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The insulin-like growth factor (IGF) signaling axis plays an important role in cancer biology. We hypothesized that genetic variation in this pathway may influence risk of ovarian cancer. A three-center study of non-Hispanic whites including 1880 control women, 1135 women with invasive epithelial ovarian cancer and 321 women with borderline epithelial ovarian tumors was carried out to test the association between tag single-nucleotide polymorphisms (tSNPs) (n=58) in this pathway and risk of ovarian cancer. We found no association between variation in IGF1, IGFBP1 or IGFBP3 and risk of invasive disease, whereas five tSNPs in IGF2 were associated with risk of invasive epithelial ovarian cancer at P<0.05 and followed-up one of the associated SNPs. We conducted genotyping in 3216 additional non-Hispanic white cases and 5382 additional controls and were able to independently replicate our initial findings. In the combined set of studies, rs4320932 was associated with a 13% decreased risk of ovarian cancer per copy of the minor allele carried (95% confidence interval 0.81–0.93, P-trend=7.4 × 10−5). No heterogeneity of effect across study centers was observed (phet=0.25). IGF2 is emerging as an important gene for ovarian cancer; additional genotyping is warranted to further confirm these associations with IGF2 and to narrow down the region harboring the causal SNP.
Ovarian cancer is the leading cause of gynecologic-related cancer death in the USA. A first-degree family history of ovarian cancer is associated with an approximate 3-fold increased risk of the disease (1). Twin studies have indicated that this risk is not completely explained by shared environment and that there is an underlying genetic basis (2). Mutations in BRCA1 and BRCA2 explain ~10% of ovarian cancer cases, but after taking these major genes into account, 60% of the excess familial risk remains unexplained (3).
The heritability of ovarian cancer is, at least in part, explained by the contribution of less penetrant genetic variants. Efforts to identify such genetic variants associated with ovarian cancer risk have met with limited success, though several promising associations have been identified over the past several years (4–6), including four definitive loci which reached genome-wide significance and two additional loci which have nearly achieved genome-wide significance (7–9).
The insulin-like growth factor (IGF) signaling axis has an important regulatory function in growth and there is substantial evidence that this pathway plays a key role in cancer biology (reviewed in 10). IGF1 is expressed in ovarian cancer cells (11) and there is evidence that IGF1 levels are associated with disease progression (12,13); however, data are conflicting on the association between IGF1 levels and risk of ovarian cancer based on results from prospective studies(14–16). There is substantial evidence that IGF2 plays a role in ovarian cancer (17–22). IGF2 is reported to be over-expressed in ovarian cancer, and several lines of evidence suggest an association between IGF2 and disease prognosis (17,20,21,23). Both IGF1 and IGF2 are primarily bound to IGFBP3 (24); prospective studies have not found an association between IGFBP3 levels and risk of ovarian cancer (14–16). One study has looked at the association of haplotype-tagging single-nucleotide polymorphisms in IGF1, IGFBP1 and IGFBP3 and risk of ovarian cancer and found some evidence of association (25). No studies have examined the association between SNPs in IGF2 and risk of ovarian cancer.
We hypothesized that genetic variation in this pathway may be related to risk of ovarian cancer and therefore carried out a multi-center effort to determine the risk associated with tagging single-nucleotide polymorphisms (tSNPs) in the IGF1, IGF2, IGFBP1 and IGFBP3 genes.
A total of 1880 controls, 1135 invasive cases and 321 borderline cases were included in the analysis of the Stage 1 studies. A total of 19, 10 and 29 tSNPs were selected to cover IGF1, IGF2 and IGFBP1/3, respectively, of which 19, 9 and 26 passed quality control (QC) evaluation (Supplementary Material, Table S1). The assay failed completely for the four SNPs which were excluded (Supplementary Material, Table S1). There was no evidence for deviations from Hardy–Weinberg equilibrium (HWE) in controls at P<0.01 (Supplementary Material, Table S1). The coverage of each of these genes was evaluated based on the current HapMap Phase II build (release 24, October 2008, CEPH population). We were able to tag 98% of the IGF1 SNPs, 61% of the IGF2 SNPs and 89% of the IGFBP1/3 SNPs in HapMap with a minor allele frequency (MAF) of 0.05 or greater at an r2 of 0.80.
