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. Author manuscript; available in PMC: 2011 Feb 1.
Published in final edited form as: Twin Res Hum Genet. 2010 Feb;13(1):43–56. doi: 10.1375/twin.13.1.43

Variation at 8q24 and 9p24 and Risk of Epithelial Ovarian Cancer

Kristin L White 1, Thomas A Sellers 2, Brooke L Fridley 1, Robert A Vierkant 1, Catherine M Phelan 2, Ya-Yu Tsai 2, Kimberly R Kalli 1, Andrew Berchuck 3, Edwin S Iversen Jr 3, Lynn C Hartmann 1, Mark Liebow 1, Sebastian Armasu 1, Zachary Fredericksen 1, Melissa C Larson 1, David Duggan 4, Fergus J Couch 1, Joellen M Schildkraut 3, Julie M Cunningham 1, Ellen L Goode 1
PMCID: PMC2932441  NIHMSID: NIHMS216367  PMID: 20158306

Abstract

The chromosome 8q24 region (specifically, 8q24.21.a) is known to harbor variants associated with risk of breast, colorectal, prostate, and bladder cancers. In 2008, variants rs10505477 and rs6983267 in this region were associated with increased risk of invasive ovarian cancer (p<0.01); however, three subsequent ovarian cancer reports of 8q24 variants were null. Here, we used a multi-site case-control study of 940 ovarian cancer cases and 1,041 controls to evaluate associations between these and other single-nucleotide polymorphisms (SNPs) in this 8q24 region, as well as in the 9p24 colorectal cancer associated-region (specifically, 9p24.1.b). A total of 35 SNPs from previous reports and additional tagging SNPs were assessed using an Illumina GoldenGate array and analyzed using logistic regression models, adjusting for population structure and other potential confounders. We observed no association between genotypes and risk of ovarian cancer considering all cases, invasive cases, or invasive serous cases. For example, at 8q24 SNPs rs10505477 and rs6983267, analyses yielded per-allele invasive cancer odds ratios of 0.95 (95% confidence interval (CI) 0.82–1.09, p-trend 0.46) and 0.97 (95% CI 0.84–1.12, p-trend 0.69), respectively. Analyses using an approach identical to that of the first positive 8q24 report also yielded no association with risk of ovarian cancer. In the 9p24 region, no SNPs were associated with risk of ovarian cancer overall or with invasive or invasive serous disease (all p-values > 0.10). These results indicate that the SNPs studied here are not related to risk of this gynecologic malignancy and that the site-specific nature of 8q24.21.a associations may not include ovarian cancer.

Ovarian cancer has the highest mortality rate among gynecologic malignancies, indicating a pressing need for better understanding of its etiology as a means to inform prevention approaches. Factors associated with increased risk of ovarian cancer include age, family history, fertility drug use, and postmenopausal hormone therapy (Morch, Lokkegaard, Andreasen, Kruger-Kjaer, & Lidegaard, 2009). In BRCA1 and BRCA2 mutation carriers, lifetime risk of ovarian cancer is approximately 40% and 20%, respectively (Antoniou et al., 2003), and these mutations are responsible for nearly half of ovarian cancer cases in families with two or more confirmed cases (Ramus et al., 2007). The remaining unexplained familial and sporadic ovarian cancer risk is likely caused by common, low-penetrance alleles which individually cause a modest change in risk and lead to a notable increased risk in combination (Fasching et al., 2009; Pharoah & Ponder, 2002). Thus far, variants in the 9p22.2 chromosomal region (Song, Ramus, Tyrer et al., 2009) and in genes involved in cell cycle control (Gayther et al., 2007), steroid hormone metabolism (Pearce et al., 2008), DNA repair (Schildkraut et al., 2009), and one-carbon metabolism (Kelemen et al., 2008) have been associated with ovarian cancer risk.

Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) in a non-coding 8q24 region (specifically, 8q24.21.a) that are associated with risk of prostate cancer (Gudmundsson et al., 2007; Haiman et al., 2007; Salinas et al., 2008; Suuriniemi et al., 2007; Yeager et al., 2007), breast cancer (Garcia-Closas et al., 2008; Schumacher et al., 2007), colorectal cancer (Ghoussaini et al., 2008; Gruber et al., 2007; Poynter et al., 2007; Tenesa et al., 2008; Tuupanen et al., 2009; Zanke et al., 2007), and bladder cancer (Kiemeney et al., 2008), and variants in the 9p24 region (specifically, 9p24.1.b) have been associated with risk of colorectal cancer (Poynter et al., 2007; Zanke et al., 2007). In 2008, a four-site study of 1,975 invasive ovarian cancer cases and 3,411 controls revealed the first association between 8q24.21.a loci (rs10505477, rs10808556, and rs6983267; 1.8 kb; 0.65 ≤ r2 ≤ 0.93) and risk of ovarian cancer (odds ratio (OR) 1.14, 95% confidence interval (CI) 1.04–1.23; OR 1.13, 95% CI 1.04–1.22; OR 1.11, 95% CI 1.03–1.20, respectively) (Ghoussaini et al., 2008). However, subsequent examinations of rs6983267 in 618 cases and 1,019 controls, rs13281615 in 2,502 cases and 3,892 controls, and rs1447295 in 274 cases and 682 controls found no association with risk (OR 1.00, 95% CI 0.81–1.23, p-trend=0.10; OR 1.00, 95% CI 0.70–1.30, p-trend=1.00; OR 0.99, 95% CI 0.92–1.06, p-trend =0.69, respectively) (Song, Ramus, Kjaer et al., 2009; Wokolorczyk et al., 2008; Wokolorczyk, Lubinski, Narod, & Cybulski, 2009). Due to discrepant ovarian cancer associations in 8q24, associations in both regions with other cancers, and the existence of other genetic factors in common across these cancers (Fasching et al., 2009), we examined risk of ovarian cancer in the 8q24.21.a and 9p24.1.b regions using case-control collections from two study populations.

