Schildkraut, Joellen M.

Abstract Inflammation is a facilitating process for multiple cancer types. It is believed to affect cancer development and progression through several etiologic pathways, including increased levels of DNA adduct formation, increased angiogenesis, and altered antiapoptotic signaling. This review highlights the application of inflammatory biomarkers in epidemiologic studies and discusses the various cellular mediators of inflammation characterizing the innate immune system response to infection and chronic insult from environmental factors. Included is a review of six classes of inflammation-related biomarkers: cytokines/chemokines, immune-related effectors, acute-phase proteins, reactive oxygen and nitrogen species, prostaglandins and cyclooxygenase-related factors, and mediators such as transcription factors and growth factors. For each of these biomarkers, we provide a brief overview of the etiologic role in the inflammation response and how they have been related to cancer etiology and progression within the literature. We provide a discussion of the common techniques available for quantification of each marker, including strengths, weaknesses, and potential pitfalls. Subsequently, we highlight a few under-studied measures to characterize the inflammatory response and their potential utility in epidemiologic studies of cancer. Finally, we suggest integrative methods for future studies to apply multifaceted approaches to examine the relationship between inflammatory markers and their roles in cancer development. Cancer Epidemiol Biomarkers Prev; 23(9); 1729–51. ©2014 AACR.

Abstract The presence of regulatory T cells (Treg) in solid tumors is known to play a role in patient survival in ovarian cancer and other malignancies. We assessed inherited genetic variations via 749 tag single-nucleotide polymorphisms (SNP) in 25 Treg-associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. We analyzed genotype and overall survival in 10,084 women with invasive epithelial ovarian cancer, including 5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous carcinoma cases of European descent across 28 studies from the Ovarian Cancer Association Consortium (OCAC). The strongest associations were found for endometrioid carcinoma and IL2RA SNPs rs11256497 [HR, 1.42; 95% confidence interval (CI), 1.22–1.64; P = 5.7 × 10−6], rs791587 (HR, 1.36; 95% CI, 1.17–1.57; P = 6.2 × 10−5), rs2476491 (HR, = 1.40; 95% CI, 1.19–1.64; P = 5.6 × 10−5), and rs10795763 (HR, 1.35; 95% CI, 1.17–1.57; P = 7.9 × 10−5), and for clear cell carcinoma and CTLA4 SNP rs231775 (HR, 0.67; 95% CI, 0.54–0.82; P = 9.3 × 10−5) after adjustment for age, study site, population stratification, stage, grade, and oral contraceptive use. The rs231775 allele associated with improved survival in our study also results in an amino acid change in CTLA4 and previously has been reported to be associated with autoimmune conditions. Thus, we found evidence that SNPs in genes related to Tregs seem to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid epithelial ovarian cancer. Cancer Immunol Res; 2(4); 332–40. ©2014 AACR.

Abstract Background: Ovarian cancer is a leading cause of cancer-related death among women. In an effort to understand contributors to disease outcome, we evaluated single-nucleotide polymorphisms (SNP) previously associated with ovarian cancer recurrence or survival, specifically in angiogenesis, inflammation, mitosis, and drug disposition genes. Methods: Twenty-seven SNPs in VHL, HGF, IL18, PRKACB, ABCB1, CYP2C8, ERCC2, and ERCC1 previously associated with ovarian cancer outcome were genotyped in 10,084 invasive cases from 28 studies from the Ovarian Cancer Association Consortium with over 37,000-observed person-years and 4,478 deaths. Cox proportional hazards models were used to examine the association between candidate SNPs and ovarian cancer recurrence or survival with and without adjustment for key covariates. Results: We observed no association between genotype and ovarian cancer recurrence or survival for any of the SNPs examined. Conclusions: These results refute prior associations between these SNPs and ovarian cancer outcome and underscore the importance of maximally powered genetic association studies. Impact: These variants should not be used in prognostic models. Alternate approaches to uncovering inherited prognostic factors, if they exist, are needed. Cancer Epidemiol Biomarkers Prev; 22(5); 987–. ©2013 AACR.