We observed statistically significant associations between five tSNPs in IGF2 and risk of invasive epithelial ovarian cancer at P<0.05 in the Stage 1 studies (Table 1). One of the five SNPs in IGF2 showing statistical significance, rs4320932, was selected for replication in additional case–control studies based on preliminary analysis in the Stage 1 studies. rs4320932, was associated with a 16% decreased risk of ovarian cancer per copy of the allele carried in the Stage 1 studies [95% confidence interval (CI) 0.73–0.96, P-trend=0.011; Fig. 1]. We observed independent replication in the seven Stage 2 studies genotyped [odds ratio (OR)=0.88, 95% CI 0.81–0.95, P=0.002]. After combining the Stage 1 and Stage 2 studies (n=10), we observed a 13% decreased risk of ovarian cancer per copy of the minor allele carried (95% CI 0.81–0.93, P-trend=7.4 × 10−5). ORs and 95% CIs by study are shown in Figure 1. We found no statistically significant heterogeneity across the Stage 1 studies (phet=0.84) or the Stage 2 studies (phet=0.25). There was no heterogeneity of effect observed across the 10 study populations combined (phet=0.45). The association between rs4320932 and risk of ovarian cancer was consistent across histological sub-types (Table 2). rs4244809 is highly correlated with rs4320932 (r2=0.78) and was also associated with ovarian cancer risk. Three other SNPs in IGF2, rs680, rs1003483 and rs7924316, were associated with risk of ovarian cancer in the Stage 1 data, but resource limitations did not allow us to attempt replication of these SNPs. The r2 values between these three SNPs and rs4320932 are 0.43, 0.18 and 0.30. Figure 2 shows the linkage disequilibrium relationships (r2) across all of the SNPs in the IGF2 region including both those that were and were not genotyped.
There were no statistically significant associations between tSNPs in IGF1 or IGFBP1/3 and risk of invasive epithelial ovarian cancer in the Stage 1 studies (Supplementary Material, Tables S2 and S3). Terry et al. (25) reported statistically significant associations between three SNPs in IGFBP1/3 and ovarian cancer risk: rs10228265, rs4988515 and rs2270628. We genotyped rs10228265 directly and identified good proxies in our data for the other two SNPs: rs7454 has an r2 value of 1 with rs4988515, and rs1496497 has an r2 value of 0.81 with rs2270628, and therefore we were able to conduct a meta-analysis where we found no statistically significant associations (rs10228265 OR=1.06, 95% CI 0.98–1.15; rs4988515/rs7454 OR=1.11, 95% CI 0.91–1.34 and rs2270628/rs1496497 OR=1.06, 95% CI 0.97–1.17).
Four tSNPs in IGF1 and four in IGFBP1/3 were associated with risk of borderline ovarian cancer at the P<0.05 level in the three Stage 1 study populations (DOVE, HOPE, USC; Supplementary Material, Tables S2 and S3). There were no statistically significant associations between risk of borderline ovarian cancer and SNPs in IGF2 (Supplementary Material, Table S4). Results by histological sub-type for IGF1 and IGFBP1/3 are shown in Supplementary Material, Tables S5 and S6, respectively.
We have observed a strong association with variation in the IGF2 gene and risk of invasive epithelial ovarian cancer both in a large initial population including subjects from the three Stage 1 case–control studies and in a replication set of seven additional studies. Overall, we have found evidence of a 13% decreased risk associated with the rs4320932 SNP (P-trend=7.4 × 10−5).
