The Effects of Common Genetic Variants in Oncogenes on Ovarian Cancer Survival

The effectiveness of CA125 and HE4 as clinical prognostic markers in epithelial ovarian cancer patients with BRCA mutation

OBJECTIVE

To investigate the efficacy of cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) in predicting survival outcomes based on breast cancer gene (BRCA) mutational status in epithelial ovarian cancer.

METHODS

Medical records of 448 patients diagnosed with epithelial ovarian cancer at a single tertiary institution in Korea were retrospectively analyzed. Area under the curve, sensitivity, specificity, and accuracy were assessed using the CA125 and HE4 values after surgery and 3 cycles of chemotherapy to predict 1-year survival based on the BRCA mutational status. Kaplan-Meier analysis was used to obtain progression-free and overall survival to evaluate CA125 and HE4 effectiveness in predicting survival outcomes.

RESULTS

A total of 423 patients were analyzed, including 180 (42.6%) who underwent interval debulking surgery (IDS) and 243 (57.4%) who underwent primary debulking surgery (PDS). BRCA mutations were observed in 37 (15.2%) and 44 (22.4%) patients in the PDS and IDS groups, respectively. CA125 and HE4 normalization demonstrated the highest specificity in patients with or without BRCA mutations, with specificities of 97.1% and 99.1% in the PDS group and 78.6% and 86.2% in the IDS group, respectively. Normalizing HE4 alone may be an effective prognostic marker, with an area under the curve of 0.774 and specificity of 75.0%, in patients with BRCA mutations.

CONCLUSION

Normalizing both biomarkers emerged as the most effective predictive marker for the 1-year recurrence rate, regardless of BRCA mutational status. A negative HE4 value can be a useful predictor for 1-year recurrence-free survival in patients with BRCA mutations.

The Performance of HE4 Alone and in Combination with CA125 for the Detection of Ovarian Cancer in an Enriched Primary Care Population

Human epididymis 4 (HE4) is a promising ovarian cancer biomarker, but it has not been evaluated in primary care. In this prospective observational study, we investigated the diagnostic accuracy of HE4 alone and in combination with CA125 for the detection of ovarian cancer in symptomatic women attending primary care. General practitioner (GP)-requested CA125 samples were tested for HE4 at a large teaching hospital in Manchester, and cancer outcomes were tracked for 12 months. We found a low incidence of ovarian cancer in primary care; thus, the cohort was enriched with pre-surgical samples from 81 ovarian cancer patients. The Risk of Ovarian Malignancy Algorithm (ROMA) was calculated using age (</>51) as a surrogate for menopause. Conventional diagnostic accuracy metrics were determined. A total of 1229 patients were included; 82 had ovarian cancer. Overall, ROMA performed best (AUC-0.96 (95%CI: 0.94−0.98, p = <0.001)). In women under 50 years, the combination of CA125 and HE4 (either marker positive) was superior (sensitivity: 100% (95%CI: 81.5−100.0), specificity: 80.1% (95%CI 76.7−83.1)). In women over 50, ROMA performed best (sensitivity: 84.4% (95%CI: 73.1−92.2), specificity: 87.2% (95%CI 84.1−90)). HE4 and ROMA may improve ovarian cancer detection in primary care, particularly for women under 50 years, in whom diagnosis is challenging. Validation in a larger primary care cohort is required.

Genetic epidemiology of ovarian cancer and prospects for polygenic risk prediction

Epithelial ovarian cancer (EOC) is a heterogeneous disease with a major heritable component. The different histotypes of invasive disease - high grade serous, clear cell, endometrioid and mucinous - are associated with different underlying genetic susceptibility and epidemiological and lifestyle risk factors, all of which contribute to the different biology and clinical characteristics of each histotype. A combination of familial and population based sequencing studies, and genome wide association studies (GWAS) have identified a range of genetic susceptibility alleles for EOC comprising rare but highly penetrant genes (e.g. BRCA1, BRCA2) that are responsible for familial clustering of ovarian cancer cases; more moderate penetrance susceptibility genes (e.g. BRIP1, RAD51C/D, MSH6); and multiple common but low penetrance susceptibility alleles identified by GWAS. Identifying genetic risk alleles for ovarian cancer has had a significant impact on disease prevention strategies; for example it is now routine clinical practice for individuals with germline BRCA1 and BRCA2 mutations to undergo risk reducing salpingo-oophorectomy. Because ovarian cancers are commonly diagnosed at a late clinical stage when the prognosis is poor, the continued development of genetic risk prediction and prevention strategies will represent an important approach to reduce mortality due to ovarian cancer. Advances in genomics technologies that enable more high-throughput genetic testing, combined with research studies that identify additional EOC risk alleles will likely provide further opportunities to establish polygenic risk prediction approaches, based on combinations of rare high/moderate penetrance susceptibility genes and common, low penetrance susceptibility alleles. This article reviews the current literature describing the genetic and epidemiological components of ovarian cancer risk, and discusses both the opportunities and challenges in using this information for clinical risk prediction and prevention.