MATERIALS AND METHODS

Study Participants

Participants were recruited at Mayo Clinic in Rochester, MN and at Duke University in Durham, NC and included cases enrolled within one year of histologically confirmed epithelial ovarian cancer and controls without ovarian cancer and without bilateral oophererectomy (Sellers et al., 2005). At Mayo Clinic, cases were women over 20 years of age living in the Upper Midwest. Controls were recruited from among women seen for general medical examinations and frequency-matched to cases on age and area of residence. At Duke University, cases were women between 20 and 75 years of age identified using the North Carolina Central Cancer Registry’s rapid case ascertainment system within a 48-county region. Controls were identified from the same region as the cases using list-assisted random digit dialing and frequency-matched to cases on race and age. Information on known and suspected risk factors was collected through in-person interviews at both sites using similar questionnaires. Mayo Clinic participants had an extra vial of blood drawn during their scheduled medical visit, and DNA was extracted using the Gentra AutoPure LS Purgene salting out methodology (Gentra, Minneapolis, MN). Duke University participants had venipuncture performed at the conclusion of their interview, and DNA samples were transferred to Mayo Clinic for whole-genome amplification (WGA) with REPLI-G (Qiagen Inc, Valencia CA) which we have shown yielded highly reproducible results with these samples (Cunningham et al., 2008). Samples were bar-coded to ensure accurate and reliable sample processing, and DNA concentrations were adjusted to 50 ng/µl and verified using PicoGreen dsDNA Quantitation kit (Molecular Probes, Inc., Eugene, OR).

SNP Selection and Genotyping

A broad SNP selection approach was applied. In 8q24.21.a, seven SNPs were included due to a prior ovarian cancer report (Ghoussaini et al., 2008), one due to a prior prostate cancer report (Haiman et al., 2007), five SNPs which tagged 1 kb surrounding the regional pseudogene POU5F1P1, and twelve SNPs which additionally tagged the region; in 9p24.1.b, we included three SNPs from a colorectal cancer report (Poynter et al., 2007) and nine additional regional tagSNPs (Table 1 about here, Figure 1 about here). Genotyping of 897 genomic and 1,279 WGA DNA samples (2,176 including 129 duplicates) on 2,047 unique study participants was performed at Mayo Clinic using the Illumina GoldenGate BeadArray assay and BeadStudio software (Oliphant, Barker, Stuelpnagel, & Chee, 2002). Briefly, of 2,047 participants genotyped, we excluded 44 due to call rate < 90% and 22 due to study ineligibility; thus 1,981 participants were analyzed here. We assessed departures from Hardy-Weinberg equilibrium (HWE) among white non-Hispanic controls using a Pearson goodness-of-fit test or, for SNPs with a minor allele frequency (MAF) < 5%, a Fisher exact test (Weir, 1996). Of 1,152 total attempted SNPs, we excluded 15 due to call rate < 90%, nine due to poor clustering, one due to unresolved replicate errors, 64 due to MAF < 0.01, and eleven due to HWE p-value < 0.0001. In the 8q24.21.a and 9p24.1.b regions, 37 SNPs were attempted, and two failed (POU5F1P1 tagSNP rs7002225 and prostate cancer-associated SNP rs7000448 (Ghoussaini et al., 2008) (Table 1 about here). Estimates of pair-wise linkage disequilibrium (LD) among genotyped SNPs were obtained for self-reported white non-Hispanic participants using Haploview v. 4.1 (Barrett, Fry, Maller, & Daly, 2005).

Table 1.

