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

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Modifiers of breast and ovarian cancer risks for BRCA1 and BRCA2 mutation carriers

Pathogenic mutations in BRCA1 and BRCA2 are associated with high risks of breast and ovarian cancer. However, penetrance estimates for mutation carriers have been found to vary substantially between studies, and the observed differences in risk are consistent with the hypothesis that genetic and environmental factors modify cancer risks for women with these mutations. Direct evidence that this is the case has emerged in the past decade, through large-scale international collaborative efforts. Here, we describe the methodological challenges in the identification and characterisation of these risk-modifying factors, review the latest evidence on genetic and lifestyle/hormonal risk factors that modify breast and ovarian cancer risks for women with BRCA1 and BRCA2 mutations and outline the implications of these findings for cancer risk prediction. We also review the unresolved issues in this area of research and identify strategies of clinical implementation so that women with BRCA1 and BRCA2 mutations are no longer counselled on the basis of 'average' risk estimates.

Coexpression and expression quantitative trait loci analyses of the angiogenesis gene-gene interaction network in prostate cancer

BACKGROUND

Prostate cancer (PCa) shows a substantial clinical heterogeneity. The existing risk classification for PCa prognosis based on clinical factors is not sufficient. Although some biomarkers for PCa aggressiveness have been identified, their underlying functional mechanisms are still unclear. We previously reported a gene-gene interaction network associated with PCa aggressiveness based on single nucleotide polymorphism (SNP)-SNP interactions in the angiogenesis pathway. The goal of this study is to investigate potential functional evidence of the involvement of the genes in this gene-gene interaction network.

METHODS

A total of 11 angiogenesis genes were evaluated. The crosstalks among genes were examined through coexpression and expression quantitative trait loci (eQTL) analyses. The study population is 352 Caucasian PCa patients in the Cancer Genome Atlas (TCGA) study. The pairwise coexpressions among the genes of interest were evaluated using the Spearman coefficient. The eQTL analyses were tested using the Kruskal-Wallis test.

RESULTS

Among all within gene and 55 possible pairwise gene evaluations, 12 gene pairs and one gene (MMP16) showed strong coexpression or significant eQTL evidence. There are nine gene pairs with a strong correlation (Spearman correlation ≥0.6, P<1×10^-13). The top coexpressed gene pairs are EGFR-SP1 (r=0.73), ITGB3-HSPG2 (r=0.71), ITGB3-CSF1 (r=0.70), MMP16-FBLN5 (r=0.68), ITGB3-MMP16 (r=0.65), ITGB3-ROBO1 (r=0.62), CSF1-HSPG2 (r=0.61), CSF1-FBLN5 (r=0.6), and CSF1-ROBO1 (r=0.60). One cis-eQTL in MMP16 and five trans-eQTLs (MMP16-ESR1, ESR1-ROBO1, CSF1-ROBO1, HSPG2-ROBO1, and FBLN5-CSF1) are significant with a false discovery rate q value less than 0.2.

CONCLUSIONS

These findings provide potential biological evidence for the gene-gene interactions in this angiogenesis network. These identified interactions between the angiogenesis genes not only provide information for PCa etiology mechanism but also may serve as integrated biomarkers for building a risk prediction model for PCa aggressiveness.

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.

Stable intronic sequence RNAs (sisRNAs): a new layer of gene regulation

Upon splicing, introns are rapidly degraded. Hence, RNAs derived from introns are commonly deemed as junk sequences. However, the discoveries of intronic-derived small nucleolar RNAs (snoRNAs), small Cajal body associated RNAs (scaRNAs) and microRNAs (miRNAs) suggested otherwise. These non-coding RNAs are shown to play various roles in gene regulation. In this review, we highlight another class of intron-derived RNAs known as stable intronic sequence RNAs (sisRNAs). sisRNAs have been observed since the 1980 s; however, we are only beginning to understand their biological significance. Recent studies have shown or suggested that sisRNAs regulate their own host's gene expression, function as molecular sinks or sponges, and regulate protein translation. We propose that sisRNAs function as an additional layer of gene regulation in the cells.

A functional variant in HOXA11-AS, a novel long non-coding RNA, inhibits the oncogenic phenotype of epithelial ovarian cancer

The homeobox A (HOXA) region of protein-coding genes impacts female reproductive system embryogenesis and ovarian carcinogenesis. The 5-prime end of HOXA includes three long non-coding RNAs (lncRNAs) (HOXA10-AS, HOXA11-AS, and HOTTIP) that are underexplored in epithelial ovarian cancer (EOC). We evaluated whether common genetic variants in these lncRNAs are associated with EOC risk and/or have functional roles in EOC development. Using genome-wide association study data from 1,201 serous EOC cases and 2,009 controls, an exonic variant within HOXA11-AS, rs17427875 (A>T), was marginally associated with reduced serous EOC risk (OR = 0.88 (95% CI: 0.78-1.01, p = 0.06). Functional studies of ectopic expression of HOXA11-AS minor allele T in EOC cells showed decreased survival, proliferation, migration, and invasion compared to common allele A expression. Additionally, stable expression of HOXA11-AS minor allele T reduced primary tumor growth in mouse xenograft models to a greater extent than common allele A. Furthermore, HOXA11-AS expression levels were significantly lower in human EOC tumors than normal ovarian tissues (p < 0.05), suggesting that HOXA11-AS has a tumor suppressor function in EOC which may be enhanced by the T allele. These findings demonstrate for the first time a role for HOXA11-AS in EOC with effects that could be modified by germline variants.