We have no evidence that any of the associated IGF2 SNPs are causal; none falls in the coding region (though rs680 is in the 3′ UTR) as shown in Figure 2. The coverage of the IGF2 region afforded by our tSNPs was fairly low (61%) and thus it is possible that other variants in the region may be associated with risk, or the associated SNPs are imperfect markers of the causal allele in IGF2 or other genes in the region. IGF2 is paternally imprinted and lies on chromosome 11p15.5 within a cluster of imprinted genes. The insulin gene (INS) is in this region and there are IGF2-INS splice variants which fall in the same block of linkage disequilibrium (Fig. 2).
However, IGF2 is the predominant IGF protein in the ovary (26) and it has been implicated as a key gene in ovarian cancer biology through several lines of evidence. Sawiris et al. (20) found that IGF2 was the most highly overexpressed gene in ovarian cancer compared with the normal ovarian surface epithelium, using their custom-designed cDNA array. Berchuck et al. (17) also showed that IGF2 expression was upregulated in serous ovarian cancer and they later extended this observation to show that overexpression of IGF2 was associated with poor prognosis in women with serous ovarian cancer (21). The mechanism of increased IGF2 expression in ovarian cancer is not understood, although several investigators have found that it is not due to loss of imprinting (LOI) of the maternal allele (18,19,22). LOI of IGF2 is observed in ovarian tumors, but at a much lower rate than found for other tumors (19). Murphy et al. (19) found LOI in 22% of serous ovarian tumors, whereas it has been reported to be 50–70% in Wilms tumors (reviewed in 27). Loss of heterozygosity (LOH) has also been found in high-grade ovarian tumors at chromosomal region 11p15.5 in several reports further suggesting that the area containing IGF2 is important (28,29). Launonen et al. (23) found that LOH at 11p15.5 was associated with advanced-stage disease, metastasis and reduced survival from ovarian cancer. Mor and co-workers (30,31) have found that a four-marker serum test, including IGF2 levels, can be used for early detection of the disease.
To determine the mechanism through which germline genetic variation in IGF2 might affect ovarian cancer risk, it would be necessary to first conduct additional genotyping to narrow down the region harboring the causal allele, followed by functional work on the identified variants. This follow-up work is critical and will provide additional valuable information on the association between the IGF2 region and risk of ovarian cancer.
We observed no statistically significant associations with germline genetic variation in IGF1, IGFBP1 or IGFBP3 and risk of invasive ovarian cancer in a large series of cases and controls with good tagging coverage of these genes, using an r2 of 0.80 (>98% for IGF1 and 88% for IGFBP1/3 based on data from the HapMap Phase II CEPH population). We also did not replicate the findings of Terry et al. (25) for IGFBP1/3-associated SNPs. There were several associations between risk of borderline ovarian cancer and variation in IGF1, IGFBP1/IGFBP3 that we were not able to follow up on due to resource limitations, but further follow-up would be warranted.
Overall, our finding of an initial association with IGF2 and validation of this finding in an independent replication set which included seven additional case–control studies is fairly convincing evidence of a role for the IGF2 gene region (or regions in LD with it) in ovarian cancer risk. Given the importance, based on multiple lines of evidence, of IGF2 in ovarian cancer and based on our Stage 1 finding of additional IGF2 SNPs that are related to risk, further follow-up of the relationship between variants in IGF2 and ovarian cancer risk is warranted.
This study was approved by the ethics committees of each institution. Each subject provided written informed consent prior to any study procedures being performed.
The initial genotyping efforts (Stage 1) were carried out in three US case–control studies: the DOVE study, the HOPE study and the USC study. The replication effort (Stage 2) consisted of studies from Australia (AUS), Denmark (MALOVA), Poland (POCS), the UK (SEARCH and UKOPS) and the USA (GEOCS and NCOCS).