Abstract Background: There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied. Methods: Data from 14 ovarian cancer case–control studies were pooled, and stratified analyses by each environmental risk factor with tests for heterogeneity were conducted to determine the presence of interactions for all histologic subtypes. A genetic “risk score” was created to consider the effects of all six variants simultaneously. A multivariate model was fit to examine the association between all environmental risk factors and genetic risk score on ovarian cancer risk. Results: Among 7,374 controls and 5,566 cases, there was no statistical evidence of interaction between the six SNPs or genetic risk score and the environmental risk factors on ovarian cancer risk. In a main effects model, women in the highest genetic risk score quartile had a 65% increased risk of ovarian cancer compared with women in the lowest [95% confidence interval (CI), 1.48–1.84]. Analyses by histologic subtype yielded risk differences across subtype for endometriosis (Phet < 0.001), parity (Phet < 0.01), and tubal ligation (Phet = 0.041). Conclusions: The lack of interactions suggests that a multiplicative model is the best fit for these data. Under such a model, we provide a robust estimate of the effect of each risk factor that sets the stage for absolute risk prediction modeling that considers both environmental and genetic risk factors. Further research into the observed differences in risk across histologic subtype is warranted. Cancer Epidemiol Biomarkers Prev; 22(5); 880–90. ©2013 AACR.

Abstract Population stratification in case-control studies can result from differences in ancestral make-up between cases and controls due to sampling variation. Ancestry is therefore routinely estimated and controlled for in these studies. Although less common, it is also possible for ancestry to truly be associated to the disease of interest. Controlling for ancestry can then compromise the power to detect variants that underlie both ancestry and disease. Using data from a multi-center case-control study of epithelial ovarian cancer (OC) among women of European-American ethnicity in which case-control samples were drawn from four geographically distinct North-American sites, we developed a three-step method to investigate whether the stratification observed across the four sites is due to chance or to a non-spurious association between European ancestry and OC. First, we collapsed genome-wide data into two principal components (PCs) that represent the major axes of European ancestral variation, which correspond to north-south and to west-east geographical clines. Next, we determined the discriminant function based on these two PCs that best separates cases and controls for each individual study site and we used the largest angle between the four discriminant function vectors as a measure of similarity ranging from 0 degrees, where all four vectors are exactly the same, to 180 degrees where two of the vectors face exactly opposite directions. If stratification is due to sampling, it is unlikely that the four sites will present similar discriminant functions by chance alone. We then gauged significance of similarity by permuting the case control status across individuals within each site and recalculating the maximum angle between the discriminant function vectors, thus obtaining a null distribution for the statistic. We found that all four sites present the greatest separation between cases and controls on the west-east axis of ancestral variation, with a higher proportion of ovarian cancer cases presenting western ancestry. The largest angle between the four discriminant function vectors observed was of 36.5 degrees. Permutation testing showed this level of similarity between the functions to have a p-value < 0.01 and suggests that OC risk is somehow tied to European ancestry. It remains to be seen whether shared culture or other exposures such as parity or oral contraceptive use explain this connection or whether genetic variants underlie it and are potentially being missed due to routine ancestry control in association testing. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1678. doi:1538-7445.AM2012-1678