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 -  7). One of the most significant signals (Pall histologies = 1.01 × 10 -  13;Pserous = 3.54 × 10 -  14) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r2 = 0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 -  5 > P≥5.0 ×10 -  7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 -  5; PSKAT-o = 9.23 × 10 -  4) and KRT13 (PAML = 1.67 × 10 -  4; PSKAT-o = 1.07 × 10 -  5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

Assessing the genetic architecture of epithelial ovarian cancer histological subtypes

Epithelial ovarian cancer (EOC) is one of the deadliest common cancers. The five most common types of disease are high-grade and low-grade serous, endometrioid, mucinous and clear cell carcinoma. Each of these subtypes present distinct molecular pathogeneses and sensitivities to treatments. Recent studies show that certain genetic variants confer susceptibility to all subtypes while other variants are subtype-specific. Here, we perform an extensive analysis of the genetic architecture of EOC subtypes. To this end, we used data of 10,014 invasive EOC patients and 21,233 controls from the Ovarian Cancer Association Consortium genotyped in the iCOGS array (211,155 SNPs). We estimate the array heritability (attributable to variants tagged on arrays) of each subtype and their genetic correlations. We also look for genetic overlaps with factors such as obesity, smoking behaviors, diabetes, age at menarche and height. We estimated the array heritabilities of high-grade serous disease ([Formula: see text] = 8.8 ± 1.1 %), endometrioid ([Formula: see text] = 3.2 ± 1.6 %), clear cell ([Formula: see text] = 6.7 ± 3.3 %) and all EOC ([Formula: see text] = 5.6 ± 0.6 %). Known associated loci contributed approximately 40 % of the total array heritability for each subtype. The contribution of each chromosome to the total heritability was not proportional to chromosome size. Through bivariate and cross-trait LD score regression, we found evidence of shared genetic backgrounds between the three high-grade subtypes: serous, endometrioid and undifferentiated. Finally, we found significant genetic correlations of all EOC with diabetes and obesity using a polygenic prediction approach.

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity, and Hormone-Related Risk Factors

BACKGROUND

Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women.

METHODS

We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed.

RESULTS

SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)).

CONCLUSIONS

We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions.

IMPACT

Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780-90. ©2016 AACR.

A targeted genetic association study of epithelial ovarian cancer susceptibility

BACKGROUND

Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci.

RESULTS

At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p <5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p< 3x10-6).

METHODS

A customized genotyping array was used to assess over 17,000 variants in coding, non-coding, regulatory, and known susceptibility regions in 4,973 EOC cases and 5,640 controls from 13 independent studies. Susceptibility for EOC overall and for select histotypes was evaluated using logistic regression adjusted for age, study site, and population substructure.

CONCLUSION

Given the novel variants identified within the 2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13 regions, larger follow-up genotyping studies, using imputation where necessary, are needed for fine-mapping and confirmation of low frequency variants that fall below statistical significance.

Evidence of a genetic link between endometriosis and ovarian cancer

OBJECTIVE

To evaluate whether endometriosis-associated genetic variation affects risk of ovarian cancer.

DESIGN

Pooled genetic analysis.

SETTING

University hospital.

PATIENT(S)

Genetic data from 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) from 41 ovarian cancer studies.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Endometriosis-associated genetic variation and ovarian cancer.

RESULT(S)

There was significant evidence of an association between endometriosis-related genetic variation and ovarian cancer risk, especially for the high-grade serous and clear cell histotypes. Overall we observed 15 significant burden statistics, which was three times more than expected.

CONCLUSION(S)

By focusing on candidate regions from a phenotype associated with ovarian cancer, we have shown a clear genetic link between endometriosis and ovarian cancer that warrants further follow-up. The functional significance of the identified regions and SNPs is presently uncertain, though future fine mapping and histotype-specific functional analyses may shed light on the etiologies of both gynecologic conditions.

Germline Mutations in the BRIP1, BARD1, PALB2, and NBN Genes in Women With Ovarian Cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, responsible for 13 000 deaths per year in the United States. Risk prediction based on identifying germline mutations in ovarian cancer susceptibility genes could have a clinically significant impact on reducing disease mortality.

METHODS

Next generation sequencing was used to identify germline mutations in the coding regions of four candidate susceptibility genes-BRIP1, BARD1, PALB2 and NBN-in 3236 invasive EOC case patients and 3431 control patients of European origin, and in 2000 unaffected high-risk women from a clinical screening trial of ovarian cancer (UKFOCSS). For each gene, we estimated the prevalence and EOC risks and evaluated associations between germline variant status and clinical and epidemiological risk factor information. All statistical tests were two-sided.

RESULTS

We found an increased frequency of deleterious mutations in BRIP1 in case patients (0.9%) and in the UKFOCSS participants (0.6%) compared with control patients (0.09%) (P = 1 x 10(-4) and 8 x 10(-4), respectively), but no differences for BARD1 (P = .39), NBN1 ( P = .61), or PALB2 (P = .08). There was also a difference in the frequency of rare missense variants in BRIP1 between case patients and control patients (P = 5.5 x 10(-4)). The relative risks associated with BRIP1 mutations were 11.22 for invasive EOC (95% confidence interval [CI] = 3.22 to 34.10, P = 1 x 10(-4)) and 14.09 for high-grade serous disease (95% CI = 4.04 to 45.02, P = 2 x 10(-5)). Segregation analysis in families estimated the average relative risks in BRIP1 mutation carriers compared with the general population to be 3.41 (95% CI = 2.12 to 5.54, P = 7×10(-7)).