Genetic variants as ovarian cancer first-line treatment hallmarks: A systematic review and meta-analysis

BACKGROUND

The potential predictive value of genetic polymorphisms in ovarian cancer first-line treatment is inconsistently reported. We aimed to review ovarian cancer pharmacogenetic studies to update and summarize the available data and to provide directions for further research.

METHODS

A systematic review followed by a meta-analysis was conducted on cohort studies assessing the involvement of genetic polymorphisms in ovarian cancer first-line treatment response retrieved through a MEDLINE database search by November 2016. Studies were pooled and summary estimates and 95% confidence intervals (CI) were calculated using random or fixed-effects models as appropriate.

RESULTS

One hundred and forty-two studies gathering 106871 patients were included. Combined data suggested that GSTM1-null genotype patients have a lower risk of death compared to GSTM1-wt carriers, specifically in advanced stages (hazard ratio (HR), 0.68; 95% CI, 0.48-0.97) and when submitted to platinum-based chemotherapy (aHR, 0.61; 95% CI, 0.39-0.94). ERCC1 rs11615 and rs3212886 might have also a significant impact in treatment outcome (aHR, 0.67; 95% CI, 0.51-0.89; aHR, 1.28; 95% CI, 1.01-1.63, respectively). Moreover, ERCC2 rs13181 and rs1799793 showed a distinct ethnic behavior (Asians: aHR, 1.41; 95% CI, 0.80-2.49; aHR, 1.07; 95% CI, 0.62-1.86; Caucasians: aHR, 0.10; 95% CI, 0.01-0.96; aHR, 0.18; 95% CI, 0.05-0.68, respectively).

CONCLUSION(S)

The definition of integrative predictive models should encompass genetic information, especially regarding GSTM1 homozygous deletion. Justifying additional pharmacogenetic investigation are variants in ERCC1 and ERCC2, which highlight the DNA Repair ability to ovarian cancer prognosis. Further knowledge could aid to understand platinum-treatment failure and to tailor chemotherapy strategies.

Dysregulation of Aromatase in Breast, Endometrial, and Ovarian Cancers: An Overview of Therapeutic Strategies

Aromatase is the rate-limiting enzyme in the biosynthesis of estrogens, which play crucial roles on a spectrum of developmental and physiological processes. The biological actions of estrogens are classically mediated by binding to two estrogen receptors (ERs), ERα and ERβ. Encoded by the cytochrome P450, family 19, subfamily A, polypeptide 1 (CYP19A1) gene, aromatase is expressed in a wide variety of tissues, as well as benign and malignant tumors, and is regulated in a pathway- and tissue-specific manner. Overexpression of aromatase, leading to elevated systemic levels of estrogen, is unequivocally linked to the pathogenesis and growth of a number malignancies, including breast, endometrium, and ovarian cancers. Aromatase inhibitors (AIs) are routinely used to treat estrogen-dependent breast cancers in postmenopausal women; however, their roles in endometrial and ovarian cancers remain obscure. While AI therapy is effective in hormone sensitive cancers, they diminish estrogen production throughout the body and, thus, generate undesirable side effects. Despite the effectiveness of AI therapy, resistance to endocrine therapy remains a major concern and is the leading cause of cancer death. Considerable advances, toward mitigating these issues, have evolved in conjunction with a number of histone deacetylase (HDAC) inhibitors for countering an assortment of diseases and cancers, including the aforesaid malignancies. HDACs are a family of enzymes that are frequently dysregulated in human tumors. This chapter will discuss the current understanding of aberrant regulation and expression of aromatase in breast, endometrial, and ovarian cancers, and potential therapeutic strategies for prevention and treatment of these life-threatening diseases.

Epithelial-Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk

Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07-1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69-0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.

Lentivirus-Mediated RNAi silencing targeting ERCC1 reverses cisplatin resistance in cisplatin-resistant ovarian carcinoma cell line