Abstract DNA copy number variations (CNVs) are a significant and ubiquitous source of human genetic variation. However, the influence of CNVs on cancer susceptibility remains poorly understood. Out of 83 genome-wide association studies (GWAS) on cancer to date, only a few studies found significant associations on germline CNVs and cancer. Here we analyzed data from our ongoing two-stage GWAS of four North American case-control studies to test the hypothesis that CNVs in germline DNA from peripheral blood lymphocytes may serve as risk factors for epithelial ovarian cancer (EOC). To reduce disease heterogeneity, we focused on the subset of cases with serous histology. The analysis was therefore based on 942 serous ovarian cancer patients and 1,682 healthy controls who were genotyped using the Illumina 610K quad array. Subjects with extreme noise and genomic waviness in log R ratio (LR) were excluded prior to segmentation; principal component analysis was performed to adjust for batch effects. CNV segmentation was performed on LR data from 22 autosomes using circular binary segmentation embedded in the Copy Number Analysis Module from Golden Helix SNP Variation Suite version 7. Copy number segment covariates were discretized based on the thresholds that signify a transition between copy number states (deletion/no deletion; duplication/no duplication) after the segmentation. Unconditional logistic regression on a log-additive model was used to evaluate the association between copy number states and serous EOC risk after adjusting for study sites. By comparing single marker copy number states at 388,958 SNPs on 22 autosomes, we observed a total of 134 SNPs significantly associated with risk of serous EOC with a p value below 10−6. Associations with deletion polymorphisms were observed on chromosomes 7, 8, 14, and 18 when controlling for false discovery rate at 1%; no duplication polymorphisms were significant. We observed a large deletion at chromosome 14 that occurred in 8.9% of cases but in only 3.9% of controls, with a p value of 5.59×10−8 (Odds Ratio (OR): 2.56, 95% confidence interval (CI): 1.82-3.60). Another common deletion on chromosome 7 occurred in 8.8% of cases and only 4.3% of controls (p=3.83×10−6; OR: 2.23, 95% CI: 1.60-3.10). Two additional regions on chromosomes 8 and 18 with deletion events less than 5% were also identified. Women who harbored the deletion on chromosome 8 were at lower risk of developing serous ovarian cancer (p=4.83×10−8; OR: 0.04, 95% CI: 0.01-0.30). Women who carried the deletion on chromosome 18 had an increased risk for serous EOC (p=9.04×10−7; OR: 7.26, 95% CI: 2.94-17.97). Further validation of these four regions using independent data sets is currently underway. In summary, this is the largest reported genome-wide study of CNVs and serous EOC risk. These preliminary results suggested that germline CNVs may play an important role in ovarian cancer susceptibility. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1649. doi:1538-7445.AM2012-1649

Abstract Mi(cro)RNAs are short non-coding RNA molecules that play a key role in carcinogenesis by regulating tumor suppressors and oncogenes. Published data has implicated miRNAs in ovarian cancer (OC) development and progression, and we hypothesize that single nucleotide polymorphisms (SNPs) in sites of miRNA: messenger RNA (mRNA) binding may influence OC risk by altering expression levels of targeted mRNAs. To evaluate associations between SNPs in miRNA binding sites and OC risk, we used bioinformatics tools and public databases to identify miRNA binding SNPs relevant to ovarian cancer. We then evaluated the frequency of approximately 1,100 SNPs in ∼20,000 epithelial OC cases and 20,000 controls represented in the international Collaborative Oncological Gene-environment Study. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status, with adjustment for the first five principal components representing European ancestry. Log-additive genetic models were applied to each SNP, modeling the number of copies of the minor allele. Subgroup analysis was conducted for serous adenocarcinomas, the most predominant histologic subtype of epithelial OC. Preliminary analysis of 11,215 invasive epithelial OCs and 15,910 controls included four SNPs with P<10−6 and 1 SNP with P<10−5. Analysis of 6,215 invasive serous adenocarcinomas revealed two SNPs with P<10−7 and three SNPs with P<10−6. Noteworthy is rs6104808, a C>T SNP predicted to reside in a highly conserved miRNA binding site of BTBD3 (BTB POZ domain containing 3), a transcription factor suggested to be involved in cell proliferation, cancer progression, and response to platinum-based chemotherapy. rs6104808 was associated with a decreased risk of OC overall (OR (95% CI): 0.42 (0.28-0.62), P=1.26 x 10−5)), and the association was stronger among cases with serous adenocarcinoma (OR (95% CI): 0.30 (0.17-0.50), P=9.89 x 10−6)). This represents the largest, most comprehensive epidemiologic study to date to evaluate associations between miRNA binding site SNPs and OC susceptibility. Although based on a preliminary analysis, these data suggest a significant role and putative biological mechanism for common germline variants in miRNA binding sites leading to cancer development. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2927. doi:1538-7445.AM2012-2927