CONCLUSIONS

Deleterious germline mutations in BRIP1 are associated with a moderate increase in EOC risk. These data have clinical implications for risk prediction and prevention approaches for ovarian cancer and emphasize the critical need for risk estimates based on very large sample sizes before genes of moderate penetrance have clinical utility in cancer prevention.

Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer

Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene.

Endometriosis as a risk factor for ovarian or endometrial cancer - results of a hospital-based case-control study

Background

No screening programs are available for ovarian or endometrial cancer. One reason for this is the low incidence of the conditions, resulting in low positive predictive values for tests, which are not very specific. One way of addressing this problem might be to use risk factors to define subpopulations with a higher incidence. The aim of this study was to investigate the extent to which a medical history of endometriosis can serve as a risk factor for ovarian or endometrial cancer.

Methods

In a hospital-based case–control analysis, the cases represented patients with endometrial or ovarian cancer who were participating in studies aimed at assessing the risk for these diseases. The controls were women between the age of 40 and 85 who were invited to take part via a newspaper advertisement. A total of 289 cases and 1016 controls were included. Using logistic regression models, it was tested whether self-reported endometriosis is a predictor of case–control status in addition to age, body mass index (BMI), number of pregnancies and previous oral contraceptive (OC) use.

Results

Endometriosis was reported in 2.1 % of the controls (n = 21) and 4.8 % of the cases (n = 14). Endometriosis was a relevant predictor for case–control status in addition to other predictive factors (OR 2.63; 95 % CI, 1.28 to 5.41).

Conclusion

This case–control study found that self-reported endometriosis may be a risk factor for endometrial or ovarian cancer in women between 40 and 85 years. There have been very few studies addressing this issue, and incorporating it into a clinical prediction model would require a more precise characterization of the risk factor of endometriosis.

The role of miRNAs in endometrial cancer

miRNAs are small noncoding RNAs that regulate gene expression at the post-transcriptional level. Since their discovery, miRNAs have been associated with every cell function including malignant transformation and metastasis. Endometrial cancer is the most common gynecologic malignancy. However, improvement should be made in interobserver agreement on histological typing and individualized therapeutic approaches. This article summarizes the role of miRNAs in endometrial cancer pathogenesis and treatment.

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations.

METHODS

We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).

RESULTS

Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.

CONCLUSION

We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.

IMPACT

Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.

Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.

Ichthyosis with confetti: clinics, molecular genetics and management

Ichthyosis with confetti (IWC) is an autosomal dominant congenital ichthyosis also known as ichthyosis variegata or congenital reticular ichthyosiform erythroderma. It manifests at birth with generalized ichthyosiform erythroderma or with a collodion baby picture. The erythrodermic and ichthyotic phenotype persists during life and its severity may modify. However, the hallmark of the disease is the appearance, in childhood or later in life, of healthy skin confetti-like spots, which increase in number and size with time. IWC is a very rare genodermatosis, with a prevalence <1/1,000,000 and only 40 cases reported worldwide. The most important associated clinical features include ear deformities, mammillae hypoplasia, palmoplantar keratoderma, hypertrichosis and ectropion. IWC is due to dominant negative mutations in the KRT10 and KRT1 genes, encoding for keratins 10 and keratin 1, respectively. In this context, healthy skin confetti-like spots represent “repaired” skin due to independent events of reversion of keratin gene mutations via mitotic recombination. In most cases, IWC clinical suspicion is delayed until the detection of white skin spots. Clinical features, which may represent hint to the diagnosis of IWC even before appearance of confetti-like spots, include ear and mammillae hypoplasia, the progressive development of hypertrichosis and, in some patients, of adherent verrucous plaques of hyperkeratosis. Altogether the histopathological finding of keratinocyte vacuolization and the nuclear staining for keratin 10 and keratin 1 by immunofluorescence are pathognomonic. Nevertheless, mutational analysis of KRT10 or KRT1 genes is at present the gold standard to confirm the diagnosis. IWC has to be differentiated mainly from congenital ichthyosiform erythroderma. Differential diagnosis also includes syndromic ichthyoses, in particular Netherton syndrome, and the keratinopathic ichthyoses. Most of reported IWC cases are sporadic, but familial cases with autosomal dominant mode of inheritance have been also described. Therefore, knowledge of the mutation is the only way to properly counsel the couples. No specific and satisfactory therapy is currently available for IWC. Like for other congenital ichthyoses, topical treatments (mainly emollients and keratolytics) are symptomatic and offer only temporary relief. Among systemic treatments, retinoids, in particular acitretin, improve disease symptoms in most patients. Although at present there is no curative therapy for ichthyoses, treatments have improved considerably over the years and the best therapy for each patient is always the result of both physician and patient efforts.

Limited evidence that cancer susceptibility regions are preferential targets for somatic mutation

BACKGROUND

Genome wide-association studies have successfully identified several hundred independent loci harboring common cancer susceptibility alleles that are distinct from the more than 110 cancer predisposition genes. The latter are generally characterized by disruptive mutations in coding genes that have been established as 'drivers' of cancer in large somatic sequencing studies. We set out to determine whether, similarly, common cancer susceptibility loci map to genes that have altered frequencies of mutation.