The aim of the study was to investigate the potential mechanisms that interferencing of excision repair cross-complementing gene 1 (ERCC1) mediated by lentiviral vector in cisplatin-resistant ovarian cancer SKOV3/DDP cells. The human platinum-resistant ovarian carcinoma cell line SKOV3/DDP was transfected by pLVX-shRNA lentivirus. Interference efficiency for ERCC1 by lentiviruses transfection was detected by real-time polymerase chain reaction and western blot assay. CCK-8 assay was used for cell proliferation on cell resistance after transfection with ERCC1. Effects of cell apoptosis and cell cycles were detected by flow cytometry. The expression levels of ERCC1 were significantly suppressed in SKOV3/DDP cells after stably transfecting with shERCC1-recombinant plasmid. The results of cell viability assay demonstrated that interference with ERCC1 gene increased the sensitivity of SKOV3/DDP cells to cisplatin (p<0.01). ERCC1 gene-specific silencing promoted cell apoptosis of SKOV3/DDP cells (p<0.01) detected by flow cytometry. Cell cycle analysis results showed that the proportion of cells in G1 and S phase decreased, while the proportion of G2 phase cells increased in ERCC1-silencing cells. The differences were statistically significant (p<0.01), which demonstrated that stable interferencing with ERCC1 induced the cells arrest in G2 phase after being treated by DDP and silencing the expression of ERCC1 inhibited cell proliferation by preventing the progression of cell mitosis. ERCC1 gene silencing effectively reversed SKOV3/DDP cell resistance to cisplatin and increased sensitivity to cisplatin resistance in cisplatin-resistant ovarian cancer cells. Interference of ERCC1 promoted the apoptosis of SKOV3/DDP cells and prevented cell mitosis by inducing G0/G1 phase arrest. Thus, ERCC1 could be a potential therapeutic target for the therapy of cisplatin-resistant ovarian cancer and it would provide new ideas for epigenetic therapy of drug-resistant epithelial ovarian cancer.

Vibrational biospectroscopy coupled with multivariate analysis extracts potentially diagnostic features in blood plasma/serum of ovarian cancer patients

Despite numerous advances in "omics" research, early detection of ovarian cancer still remains a challenge. The aim of this study was to determine whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) or Raman spectroscopy could characterise alterations in the biomolecular signatures of human blood plasma/serum obtained from ovarian cancer patients compared to non-cancer controls. Blood samples isolated from ovarian cancer patients (n = 30) and healthy controls (n = 30) were analysed using ATR-FTIR spectroscopy. For comparison, a smaller cohort of samples (n = 8) were analysed using an InVia Renishaw Raman spectrometer. Resultant spectra were pre-processed prior to being inputted into principal component analysis (PCA) and linear discriminant analysis (LDA). Statistically significant differences (P < 0.001) were observed between spectra of ovarian cancer versus control subjects for both biospectroscopy methods. Using a support vector machine classifier for Raman spectra of blood plasma, a diagnostic accuracy of 74% was achieved, while the same classifier showed 93.3% accuracy for IR spectra of blood plasma. These observations suggest that a biospectroscopy approach could be applied to identify spectral alterations associated with the presence of insidious ovarian cancer.

Genotyping of stathmin and its association with clinical factors and survival in patients with ovarian cancer

Stathmin is closely correlated with the progression and prognosis of a number of types of human cancer. The present study analyzed the associations between genetic variations in the stathmin gene and clinical outcomes of ovarian cancer. A total of 178 patients with epithelial ovarian cancer were treated with cytoreductive surgery followed by platinum-based chemotherapy. DNA was extracted from fresh tumor samples obtained during surgery. A total of 32 DNA samples were selected randomly for resequencing of the stathmin gene. Tag single nucleotide polymorphisms (SNPs) were identified based on the haplotype model as analyzed by PolyPhred software. Direct sequencing was employed in the genotyping of stathmin in 178 cases. A total of 10 nucleotide variations in stathmin were identified, of which 3 high-frequency variations were known SNPs from databases and 7 were new variations with low frequencies. The tag SNPs rs159531 and rs11376635 were selected from the linkage disequilibrium block of the gene to genotype stathmin in 178 cases. The distribution of the rs159531 genotype in ovarian cancer was 52.8% C/C, 35.4% C/T and 11.2% T/T. The distribution of the rs11376635 genotype in ovarian cancer was 32.0% G/G, 48.3% G/-, 18.5% -/-. The main haplotypes calculated by phase2.0 software were 55.6% CG, 27.8% T-, 15.4% C- and 1.2% TG. However, no associations between the stathmin genotype or haplotype and the outcomes in patients with ovarian cancer were observed. The stathmin genotype and haplotype were not associated with the phenotype of patients with ovarian cancer.