Abstract As pathways of the immune system play an important role in multiple malignancies, we assessed the association between single-nucleotide polymorphisms (SNPs) in inflammation-related genes and risk of ovarian cancer in a multi-site case-control study. Using a custom array, we genotyped 930 epithelial ovarian cancer cases and 1,037 controls for SNPs in ALOX12, ALOX15, ALOX5, CCL11, CCL2, CCL3, CCR3, CRP, CXCL16, IL10, IL15RA, IL18, IL1A, IL1B, IL1RN, IL4R, IL6, IL6R, IL7R, IL8RA, IL8RB, IL9, NOS3, PTGS1, PTGS2, TLR2, and TNF. After analysis by logistic regression, SNPs with p<0.10 were evaluated in an independent data set of 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) collaboration. Combined analysis revealed association with interleukin 1, alpha (IL1A) SNPs (rs17561 and rs4848300, r2=0.990, p=0.005) which varied by histological subtype (heterogeneity p=0.03). For example, IL1A rs17561, which results in a missense change in amino acid at position 114 and correlates with multiple inflammatory phenotypes, was inversely associated with risk of clear cell, mucinous, and endometrioid subtypes, but not with the serous subtype (Table 1). Additional data on IL1A rs17561 in an even larger collection of ovarian cancer cases and controls are pending and will be analyzed soon. We also found that genotype at rs1864414 in ALOX5 (arachidonate 5-lipoxygenase) was associated with decreased risk combined across subtypes (OR 0.86, 95% CI 0.78-0.95; p=0.002). Thus, inherited variation in IL1A and ALOX5 appears to have a role in ovarian cancer risk, though it is limited to rarer subtypes for IL1A. These data add to existing literature on the importance of inflammation in tumorigenesis and growing evidence of subtype-specific traits in ovarian cancer and may provide important clues on prevention. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2603. doi:1538-7445.AM2012-2603

Abstract Epithelial ovarian cancer (EOC) is the 6th most commonly diagnosed cancer among women in the world, accounting for 4% of all female cancers. On a worldwide basis, an estimated 204,000 new cases are diagnosed and 125,000 women die of EOC annually, with 5-year survival rate at 45%. Metastasis and its complications are the usual cause of EOC-related deaths. Thus, factors related to tumor aggressiveness, response to therapy, and the underlying health state of the patient often predict survival. Candidate gene and genome-wide association studies (GWAS) for survival from EOC have discovered only a few the genetic variants, accounting for only a small proportion of the heritability. One explanation for the missing heritability is that the common analysis approach _ assessing the effect of each single nucleotide polymorphism (SNP) individually _ is not well suited to the detection of small effects of multiple SNPs. Gene set analysis (GSA) overcomes this limitation by assessing the overall evidence of association of a phenotype with all measured variation in a set of genes or pathway. Therefore, we conducted a GSA using data from an EOC GWAS, using the Illumina 610-quad SNP array, to determine novel gene sets (GSs) associated with overall survival (OS) from EOC (N cases = 1057, N deaths = 495). All subjects were non-Hispanic, non-Jewish Caucasians, with sample and SNP call rates >95%. Subjects with ambiguous gender, unresolved identical genotypes, and less than 80% European ancestry were also excluded. SNPs were mapped to genes within 20 kb, with genes then mapped to GSs defined by the following: KEGG, Gene Ontology (biological, cellular, molecular) and PharmGKB. GSA was completed in which the association of each gene with OS was assessed using a principal component gene-level test (adjusting for study site, age and population sub-structure based on the first eigenvector from EigenStrat), followed by the aggregation of the gene-level p-values using the Gamma method with a soft truncation threshold of 0.15. Empirical p-values were determined using permutation methods. Of the 2,573 GSs assessed, 30 GSs had a p-value < 0.01. The top GSs were related to: mismatch repair (p = 3.0E-4), platelet formation (p=0.001), leukocyte adhesive activation (p=0.002), antigen processing and presentation of endogenous antigens (p = 0.002) or peptide antigens (p = 0.002), platinum pathway (p = 0.003), aging and lifespan (p = 0.004, p = 0.007), immune system development (p = 0.004) and somatic diversification (p=0.007). These results illustrate the usefulness of GSA for the development of novel hypotheses that can be followed-up with additional clinical or functional studies. Moreover, application of GSA to survival from EOC allowed the detection of significant GSs (and the corresponding genes/SNPs within these GSs) that impact OS that were not detected by assessing each SNP individually, where the smallest p-value from single SNP analysis of the GWAS for OS was 1.3E-05. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2738. doi:10.1158/1538-7445.AM2011-2738