RESULTS

In our analysis of the intervals defined by the cancer susceptibility markers, we observed that cancer susceptibility regions have gene mutation frequencies comparable to background mutation frequencies. Restricting analyses to genes that have been determined to be pleiotropic across cancer types, genes affected by expression quantitative trait loci, or functional genes indicates that most cancer susceptibility genes classified into these subgroups do not display mutation frequencies that deviate from those expected. We observed limited evidence that cancer susceptibility regions that harbor common alleles with small estimated effect sizes are preferential targets for altered somatic mutation frequencies.

CONCLUSIONS

Our findings suggest a complex interplay between germline susceptibility and somatic mutation, underscoring the cumulative effect of common variants on redundant pathways as opposed to driver genes. Complex biological pathways and networks likely link these genetic features of carcinogenesis, particularly as they relate to distinct polygenic models for each cancer type.

Contribution of Germline Mutations in the RAD51B, RAD51C, and RAD51D Genes to Ovarian Cancer in the Population

PURPOSE

The aim of this study was to estimate the contribution of deleterious mutations in the RAD51B, RAD51C, and RAD51D genes to invasive epithelial ovarian cancer (EOC) in the population and in a screening trial of individuals at high risk of ovarian cancer.

PATIENTS AND METHODS

The coding sequence and splice site boundaries of the three RAD51 genes were sequenced and analyzed in germline DNA from a case-control study of 3,429 patients with invasive EOC and 2,772 controls as well as in 2,000 unaffected women who were BRCA1/BRCA2 negative from the United Kingdom Familial Ovarian Cancer Screening Study (UK_FOCSS) after quality-control analysis.

RESULTS

In the case-control study, we identified predicted deleterious mutations in 28 EOC cases (0.82%) compared with three controls (0.11%; P < .001). Mutations in EOC cases were more frequent in RAD51C (14 occurrences, 0.41%) and RAD51D (12 occurrences, 0.35%) than in RAD51B (two occurrences, 0.06%). RAD51C mutations were associated with an odds ratio of 5.2 (95% CI, 1.1 to 24; P = .035), and RAD51D mutations conferred an odds ratio of 12 (95% CI, 1.5 to 90; P = .019). We identified 13 RAD51 mutations (0.65%) in unaffected UK_FOCSS participants (RAD51C, n = 7; RAD51D, n = 5; and RAD51B, n = 1), which was a significantly greater rate than in controls (P < .001); furthermore, RAD51 mutation carriers were more likely than noncarriers to have a family history of ovarian cancer (P < .001).

CONCLUSION

These results confirm that RAD51C and RAD51D are moderate ovarian cancer susceptibility genes and suggest that they confer levels of risk of EOC that may warrant their use alongside BRCA1 and BRCA2 in routine clinical genetic testing.

DNA methylation changes in epithelial ovarian cancer histotypes

Survival after a diagnosis of ovarian cancer has not improved, and despite histological differences, treatment is similar for all cases. Understanding the molecular basis for ovarian cancer risk and prognosis is fundamental, and to this end much has been gleaned about genetic changes contributing to risk, and to a lesser extent, survival. There's considerable evidence for genetic differences between the four pathologically defined histological subtypes; however, the contribution of epigenetics is less well documented. In this report, we review alterations in DNA methylation in ovarian cancer, focusing on histological subtypes, and studies examining the roles of methylation in determining therapy response. As epigenetics is making its way into clinical care, we review the application of cell free DNA methylation to ovarian cancer diagnosis and care. Finally, we comment on recurrent limitations in the DNA methylation literature for ovarian cancer, which can and should be addressed to mature this field.

Regulatory T cells, inherited variation, and clinical outcome in epithelial ovarian cancer

The immune system constitutes one of the host factors modifying outcomes in ovarian cancer. Regulatory T cells (Tregs) are believed to be a major factor in preventing the immune response from destroying ovarian cancers. Understanding mechanisms that regulate Tregs in the tumor microenvironment could lead to the identification of novel targets aimed at reducing their influence. In this study, we used immunofluorescence-based microscopy to enumerate Tregs, total CD4 T cells, and CD8(+) cytotoxic T cells in fresh frozen tumors from over 400 patients with ovarian cancer (>80 % high-grade serous). We sought to determine whether Tregs were associated with survival and genetic variation in 79 genes known to influence Treg induction, trafficking, or function. We used Cox regression, accounting for known prognostic factors, to estimate hazard ratios (HRs) associated with T cell counts and ratios. We found that the ratios of CD8 T cells and total CD4 T cells to Tregs were associated with improved overall survival (CD8/Treg HR 0.84, p = 0.0089; CD4/Treg HR 0.88, p = 0.046) and with genetic variation in IL-10 (p = 0.0073 and 0.01, respectively). In multivariate analyses, the associations between the ratios and overall survival remained similar (IL-10 and clinical covariate-adjusted CD8/Treg HR 0.85, p = 0.031; CD4/Treg HR 0.87, p = 0.093), suggesting that this association was not driven by variation in IL-10. Thus, integration of novel tumor phenotyping measures with extensive clinical and genetic information suggests that the ratio of T cells to Tregs may be prognostic of outcome in ovarian cancer, regardless of inherited genotype in genes related to Tregs.