Fourier-transform infrared spectroscopy coupled with a classification machine for the analysis of blood plasma or serum: a novel diagnostic approach for ovarian cancer

Currently available screening tests do not deliver the required sensitivity and specificity for accurate diagnosis of ovarian or endometrial cancer. Infrared (IR) spectroscopy of blood plasma or serum is a rapid, versatile, and relatively non-invasive approach which could characterize biomolecular alterations due to cancer and has potential to be utilized as a screening or diagnostic tool. In the past, no such approach has been investigated for its applicability in screening and/or diagnosis of gynaecological cancers. We set out to determine whether attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy coupled with a proposed classification machine could be applied to IR spectra obtained from plasma and serum for accurate class prediction (cancer vs. normal). Plasma and serum samples were obtained from ovarian cancer cases (n = 30), endometrial cancer cases (n = 30) and non-cancer controls (n = 30), and subjected to ATR-FTIR spectroscopy. Four derived datasets were processed to estimate the real-world diagnosis of ovarian and endometrial cancer. Classification results for ovarian cancer were remarkable (up to 96.7%), whereas endometrial cancer was classified with a relatively high accuracy (up to 81.7%). The results from different combinations of feature extraction and classification methods, and also classifier ensembles, were compared. No single classification system performed best for all different datasets. This demonstrates the need for a framework that can accommodate a diverse set of analytical methods in order to be adaptable to different datasets. This pilot study suggests that ATR-FTIR spectroscopy of blood is a robust tool for accurate diagnosis, and carries the potential to be utilized as a screening test for ovarian cancer in primary care settings. The proposed classification machine is a powerful tool which could be applied to classify the vibrational spectroscopy data of different biological systems (e.g., tissue, urine, saliva), with their potential application in clinical practice.

Detection of the BRAF V600E mutation in serous ovarian tumors: a comparative analysis of immunohistochemistry with a mutation-specific monoclonal antibody and allele-specific PCR

Mutations of components of the mitogen-activated protein kinase pathway, mainly BRAF, are common in serous ovarian borderline tumors, whereas high-grade serous ovarian carcinomas rarely show this feature. With the advent of specific kinase inhibitors active against BRAF-mutated cancers, rapid and sensitive detection of the BRAF V600E, by far the most common mutation of this gene, is of great practical relevance. Currently, BRAF mutations are detected by DNA-based techniques. Recently, a monoclonal antibody (VE1) specific for the BRAF V600E protein suitable for archival tissues has been described. In this study, we compared detection of the V600E mutation in serous ovarian tumors by VE1 immunostaining and by allele-specific polymerase chain reaction. All 141 cases of high-grade serous ovarian cancer showed negative or rarely weak, diffuse background VE1 immunostaining, and BRAF wild type was confirmed by molecular analysis in all tested cases. In contrast, 1 (14%) of 7 low-grade serous carcinomas and 22 (71%) of 31 serous borderline tumors revealed moderate to strong VE1 positivity. Immunostaining was clearly evaluable in all cases with sufficient tumor cells, and only rare cases with narrow cytoplasm were difficult to interpret. The V600E mutation was confirmed by allele-specific polymerase chain reaction and sequencing in all VE1-positive cases. Two VE1-positive cases with low epithelial cell content required repeat microdissection to confirm the presence of the mutation. Immunohistochemistry with the VE1 antibody is a specific and sensitive tool for detection of the BRAF V600E mutation in serous ovarian tumors and may provide a practical screening test, especially in tumor samples with low epithelial content.

Symptoms and risk factors of ovarian cancer: a survey in primary care

In spite of the increased awareness of ovarian cancer symptoms, the predictive value of symptoms remains very low. The aim of this paper is to obtain the views of general practitioners (GPs) in relation to symptom-based detection of ovarian cancer and to assess their knowledge for family history of breast and/or ovarian cancer as a predisposing factor for ovarian cancer. In this questionnaire survey, postal questionnaires were sent to 402 GPs in 132 primary care clinics, out of which we obtained 110 replies (27.4%). Approximately 26% of respondent GPs thought that the symptoms were more likely to be frequent, sudden, and persistent, and one-fifth were unsure of the importance of family history of breast cancer in relation to ovarian cancer. The participant GPs scored a set of symptoms for their relevance to ovarian cancer from 0 (not relevant) to 10 (most relevant). The highest scored symptoms were abdominal swelling (mean ± SD, 8.19 ± 2.33), abdominal bloating (7.01 ± 3.01), and pelvic pain (7.46 ± 2.26). There was a relative lack of awareness for repetitive symptoms as well as gastrointestinal symptoms as an important feature in a symptom-based detection of ovarian cancer.

Role of common genetic variants in ovarian cancer susceptibility and outcome: progress to date from the Ovarian Cancer Association Consortium (OCAC)

In this article, we review the current knowledge of the inherited genetics of epithelial ovarian cancer (EOC) susceptibility and clinical outcome. We focus on recent developments in identifying low-penetrance susceptibility genes and the role of the Ovarian Cancer Association Consortium (OCAC) in these discoveries. The OCAC was established to facilitate large-scale replication analyses for reported genetic associations for EOC. Since its inception, the OCAC has conducted both candidate gene and genome-wide association studies (GWAS); the latter has identified six established loci for EOC susceptibility, most of which showed stronger association with the serous histological subtype. Future GWAS and sequencing studies are likely to result in the discovery of additional susceptibility loci and may result in established associations with clinical outcome. Additional rare and uncommon ovarian cancer loci will likely be uncovered from high-throughput next-generation sequencing studies. Applying these novel findings to establish improved preventative and clinical intervention strategies will be one of the major challenges of future work.