The DOVE study is a population-based case–control study conducted in a 13-county area of western Washington State covered by the Cancer Surveillance System, a population-based registry that is part of the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute (32). Cases were English-speaking women, 35–74 years of age, who were diagnosed with a primary invasive or borderline epithelial ovarian cancer between 2002 and 2005. Controls were selected by random digit dialing in a 2:1 ratio to women with invasive epithelial ovarian cancer and frequency-matched to cases by age and county of residence. The response rate among cases was 77%, and that among controls was 69%.
The HOPE study is a population-based, case–control study of primary ovarian, peritoneal and fallopian tube cancer in the contiguous counties of western Pennsylvania (Pittsburgh), eastern Ohio (Cleveland), and western New York (Buffalo) (33). Cases included in the study were identified through a variety of sources including physician offices, cancer registries, hospital records and pathology databases from 2003 to 2008. Case diagnosis, histology and grade were confirmed by pathology report review. Population-based controls (2:1 control:case ratio) from the same regions were identified using random digit dialing and were frequency-matched to cases by age and race. The response rate among cases was 83%, and that among controls was 58%.
The USC study is a population-based case–control study of epithelial ovarian cancer conducted in Los Angeles County, California (34,35). Cases were identified from the Cancer Surveillance Program of the Los Angeles SEER program from 1993 through 2003. Controls were identified through a well-established neighborhood recruitment strategy and were matched to cases on ethnicity, age and neighborhood. The response rate among cases as well as controls was 73%.
All Stage 2 studies are participants in the Ovarian Cancer Association Consortium (OCAC).
The Australian Ovarian Cancer Study (AOCS) and Australian Cancer Study (ACS) are population-based case–control studies and together they cover all of the states of Australia (36). Accrual began in 2002 and continued to June 2006 for AOCS and June 2005 for ACS (AOCS and ACS are referred to as AUS throughout). Cases were identified through all of the major surgical treatment centers and state-based cancer registries in the country. Potential controls for both studies were selected at random from the Commonwealth electoral roll (enrollment to vote is a legal requirement) and frequency-matched to the age and geographic distribution of the cases. The response rate among cases was 85%, and that among controls was 47%.
The MALOVA study was a population-based case–control study carried out in selected Danish counties with a gynecological hospital department from 1995 to 1999 (37). Cases were identified in each of the hospitals, and controls were randomly drawn among Danish-born women in the study area by means of the computerized Danish Central Population Register. Controls were frequency-matched to the age and county of the cases. The participation rate among cases was 79%, and that among controls was 68%.
The POCS is a hospital-based case–control study recruiting invasive epithelial ovarian cancer cases and controls since 1998. Cases are drawn from five gynecological oncology centers in Poland, and controls are drawn from women registered in collaborating practices of family doctors, matched for place of residence and year of birth for cases. Participation rates were 76% among cases and 81% among controls.
SEARCH (ovary) is an ongoing, population-based ovarian cancer case–control study which began in 1998 (38). Cases are those who live in the regions served by the Eastern Cancer Registration and Information Center and who were diagnosed with invasive epithelial ovarian cancer since 1991. Controls have been randomly selected from the EPIC-Norfolk component of the European Prospective Investigation of Cancer (EPIC), a prospective study of diet and cancer being carried out in the same population from which the cases have been drawn. The response rate among cases was 59%.
UKOPS is a case–control study which began in 2006 and is ongoing (39). Cases include women with primary invasive epithelial ovarian cancer and are recruited from gynecological oncology centers in England, Wales and Northern Ireland. Controls are women without cancer who are participating in the screening arm of an ovarian cancer screening trial (UKCTOCS) (40). Centers recruited 76% of their target for controls and 66% of cases.
The GEOCS is a population-based case–control study in six counties in the San Francisco Bay area which began in 1997 and was completed in 2002 (41). Patients with epithelial ovarian cancer were identified via rapid case ascertainment through the Greater Bay Area Cancer Registry operated by the Northern California Cancer Center as part of the SEER program. Control women were identified through random-digit dialing and were frequency-matched to cases on race/ethnicity and 5-year age group. The response rate for cases was 75%, and that for controls was 75%.