Genome-wide significant risk associations for mucinous ovarian carcinoma

Genome-wide association studies have identified several risk associations for ovarian carcinomas but not for mucinous ovarian carcinomas (MOCs). Our analysis of 1,644 MOC cases and 21,693 controls with imputation identified 3 new risk associations: rs752590 at 2q13 (P = 3.3 × 10(-8)), rs711830 at 2q31.1 (P = 7.5 × 10(-12)) and rs688187 at 19q13.2 (P = 6.8 × 10(-13)). We identified significant expression quantitative trait locus (eQTL) associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10(-4), false discovery rate (FDR) = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk-associated SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease.

Population distribution of lifetime risk of ovarian cancer in the United States

BACKGROUND

In U.S. women, lifetime risk of ovarian cancer is 1.37%, but some women are at a substantially lower or higher risk than this average.

METHODS

We have characterized the distribution of lifetime risk in the general population. Published data on the relative risks and their variances for five well-accepted risk and protective factors for ovarian cancer, oral contraceptive use, parity, tubal ligation, endometriosis, and first-degree family history of ovarian cancer in conjunction with a genetic risk score using genome-wide significant common, low penetrance variants were used. The joint distribution of these factors (i.e., risk/protective factor profiles) was derived using control data from four U.S. population-based studies, providing a broad representation of women in the United States.

RESULTS

A total of 214 combinations of risk/protective factors were observed, and the lifetime risk estimates ranged from 0.35% [95% confidence interval (CI), 0.29-0.42] to 8.78% (95% CI, 7.10-10.9). Among women with lifetime risk ranging from 4% to 9%, 73% had no family history of ovarian cancer; most of these women had a self-reported history of endometriosis.

CONCLUSIONS

Profiles including the known modifiable protective factors of oral contraceptive use and tubal ligation were associated with a lower lifetime risk of ovarian cancer. Oral contraceptive use and tubal ligation were essentially absent among the women at 4% to 9% lifetime risk.

IMPACT

This work demonstrates that there are women in the general population who have a much higher than average lifetime risk of ovarian cancer. Preventive strategies are available. Should effective screening become available, higher than average risk women can be identified.

Evaluating the ovarian cancer gonadotropin hypothesis: a candidate gene study

OBJECTIVE

Ovarian cancer is a hormone-related disease with a strong genetic basis. However, none of its high-penetrance susceptibility genes and GWAS-identified variants to date are known to be involved in hormonal pathways. Given the hypothesized etiologic role of gonadotropins, an assessment of how variability in genes involved in the gonadotropin signaling pathway impacts disease risk is warranted.

METHODS

Genetic data from 41 ovarian cancer study sites were pooled and unconditional logistic regression was used to evaluate whether any of the 2185 SNPs from 11 gonadotropin signaling pathway genes was associated with ovarian cancer risk. A burden test using the admixture likelihood (AML) method was also used to evaluate gene-level associations.

RESULTS

We did not find any genome-wide significant associations between individual SNPs and ovarian cancer risk. However, there was some suggestion of gene-level associations for four gonadotropin signaling pathway genes: INHBB (p=0.045, mucinous), LHCGR (p=0.046, high-grade serous), GNRH (p=0.041, high-grade serous), and FSHB (p=0.036, overall invasive). There was also suggestive evidence for INHA (p=0.060, overall invasive).

CONCLUSIONS

Ovarian cancer studies have limited sample numbers, thus fewer genome-wide susceptibility alleles, with only modest associations, have been identified relative to breast and prostate cancers. We have evaluated the majority of ovarian cancer studies with biological samples, to our knowledge, leaving no opportunity for replication. Using both our understanding of biology and powerful gene-level tests, we have identified four putative ovarian cancer loci near INHBB, LHCGR, GNRH, and FSHB that warrant a second look if larger sample sizes and denser genotype chips become available.

Identification of six new susceptibility loci for invasive epithelial ovarian cancer

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.

PLEKHM1 regulates autophagosome-lysosome fusion through HOPS complex and LC3/GABARAP proteins

The lysosome is the final destination for degradation of endocytic cargo, plasma membrane constituents, and intracellular components sequestered by macroautophagy. Fusion of endosomes and autophagosomes with the lysosome depends on the GTPase Rab7 and the homotypic fusion and protein sorting (HOPS) complex, but adaptor proteins that link endocytic and autophagy pathways with lysosomes are poorly characterized. Herein, we show that Pleckstrin homology domain containing protein family member 1 (PLEKHM1) directly interacts with HOPS complex and contains a LC3-interacting region (LIR) that mediates its binding to autophagosomal membranes. Depletion of PLEKHM1 blocks lysosomal degradation of endocytic (EGFR) cargo and enhances presentation of MHC class I molecules. Moreover, genetic loss of PLEKHM1 impedes autophagy flux upon mTOR inhibition and PLEKHM1 regulates clearance of protein aggregates in an autophagy- and LIR-dependent manner. PLEKHM1 is thus a multivalent endocytic adaptor involved in the lysosome fusion events controlling selective and nonselective autophagy pathways.

