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Erschienen in: Pathology & Oncology Research 2/2015

Open Access 01.04.2015 | Research

Replication Study for the Association of Seven Genome- Gwas-Identified Loci With Susceptibility to Ovarian Cancer in the Polish Population

verfasst von: Adrianna Mostowska, Stefan Sajdak, Piotr Pawlik, Janina Markowska, Monika Pawałowska, Margarita Lianeri, Paweł P. Jagodzinski

Erschienen in: Pathology & Oncology Research | Ausgabe 2/2015

Abstract

We investigated the previously-demonstrated association of seven genome-wide association studies (GWAS) single nucleotide polymorphisms (SNPs), including rs2072590 (HOXD-AS1), rs2665390 (TIPARP), rs10088218 and rs10098821 (8q24), rs3814113 (9p22), rs9303542 (SKAP1) and rs2363956 (ANKLE1), as risk factors of epithelial ovarian tumors (EOTs). These SNPs were genotyped in two hundred seventy three patients with EOTs and four hundred sixty four unrelated healthy females from the Polish population. We observed the lowest p values of the trend test for the 9p22 rs3814113 and 8q24 rs10098821 SNPs in patients with all subtypes of ovarian cancer (ptrend = 0.010 and ptrend = 0.014, respectively). There were also significant p values for the trend of the 9p22 rs3814113 and the 8q24 rs10098821 SNPs for serous histological subtypes of ovarian cancer (ptrend = 0.006, ptrend = 0.033, respectively). Moreover, stratification of the patients based on their histological type of cancer demonstrated, in the dominant hereditary model, a significant association of the 9p22 rs3814113 SNP with serous ovarian carcinoma OR = 0.532 (95 % CI = 0.342 - 0.827, p = 0.005, pcorr = 0.035). Despite the relatively small sample size of cases and controls, our studies confirmed some of the previously-demonstrated GWAS SNPs as genetic risk factors for EOTs.
Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1007/​s12253-014-9822-6) contains supplementary material, which is available to authorized users.

Introduction

Epithelial ovarian tumors (EOTs) are currently the leading cause of mortality among gynecological carcinomas in Europe and the United States, causing approximately 4 % of deaths from malignancies in women [1, 2]. This high mortality of EOTs is due to late diagnosis, which results from the nonspecific symptoms in the beginning stages of EOTs and a lack of robust serum biomarkers for EOTs screening [3]. There are recognized factors that can either reduce or increase the risk of EOTs development [416]. Multiparity, breastfeeding, tubal ligation and oral contraceptive use all display a protective role in ovarian cancer development [48]. The risk factors for EOTs include early age of menarche, late age of natural menopause, hormone replacement therapy (HRT), nulliparity , infertility, obesity and some lifestyle factors [813]. Other factors contributing to EOTs development include endometriosis, pelvic inflammatory disease, environmental toxins and geographical location, the latter related to sun exposure and vitamin D production [1316]. However, one of the greatest risk factors for EOTs are inherited genetic components, including a family history of ovarian tumors, especially in first-degree relatives, and a personal history of breast tumors [1721]. The firmly established genetic background of EOTs encompasses certain high-penetrance genes: BRCA1 (3–6 %), BRCA2 (1–3 %), and HNPCC DNA mismatch repair genes (1–2 %) [1921]. However, the genetic variants of high-penetrance genes are involved in less than 40 % of the hereditary susceptibility to EOTs [1921]. This suggests that the development of EOTs may involve low-penetrance risk genes that may account for a variable heritability pattern. in a multigenic EOTs model [1921]. The early events and pathogenesis of ovarian tumorigenesis remain elusive [21]. Three recently conducted genome-wide association studies (GWAS) in patients with EOTs indicated seven risk alleles amounting genome-wide significance, at loci 9p22, 8q24, 2q31, 19p13, 3q25 and 17q21 [2224]. We replicated the distribution of the top seven ovarian cancer susceptibility GWAS SNPs including rs2072590 on 2q31 (HOXD-AS1), rs2665390 on 3q25 (TIPARP), rs10088218 and rs10098821 on 8q24, rs3814113 on 9p22, rs9303542 on 17q21 (SKAP1) and rs2363956 on 19p13 (ANKLE1), in patients with ovarian cancer and controls from a sample of the Polish population.

Material and Methods

Patients and Controls

The patient group consisted of 273 women with histologically diagnosed ovarian carcinoma according to the International Federation of Gynecology and Obstetrics (FIGO). They were enrolled into the study from the University Hospital, Clinic of Gynecological Surgery and Chair of Gynecologic Oncology at Poznan University of Medical Sciences. Histopathological classification, describing the stage, grade and tumor type, was carried out by an experienced pathologist (Table 1). The controls included 464 unrelated healthy female volunteers who were matched by age to the cancer patients (Table 1). The patients and healthy female volunteers were Caucasian from the Wielkopolska area of Poland. Written informed consent was obtained from all participating individuals. The study design was accepted by the Local Ethical Committee of Poznań University of Medical Sciences.
Table 1
Clinical characteristics of ovarian cancer patients and healthy controls
Characteristic
Patients
Controls
(n = 273)
(n = 464)
Mean age ± SD
53.9 ± 9.1
52.8 ± 8.2
Histological grade
 G1
81 (29.7 %)
 
 G2
101 (37.0 %)
 G3
91 (33.3 %)
 Gx
0 (0.0 %)
Clinical stage
 I
104 (38.1 %)
 
 II
43 (15.8 %)
 III
91 (33.3 %)
 IV
35 (12.8 %)
Histological type
 Serous
97 (35.5 %)
 
 Mucinous
30 (11.0 %)
 Endometrioid
53 (19.4 %)
 Clear cell
26 (9.5 %)
 Brenne
0 (0.0 %)
 Mixed
24 (8.8 %)
 Solid
18 (6.6 %)
 Untyped carcinoma
25 (9.2 %)

Genotyping

Genomic DNA was obtained from peripheral blood leucocytes by salt extraction. DNA samples were genotyped for the seven SNPs: intronic rs2072590 on 2q31 (HOXD-AS1), intronic rs2665390 on 3q25 (TIPARP), rs10088218 and rs10098821 on 8q24, rs3814113 on 9p22, intronic rs9303542 on 17q21 (SKAP1) and missense rs2363956 on 19p13 (Leu184Trp, ANKLE1) (Supplemental Table 1). SNPs were selected based on the highest association in GWAS studies [2224]. Genotyping of the HOXD-AS1 rs2072590, TIPARP rs2665390, 8q24 rs10088218 and rs10098821, SKAP1 rs9303542 and ANKLE1 rs2363956 was performed by high resolution melting curve analysis (HRM) on the LightCycler 480 system (Roche Diagnostics, Mannheim, Germany (Supplemental Table 2). Genotyping of the 9p22 rs3814113 SNP was performed by PCR, followed by appropriate restriction enzyme digestion (PCR-RFLP) according to the manufacturer’s instructions (Fermentas, Vilnius, Lithuania). Primer sequences and conditions for HRM and PCR-RFLP analyses are presented in Supplemental Table 2. Genotyping quality was assessed by commercial sequencing of approximately 10 % randomly selected samples.

Statistical Analysis

Hardy-Weinberg equilibrium (HWE) was evaluated by Pearson’s goodness-of-fit Chi-squared (χ2) statistic. The data were tested for association with ovarian cancer using the Cochran-Armitage trend test. The distinction in the allele and genotype frequencies between cancer patients and healthy female volunteers were determined using standard χ2 or Fisher tests. The odds ratio (OR) and associated 95 % confidence intervals (95%CI) were also calculated. SNPs were assessed under recessive and dominant inheritance models. To adjust for the multiple testing, we used a Bonferroni correction. High order gene-gene interactions among all tested polymorphic loci were evaluated by the multifactor dimensionality reduction (MDR) approach (MDR version 2.0 beta 5) [25]. Based on the obtained testing balanced accuracy and cross-validation consistency values, the best statistical gene-gene interaction models were established. A 1000-fold permutation test was used to assess the statistical significance of MDR models (MDR permutation testing module 0.4.9 alpha).

Results

Contribution of rs2072590 (HOXD-AS1), rs2665390 (TIPARP), rs10088218 and rs10098821 (8q24), rs3814113 (9p22), rs9303542 (SKAP1) and rs2363956 (ANKLE1) SNPs to Ovarian Cancer Development

The prevalence of HOXD-AS1, TIPARP, 8q24, 9p22, SKAP1 and ANKLE1 genotypes did not display deviation from HWE between the patient and control groups (p > 0.05). The number of genotypes, OR, and 95 % CI values for the seven HOXD-AS1, TIPARP, 8q24, 9p22, SKAP1 and ANKLE1 polymorphisms are presented in Table 2. The lowest p values of the trend test in patients with all histological EOT subtypes were found for the 9p22 rs3814113 and 8q24 rs10098821 SNPs (ptrend = 0.010 and ptrend = 0.014, respectively) (Table 2). Moreover, we observed significant p values of the trend for the 9p22 rs3814113 and 8q24 rs10098821SNPs for serous histological subtypes of ovarian cancer (ptrend = 0.006 and ptrend = 0.033, respectively) (Table 2).
Table 2
Associations of nucleotide variants identified by GWAS with the risk of ovarian cancer
Chr
rs no.
Allelesa
MAFb
Genotypes casesc
Genotypes controlsc
pgenotypic value
ptrend value
pallelic value
ORdominant (95 % CI)d; p value
ORrecessive(95 % CI)e; p value
2q31
rs2072590
G / t
0.35
All
116 / 115 / 41
198 / 207 / 59
0.633
0.652
0.686
1.001 (0.740–1.355); 0.995
1.218 (0.793–1.873); 0.368
    
Serous
38 / 43 / 16
 
0.579
0.343
0.379
1.156 (0.739–1.808); 0.526
1.356 (0.743–2.475); 0.320
    
Mucinous
11 / 16 / 3
 
0.644
0.797
0.905
1.286 (0.598–2.764); 0.519
0.763 (0.224–2.594); 1.000f
    
Endometrioid
28 / 15 / 10
 
0.067
0.690
0.762
0.665 (0.376–1.175) ; 0.159
1.596 (0.761–3.348); 0.212
    
Clear cell
9 / 11 / 6
 
0.301
0.183
0.230
1.406 (0.614–3.221); 0.418
2.059 (0.794–5.338); 0.130
    
Mixed
11 / 10 / 3
 
0.952
0.813
0.933
0.880 (0.386–2.005); 0.760
0.981 (0.284–3.390); 1.000f
    
Solid tumor
7 / 9 / 1
 
0.645
0.750
0.891
1.063 (0.398–2.843); 0.903
0.429 (0.056–3.297); 0.708f
    
Untyped
12 / 11 / 2
 
0.748
0.471
0.566
0.806 (0.360–1.806); 0.600
0.597 (0.137–2.598); 0.756f
3q25
rs2665390
c / T
0.09
All
218 / 50 / 2
380 / 77 / 5
0.744
0.715
0.784
1.105 (0.742–1.625); 0.610
0.682 (0.131–3.542); 1.000f
    
Serous
75 / 20 / 1
 
0.619
0.389
0.463
1.298 (0.756–2.226); 0.343
0.962 (0.111–8.333); 1.000f
    
Mucinous
27 / 3 / 0
 
0.522
0.255
0.354f
0.515 (0.153–1.739); 0.452f
N/A
    
Endometrioid
43 / 8 / 0
 
0.740
0.606
0.734
0.862 (0.391–1.903); 0.713
N/A
    
Clear cell
20 / 5 / 1
 
0.425
0.344
0.471
1.390 (0.541–3.571); 0.492
3.656 (0.411–32.504); 0.281f
    
Mixed
17 / 7 / 0
 
0.261
0.240
0.082
1.908 (0.766–4.751); 0.159
N/A
    
Solid tumor
15 / 3 / 0
 
0.906
0.829
0.400f
0.818 (0.234–2.856); 1.000f
N/A
    
Untyped
21 / 4 / 0
 
0.867
0.740
0.791
0.883 (0.295–2.641); 1.000f
N/A
8q24
rs10088218
a / G
0.12
All
223 / 44 / 4
357 / 100 / 7
0.214
0.120
0.137
0.718 (0.491–1.050); 0.086
0.978 (0.284–3.373); 1.000f
    
Serous
80 / 16 / 0
 
0.249
0.118
0.152
0.667 (0.374–1.190); 0.168
N/A
    
Mucinous
26 / 4 / 0
 
0.427
0.193
0.301f
0.513 (0.175–1.504); 0.265f
N/A
    
Endometrioid
42 / 11 / 0
 
0.655
0.566
0.679
0.874 (0.435–1.757); 0.705
N/A
    
Clear cell
21 / 4 / 1
 
0.519
0.874
0.873
0.794 (0.293–2.158); 0.812f
2.611 (0.309–22.066); 0.356f
    
Mixed
19 / 3 / 2
 
0.036
0.642
0.805
0.878 (0.320–2.408); 1.000f
5.935 (1.164–30.263); 0.068f
    
Solid tumor
15 / 2 / 0
 
0.531
0.260
0.418f
0.445 (0.100–1.977); 0.383f
N/A
    
Untyped
20 / 4 / 1
 
0.529
0.953
0.952
0.834 (0.306–2.276); 1.000f
2.720 (0.321–23.020); 0.345
8q24
rs10098821
C / t
0.11
All
233 / 34 / 3
363 / 94 / 6
0.028
0.014
0.016
0.576 (0.382–0.870); 0.008
0.856 (0.212–3.451); 1.000f
    
Serous
84 / 12 / 0
 
0.099
0.033
0.045
0.519 (0.272–0.988); 0.043
N/A
    
Mucinous
25 / 4 / 0
 
0.558
0.285
0.390f
0.581 (0.196–1.708); 0.481f
N/A
    
Endometrioid
44 / 9 / 0
 
0.583
0.358
0.451
0.743 (0.351–1.576); 0.435f
N/A
    
Clear cell
25 / 1 / 0
 
0.093
0.033
0.036f
0.145 (0.019–1.085); 0.025f
N/A
    
Mixed
19 / 3 / 2
 
0.023
0.514
0.667
0.955 (0.348–2.623); 1.000f
6.924 (1.321–36.304); 0.054f
    
Solid tumor
16 / 1 / 0
 
0.293
0.122
0.165f
0.227 (0.030–1.732); 0.141f
NA
    
Untyped
20 / 4 / 1
 
0.488
0.905
0.905
0.908 (0.332–2.479); 1.000f
3.174 (0.367–27.435); 0.310f
9p22
rs3814113
c / T
0.41
All
123 / 114 / 35
167 / 213 / 82
0.033
0.010
0.009
0.696 (0.505–0.930); 0.015
0.684 (0.446–1.050); 0.081
    
Serous
50 / 36 / 11
 
0.016
0.006
0.006
0.532 (0.342–0.827); 0.005
0.593 (0.303–1.160); 0.123
    
Mucinous
12 / 12 / 6
 
0.809
0.905
0.903
0.849 (0.399–1.806); 0.671
1.159 (0.459–2.925); 0.755
    
Endometrioid
19 / 24 / 9
 
0.996
0.936
0.935
0.983 (0.542–1.784); 0.956
0.970 (0.455–2.068); 0.937
    
Clear cell
12 / 11 / 3
 
0.524
0.257
0.310
0.661 (0.299–1.461); 0.303
0.605 (0.177–2/062); 0.596f
    
Mixed
9 / 12 / 3
 
0.800
0.656
0.762
0.944 (0.404–2.203); 0.893
0.662 (0.193–2.272); 0.782f
    
Solid tumor
10 / 7 / 1
 
0.178
0.064
0.085
0.453 (0.175–1.170); 0.094
0.273 (0.036–2.078); 0.335f
    
Untyped
11 / 12 / 2
 
0.422
0.226
0.277
0.721 (0.320–1.623); 0.427
0.403 (0.093–1.744); 0.282f
17q21
rs9303542
A / g
0.25
All
134 / 123 / 15
261 / 175 / 28
0.134
0.162
0.193
1.324 (0.981–1.788); 0.067
0.909 (0.476–1.734); 0.772
    
Serous
54 / 36 / 6
 
0.997
0.975
0.975
1.000 (0.642–1.558); 1.000
1.038 (0.418–2.581); 0.936
    
Mucinous
17 / 12 / 1
 
0.823
0.785
0.907
0.983 (0.467–2.072); 0.964
0.537 (0.071–4.089); 1.000f
    
Endometrioid
24 / 26 / 3
 
0.270
0.230
0.285
1.554 (0.876–2.751); 0.128
0.934 (0.274–3.185); 1.000f
    
Clear cell
12 / 11 / 3
 
0.414
0.207
0.274
1.500 (0.679–3.314); 0.313
2.031 (0.575–7.179); 0.222f
    
Mixed
9 / 15 / 0
 
0.039
0.315
0.413
2.143 (0.919–4.997); 0.072
N/A
    
Solid tumor
9 / 9 / 0
 
0.388
0.988
0.988
1.286 (0.501–3.299); 0.600
N/A
    
Untyped
9 / 14 / 2
 
0.138
0.076
0.112
2.286 (0.990–5.280); 0.047
1.354 (0.304–6.038); 0.660f
19p13
rs2363956
G / t
0.49
All
56 / 154 / 62
115 / 244 / 105
0.196
0.399
0.451
1.271 (0.885–1.825); 0.193
1.009 (0.706–1.443); 0.959
    
Serous
17 / 53 / 26
 
0.235
0.139
0.169
1.531 (0.870–2.694); 0.137
1.270 (0.770–2.094); 0.348
    
Mucinous
7 / 18 / 5
 
0.559
0.738
0.837
1.083 (0.453–2.590); 0.858
0.684 (0.255–1.831); 0.650f
    
Endometrioid
13 / 28 / 12
 
0.948
0.971
0.979
1.104 (0.524–1.962); 0.967
1.001 (0.507–1.974); 0.998
    
Clear cell
8 / 11 / 7
 
0.719
0.911
0.906
0.741 (0.314–1.751); 0.493
1.260 (0.515–3.079); 0.612
    
Mixed
6 / 17 / 1
 
0.059
0.203
0.265
0.989 (0.383–2.551); 0.981
0.149 (0.020–1.114); 0.039f
    
Solid tumor
1 / 12 / 5
 
0.145
0.146
0.206
5.602 (0.737–42.578); 0.088f
1.315 (0.458–3.774); 0.574f
    
Untyped
4 / 15 / 6
 
0.512
0.476
0.579
1.730 (0.582–5.146); 0.473f
1.080 (0.420–2.774); 0.873
N/A not applicable
Statistically significant results for dominan and recessive model are highlighted in bold (p < 0.00714)
aUppercase denotes the more frequent allele in the control samples
bMAF, minor allele frequency calculated from the control samples
cThe order of genotypes: DD / Dd / dd (d is the minor allele in the control samples)
dDominant model: dd + Dd vs DD (d is the minor allele)
eRecessive model: dd vs Dd + DD (d is the minor allele)
fFisher exact test
The statistical significance for multiple testing determined by correction of gene number was p = 0.007. Therefore, none of the seven HOXD-AS1, TIPARP ,8q24, 9p22, SKAP1,and ANKLE1 polymorphisms displayed a significant association with all subtypes of ovarian cancer either in dominant or recessive inheritance models (Table 2). Stratification of the patients based on histological type of cancer revealed, in the dominant hereditary model, a significant association of the 9p22 rs3814113 SNP with serous ovarian carcinoma, OR = 0.532 (95 % CI = 0.342 - 0.827, p = 0.005). However, the 9p22 rs3814113 polymorphism did not display significant association with other histological types and any histological grade and clinical stage. Furthermore, there was no significant association between the HOXD-AS, TIPARP, 8q24, SKAP1 and ANKLE1 polymorphisms with clinical stage, histological grade and subtype.

MDR Analysis of Gene-gene Interactions among the rs2072590 (HOXD-AS1), rs2665390 (TIPARP), rs10088218 and rs10098821 (8q24), rs3814113 (9p22), rs9303542 (SKAP1) and rs2363956 (ANKLE1) SNPs

Exhaustive MDR analysis assessing two- to four-loci combinations of all studied SNPs for each comparison did not reveal statistical significance in predicting susceptibility to EOTs development (Table 3). The best combination of possibly interactive polymorphisms was observed for 8q24 rs10098821 and 9p22 rs3814113 (testing balanced accuracy = 0.516 %, cross validation consistency of 3 out of 10, permutation test p = 0.682).
Table 3
Results of gene-gene interactions analyzed by MDR method
Polymorphisms
Testing balanced accuracy
Cross validation consistency
p valuea
8q24_rs10098821, 9p22_rs3814113
0.516
60 %
0.682
8q24_rs10098821, 9p22_rs3814113, 17q21_rs9303542
0.514
40 %
0.708
2q31_rs2072590, 9p22_rs3814113, 17q12_rs757210, 19p13_rs2363956
0.507
70 %
0.783
aSignificance of accuracy (empirical p value based on 1,000 permutations)

Discussion

Family and twin investigations have provided us with concrete evidence indicating that there are inherited genetic factors involved in susceptibility to the development of EOTs [17, 18]. GWAS have been performed in order to identify common low-penetrance ovarian cancer susceptibility genes [2224]. The GWAS conducted by Song et al. (2009) demonstrated the 9p22 rs3814113 SNP to be a significant genetic risk factor contributing to all histological subtypes of EOTs [22]. In addition to this finding, GWAS analysis performed by Goode et al. (2010) found genome-wide significant association for the 3q25 rs2665390, 17q21 rs9303542, 8q24 rs10088218 and 2q31 rs2072590 SNPs with all EOTs subtypes [23]. The GWAS by Bolton et al. (2010) demonstrated that SNPs rs8170 and rs2363956 on 19p13 displayed genome-wide significance for susceptibility of serous ovarian cancer but not all histological subtypes of EOTs [24].
Our follow-up studies, conducted in Caucasian women with ovarian cancer enrolled in the Wielkopolska area of Poland, identify a significant p trend of rs3814113 on 9p22 with all sybtypes of EOTs. In addition to this finding, we observed that rs3814113 on 9p22 may play a protective role from the development of serous histological subtypes of ovarian carcinoma. The stratification of the GWAS by Song et al. (2009) that was based on histological subtypes also indicated that rs3814113 exhibited the greatest association with serous subtypes of EOTs [22]. Moreover, the 9p22 rs3814113 SNP has been demonstrated to be a protective genetic factor of ovarian cancer for carriers of BRCA1 or BRCA2 mutations [26]. There has also been a recent evaluation of the functional role of seven ovarian cancer susceptibility GWAS polymorphisms in association with microRNAs (miRNAs) presence [27]. This study demonstrated the highest numbers of miRNAs, 68 significantly linked to the rs3814113 SNP [27]. Moreover, the rs3814113 polymorphism was significantly associated with miR-17–92 cluster, which is considered the most remarkable cluster involved in tumorigenesis [27]. Additionally, cell carriers of the rs3814113 SNP displayed prominence of several elementary biological pathways such as cellular response to stress, adenyl nucleotide binding, intracellular organelle lumen, and others [27]. Other functional studies assessed the relationship between changeability of gene expression and the presence of seven ovarian cancer susceptibility GWAS SNPs [28]. These studies demonstrated significant association between the 9p22 rs3814113 SNP and changes in the levels of 274 mRNAs [28]. However, the strongest association of the rs3814113 SNP was observed for increased levels of MT1G and ATL2 mRNAs, which respectively encode metallothionein 1G (OMIM *156353) and atlastin GTPase (OMIM *609368) [28].
Our studies also found significant p trend values for the 8q24 rs10098821 SNP for all patients with ovarian cancer, and also specifically for serous histological subtype. The Goode et al. (2010) GWAS analysis also demonstrated a generally greater association of the 8q24 rs10098821 SNPs with serous as compared to other ovarian EOTs subtypes [23]. Moreover, the 8q24 locus was found to be a risk for several malignancies encompassing breast, prostate, and colorectal cancer [29, 30]. A functional association study between GWAS SNPs and whole genome mRNA expression profiles revealed that the 8q24 rs10098821 SNP had the largest number of significant associations, specifically 38 [28]. The study also indicated possible cis-associations between rs10098821 and MYC expression [28]. The 8q24 polymorphisms linked to EOTs and other carcinomas are situated approximately 700 kb 3′ of the MYC protooncogene, and these SNPs probably control the expression of this oncogene distally [28, 31].
Presently, genetic risk evaluation for ovarian cancer can be conducted for subjects with a family history of some cancer and/or BRCA1/2 mutations identified within families. However, the usage of low-penetrance SNPs in screening for the risk of ovarian cancer in various ethnicities has not yet been employed. This is in contrast to colorectal and breast cancers, where combinations of low penetrance risk genetic variants are already employed for susceptibility screening in some populations [32, 33].
It was demonstrated that the 9p22 rs3814113 and 8q24 rs10098821 variants were associated with the risk of EOTs in subjects of European ancestry [22, 23]. In the subjects of non-European ancestry (African or Asian ethnic group), these SNPs did not show statistically significant correlations with the risk of EOTs; however, these results could be due to small sample size [22]. Our study found a significant association of the 9p22 rs3814113 SNP with serous subtypes, and significant trend p-values for the 9p22 rs3814113 and 8q24 rs10098821 SNPs with all EOTs and serous subtypes in Caucasian patients from the Wielkopolska region of Poland. However, our replication studies have been conducted in relatively small patient and control groups, resulting in a possible missed significant association for the other studied SNPs in ovarian cancer. Therefore, this study should be replicated in other independent cohorts to validate the role of low penetrance SNPs in EOTs development and also in their use as screening tools in the evaluation of ovarian cancer susceptibility.

Acknowledgments

Supported by grant No 502-01-01124182-07474, Poznan University of Medical Sciences.

Conflict of interest

The authors declare no conflict of interest.
Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

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Literatur
1.
2.
Zurück zum Zitat Siegel R, Naishadham D, Jemal A, Jemal A, Siegel R, Ward E, Hao Y, Xu J et al (2008) Cancer statistics. CA Cancer J Clin 58:71–96CrossRefPubMed Siegel R, Naishadham D, Jemal A, Jemal A, Siegel R, Ward E, Hao Y, Xu J et al (2008) Cancer statistics. CA Cancer J Clin 58:71–96CrossRefPubMed
3.
Zurück zum Zitat Gurung A, Hung T, Morin J et al (2013) Molecular abnormalities in ovarian carcinoma: clinical, morphological and therapeutic correlates. Histopathology 62:59–70CrossRefPubMed Gurung A, Hung T, Morin J et al (2013) Molecular abnormalities in ovarian carcinoma: clinical, morphological and therapeutic correlates. Histopathology 62:59–70CrossRefPubMed
4.
Zurück zum Zitat Danforth KN, Tworoger SS, Hecht JL et al (2007) Breastfeeding and risk of ovarian cancer in two prospective cohorts. Cancer Causes Control 18:517–523CrossRefPubMed Danforth KN, Tworoger SS, Hecht JL et al (2007) Breastfeeding and risk of ovarian cancer in two prospective cohorts. Cancer Causes Control 18:517–523CrossRefPubMed
5.
Zurück zum Zitat Whittemore AS, Harris R, Itnyre J et al (1992) Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case–control studies. I. Methods. Collaborative Ovarian Cancer Group. Am J Epidemiol 136:1175–1183PubMed Whittemore AS, Harris R, Itnyre J et al (1992) Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case–control studies. I. Methods. Collaborative Ovarian Cancer Group. Am J Epidemiol 136:1175–1183PubMed
6.
Zurück zum Zitat Cibula D, Widschwendter M, Májek O et al (2011) Tubal ligation and the risk of ovarian cancer: review and meta-analysis. Hum Reprod Update 17:55–67CrossRefPubMed Cibula D, Widschwendter M, Májek O et al (2011) Tubal ligation and the risk of ovarian cancer: review and meta-analysis. Hum Reprod Update 17:55–67CrossRefPubMed
7.
Zurück zum Zitat Havrilesky LJ, Moorman PG, Lowery WJ et al (2013) Oral contraceptive pills as primary prevention for ovarian cancer: a systematic review and meta-analysis. Obstet Gynecol 122:139–147CrossRefPubMed Havrilesky LJ, Moorman PG, Lowery WJ et al (2013) Oral contraceptive pills as primary prevention for ovarian cancer: a systematic review and meta-analysis. Obstet Gynecol 122:139–147CrossRefPubMed
8.
Zurück zum Zitat Tsilidis KK, Allen NE, Key TJ et al (2011) Oral contraceptive use and reproductive factors and risk of ovarian cancer in the European Prospective Investigation into Cancer and Nutrition. Br J Cancer 105:1436–1442CrossRefPubMedCentralPubMed Tsilidis KK, Allen NE, Key TJ et al (2011) Oral contraceptive use and reproductive factors and risk of ovarian cancer in the European Prospective Investigation into Cancer and Nutrition. Br J Cancer 105:1436–1442CrossRefPubMedCentralPubMed
9.
Zurück zum Zitat Lacey JV Jr, Mink PJ, Lubin JH et al (2002) Menopausal hormone replacement therapy and risk of ovarian cancer. JAMA 288:334–341CrossRefPubMed Lacey JV Jr, Mink PJ, Lubin JH et al (2002) Menopausal hormone replacement therapy and risk of ovarian cancer. JAMA 288:334–341CrossRefPubMed
10.
Zurück zum Zitat Trabert B, Wentzensen N, Yang HP et al (2012) Ovarian cancer and menopausal hormone therapy in the NIH-AARP diet and health study. Br J Cancer 25:1181–1187CrossRef Trabert B, Wentzensen N, Yang HP et al (2012) Ovarian cancer and menopausal hormone therapy in the NIH-AARP diet and health study. Br J Cancer 25:1181–1187CrossRef
11.
Zurück zum Zitat Pięta B, Chmaj-Wierzchowska K, Opala T (2012) Past obstetric history and risk of ovarian cancer. Ann Agric Environ Med 19:385–388PubMed Pięta B, Chmaj-Wierzchowska K, Opala T (2012) Past obstetric history and risk of ovarian cancer. Ann Agric Environ Med 19:385–388PubMed
13.
Zurück zum Zitat Salehi F, Dunfield L, Phillips KP et al (2008) Risk factors for ovarian cancer: an overview with emphasis on hormonal factors. J Toxicol Environ Health B Crit Rev 11:301–321CrossRefPubMed Salehi F, Dunfield L, Phillips KP et al (2008) Risk factors for ovarian cancer: an overview with emphasis on hormonal factors. J Toxicol Environ Health B Crit Rev 11:301–321CrossRefPubMed
15.
Zurück zum Zitat Lin HW, Tu YY, Lin SY et al (2011) Risk of ovarian cancer in women with pelvic inflammatory disease: a population-based study. Lancet Oncol 12:900–904CrossRefPubMed Lin HW, Tu YY, Lin SY et al (2011) Risk of ovarian cancer in women with pelvic inflammatory disease: a population-based study. Lancet Oncol 12:900–904CrossRefPubMed
16.
Zurück zum Zitat Garland CF, Mohr SB, Gorham ED et al (2006) Role of ultraviolet B irradiance and vitamin D in prevention of ovarian cancer. Am J Prev Med 31:512–514CrossRefPubMed Garland CF, Mohr SB, Gorham ED et al (2006) Role of ultraviolet B irradiance and vitamin D in prevention of ovarian cancer. Am J Prev Med 31:512–514CrossRefPubMed
17.
Zurück zum Zitat Lichtenstein P, Holm NV, Verkasalo PK et al (2000) Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark and Finland. N Engl J Med 343:78–85CrossRefPubMed Lichtenstein P, Holm NV, Verkasalo PK et al (2000) Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark and Finland. N Engl J Med 343:78–85CrossRefPubMed
18.
Zurück zum Zitat Stratton JF, Pharoah P, Smith SK et al (1998) A systematic review and meta-analysis of family history and risk of ovarian cancer. Br J Obstet Gynaecol 105:493–499CrossRefPubMed Stratton JF, Pharoah P, Smith SK et al (1998) A systematic review and meta-analysis of family history and risk of ovarian cancer. Br J Obstet Gynaecol 105:493–499CrossRefPubMed
19.
Zurück zum Zitat Berchuck A, Schildkraut JM, Marks JR et al (1999) Managing hereditary ovarian cancer risk. Cancer 86:2517–2524CrossRefPubMed Berchuck A, Schildkraut JM, Marks JR et al (1999) Managing hereditary ovarian cancer risk. Cancer 86:2517–2524CrossRefPubMed
20.
Zurück zum Zitat Frank TS, Manley SA, Olopade OI et al (1998) Sequence analysis of BRCA1 and BRCA2: correlation of mutations with family history and ovarian cancer risk. J Clin Oncol 16:2417–2425PubMed Frank TS, Manley SA, Olopade OI et al (1998) Sequence analysis of BRCA1 and BRCA2: correlation of mutations with family history and ovarian cancer risk. J Clin Oncol 16:2417–2425PubMed
21.
Zurück zum Zitat Holschneider CH, Berek JS (2000) Ovarian cancer: epidemiology, biology, and prognostic factors. Semin Surg Oncol 19:3–10CrossRefPubMed Holschneider CH, Berek JS (2000) Ovarian cancer: epidemiology, biology, and prognostic factors. Semin Surg Oncol 19:3–10CrossRefPubMed
22.
Zurück zum Zitat Song H, Ramus SJ, Tyrer J et al (2009) A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2. Nat Genet 41:996–1000CrossRefPubMedCentralPubMed Song H, Ramus SJ, Tyrer J et al (2009) A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2. Nat Genet 41:996–1000CrossRefPubMedCentralPubMed
23.
Zurück zum Zitat Goode EL, Chenevix-Trench G, Song H et al (2010) A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24. Nat Genet 42:874–879CrossRefPubMedCentralPubMed Goode EL, Chenevix-Trench G, Song H et al (2010) A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24. Nat Genet 42:874–879CrossRefPubMedCentralPubMed
24.
Zurück zum Zitat Couch FJ, Gaudet MM, Antoniou AC et al (2010) Common variants at 19p13 are associated with susceptibility to ovarian cancer. Nat Genet 42:880–884CrossRef Couch FJ, Gaudet MM, Antoniou AC et al (2010) Common variants at 19p13 are associated with susceptibility to ovarian cancer. Nat Genet 42:880–884CrossRef
25.
Zurück zum Zitat Hahn LW, Ritchie MD, Moore JH (2003) Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 19:376–382CrossRefPubMed Hahn LW, Ritchie MD, Moore JH (2003) Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 19:376–382CrossRefPubMed
26.
Zurück zum Zitat Ramus SJ, Kartsonaki C, Gayther SA et al (2011) Consortium of Investigators of Modifiers of BRCA1/2.Genetic variation at 9p22.2 and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst 103:105–116CrossRefPubMedCentralPubMed Ramus SJ, Kartsonaki C, Gayther SA et al (2011) Consortium of Investigators of Modifiers of BRCA1/2.Genetic variation at 9p22.2 and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst 103:105–116CrossRefPubMedCentralPubMed
27.
Zurück zum Zitat Shen J, Wang D, Gregory SR et al (2012) Evaluation of microRNA expression profiles and their associations with risk alleles in lymphoblastoid cell lines of familial ovarian cancer. Carcinogenesis 33:604–612CrossRefPubMedCentralPubMed Shen J, Wang D, Gregory SR et al (2012) Evaluation of microRNA expression profiles and their associations with risk alleles in lymphoblastoid cell lines of familial ovarian cancer. Carcinogenesis 33:604–612CrossRefPubMedCentralPubMed
28.
Zurück zum Zitat Zhao H, Shen J, Wang D et al (2012) Associations between gene expression variations and ovarian cancer risk alleles identified from genome wide association studies. PLoS One 7:e47962CrossRefPubMedCentralPubMed Zhao H, Shen J, Wang D et al (2012) Associations between gene expression variations and ovarian cancer risk alleles identified from genome wide association studies. PLoS One 7:e47962CrossRefPubMedCentralPubMed
29.
Zurück zum Zitat Ghoussaini M, Song H, Koessler T et al (2008) Multiple loci with different cancer specificities within the 8q24 gene desert. J Natl Cancer Inst 100:962–966CrossRefPubMedCentralPubMed Ghoussaini M, Song H, Koessler T et al (2008) Multiple loci with different cancer specificities within the 8q24 gene desert. J Natl Cancer Inst 100:962–966CrossRefPubMedCentralPubMed
30.
Zurück zum Zitat Gong WF, Zhong JH, Xiang BD et al (2013) Single nucleotide polymorphism 8q24 rs13281615 and risk of breast cancer: meta-analysis of more than 100,000 cases. PLoS One 8:e60108CrossRefPubMedCentralPubMed Gong WF, Zhong JH, Xiang BD et al (2013) Single nucleotide polymorphism 8q24 rs13281615 and risk of breast cancer: meta-analysis of more than 100,000 cases. PLoS One 8:e60108CrossRefPubMedCentralPubMed
32.
Zurück zum Zitat Hawken SJ, Greenwood CM, Hudson TJ et al (2010) The utility andpredictive value of combinations of low penetrance genes forscreening and risk prediction of colorectal cancer. Hum Genet 128:89–101CrossRefPubMedCentralPubMed Hawken SJ, Greenwood CM, Hudson TJ et al (2010) The utility andpredictive value of combinations of low penetrance genes forscreening and risk prediction of colorectal cancer. Hum Genet 128:89–101CrossRefPubMedCentralPubMed
33.
Zurück zum Zitat Park JH, Wacholder S, Gail MH et al (2010) Estimation of effect size distribution from genome-wide association studies an dimplicationsfor future discoveries. NatGenet 42:570–575 Park JH, Wacholder S, Gail MH et al (2010) Estimation of effect size distribution from genome-wide association studies an dimplicationsfor future discoveries. NatGenet 42:570–575
Metadaten
Titel
Replication Study for the Association of Seven Genome- Gwas-Identified Loci With Susceptibility to Ovarian Cancer in the Polish Population
verfasst von
Adrianna Mostowska
Stefan Sajdak
Piotr Pawlik
Janina Markowska
Monika Pawałowska
Margarita Lianeri
Paweł P. Jagodzinski
Publikationsdatum
01.04.2015
Verlag
Springer Netherlands
Erschienen in
Pathology & Oncology Research / Ausgabe 2/2015
Print ISSN: 1219-4956
Elektronische ISSN: 1532-2807
DOI
https://doi.org/10.1007/s12253-014-9822-6

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