SNP and genotype information

rsid Position Alleles Selection Strategy Nearest
gene		 Location to
gene		 Distance
to gene		 Call
Rate		 HWE
p-value		 MAF Case
Genotype, N		 Control
Genotype, N
AA AB BB AA AB BB
8q24.21.a
rs10808550 127,691,632 A/G Ghoussaini et al., 2008 FAM84B 5′ upstream 51,984 0.997 0.78 0.16 667 243 26 729 287 23
rs13254738 128,173,525 A/C Ghoussaini et al., 2008 POU5F1P1 5′ upstream 323,769 0.998 0.50 0.33 430 383 126 465 453 120
rs6983561 128,176,062 A/C Ghoussaini et al., 2008 POU5F1P1 5′ upstream 321,232 0.999 0.62 0.07 822 101 16 921 93 26
rs16901979 128,194,098 C/A Ghoussaini et al., 2008 POU5F1P1 5′ upstream 303,196 0.999 0.62 0.07 825 99 15 924 94 22
rs13281615 128,424,800 A/G Ghoussaini et al., 2008 POU5F1P1 5′ upstream 72,494 0.996 0.77 0.40 338 439 158 371 506 162
rs16902149 128,476,287 G/C regional tagSNP POU5F1P1 5′ upstream 21,007 0.992 0.71 0.07 794 131 6 897 133 4
rs10505477 128,476,625 A/G regional tagSNP POU5F1P1 5′ upstream 20,669 0.998 0.81 0.48 270 445 222 287 500 254
rs10808555 128,478,693 A/G regional tagSNP POU5F1P1 5′ upstream 18,601 0.998 0.34 0.33 422 420 97 465 468 105
rs10505475 128,480,639 A/C regional tagSNP POU5F1P1 5′ upstream 16,655 0.999 0.30 0.06 824 109 7 921 116 2
rs6983267 128,482,487 C/A Haiman et al., 2007 POU5F1P1 5′ upstream 14,807 0.998 0.77 0.47 288 433 217 311 483 245
rs10956368 128,492,832 G/A regional tagSNP POU5F1P1 5′ upstream 4,462 0.998 0.59 0.41 325 435 177 366 494 181
rs4871789 128,497,243 A/G POU5FIP1 tagSNP POU5F1P1 5′ upstream 51 0.999 0.48 0.50 244 452 243 273 494 273
rs6998061 128,497,820 G/A POU5FIP1 tagSNP POU5F1P1 rna_exon 0 0.991 0.93 0.40 346 431 154 376 479 177
rs13274084 128,497,933 A/G POU5FIP1 tagSNP POU5F1P1 rna_exon 0 0.999 0.29 0.13 716 206 16 796 223 22
rs7002225 128,498,005 C/G POU5FIP1 tagSNP POU5F1P1 rna_exon 0 Failed, cluster compression
rs9297754 128,498,444 C/G POU5FIP1 tagSNP POU5F1P1 3′ downstream 71 0.989 0.42 0.22 560 330 41 628 356 45
rs7005829 128,504,126 G/A regional tagSNP POU5F1P1 3′ downstream 5,753 0.995 0.72 0.28 504 362 71 545 405 85
rs9297756 128,509,349 C/A regional tagSNP POU5F1P1 3′ downstream 10,976 0.995 0.89 0.14 698 219 19 763 249 24
rs6999921 128,510,110 A/G regional tagSNP POU5F1P1 3′ downstream 11,737 0.999 0.21 0.09 781 150 8 874 157 10
rs7000448 128,510,352 C/T Ghoussaini et al., 2008 POU5F1P1 3′ downstream 11,979 Failed, cluster compression
rs12334695 128,523,110 A/G regional tagSNP POU5F1P1 3′ downstream 24,737 0.998 0.14 0.38 411 397 131 415 465 158
rs10109622 128,527,333 G/A regional tagSNP POU5F1P1 3′ downstream 28,960 0.997 0.87 0.25 552 308 78 589 371 78
rs10094059 128,530,789 G/C regional tagSNP POU5F1P1 3′ downstream 32,416 0.999 0.14 0.26 517 359 63 576 381 83
rs9643221 128,534,669 G/A regional tagSNP POU5F1P1 3′ downstream 36,296 0.998 0.13 0.21 592 291 53 655 326 60
rs1447295 128,554,220 C/A Ghoussaini et al., 2008 POU5F1P1 3′ downstream 55,847 0.997 0.33 0.12 725 203 9 812 206 20
9p24.1.b
rs12237914 6,296,896 A/G regional tagSNP TPD52L3 5′ upstream 21,479 0.983 0.20 0.38 335 431 159 409 453 161
rs17705436 6,300,908 G/C regional tagSNP TPD52L3 5′ upstream 17,467 0.998 0.35 0.22 600 282 56 647 337 56
rs10491835 6,315,345 G/A regional tagSNP TPD52L3 5′ upstream 3,030 0.998 0.17 0.17 649 262 27 726 277 36
rs3847262 6,318,947 G/A regional tagSNP TPD52L3 F118L 0 0.999 0.35 0.06 820 114 6 913 122 4
rs721352 6,322,901 C/A regional tagSNP TPD52L3 3′ downstream 2,231 0.998 0.02 0.34 440 364 133 479 413 148
rs7850988 6,325,760 T/A regional tagSNP TPD52L3 3′ downstream 5,090 0.998 0.10 0.26 539 327 73 579 379 80
rs16924434 6,348,334 A/G regional tagSNP TPD52L3 3′ downstream 27,664 0.999 0.26 0.11 756 174 10 823 198 18
rs719725 6,355,683 A/C regional tagSNP TPD52L3 3′ downstream 35,013 0.997 0.32 0.37 395 421 120 417 466 156
rs7865955 6,398,247 C/G regional tagSNP UHRF2 5′ upstream 4,904 0.998 <0.01 0.45 306 442 190 342 459 238
rs1821892 6,606,648 G/C CRC Affymetrix 10k 2.0 GLDC intron 0 0.998 0.88 0.15 674 234 30 750 259 30
rs1340513 6,967,633 A/G CRC Affymetrix 10k 2.0 JMJD2C intron 0 0.997 0.97 0.25 541 345 51 595 378 66
rs1407856 7,036,901 G/C CRC Affymetrix 10k 2.0 JMJD2C Q767E 0 0.998 0.43 0.17 646 265 26 720 286 35
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Position from genome build 36.3; Refseq release 29 (May 4, 2008); Gene information: FAM84B, - strand, geneID 157638, protein-coding, NM_174911.3, mRNA; POU5F1P1, + strand, geneID 5462, pseudo-gene, NR_002304.1, misc_RNA; TPD52L3, + strand, geneID 89882, protein-coding, NM_001001875.2, mRNA; UHRF2, + strand, geneID 115426, protein-coding, NM_152896.1, mRNA; GLDC, - strand, geneID 2731, protein-coding, NM_000170.2, mRNA; JMJD2C, + strand, geneID 23081, protein-coding, NM_015061.2, mRNA; Call rate among all participants; MAF calculated using all controls; HWE p-value calculated using White non-Hispanic controls only; AA, common homozygotes; AB, heterozygotes; BB, rare homozygotes.