Abstract The etiology of ovarian cancer is poorly understood but there is clearly a heritable component. Efforts to identify susceptibility alleles rarely consider interactions among alleles or their joint effects because it quickly becomes computationally intractable. In this study, we sought to identify multi-SNP effects jointly with a pathway-based analysis (GSEA-SNP) of 1,952 EOC cases and 2,042 frequency-matched controls genotyped with the Illumina 610K array. All subjects were self-reported non-Hispanic non-Jewish Caucasians, with SNP and sample call rates > 95%. Subjects with ambiguous gender, unresolved identical genotypes and < 80% European ancestry were excluded. SNPs with MAF < 1% were excluded. Missing genotypes were inferred using Mach based on the HapMap CEU population. SNPs not within introns were annotated to genes within 100 bp. We retrieved the following databases of gene sets (GSs) from a compiled database, MsigDB: human chromosome and cytogenetic band, chemical and genetic perturbations, canonical pathways, microRNA binding targets, transcription factor targets (TFT), cancer gene neighborhood (CGN), Cancer modules and Gene Ontology. The GSEA-SNP approach calculates and rank orders the trend statistic for association between each SNP and EOC risk. The Enrichment Score (ES) estimates the overrepresentation of top-ranked SNPs for each GS; the statistical significance was estimated using 10,000 permutations. The ES was normalized according to the size of GS to yield Normalized Enrichment Score (NES). The false discovery (FDR) rate was estimated using NES to adjust for multiple hypothesis testing. A total of 5181 gene-sets were included in the analysis. When controlling the FDR at 15%, 14 of the GSs were highly enriched with association signals, including two chromosomal regions, 8q13 (p = 0.0055, FDR = 0.15) and 6p24 (p = 0.0012, FDR = 0.08). BIOCARTA_LYM_PATHWAY, a pathway related to cell adhesion and diapedesis of lymphocytes, was also significant (p = 0.0002, FDR = 0.12). A TFT GS, composed of genes with promoter regions around transcription start sites containing the motif GGCNRNWCTTYS, was associated with risk (p = 0.0004, FDR = 0.08). Currently, no known transcription factors bind to this computationally predicted motif. Molecular function of double stranded RNA binding was also enriched (p = 0.005, FDR = 0.10). The remaining enriched sets were CGN sets, for which the neighborhoods around the cancer genes were originally defined using correlation of gene expression from 4 large data sets of various cancer types. The enriched CGN included: CD48 (p = 0.011), CD53 (p = 0.009), CD97 (p = 0.011), INPP5D (p = 0.010), PTPN6 (p = 0.008), VAV1 (p = 0.011), ITGAL (p = 0.012), PTPRC (p = 0.012), and STAT6 (p = 0.010). In summary, these analyses detected biologically plausible GSs related to etiology of EOC, highlighting SNPs in core enrichment groups that were not identified using individual SNP tests. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4729. doi:10.1158/1538-7445.AM2011-4729