Genetic polymorphisms as predictive and prognostic biomarkers in gynecological cancers: a systematic review

PURPOSE

Numerous studies have explored the potential role of genetic polymorphisms as predictive or prognostic biomarkers in gynecologic malignancies. A systematic review for all eligible polymorphisms has not yet been reported. The aim of this study was to summarize the current status of the field and provide direction for future research.

DESIGN

We searched literature databases (MEDLINE, EMBASE, Cochrane) from 2006 to April 2011 to identify studies evaluating the association between gene polymorphisms and clinical outcome in ovarian, endometrial, cervical, or vulvar cancer. The main outcome measures were overall survival (OS) and progression-free survival (PFS). Studies reporting relationships between polymorphisms and toxicity were also included.

RESULTS

Sixty two studies met the inclusion criteria. The median sample size was 140. Most of the included studies (n=50, 81%) were conducted in ovarian cancer patients. Almost a third assessed potential predictive associations between gene polymorphism and outcome in ovarian cancer. The most commonly evaluated genes were ERCC1, VEGF, ABCB1 (MDR), and GSTP1. Most studies (n=44, 71%) were observational case-series. Only four studies (6%) included a validation arm and patient population ethnicity was explicitly stated only in 27% of included studies.

CONCLUSION

No consistent association between any gene polymorphism and clinical outcome in gynecological cancers has been found across studies. There is incomplete adherence to the REMARK guidelines and inadequate methodology reporting in most studies. Moving forward, analysis of large trial-based clinical samples; adherence to the highest methodological standards, and focus on validation analyses are necessary to identify clinically useful pharmacogenomic biomarkers of outcome.

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.

Genomics of the NF-κB signaling pathway: hypothesized role in ovarian cancer

OBJECTIVE

We sought to review evidence linking nuclear factor-kappa B (NF-κB) to ovarian cancer and to identify genetic variants involved in NF-κB signaling.

METHODS

PubMed was reviewed to inform on ovarian cancer biology and NF-κB signaling and to identify key genes. Public linkage disequilibrium (LD) data were analyzed to identify informative inherited variants (tagSNPs) using ldSelect.

RESULTS

We identified 319 key NF-κB genes including five NF-κB subunits, 167 activating genes, and 55 inhibiting genes. We found that the 1000 Genomes Project was the most informative LD source for most genes (92.8%), and we identified 13,027 LD bins (r (2) ≥ 0.9, minor allele frequency ≥ 0.05) and 1,018 putative-functional variants worthy of investigation. We also report that reliance on a commonly used genome-wide SNP array and genotype imputation with HapMap Phase II data provides data on only 74% of the common inherited NF-κB SNPs of interest.

CONCLUSIONS

Compelling evidence suggests that NF-κB plays a critical role in ovarian cancer, yet inherited variation in these genes has not been thoroughly assessed in relation to disease risk or outcome. We present a collection of variants in key genes and suggest creation of a custom genotyping array as an optimal approach.

Genetic variants in MicroRNA biosynthesis pathways and binding sites modify ovarian cancer risk, survival, and treatment response

MicroRNAs (miRNA) play important roles in tumorigenesis. Genetic variations in miRNA processing genes and miRNA binding sites may affect the biogenesis of miRNA and the regulatory effect of miRNAs to their target genes, hence promoting tumorigenesis. This study analyzed 226 single nucleotide polymorphisms (SNP) in miRNA processing genes and miRNA binding sites in 339 ovarian cancer cases and 349 healthy controls to assess association with cancer risk, overall survival, and treatment response. Thirteen polymorphisms were found to have significant association with risk. The most significant were 2 linked SNPs (r(2) = 0.99), rs2740351 and rs7813 in GEMIN4 [odds ratio (OR) = 0.71; 95% confidence interval (CI), 0.57-0.87 and OR = 0.71; 95% CI, 0.57-0.88, respectively]. Unfavorable genotype analysis showed the cumulative effect of these 13 SNPs on risk (P for trend < 0.0001). Potential higher order gene-gene interactions were identified, which categorized patients into different risk groups according to their genotypic signatures. In the clinical outcome study, 24 SNPs exhibited significant association with overall survival and 17 SNPs with treatment response. Notably, patients carrying a rare homozygous genotype of rs1425486 in PDGFC had poorer overall survival [hazard ratio (HR) = 2.69; 95% CI, 1.67-4.33] and worse treatment response (OR = 3.38; 95% CI, 1.39-8.19), compared to carriers of common homozygous and heterozygous genotypes. Unfavorable genotype analyses also showed a strong gene-dosage effect with decreased survival and increased risk of treatment nonresponse in patients with greater number of unfavorable genotypes (P for trend < 0.0001). Taken together, miRNA-related genetic polymorphisms may impact ovarian cancer predisposition and clinical outcome both individually and jointly.