The NCOCS is a population-based, case–control, molecular epidemiological study in a 48-county region of eastern and central North Carolina (42). Accrual occurred between 1999 and 2008 (diagnoses between 1999 and 2007). Ovarian cancer cases are identified through the statewide registry, using rapid case ascertainment. Population-based controls are identified from the same regions and are frequency-matched to the ovarian cancer cases on the basis of race and age. The response rate among cases is 66%, and that among controls is 61%.
tSNPs were selected in four candidate genes in the IGF signaling axis: IGF1, IGF2, IGFBP1/3. IGFBP1 and IGFBP3 were considered together for tSNP selection purposes because they are so near to one another (within 33 kb of each other). For IGF1 and IGFBP1/3, tSNPs were selected using the program Snagger (43) with data from the International HapMap Project White CEPH (Utah residents with ancestry from northern and western Europe) population (HapMap, release 21, July 2006). tSNPs were selected to cover all SNPs with an MAF of 0.05 or greater, with a pairwise r2 of ≥0.80 in the region covering each gene of interest as well as 20 kb upstream and 10 kb downstream of the gene.
For IGF2, tSNPs selected for the Breast and Prostate Cohort Consortium (44) were used. Briefly, tSNPs were selected from genotyping data generated for this gene from several characterization panels: 70 white subjects from the Multiethnic Cohort Study of Diet and Cancer (MEC), 30 CEPH trios from the International HapMap Project and 14 additional CEPH trios. tSNPs were selected to cover all SNPs with an MAF of 0.02 or greater, with a pairwise r2 of ≥0.80 in the region covering each gene of interest as well as 20 kb upstream and 10 kb downstream of the gene.
Genotyping of the tSNPs in DOVE, HOPE and USC was done in the USC Norris Comprehensive Cancer Center's genomics core facility, using the Illumina Golden Gate Assay™ (Illumina, Inc., San Diego, CA, USA). A total of 1536 SNPs were genotyped in the entire panel, of which 58 were in the IGF pathway. The other pathways included in the genotyping panel were inflammation (cytokines), sex steroid hormone biosynthesis, metabolism, transport and binding, and gonadotropin signaling.
Samples were excluded from further analysis if the genotyping success rate was <90% after eliminating SNPs which failed genotyping completely (no calls) or had an MAF of <1%. SNPs that were successfully genotyped in <95% of samples were then excluded.
QC measures included testing for deviations from HWE in non-Hispanic whites, the inclusion of blinded duplicate samples and mixing cases and controls on genotyping plates. A total of 128 blinded duplicate pairs were included for genotyping. Concordance for the duplicate samples was >99%.
Tagging coverage of the gene was evaluated on the basis of HapMap Phase II build (release 24, October 2008, CEPH population) using Snagger (43). The percent coverage was calculated for each gene for all SNPs with an MAF of ≥0.05, using an r2 value of 0.80.
One of the tSNP associations in the IGF2 gene was selected for replication in additional studies participating in the OCAC. The OCAC was organized to provide a forum for attempting replication of genetic associations that appear promising. Participating in any given genotyping effort is voluntary and further based on available funding for the follow-up genotyping. rs4320932 was selected for replication on the basis of being the most strongly associated SNP after initial preliminary analysis in the Stage 1 studies, although after final analyses with minor exclusions for QC purposes were completed it was no longer the most strongly associated. Genotyping was done using the TaqMan allelic discrimination assay (TaqMan; Applied Biosystems, Foster City, CA, USA) for all Stage 2 studies except ACS/AOCS which used the Sequenom iPlex gold genotyping platform (Sequenom, Inc., San Diego, CA, USA). All data for each replication study passed the QC guidelines set by the OCAC, including >98% concordance among duplicate samples, cases and controls mixed on the same plates, and >95% genotyping success. There were no significant deviations from HWE in any of the replication studies. In addition, each laboratory genotyped a common set of DNAs (90 CEPH trios and 5 duplicate samples; HAPMAPPT01 provided by Coriell, Camden, NJ, USA). Concordance for these common DNAs was >99% across laboratories.