Role of microRNAs in cancers of the female reproductive tract: insights from recent clinical and experimental discovery studies

microRNAs (miRNAs) are small RNA molecules that represent the top of the pyramid of many tumorigenesis cascade pathways as they have the ability to affect multiple, intricate, and still undiscovered downstream targets. Understanding how miRNA molecules serve as master regulators in these important networks involved in cancer initiation and progression open up significant innovative areas for therapy and diagnosis that have been sadly lacking for deadly female reproductive tract cancers. This review will highlight the recent advances in the field of miRNAs in epithelial ovarian cancer, endometrioid endometrial cancer and squamous-cell cervical carcinoma focusing on studies associated with actual clinical information in humans. Importantly, recent miRNA profiling studies have included well-characterized clinical specimens of female reproductive tract cancers, allowing for studies correlating miRNA expression with clinical outcomes. This review will summarize the current thoughts on the role of miRNA processing in unique miRNA species present in these cancers. In addition, this review will focus on current data regarding miRNA molecules as unique biomarkers associated with clinically significant outcomes such as overall survival and chemotherapy resistance. We will also discuss why specific miRNA molecules are not recapitulated across multiple studies of the same cancer type. Although the mechanistic contributions of miRNA molecules to these clinical phenomena have been confirmed using in vitro and pre-clinical mouse model systems, these studies are truly only the beginning of our understanding of the roles miRNAs play in cancers of the female reproductive tract. This review will also highlight useful areas for future research regarding miRNAs as therapeutic targets in cancers of the female reproductive tract.

Genomic alterations as mediators of miRNA dysregulation in ovarian cancer

Ovarian cancer is the fifth most common cause of cancer death in women worldwide. Serous epithelial ovarian cancer (SEOC) is the most common and aggressive histological subtype. Widespread genomic alterations go hand-in-hand with aberrant DNA damage signaling and are a hallmark of high-grade SEOC. MicroRNAs (miRNAs) are a class of small noncoding RNA molecules that are nonrandomly distributed in the genome. They are frequently located in chromosomal regions susceptible to copy number variation (CNV) associated with malignancy that can influence their expression. Widespread changes in miRNA expression have been reported in multiple cancer types including ovarian cancer. This review examines CNV and single nucleotide polymorphisms, two common types of genomic alterations that occur in ovarian cancer, in the context of their influence on the expression of miRNA and the ability of miRNA to bind to and regulate their target genes. This includes genes encoding proteins involved in DNA repair and the maintenance of genomic stability. Improved understanding of mechanisms of miRNA dysregulation and the role of miRNA in ovarian cancer will provide further insight into the pathogenesis and treatment of this disease.

Family based genome-wide copy number scan identifies complex rearrangements at 17q21.31 in dyslexics

Developmental dyslexia (DD) is a complex heritable disorder with unexpected difficulty in learning to read and spell despite adequate intelligence, education, environment, and normal senses. We performed genome-wide screening for copy number variations (CNVs) in 10 large Indian dyslexic families using Affymetrix Genome-Wide Human SNP Array 6.0. Results revealed the complex genomic rearrangements due to one non-contiguous deletion and five contiguous micro duplications and micro deletions at 17q21.31 region in three dyslexic families. CNVs in this region harbor the genes KIAA1267, LRRC37A, ARL17A/B, NSFP1, and NSF. The CNVs in case 1 and case 2 at this locus were found to be in homozygous state and case 3 was a de novo CNV. These CNVs were found with at least one CNV having a common break and end points in the parents. This cluster of genes containing NSF is implicated in learning, cognition, and memory, though not formally associated with dyslexia. Molecular network analysis of these and other dyslexia related module genes suggests NSF and other genes to be associated with cellular/vesicular membrane fusion and synaptic transmission. Thus, we suggest that NSF in this cluster would be the nearest gene responsible for the learning disability phenotype.

The contribution of deleterious germline mutations in BRCA1, BRCA2 and the mismatch repair genes to ovarian cancer in the population

The aim of this study was to estimate the contribution of deleterious mutations in BRCA1, BRCA2, MLH1, MSH2, MSH6 and PMS2 to invasive epithelial ovarian cancer (EOC) in the population. The coding sequence and splice site boundaries of all six genes were amplified in germline DNA from 2240 invasive EOC cases and 1535 controls. Barcoded fragment libraries were sequenced using the Illumina GAII or HiSeq and sequence data for each subject de-multiplexed prior to interpretation. GATK and Annovar were used for variant detection and annotation. After quality control 2222 cases (99.2%) and 1528 controls (99.5%) were included in the final analysis. We identified 193 EOC cases (8.7%) carrying a deleterious mutation in at least one gene compared with 10 controls (0.65%). Mutations were most frequent in BRCA1 and BRCA2, with 84 EOC cases (3.8%) carrying a BRCA1 mutation and 94 EOC cases (4.2%) carrying a BRCA2 mutation. The combined BRCA1 and BRCA2 mutation prevalence was 11% in high-grade serous disease. Seventeen EOC cases carried a mutation in a mismatch repair gene, including 10 MSH6 mutation carriers (0.45%) and 4 MSH2 mutation carriers (0.18%). At least 1 in 10 women with high-grade serous EOC has a BRCA1 or BRCA2 mutation. The development of next generation sequencing technologies enables rapid mutation screening for multiple susceptibility genes at once, suggesting that routine clinical testing of all incidence cases should be considered.