Effect of bilateral oophorectomy on women's long-term health

Bilateral oophorectomy at the time of hysterectomy for benign disease is commonly practiced in order to prevent the subsequent development of ovarian cancer or other ovarian pathology that might require additional surgery. At present, bilateral oophorectomy is performed in 78% of women aged between 45 and 64 years having a hysterectomy, and a total of approximately 300,000 prophylactic oophorectomies are performed in the USA every year. Estrogen deficiency resulting from pre- and post-menopausal oophorectomies has been associated with higher risks of coronary heart disease, stroke, hip fracture, Parkinsonism, dementia, cognitive impairment, depression and anxiety in many studies. While ovarian cancer accounts for 14,800 deaths per year in the USA, coronary heart disease accounts for 350,000 deaths per year. In addition, 100,000 cases of dementia may be attributable annually to prior bilateral oophorectomy. At present, observational studies suggest that bilateral oophorectomy may do more harm than good. In women who are not at high risk of developing ovarian or breast cancer, removing the ovaries at the time of hysterectomy should be approached with caution.

Vascular endothelial growth factor gene polymorphisms and ovarian cancer survival

OBJECTIVES

We sought to evaluate the effect of polymorphisms in the VEGF (Vascular Endothelial Growth Factor) gene on overall survival in ovarian cancer patients.

METHODS

A sample of 319 women diagnosed with primary invasive epithelial ovarian cancer in Australia between 1985 and 1997, recruited as incident cases, were genotyped for four VEGF single nucleotide polymorphisms (three tagSNPs and one functional SNP) using the Sequenom MassARRAY platform. A SNP found to be associated with ovarian cancer survival in this sample set was then evaluated in two independent datasets in an attempt to replicate the association.

RESULTS

VEGF tagSNPs rs3025033 and rs2146323 were not associated with ovarian cancer survival in the Australian sample. Ovarian cancer patients homozygous for tagSNP rs833068 or the functional SNP rs2010963 displayed significantly shortened overall survival in the Australian sample (HR 2.09, 95% CI 1.16-3.78), an effect most apparent in the first 5years after diagnosis. This association was not replicated in two independent datasets.

CONCLUSIONS

Findings from this study provide no evidence that rs3025033 and rs2146323 VEGF polymorphisms are associated with ovarian cancer survival. Although homozygous carriers of the tagSNP rs833068 experienced significantly worse survival in our Australian dataset, we were unable to replicate this in two independent datasets.

Germline BRCA mutations denote a clinicopathologic subset of prostate cancer

PURPOSE

Increased prostate cancer risk has been reported for BRCA mutation carriers, but BRCA-associated clinicopathologic features have not been clearly defined.

EXPERIMENTAL DESIGN

We determined BRCA mutation prevalence in 832 Ashkenazi Jewish men diagnosed with localized prostate cancer between 1988 and 2007 and 454 Ashkenazi Jewish controls and compared clinical outcome measures among 26 BRCA mutation carriers and 806 noncarriers. Kruskal-Wallis tests were used to compare age of diagnosis and Gleason score, and logistic regression models were used to determine associations between carrier status, prostate cancer risk, and Gleason score. Hazard ratios (HR) for clinical end points were estimated using Cox proportional hazards models.

RESULTS

BRCA2 mutations were associated with a 3-fold risk of prostate cancer [odds ratio, 3.18; 95% confidence interval (95% CI), 1.52-6.66; P = 0.002] and presented with more poorly differentiated (Gleason score > or =7) tumors (85% versus 57%; P = 0.0002) compared with non-BRCA-associated prostate cancer. BRCA1 mutations conferred no increased risk. After 7,254 person-years of follow-up, and adjusting for clinical stage, prostate-specific antigen, Gleason score, and treatment, BRCA2 and BRCA1 mutation carriers had a higher risk of recurrence [HR (95% CI), 2.41 (1.23-4.75) and 4.32 (1.31-13.62), respectively] and prostate cancer-specific death [HR (95% CI), 5.48 (2.03-14.79) and 5.16 (1.09-24.53), respectively] than noncarriers.

CONCLUSIONS

BRCA2 mutation carriers had an increased risk of prostate cancer and a higher histologic grade, and BRCA1 or BRCA2 mutations were associated with a more aggressive clinical course. These results may have implications for tailoring clinical management of this subset of hereditary prostate cancer.

Pathways to the diagnosis of ovarian cancer in the UK: a cohort study in primary care

OBJECTIVE

To identify the routes patients with ovarian cancer take between first symptom presentation and diagnosis.