Deviation of genotype frequencies from those expected under HWE was assessed using a χ2 test. The current report is restricted to non-Hispanic white subjects. Logistic regression was used to obtain ORs and 95% CIs for the association between each tSNP and risk of invasive epithelial ovarian cancer or borderline epithelial ovarian cancer. The primary test of association was a test for trend carried out by treating the number of minor alleles carried as an ordinal variable in the logistic regression model which also provides the per-allele OR. This test is most powerful under a co-dominant, log-additive genetic model. Genotype-specific risks/ORs for heterozygotes and minor allele homozygotes, compared with major allele homozygotes, were estimated by treating genoptype as a categorical variable in the logistic model. All analyses were carried out matched on study site and 5-year age groups (<40, 40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70+). Additional analyses were conducted to assess the association with different histological sub-types (serous, endometrioid, clear cell and mucinous) by creating a separate outcome variable for each sub-type. Heterogeneity of effect across study sites was evaluated using a likelihood ratio test comparing a model with an interaction term for study site and genotype with a model without the interaction term.
We also conducted a meta-analysis of reported associations by Terry et al. (25) between three SNPs in IGFBP1/3 and ovarian cancer risk. For the meta-analysis, the individual ORs and 95% CIs for DOVE, HOPE, USC and the two study populations included in Terry et al. (25) (NECC and NHS) were utilized [i.e. we did not utilize the pooled estimates from the Stage 1 populations in our study or those reported by Terry et al. (25), but rather the individual study data]. rs10228265 reported by Terry et al. (25) was genotyped in our study and two others (rs4988515 and rs2270628) were correlated with SNPs we genotyped. rs7454, genotyped by us, was perfectly correlated (r2=1) with rs4988515, and rs1496497, also genotyped by us, was strongly correlated (r2=0.81) with rs2270628, and therefore these data were combined.
Conflict of Interest statement. None declared.
The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith. Funding for the DOVE study was provided by NIH grants R01CA112523 and R01CA87538. The HOPE study was supported by grants from the Department of Defense DAMD 17–02–1–0669 and National Cancer Institute R01CA095023. The USC study was supported by the California Cancer Research Program grants 00–01389V-20170 and 2110200, US Public Health Service grants CA14089, CA17054, CA61132, CA63464, N01-PC-67010 and R03-CA113148 and California Department of Health Services sub-contract 050-E8709 as part of its statewide cancer reporting program. The Australian Ovarian Cancer Study (AOCS) was supported by the US Army Medical Research and Materiel Command (DAMD17–01–1–0729) and the Cancer Council Tasmania and Cancer Foundation of Western Australia; and the Australian Cancer Study (ACS) was supported by the National Health and Medical Research Council of Australia (199600). G.C.-T. and P.M.W. are supported by the NHMRC of Australia. The GEOCS was supported by US National Institute of Health grants U01 CA71966 (A.S.W., V.M.), CA16056, K07CA143047, and U01 CA69417 (for recruitment of controls by the Northern California Cancer Center). The MALOVA study is supported by grants from Mermaid 1, The Danish Cancer Society and the NIH R01-CA61107. The NCO study was supported by the US National Cancer Institute Grants R01-CA76016 and R01-HL090559. The SEARCH study was funded by Cancer Research UK. UKOPS was funded by the Eve Appeal, the Oak Foundation and Vermillion plc (formerly Ciphergen plc). A major portion of this work was done within the ‘Women's Health Theme’ of the NIHR UCLH/UCL Comprehensive Biomedical Research Centre supported by the Department of Health.