Genome-wide association study identifies new susceptibility loci for epithelial ovarian cancer in Han Chinese women

Ovarian cancer is the leading cause of death from gynaecological malignancies worldwide. Here we perform a three-stage genome-wide association study (GWAS) in Han Chinese women to identify risk genetic variants for epithelial ovarian cancer (EOC). We scan 900,015 single-nucleotide polymorphisms (SNPs) in 1,057 EOC cases and 1,191 controls in stage I, and replicate 41 SNPs (P(meta)<10(-4)) in 960 EOC cases and 1,799 controls (stage II), and an additional 492 EOC cases and 1,004 controls (stage III). Finally, we identify two EOC susceptibility loci at 9q22.33 (rs1413299 in COL15A1, P(meta) = 1.88 × 10(-8)) and 10p11.21 (rs1192691 near ANKRD30A, P(meta) = 2.62 × 10(-8)), and two consistently replicated loci at 12q14.2 (rs11175194 in SRGAP1, P(meta) = 1.14 × 10(-7)) and 9q34.2 (rs633862 near ABO and SURF6, P(meta) = 8.57 × 10(-7)) (P<0.05 in all three stages). These results may advance our understanding of genetic susceptibility to EOC.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis

BACKGROUND

Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan.

RESULTS

We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations.

CONCLUSIONS

We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Cross-cancer pleiotropic analysis of endometrial cancer: PAGE and E2C2 consortia

Genome-wide association studies (GWAS) have identified a large number of cancer-associated single nucleotide polymorphisms (SNPs), several of which have been associated with multiple cancer sites suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesized that SNPs associated with other cancers may be additionally associated with endometrial cancer. We examined 213 SNPs previously associated with 14 other cancers for their associations with endometrial cancer in 3758 endometrial cancer cases and 5966 controls of European ancestry from two consortia: Population Architecture Using Genomics and Epidemiology and the Epidemiology of Endometrial Cancer Consortium. Study-specific logistic regression estimates adjusted for age, body mass index and the most significant principal components of genetic ancestry were combined using fixed-effect meta-analysis to evaluate the association between each SNP and endometrial cancer risk. A Bonferroni-corrected P value of 2.35×10(-4) was used to determine statistical significance of the associations. SNP rs7679673, ~6.3kb upstream of TET2 and previously reported to be associated with prostate cancer risk, was associated with endometrial cancer risk in the direction opposite to that for prostate cancer [meta-analysis odds ratio = 0.87 (per copy of the C allele), 95% confidence interval = 0.81, 0.93; P = 7.37×10(-5)] with no evidence of heterogeneity across studies (P heterogeneity = 0.66). This pleiotropic analysis is the first to suggest TET2 as a susceptibility locus for endometrial cancer.

Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA

Epithelial ovarian cancer (EOC) is a heterogeneous cancer with both genetic and environmental risk factors. Variants influencing the risk of developing the less-common EOC subtypes have not been fully investigated. We performed a genome-wide association study (GWAS) of EOC according to subtype by pooling genomic DNA from 545 cases and 398 controls of European descent, and testing for allelic associations. We evaluated for replication 188 variants from the GWAS [56 variants for mucinous, 55 for endometrioid and clear cell, 53 for low-malignant potential (LMP) serous, and 24 for invasive serous EOC], selected using pre-defined criteria. Genotypes from 13,188 cases and 23,164 controls of European descent were used to perform unconditional logistic regression under the log-additive genetic model; odds ratios (OR) and 95 % confidence intervals are reported. Nine variants tagging six loci were associated with subtype-specific EOC risk at P < 0.05, and had an OR that agreed in direction of effect with the GWAS results. Several of these variants are in or near genes with a biological rationale for conferring EOC risk, including ZFP36L1 and RAD51B for mucinous EOC (rs17106154, OR = 1.17, P = 0.029, n = 1,483 cases), GRB10 for endometrioid and clear cell EOC (rs2190503, P = 0.014, n = 2,903 cases), and C22orf26/BPIL2 for LMP serous EOC (rs9609538, OR = 0.86, P = 0.0043, n = 892 cases). In analyses that included the 75 GWAS samples, the association between rs9609538 (OR = 0.84, P = 0.0007) and LMP serous EOC risk remained statistically significant at P < 0.0012 adjusted for multiple testing. Replication in additional samples will be important to verify these results for the less-common EOC subtypes.

Large-scale evaluation of common variation in regulatory T cell-related genes and ovarian cancer outcome

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 genomics and inherited risk

Next-generation sequencing (NGS) has enabled whole-exome and whole-genome sequencing of tumors for causative mutations, allowing for more accurate targeting of therapies. In the process of sequencing the tumor, comparisons to the germline genome may identify variants associated with susceptibility to cancer as well as other hereditary diseases. Already, the combination of massively parallel sequencing and selective capture approaches has facilitated efficient simultaneous genetic analysis (multiplex testing) of large numbers of candidate genes. As the field of oncology incorporates NGS approaches into tumor and germline analyses, it has become clear that the ability to achieve high-throughput genotyping surpasses our current ability to interpret and appropriately apply the vast amounts of data generated from such technologies. A review of the current state of knowledge of rare and common genetic variants associated with cancer risk or treatment outcome reveals significant progress, as well as a number of challenges associated with the clinical translation of these discoveries. The combined efforts of oncologists, genetic counselors, and cancer geneticists will be required to drive the paradigm shift toward personalized or precision medicine and to ensure the incorporation of NGS technologies into the practice of preventive oncology.