DESIGN

Cohort study.

SETTING

The study took place in 39 general practices in Devon, UK.

POPULATION

All ovarian cancer patients identified in the practices, with a diagnosis between 2000 and 2007 inclusive.

METHODS

All patients had their cancer symptoms, referrals, and diagnoses identified and dated using their doctors' records.

MAIN OUTCOME MEASURES

Numbers of patients taking specific routes to diagnosis, together with the time taken to diagnosis.

RESULTS

Three main routes to diagnosis emerged. The first was the expected route of outpatient referral: 195 (92% of the total) had at least one of the seven ovarian cancer symptoms or an abdominal mass. A total of 123 (58%) were referred to a specialist, although only 65 (31%) were referred to a gynaecologist. Thirty-five (17%) were initially investigated within primary care by ultrasound scanning, and a further 35 (17%) were admitted as emergencies. The interval from first symptom to referral was similar across the different pathways, with a median (interquartile range) time between the first symptom presenting to primary care and first investigation or referral being 2.5 (0, 27.5) days. The median interval from first symptom reported in primary care to diagnosis was 74.5 (32, 159) days.

CONCLUSIONS

Only a minority of ovarian cancer patients follow the expected route to diagnosis, of urgent referral to a gynaecologist. In most women, GPs rapidly identified the need to investigate. Avoidable delays generally occurred after the decision to investigate was made.

Inherited determinants of ovarian cancer survival

PURPOSE

Due to variation of outcome among cases, we sought to examine whether overall survival in ovarian cancer was associated with common inherited variants in 227 candidate genes from ovarian cancer-related pathways including angiogenesis, inflammation, detoxification, glycosylation, one-carbon transfer, apoptosis, cell cycle regulation, and cellular senescence.

EXPERIMENTAL DESIGN

Blood samples were obtained from 325 women with invasive epithelial ovarian cancer diagnosed at the Mayo Clinic from 1999 to 2006. During a median follow-up of 3.8 years (range, 0.1-8.6 years), 157 deaths were observed. Germline DNA was analyzed at 1,416 single nucleotide polymorphisms (SNP). For all patients, and for 203 with serous subtype, we assessed the overall significance of each gene and pathway, and estimated risk of death via hazard ratios (HR) and 95% confidence intervals (CI), adjusting for known prognostic factors.

RESULTS

Variation within angiogenesis was most strongly associated with survival time overall (P = 0.03) and among patients with serous cancer (P = 0.05), particularly for EIF2B5 rs4912474 (all patients HR, 0.69; 95% CI, 0.54-0.89; P = 0.004), VEGFC rs17697305 (serous subtype HR, 2.29; 95% CI, 1.34-3.92; P = 0.003), and four SNPs in VHL. Variation within the inflammation pathway was borderline significant (all patients, P = 0.09), and SNPs in CCR3, IL1B, IL18, CCL2, and ALOX5 which correlated with survival time are worthy of follow-up.

CONCLUSION

An extensive multiple-pathway assessment found evidence that inherited differences may play a role in outcome of ovarian cancer patients, particularly in genes within the angiogenesis and inflammation pathways. Our work supports efforts to target such mediators for therapeutic gain.

Cell cycle genes and ovarian cancer susceptibility: a tagSNP analysis

Background:

Dysregulation of the cell cycle is a hallmark of many cancers including ovarian cancer, a leading cause of gynaecologic cancer mortality worldwide.

Methods:

We examined single nucleotide polymorphisms (SNPs) (n=288) from 39 cell cycle regulation genes, including cyclins, cyclin-dependent kinases (CDKs) and CDK inhibitors, in a two-stage study. White, non-Hispanic cases (n=829) and ovarian cancer-free controls (n=941) were genotyped using an Illumina assay.

Results:

Eleven variants in nine genes (ABL1, CCNB2, CDKN1A, CCND3, E2F2, CDK2, E2F3, CDC2, and CDK7) were associated with risk of ovarian cancer in at least one genetic model. Seven SNPs were then assessed in four additional studies with 1689 cases and 3398 controls. Association between risk of ovarian cancer and ABL1 rs2855192 found in the original population [odds ratio, OR_{BB vs AA} 2.81 (1.29–6.09), P=0.01] was also observed in a replication population, and the association remained suggestive in the combined analysis [OR_{BB vs AA} 1.59 (1.08–2.34), P=0.02]. No other SNP associations remained suggestive in the replication populations.

Conclusion:

ABL1 has been implicated in multiple processes including cell division, cell adhesion and cellular stress response. These results suggest that characterization of the function of genetic variation in this gene in other ovarian cancer populations is warranted.

A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2

Epithelial ovarian cancer has a major heritable component, but the known susceptibility genes explain less than half the excess familial risk. We performed a genome-wide association study (GWAS) to identify common ovarian cancer susceptibility alleles. We evaluated 507,094 SNPs genotyped in 1,817 cases and 2,353 controls from the UK and approximately 2 million imputed SNPs. We genotyped the 22,790 top ranked SNPs in 4,274 cases and 4,809 controls of European ancestry from Europe, USA and Australia. We identified 12 SNPs at 9p22 associated with disease risk (P < 10(-8)). The most significant SNP (rs3814113; P = 2.5 x 10(-17)) was genotyped in a further 2,670 ovarian cancer cases and 4,668 controls, confirming its association (combined data odds ratio (OR) = 0.82, 95% confidence interval (CI) 0.79-0.86, P(trend) = 5.1 x 10(-19)). The association differs by histological subtype, being strongest for serous ovarian cancers (OR 0.77, 95% CI 0.73-0.81, P(trend) = 4.1 x 10(-21)).

Risk of ovarian cancer in women with symptoms in primary care: population based case-control study

OBJECTIVE

To identify and quantify symptoms of ovarian cancer in women in primary care.

DESIGN

Case-control study, with coding of participants' primary care records for one year before diagnosis.

SETTING

39 general practices in Devon, England.

PARTICIPANTS

212 women aged over 40 with a diagnosis of primary ovarian cancer, 2000-7; 1060 controls matched by age and general practice.

MAIN OUTCOME MEASURES

Odds ratios and positive predictive values for symptoms from conditional logistic regression analyses.

RESULTS

Seven symptoms were associated with ovarian cancer in multivariable analysis. The univariable positive predictive values and multivariable odds ratios (with 95% confidence intervals) for these were 2.5% (1.2% to 5.9%) and 240 (46 to 1200) for abdominal distension; 0.5% (0.2% to 0.9%) and 24 (9.3 to 64) for postmenopausal bleeding; 0.6% (0.3% to 1.0%) and 17 (6.1 to 50) for loss of appetite; 0.2% (0.1% to 0.3%) and 16 (5.6 to 48) for increased urinary frequency; 0.3% (0.2% to 0.3%) and 12 (6.1 to 22) for abdominal pain; 0.2% (0.1% to 0.4%) and 7.6 (2.5 to 23) for rectal bleeding; and 0.3% (0.2% to 0.6%) and 5.3 (1.8 to 16) for abdominal bloating. In 181 (85%) cases and 164 (15%) controls at least one of these seven symptoms was reported to primary care before diagnosis. After exclusion of symptoms reported in the 180 days before diagnosis, abdominal distension, urinary frequency, and abdominal pain remained independently associated with a diagnosis of ovarian cancer.

CONCLUSIONS

Women with ovarian cancer usually have symptoms and report them to primary care, sometimes months before diagnosis. This study provides an evidence base for selection of patients for investigation, both for clinicians and for developers of guidelines.

Functional complementation studies identify candidate genes and common genetic variants associated with ovarian cancer survival

Common germline genetic variation and/or somatic alterations in tumours may be associated with survival in women diagnosed with ovarian cancer. The successful identification of genetic associations relies on a suitable strategy for identifying and testing candidate genes. We used microcell-mediated chromosome transfer approach and expression microarray analysis to identify genes that were associated with neoplastic suppression in ovarian cancer cell lines. Sixty-five tagging single nucleotide polymorphisms (tSNPs) in nine candidate genes were genotyped in approximately 1700 invasive ovarian cancer cases to look for associations with survival. For two of these genes, loss of heterozygosity (LOH) analysis of tSNPs in 314 ovarian tumours was used to identify associations between somatic gene deletions and survival. We identified significant associations with survival for a tSNP in caspase 5 (CASP5) [hazard ratio (HR) = 1.13 (95% CI: 1.00-1.27), P = 0.042] and two tSNPs in the retinoblastoma binding protein (RBBP8) gene [HR = 0.85 (95% CI: 0.75-0.95), P = 0.007 and HR = 0.83 (95% CI: 0.71-0.95), P = 0.009]. After adjusting for multiple prognostic factors in a multivariate Cox regression analysis, both associations in RBBP8 remained significant (P = 0.028 and 0.036). We then genotyped 314 ovarian tumours for several tSNPs in CASP5 and RBBP8 to identify gene deletions by LOH. For RBBP8, 35% of tumours in 101 informative cases showed somatic allelic deletion; LOH of RBBP8 was associated with a significantly worse prognosis [HR = 2.19 (95% CI: 1.36-3.54), P = 0.001]. In summary, a novel in vitro functional approach in ovarian cancer cells has identified RBBP8 as a gene for which both germline genetic variation and somatic alterations in tumours are associated with survival in ovarian cancer patients.