Figure 1. Regional linkage disequilibrium.

Figure 1

Figure 1

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Haploview 4.1 (Barrett et al., 2005) based on self-reported white-non-Hispanic controls; r2=0=white and r2=1=black; numbers represent r2 * 100; associations with risk of other cancers with at least one replication study and a p-value < 1 × 10−15 are shown for genotyped SNPs based on Hindorff LA, Junkins HA, Mehta JP, and Manolio TA. A Catalog of Published Genome-Wide Association Studies, available at www.genome.gov/gwastudies, accessed July 29, 2009.

Statistical Methods

Data were summarized using frequencies and percents for categorical variables and means and standard deviations for continuous variables; we compared distributions of demographic variables across case status using chi-square tests and t-tests, as appropriate. Individual SNP associations with ovarian cancer risk were assessed using logistic regression models, in which ORs and 95% CIs were estimated. Separate analyses were carried out using all ovarian cancer cases (N=940), all invasive cases (N=749), and all serous invasive cases (N=452). Primary tests of association assumed an ordinal (log-additive) effect using simple tests for trend. Association analyses included adjustment for the following covariates: study site, age, body mass index (BMI), hormone therapy, oral contraceptive use, number of live births, age at first live birth, geographic region, and principal components which accounted for the possibility of population stratification using an approach similar to that described previously (Price et al., 2006). Briefly, population structure principal components were created using 2,517 SNPs from this and prior genotyping panels (Kelemen et al., 2008); scatter-plot matrices by self-reported race indicated that the first four principal components reasonably approximated racial differences across individuals and were thus included as covariates in all models (Figure 2 about here). No adjustments were made for multiple testing; all statistical tests were two-sided and, unless otherwise indicated, analyses were carried out using SAS software (SAS Institute, Inc., Cary, NC).

Figure 2. Matrix of scatterplots for four population structure principal components by self-reported race.

Figure 2

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Population structure principal components analysis based on 1,981 participants and 2,517 SNPs including imputed genotypes; for each scatterplot, vertical axis corresponds to the component listed in diagonal element to the left of the plot, and horizontal axis corresponds to the component listed in diagonal underneath the plot; results suggest that the first component differentiated white non-Hispanic and black non-Hispanic from other samples, while the fourth component helped to further differentiate Asian from other samples; these four population structure principal components were used as covariates in association analyses.

RESULTS

Demographic, lifestyle, reproductive, and tumor characteristics of 940 epithelial ovarian cancer cases and 1,041 controls are described (Table 2 about here). In general, the expected distributions of risk factors were observed: a larger proportion of cases than controls had a first or second degree relative with ovarian cancer, had not used oral contraceptives, had used postmenopausal hormone therapy, and were nulliparous. Overall, 80% of tumors were invasive and 20% were borderline; the distribution of histologic subtypes was 61% serous, 14% endometrioid, 10% mucinous, 6% clear cell, and 9% other histologies. LD (defined as r2 ≥ 0.65) was observed between six pairs of 8q24.21.a SNPs and four pairs of 9p24.1.b SNPs in these study populations (Figure 1 about here).

Table 2.

Characteristics of study participants

Mayo Clinic Duke University
Cases
(N=401)		 Controls
(N=469)		 p
value		 Cases
(N=539)		 Controls
(N=572)		 p
value
Age Mean (S.D.) yrs 59.9 (13.27) 60 (12.98) 0.88 54 (11.47) 54.5 (12.14) 0.48
Race White 386 (98%) 460 (98.9%) 0.61 453 (84.2%) 484 (84.6%) 0.71
African American 3 (0.8%) 2 (0.4%) 70 (13%) 77 (13.5%)
Asian 2 (0.5%) 2 (0.4%) 6 (1.1%) 3 (0.5%)
Other 3 (0.8%) 1 (0.2%) 9 (1.7%) 8 (1.4%)
Missing 7 4 1 0
Body mass index < 23 kg/m2 84 (21.8%) 109 (24.9%) 0.03 134 (25.5%) 142 (25.6%) 0.24
23–26 kg/m2 87 (22.5%) 122 (27.9%) 117 (22.3%) 125 (22.5%)
26–29 kg/m2 99 (25.6%) 112 (25.6%) 105 (20%) 135 (24.3%)
≥ 29 kg/m2 116 (30.1%) 95 (21.7%) 169 (32.2%) 153 (27.6%)
Missing 15 31 14 17
Age at menarche < 12 years 54 (18.1%) 68 (15.8%) 0.58 133 (24.8%) 118 (20.6%) 0.36
12 years 78 (26.1%) 100 (23.2%) 153 (28.5%) 164 (28.7%)
13 years 81 (27.1%) 127 (29.5%) 136 (25.3%) 163 (28.5%)
≥ 14 years 86 (28.8%) 136 (31.6%) 115 (21.4%) 127 (22.2%)
Missing 102 38 2 0
Oral contraceptive use Never 178 (47.5%) 166 (38.4%) <0.001 185 (35%) 180 (31.7%) 0.26
1–48 months 100 (26.7%) 92 (21.3%) 158 (29.9%) 161 (28.4%)
≥ 48 months 97 (25.9%) 174 (40.3%) 186 (35.2%) 226 (39.9%)
Missing 26 37 10 5
Hormone therapy Never 241 (63.3%) 249 (58.9%) 0.44 193 (37.5%) 339 (62.8%) <0.001
1–60 months 65 (17.1%) 79 (18.7%) 206 (40.1%) 106 (19.6%)
≥ 60 months 75 (19.7%) 95 (22.5%) 115 (22.4%) 95 (17.6%)
Missing 20 46 25 32
Parity, n /Age at first birth, yrs Nulliparous 71 (18.3%) 66 (15.0%) 0.09 115 (21.4%) 75 (13.1%) <0.001
1–2 / ≤ 20 yrs 29 (7.5%) 25 (5.7%) 75 (13.9%) 72 (12.6%)
1–2 / >20 yrs 105 (27.1%) 132 (30.0%) 191 (35.5%) 233 (40.7%)
≥ 3 / ≤ 20 yrs 73 (18.8%) 64 (14.5%) 82 (15.2%) 91 (15.9%)
≥ 3 / >20 yrs 110 (28.4%) 153 (34.8%) 75 (13.9%) 101 (17.7%)
Missing 13 29 1 0
Ovarian cancer family history Yes 51 (13.1%) 33 (7.4%) 0.01 48 (8.9%) 31 (5.4%) 0.02
No 338 (86.9%) 411 (92.6%) 491 (91.1%) 541 (94.6%)
Missing 12 25 0 0
Ovarian or breast cancer family history Yes 168 (43.2%) 189 (42.6%) 0.86 202 (37.5%) 195 (34.1%) 0.24
No 221 (56.8%) 255 (57.4%) 337 (62.5%) 377 (65.9%)
Missing 12 25 0 0
Smoking, pack years None 236 (64.8%) 285 (68.3%) 0.28 300 (57.6%) 293 (53.4%) 0.37
<=20 72 (19.8%) 84 (20.1%) 132 (25.3%) 150 (27.3%)
>20 56 (15.4%) 48 (11.5%) 89 (17.1%) 106 (19.3%)
Missing 37 52 18 23
Mayo Clinic Cases (N=401) Duke University Cases (N=539)
Histology Serous 242 (60.5%) 331 (61.8%)
Mucinous 28 (7%) 64 (11.9%)
Endometrioid 65 (16.3%) 65 (12.1%)
Clear Cell 23 (5.8%) 33 (6.2%)
Other 42 (10.5%) 43 (8%)
Missing 1 3
Stage I 102 (25.9%) 189 (35.6%)
II 29 (7.4%) 41 (7.7%)
III 205 (52%) 281 (52.9%)
IV 58 (14.7%) 20 (3.8%)
Missing 7 8
Grade 0 62 (15.7%) 127 (25.3%)
1 13 (3.3%) 52 (10.4%)
2 42 (10.7%) 121 (24.2%)
3 156 (39.6%) 193 (38.5%)
4 121 (30.7%) 8 (1.6%)
Missing 7 38
Behavior Invasive 339 (84.5%) 410 (76.2%)
Borderline 62 (15.5%) 128 (23.8%)
Missing 0 1
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Data are counts (percentage) unless otherwise indicated; p-values are from t-test for continuous variables and Chi square test for categorical variables; family history indicates first or second degree relative.

No associations between SNP genotypes and ovarian cancer risk were seen in the current study (Table 3 about here). In the 8q24 region, SNPs previously associated with increased risk (rs10505477 and rs6983267) revealed invasive cancer per-allele ORs of 0.95 (95% CI 0.82–1.09, p-trend=0.46) and 0.97 (95% CI 0.84–1.12, p-trend=0.69), respectively. Thus, these results contradict prior findings from the first report (OR 1.14, 95% CI 1.04–1.23, p-trend<0.01; OR 1.11, 95% CI 1.03–1.20, p-trend<0.01, respectively) (Ghoussaini et al., 2008), but are consistent with other results for rs6983267 (OR 1.00, 95% CI 0.81–1.23, p-trend=0.10) (Wokolorczyk et al., 2008). Our null invasive cancer results for 8q24 SNPs rs13281615 (OR 0.92, 95% CI 0.74–1.15, p-trend=0.48), and rs1447295 (OR 0.97, 95% CI 0.85–1.12, p-trend=0.72) are also consistent with results from prior studies (Ghoussaini et al., 2008; Song, Ramus, Kjaer et al., 2009; Wokolorczyk et al., 2009). Analyses also failed to reveal associations between any of the 23 selected 8q24 SNPs and risk of serous invasive disease. To examine potential heterogeneity due to sample characteristics or statistical methods, we repeated analyses restricted to self-reported white non-Hispanic women and used minimal covariate adjustments. No suggestion of association with increased risk was observed for previously-reported SNPs (Table 4 about here) or for any other 8q24 SNPs (data not shown). In the 9p24 region, no SNPs were associated with risk of ovarian cancer overall or with invasive or invasive serous disease (p-values > 0.10; Table 3 about here).

Table 3.

8q24 and 9p24 polymorphisms and covariate-adjusted risk of epithelial ovarian cancer

All Cases Invasive Cases Invasive Serous Cases
Ordinal Model OR (95% CI) Ordinal Model OR (95% CI) Ordinal Model OR (95% CI)
Region rsid kb to next MAF per-allele p-value per-allele p-value per-allele p-value
8q24.21.a rs10808550 481.9 0.16 0.97 (0.81–1.16) 0.73 0.96 (0.79–1.16) 0.68 0.92 (0.74–1.16) 0.50
rs13254738 2.5 0.33 1.01 (0.88–1.17) 0.84 0.98 (0.85–1.14) 0.83 0.96 (0.80–1.15) 0.65
rs6983561 18.0 0.07 0.93 (0.70–1.23) 0.61 1.00 (0.74–1.36) 0.98 0.86 (0.60–1.25) 0.43
rs16901979 230.7 0.07 0.95 (0.72–1.26) 0.73 1.04 (0.76–1.41) 0.82 0.87 (0.59–1.26) 0.45
rs13281615 51.5 0.40 1.01 (0.88–1.15) 0.90 0.97 (0.85–1.12) 0.72 0.94 (0.80–1.11) 0.48
rs16902149 0.3 0.07 1.22 (0.94–1.57) 0.13 1.28 (0.98–1.68) 0.07 1.14 (0.82–1.59) 0.42
rs10505477 2.1 0.48 0.99 (0.87–1.13) 0.87 0.95 (0.82–1.09) 0.46 0.90 (0.76–1.06) 0.22
rs10808555 1.9 0.33 0.99 (0.86–1.14) 0.93 0.99 (0.86–1.15) 0.92 1.11 (0.93–1.32) 0.25
rs10505475 1.8 0.06 1.11 (0.85–1.45) 0.46 1.11 (0.83–1.48) 0.47 1.15 (0.82–1.60) 0.43
rs6983267 10.3 0.47 1.01 (0.88–1.15) 0.90 0.97 (0.84–1.12) 0.69 0.92 (0.78–1.09) 0.35
rs10956368 4.4 0.41 1.02 (0.89–1.16) 0.80 1.07 (0.93–1.24) 0.33 1.12 (0.95–1.33) 0.17
rs4871789 0.6 0.50 1.00 (0.88–1.14) 0.99 0.95 (0.83–1.09) 0.46 0.94 (0.80–1.11) 0.47
rs6998061 0.1 0.40 0.98 (0.85–1.12) 0.74 0.93 (0.81–1.08) 0.34 0.92 (0.78–1.09) 0.35
rs13274084 0.5 0.13 1.01 (0.83–1.22) 0.92 1.02 (0.84–1.26) 0.82 0.94 (0.74–1.21) 0.64
rs9297754 5.7 0.22 0.99 (0.84–1.16) 0.92 1.03 (0.87–1.22) 0.71 1.05 (0.86–1.28) 0.66
rs7005829 5.2 0.28 0.99 (0.86–1.14) 0.90 1.01 (0.87–1.18) 0.88 1.01 (0.85–1.21) 0.87
rs9297756 0.8 0.14 0.98 (0.81–1.18) 0.82 1.00 (0.82–1.21) 0.98 1.08 (0.86–1.36) 0.49
rs6999921 130.0 0.09 1.00 (0.79–1.25) 0.98 1.01 (0.79–1.28) 0.96 0.92 (0.68–1.24) 0.59
rs12334695 4.2 0.38 0.92 (0.81–1.05) 0.20 0.95 (0.82–1.09) 0.45 0.94 (0.80–1.11) 0.50
rs10109622 3.5 0.25 0.97 (0.83–1.13) 0.68 0.98 (0.83–1.14) 0.76 0.98 (0.80–1.19) 0.82
rs10094059 3.9 0.26 0.97 (0.84–1.12) 0.69 0.94 (0.81–1.10) 0.45 0.95 (0.79–1.14) 0.57
rs9643221 19.6 0.21 0.97 (0.82–1.14) 0.68 0.92 (0.77–1.09) 0.34 0.94 (0.77–1.15) 0.54
rs1447295 n.a. 0.12 0.96 (0.78–1.18) 0.72 0.92 (0.74–1.15) 0.48 0.92 (0.71–1.20) 0.53
9p24.1.b rs12237914 4.0 0.38 1.09 (0.96–1.25) 0.19 1.08 (0.94–1.24) 0.30 1.11 (0.94–1.31) 0.23
rs17705436 14.4 0.22 0.98 (0.84–1.15) 0.85 0.99 (0.84–1.17) 0.88 1.09 (0.90–1.32) 0.40
rs10491835 3.6 0.17 1.03 (0.87–1.22) 0.75 1.02 (0.85–1.22) 0.85 0.95 (0.76–1.18) 0.63
rs3847262 4.0 0.06 1.13 (0.87–1.48) 0.36 1.21 (0.91–1.60) 0.18 0.93 (0.65–1.32) 0.67
rs721352 2.9 0.34 1.00 (0.88–1.15) 0.94 1.01 (0.87–1.17) 0.89 1.01 (0.85–1.20) 0.91
rs7850988 22.6 0.26 0.98 (0.85–1.14) 0.81 0.99 (0.85–1.15) 0.86 1.06 (0.89–1.27) 0.50
rs16924434 7.3 0.11 0.89 (0.72–1.10) 0.27 0.91 (0.73–1.13) 0.40 1.02 (0.80–1.32) 0.85
rs719725 42.6 0.37 0.92 (0.81–1.05) 0.24 0.93 (0.81–1.07) 0.33 1.04 (0.88–1.22) 0.66
rs7865955 208.4 0.45 0.97 (0.85–1.10) 0.62 0.98 (0.86–1.13) 0.81 1.02 (0.87–1.20) 0.80
rs1821892 361.0 0.15 1.04 (0.87–1.25) 0.65 1.01 (0.83–1.22) 0.93 0.95 (0.76–1.19) 0.67
rs1340513 69.3 0.25 0.97 (0.83–1.12) 0.66 0.97 (0.83–1.14) 0.73 0.96 (0.80–1.16) 0.69
rs1407856 n.a. 0.17 0.96 (0.81–1.15) 0.68 1.01 (0.84–1.21) 0.93 1.10 (0.90–1.36) 0.36
Open in a new tab

Kb to previous represents distance in kilo-base pairs between SNPs; MAF, minor allele frequency among controls; adjusted for study site, population structure, age area of residence, body mass index, hormone therapy use, oral contraceptive use, parity, and age at first birth.

Table 4.

8q24 SNPs and risk of invasive ovarian cancer in self-reported white non-Hispanic women across multiple studies

Ghoussaini et al 2008 Wokolorczyk et al 2008 Wokolorczyk et al., 2009 Song et al 2009 Current Analysis
N Cases 1,975 618 274 2,502 671
N Controls 3,411 1,019 682 3,892 939
Studies MAL, SEA, STA, UKO POL1 POL1 AOS, MAL, SEA, STA, UKO, USC MAY, NCO
Adjustments Study site None None Study site Study site
rsid kb to next OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
rs13254738 2.5 1.02 (0.94–1.11) 0.64 -- -- -- -- 0.98 (0.84–1.14) 0.77
rs6983561 18.0 0.90 (0.72–1.13) 0.36 -- -- -- -- -- -- 1.13 (0.77–1.66) 0.53
rs16901979 230.7 0.89 (0.71–1.11) 0.30 -- -- -- -- -- -- 1.15 (0.78–1.69) 0.48
rs13281615 51.8 0.99 (0.91–1.07) 0.75 -- -- -- -- 0.99 (0.92–1.06) 0.69 1.00 (0.87–1.15) 1.00
rs10505477 5.9 1.14 (1.04–1.23) <0.01 -- -- -- -- -- -- 0.94 (0.82–1.08) 0.40
rs6983267 71.7 1.11 (1.03–1.20) <0.01 1.00 (0.81–1.23) 0.10 -- -- -- -- 0.95 (0.83–1.09) 0.46
rs1447295 n.a. 1.07 (0.93–1.22) 0.35 -- -- 1.00 (0.70–1.30) 1.00 -- -- 1.00 (0.79–1.27) 0.98
Open in a new tab

Citations provided in References (Ghoussaini et al., 2008; Song, Ramus, Kjaer et al., 2009; Wokolorczyk et al., 2008; Wokolorczyk et al., 2009); study names based on Ovarian Cancer Association Consortium study acronyms: MAL, Malignant Ovarian Cancer Study (Copenhagen, Denmark); SEA, SEARCH Cambridge UK (UK); STA, Genetic Epidemiology of Ovarian Cancer Study (California, USA); UKO, United Kingdom Ovarian Cancer Population Study (UK); POL1, Polish Ovarian Cancer Study (Poland); AOS, Australian Ovarian Cancer Study (Australia); USC, Los Angeles County Case-Control Studies of Ovarian Cancer (Los Angeles, USA); MAY, Mayo Clinic Ovarian Cancer Study (Upper Midwest, USA); NCO, North Carolina Ovarian Cancer Study (North Carolina, USA); kb to next represents distance in kilo-base pairs between SNPs; per-allele ORs are shown; pair-wise r2>0.90 indicated by dotted lines (based on self-reported white non-Hispanic controls in current analysis; rs6983561-rs16901979 r2=0.98, rs6983267-rs10505477 r2=0.91); all other pair-wise r2<0.67; only SNPs analyzed in more than one report are shown.

DISCUSSION

Association studies have highlighted the undisputed importance of variation in the 8q24.21.a chromosomal region in etiology of breast cancer, prostate cancer, and colorectal cancer (Garcia-Closas et al., 2008; Ghoussaini et al., 2008; Gruber et al., 2007; Gudmundsson et al., 2007; Haiman et al., 2007; Poynter et al., 2007; Salinas et al., 2008; Schumacher et al., 2007; Suuriniemi et al., 2007; Tenesa et al., 2008; Tuupanen et al., 2009; Yeager et al., 2007; Zanke et al., 2007). Growing evidence, at least in colorectal cancer, suggests that rs6983267 lies in a transcriptional enhancer and that the risk G allele increases binding of the transcription factor TCF4 (also called TCF7L2) (Pomerantz et al., 2009; Tuupanen et al., 2009). TCF4 interacts with β-catenin to activate transcription of Wnt target genes, thus a connection between inherited associations and cancer-related functional consequences including possible interaction with the MYC promoter (335 kb downstream) is emerging (Pomerantz et al., 2009; Tuupanen et al., 2009). Somatic amplifications at 8q are trademarks of prostate tumors (Cher et al., 1996; van Duin et al., 2005; Visakorpi et al., 1995), indicating that 8q24 risk variants may lead to amplification of a larger chromosomal region, which contains the protooncogene c-Myc (Haiman et al., 2007; Harismendy & Frazer, 2009; Sole et al., 2008; Witte, 2007). The 9p24.1.b chromosomal region has also been shown to contain colorectal cancer associated SNPs (Poynter et al., 2007; Zanke et al., 2007), although mechanisms are unknown.

In ovarian cancer, seven 8q24.21.a SNPs (rs13254738, rs6983561, rs16901979, rs13281615, rs10505477, rs6983267, and rs1447295) have been evaluated in more than one report, including the current analysis (Ghoussaini et al., 2008; Song, Ramus, Kjaer et al., 2009; Wokolorczyk et al., 2008; Wokolorczyk et al., 2009). The first association study of 1,975 invasive ovarian cancer cases and 3,411 controls found evidence of the 8q24 ovarian cancer susceptibility SNPs rs10505477, rs10808556, and rs6983267 (Ghoussaini et al., 2008), but another examination of 618 invasive cases and 1,019 controls found no association with rs6983267 (OR 1.00, 95% CI 0.75–1.30, p-trend=0.10) (Wokolorczyk et al., 2008) and other reports at 8q24 SNPs were null (Ghoussaini et al., 2008; Song, Ramus, Kjaer et al., 2009; Wokolorczyk et al., 2008; Wokolorczyk et al., 2009). Additionally, no endometrial cancer 8q24 susceptibility loci were revealed in a recent study (Setiawan et al., 2007), suggesting that not all cancers will have an 8q24 association. The 9p24 region has not yet been targeted in gynecologic cancer studies; our data suggest that additional study of this region in ovarian cancer is not warranted.

This analysis evaluated the largest number of 8q24.21.a SNPs (N=23) in ovarian cancer to date. Although associations were non-significant, it is also noteworthy that rs10505477 and rs6983267 risk estimates were close to 1.0, consistent with a prior report of rs6983267 (Wokolorczyk et al., 2008), but contradicting the larger first report (Ghoussaini et al., 2008). Our smaller sample size is a concern; however, current risk estimates were also inconsistent with increased risk. Differing analytical approaches and study populations could also contribute to the opposing 8q24 results; yet, our analyses of invasive cancer in white non-Hispanic women with study site as the only covariate also yielded no suggestion of association with risk of ovarian cancer. These results indicate that differing covariate adjustments, including our adjustment for population structure, do not account for the contradictory results. Based on data from the Ovarian Cancer Association Consortium (Song et al., 2006), cases recruited at the largest site in the first report may have longer survival times than other studies. Thus, SNPs in 8q24.21.a may confer risk of invasive ovarian cancer only among women with longer survival times; however, this situation is unlikely. Additionally, it is likely that case populations have varied histological distributions (Goode et al., 2009). Although risk estimates from other study populations have not been reported by histological subtype, our results for women with serous disease were also null and non-suggestive. Finally, a true association may exist only between ovarian cancer risk and rs10808556, which we did not assess. However, because r2 ≥ 0.65 with this SNP and both rs10505477 and rs6983267 (Ghoussaini et al., 2008), a modest signal would likely have been detected in our analysis.

In conclusion, SNPs in 9p24.1.b are not worthy of follow-up in ovarian cancer, and SNPs in 8q24.21.a are increasingly unlikely to represent ovarian cancer susceptibility alleles. Thus, much remains to be learned about the cancer site-specific role that variants in these regions play in carcinogenic processes, and the search for additional ovarian cancer loci must continue.

ACKNOWLEDGEMENTS

This work was supported by the National Cancer Institute [R01 CA122443, R01 CA88868, and R01 CA76016], the Ovarian Cancer Research Fund, and the Mayo Foundation. We thank Mr. Matt Kosel for statistical analysis, Dr. Paul P.D. Pharoah for advice on SNP selection, Ms. Ashley Pitzer and Ms. Karin Goodman for subject recruitment, and Ms. Katelyn Goodman for assistance with preparation of Tables and Figures.

Footnotes

CONFLICT OF INTEREST

The authors have no conflicts of interest.

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