Clinical characteristics of ovarian cancer classified by BRCA1, BRCA2, and RAD51C status

We evaluated homologous recombination deficient (HRD) phenotypes in epithelial ovarian cancer (EOC) considering BRCA1, BRCA2, and RAD51C in a large well-annotated patient set. We evaluated EOC patients for germline deleterious mutations (n = 899), somatic mutations (n = 279) and epigenetic alterations (n = 482) in these genes using NGS and genome-wide methylation arrays. Deleterious germline mutations were identified in 32 (3.6%) patients for BRCA1, in 28 (3.1%) for BRCA2 and in 26 (2.9%) for RAD51C. Ten somatically sequenced patients had deleterious alterations, six (2.1%) in BRCA1 and four (1.4%) in BRCA2. Fifty two patients (10.8%) had methylated BRCA1 or RAD51C. HRD patients with germline or somatic alterations in any gene were more likely to be high grade serous, have an earlier diagnosis age and have ovarian and/or breast cancer family history. The HRD phenotype was most common in high grade serous EOC. Identification of EOC patients with an HRD phenotype may help tailor specific therapies.

Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer

BACKGROUND

Both genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and the extent to which they interact to impact disease risk. In the present study, we aimed to gain insight into this relationship by identifying DNA methylation marks that are candidate mediators of ovarian cancer genetic risk.

METHODS

We used 214 cases and 214 age-matched controls from the Mayo Clinic Ovarian Cancer Study. Pretreatment, blood-derived DNA was profiled for genome-wide methylation (Illumina Infinium HumanMethylation27 BeadArray) and single nucleotide polymorphisms (SNPs, Illumina Infinium HD Human610-Quad BeadArray). The Causal Inference Test (CIT) was implemented to distinguish CpG sites that mediate genetic risk, from those that are consequential or independently acted on by genotype.

RESULTS

Controlling for the estimated distribution of immune cells and other key covariates, our initial epigenome-wide association analysis revealed 1,993 significantly differentially methylated CpGs that between cases and controls (FDR, q < 0.05). The relationship between methylation and case-control status for these 1,993 CpGs was found to be highly consistent with the results of previously published, independent study that consisted of peripheral blood DNA methylation signatures in 131 pretreatment cases and 274 controls. Implementation of the CIT test revealed 17 CpG/SNP pairs, comprising 13 unique CpGs and 17 unique SNPs, which represent potential methylation-mediated relationships between genotype and EOC risk. Of these 13 CpGs, several are associated with immune related genes and genes that have been previously shown to exhibit altered expression in the context of cancer.

CONCLUSIONS

These findings provide additional insight into EOC etiology and may serve as novel biomarkers for EOC susceptibility.

Ovarian cancer screening--current status, future directions

Evidence of a mortality benefit continues to elude ovarian cancer (OC) screening. Data from the US Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial which used a screening strategy incorporating CA125 cut-off and transvaginal ultrasound has not shown mortality benefit. The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) is using the Risk of Ovarian Cancer (ROC) time series algorithm to interpret CA125, which has shown an encouraging sensitivity and specificity however the mortality data will only be available in 2015. The article explores the impact of growing insights into disease aetiology and evolution and biomarker discovery on future screening strategies. A better understanding of the target lesion, improved design of biomarker discovery studies, a focus on detecting low volume disease using cancer specific markers, novel biospecimens such as cervical cytology and targeted imaging and use of time series algorithms for interpreting markers profile suggests that a new era in screening is underway.

In vitro three-dimensional modeling of fallopian tube secretory epithelial cells

Background

Fallopian tube secretory epithelial cells (FTSECs) have been implicated as a cell-of-origin for high-grade serous epithelial ovarian cancer. However, there are relatively few in vitro models of this tissue type available for use in studies of FTSEC biology and malignant transformation. In vitro three-dimensional (3D) cell culture models aim to recreate the architecture and geometry of tissues in vivo and restore the complex network of cell-cell/cell-matrix interactions that occur throughout the surface of the cell membrane.

Results

We have established and characterized 3D spheroid culture models of primary FTSECs. FTSEC spheroids contain central cores of hyaline matrix surrounded by mono- or multi-layer epithelial sheets. We found that 3D culturing alters the molecular characteristics of FTSECs compared to 2D cultures of the same cells. Gene expression profiling identified more than a thousand differentially expressed genes between 3D and 2D cultures of the same FTSEC lines. Pathways significantly under-represented in 3D FTSEC cultures were associated with cell cycle progression and DNA replication. This was also reflected in the reduced proliferative indices observed in 3D spheroids stained for the proliferation marker MIB1. Comparisons with gene expression profiles of fresh fallopian tube tissues revealed that 2D FTSEC cultures clustered with follicular phase tubal epithelium, whereas 3D FTSEC cultures clustered with luteal phase samples.

Conclusions

This 3D model of fallopian tube secretory epithelial cells will advance our ability to study the underlying biology and etiology of fallopian tube tissues and the pathogenesis of high-grade serous epithelial ovarian cancer.

Public health implications from COGS and potential for risk stratification and screening

The PHG Foundation led a multidisciplinary program, which used results from COGS research identifying genetic variants associated with breast, ovarian and prostate cancers to model risk-stratified prevention for breast and prostate cancers. Implementing such strategies would require attention to the use and storage of genetic information, the development of risk assessment tools, new protocols for consent and programs of professional education and public engagement.