). In addition to the application of the BLVM to the ovarian GWAS, we applied the BLVM to simulated data which mimics the setting involving the prioritization of markers across multiple GWAS for related diseases/traits. The top ranked SNP by BLVM for the ovarian GWAS, ranked 2(nd) and 7(th) based on p-values from analyses of all invasive and invasive serous cases. The top SNP based on serous case analysis p-value (which ranked 197(th) for invasive case analysis), was ranked 8(th) based on the posterior probability of being in the top 5 markers (0.13). In summary, the application of the BLVM allows for the systematic integration of multiple SNP "features" for the prioritization of loci for fine-mapping or functional studies, taking into account the uncertainty in ranking.

MicroRNA processing and binding site polymorphisms are not replicated in the Ovarian Cancer Association Consortium.

BACKGROUND: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. METHODS: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. RESULTS: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. CONCLUSIONS: Common variants in these evaluated genes do not seem to be strongly associated with EOC risk. IMPACT: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered.