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  • Research article
  • Open Access
  • Open Peer Review

Cumulative evidence for relationships between multiple variants of HNF1B and the risk of prostate and endometrial cancers

BMC Medical Genetics201819:128

https://doi.org/10.1186/s12881-018-0640-7

  • Received: 26 April 2018
  • Accepted: 3 July 2018
  • Published:
Open Peer Review reports

Abstract

Background

To provide a synopsis of the current understanding of the association between variants of HNF1B and cancer susceptibility, we conducted a comprehensive research synopsis and meta-analysis to evaluate associations between HNF1B variants and prostate and endometrial cancers.

Results

Eighteen studies totaling 34,937 patients and 55,969 controls were eligible for this meta-analysis. Four variants showed a significant association with the risk of individual cancer. Strong significant associations were found between rs4430796 A and the risk of both prostate cancer (OR = 1.247, p = 2.21 × 10− 77) and endometrial cancer (OR = 1.217, p = 8.98 × 10− 16); the AA, AG genotypes also showed strong significant associations with the risk of prostate cancer (OR1 = 1.517, p = 4.46 × 10− 22; OR2 = 1.180, p = 0.002). There was a strong significant association between rs7501939 G and the risk of prostate cancer (OR = 1.201, p = 9.31 × 10− 31). Strong significant association was found between rs11649743 G (OR = 1.138, p = 1.08 × 10− 12), rs3760511 C (OR = 1.214, p = 1.57 × 10− 19) and the prostate cancer risk;the GG, AG genotypes of rs11649743 also showed strong significant associations with the risk of prostate cancer (OR1 = 1.496, p = 3.32 × 10− 6; OR2 = 1.276, p = 7.82 × 10− 6). All the cumulative epidemiological evidence of associations was graded as strong.

Conclusions

Our study summarizes the evidence and helps to reveal that common variants of HNF1B are associated with risk of prostate and endometrial cancer.

Keywords

  • HNF1B
  • Variants
  • Prostate cancer
  • Endometrial cancer

Background

Human cancers result in Considerable morbidity and mortality. Family history, ethnicity, lifestyle and region are potential risk factors for cancer development [14]. However, family-based and adoption studies have provided major evidence for the role of genes in the development of cancers [57].

Owing to advances in sequencing technologies and genome-wide association studies (GWAS), a large number of genetic variants correlated with various cancers have been identified [8, 9]. Multiple studies have examined the relationship between the hepatocyte nuclear factor-1 beta (HNF1B, formerly known as TCF2) locus (on chromosome 17q12) and cancer risk [1013]. HNF1B is a member of the homeodomain-containing superfamily of transcription factors and is involved in the tissue-specific regulation of many genes expressed in various organs [14] and during embryonic development [15]. Patients with a heterozygous HNF1B deletion exhibit renal disease, elevated liver enzymes, and diabetes [16]. HNF1B is strongly associated with the risks of many cancers, including prostate cancer [10, 17],ovarian cancer [1820],endometrial cancer [12, 21, 22] and lung cancer [13]. Recently, it has been reported that the rs7501939 single-nucleotide polymorphism (SNP) in HNF1B confers a poor overall survival in patients with multiple myeloma [23].

However, fine-mapping studies have revealed a complex genetic architecture of the HNF1B locus, demonstrating that variants of HNF1B and the direction of their effects differ between cancer types. SNPs rs4430796 and rs7501939, are both associated with the prostate cancer risk across many ethnic groups [24]. The same SNPs, are also associated with endometrial cancer risk in women of European background [12]. Yet, the SNP rs757210, in high linkage disequilibrium with rs4430796, is the most strongly associated with serous epithelial ovarian cancer [18].

Here, we collected data related to the associations between HNF1B variants and cancer phenotypes, and performed a comprehensive meta-analysis, involving a total of 34,937 patients and 55,969 controls, to derive more precise estimates of the associations between HNF1B variants and susceptibility to prostate and endometrial cancers.

Methods

Search strategy and inclusion criteria

The US National Library of Medicine’s PubMed, Embase, OMIM, ISI Web of Science, and Chinese National Knowledge Infrastructure (CNKI) databases were searched in a systematic manner to retrieve all genetic association studies of HNF1B variants and cancers published before July 2017. The search strategy was based on a combination of the terms (Hepatocyte nuclear factor-1 beta or HNF1B) and (cancers or tumors). The references of all computer-identified publications were searched for additional studies, and the PubMed option “Related Articles” was also used to search for potentially relevant papers. Searches were performed by two independent reviewers (Yu Tong and Yibin Wang). The language of the publications did not influence article selections.

Studies were included if they met the following criteria. (1) the study reported original data from case-control or cohort studies, (2) the study reported alleles and genotypes for HNF1B variants, and (3) the numbers of subjects possessing each allele and genotype in the cancer and control groups were available. No restrictions were set for the source of controls (general population, clinic, or hospital). Studies were excluded when: (i) they lacked sufficient information; (ii) they were published as letters to editors or conference abstracts; (iii) they were studies about cancer mortality.

Data extraction

Data were extracted independently by two investigators (Yu Tong and Yibin Wang), who used recommended guidelines for reporting on meta-analyses of observational studies. The following data were extracted from the eligible studies: authors, journal title, year of publication, country of origin, selection and characteristics of cases and controls, demographic data, ethnicity of the study population, numbers of eligible and genotyped cases and controls, and genotype distributions in cases, controls, and available subgroups. Furthermore, we examined whether genotype frequencies in control groups conformed to the Hardy-Weinberg equilibrium (HWE) was determined. Any disagreement was adjudicated by a third author (Yi Qu).

Statistical analysis

The odds ratio was used as the metric of choice for each study. To detect overall genetic associations, allele frequencies were computed for studies reporting allele and genotype data. Pooled odds ratios were computed by the fixed effects model and the random effects model based on heterogeneity estimates. Once an overall gene effect was confirmed, the genetic effects and mode of inheritance were estimated using the genetic model-free approach suggested by Minelli et al. We performed Cochran’s Q test and calculated І2 statistic to evaluate heterogeneity between studies. Harbord’s test was performed to evaluate publication bias. Potential small-study bias was evaluated by Egger’s test [25]. Sensitivity analyses were conducted to examine if the significant association would be lost when the first published report was excluded, or studies deviated from HWE in controls were excluded. All analyses were conducted using Stata, version 14.0 (StataCorp, 2017), with the metan, metabias, metacum, and metareg commands.

Venice criteria [26] were applied to evaluate the epidemiological credibility of significant associations identified by meta-analysis. Credibility was defined in three categories: amount of evidence (graded by the sum of test alleles or genotypes among cases and controls: A for > 1000, B for 100–1000, and C for < 100), replication of the association (graded by the heterogeneity statistic: A for I2 < 25%, B for I2 between 25 and 50%, and C for I2 > 50%), and protection from bias (graded as A: there was no observable bias, and bias was unlikely to explain the presence of the association, B: bias could be present, C: bias was evident or was likely to explain the presence of the association, association. C was also assigned to an association with a summary OR less than 1.15, unless the association had been replicated by GWAS or GWAS meta-analysis from collaborative studies. With no evidence of publication bias). Cumulative epidemiological evidence for significant associations was thought to be strong if all three grades were A, moderate if all three grades were A or B, and weak if any grade was C.

To determine whether a significant association could be excluded as a false positive finding, FPRP (false positive report probability) was calculated using the method described by Wacholder et al. [27]. FPRP < 0.05, 0.05 ≤ FPRP ≤0.20, and FPRP > 0.20 were considered strong, moderate, and weak evidence of true association, respectively.

Results

Eligible studies

Our initial database search identified 113 potentially relevant studies. Based on a review of titles and abstracts, 55 articles were retained. The full text of these 55 articles was reviewed in detail, and 18 studies containing 36 datasets were eligible for inclusion in the meta-analysis. The specific process for identifying eligible studies and inclusion and exclusion criteria are summarized in Fig. 1a.
Fig. 1
Fig. 1

Flow diagram of included and excluded studies

Characteristics of the included articles are presented in Allelic associations: 1. Of the 36 datasets, 26 were on prostate cancer [10, 24, 2841]; and10 were on endometrial cancer [42, 43]. All eligible studies had case-control designs. Cases were recruited from hospital patients and controls were mainly healthy individuals recruited from the hospital or community and were unrelated to cases.
Table 1

Characteristics of case-control studies included in a meta-analysis of the association between HNF1B variants and human cancers

Ref

Cancer

Region/Center

Ethnicity

rs4430796 cases/ controls

rs7501939 cases/ controls

rs11649743 cases/ controls

rs3760511 cases/ controls

[31]

prostate

China

Asian

195/160

   

[32]

prostate

Korean

Asian

240/223

240/223

 

240/223

[24]

prostate

USA Europe

Caucasian

10,272/9123

10,247/9100

10,272/9123

10,272/9123

[10]

prostate

CAPS

Caucasian

2874/1708

 

2852/1688

 

[10]

prostate

JHH

Caucasian

1521/479

 

1490/470

 

[10]

prostate

ATBC

Caucasian

901/902

 

927/921

 

[10]

prostate

FPCC

Caucasian

620/618

 

656/656

 

[10]

prostate

HPFS

Caucasian

581/591

 

596/611

 

[10]

prostate

PLCO

Caucasian

1121/1048

 

1166/1093

 

[10]

prostate

ACS

Caucasian

1716/1718

 

1759/1775

 

[28]a

prostate

Iceland

Caucasian

1501/11289

1501/11289

  

[28]

prostate

Netherlands

Caucasian

997/1464

997/1464

  

[28]

prostate

Spain

Caucasian

456/1078

456/1078

  

[28]

prostate

USA

Caucasian

536/514

536/514

  

[29]

prostate

USA

Caucasian

542/473

542/473

  

[30]

prostate

USA

Caucasian

1563/576

1563/576

 

1563/576

[30]

prostate

USA

African

364/353

364/353

 

364/353

[36]

prostate

Japan

Asian

311/1035

   

[40]

prostate

USA

African

454/301

454/301

  

[37]

prostate

China

Asian

105/78

   

[38]

prostate

Japan

Asian

518/323

   

[31]

prostate

USA

Caucasian

754/2713

   

[31]

prostate

CGEM

Caucasian

1176/1101

   

[39]

prostate

Singapore

Asian

289/141

   

[32]

prostate

USA

Caucasian

166/33

   

[41]

prostate

USA

Caucasian

759/790

   

[42]a

endometrial

MEC

Caucasian

106/813

106/813

  

[42]

endometrial

WHI

Caucasian

868/3037

868/3037

  

[42]

endometrial

MEC

African

68/820

68/820

  

[42]

endometrial

WHI

African

35/350

35/350

  

[42]

endometrial

MEC

Asian

121/1204

121/1204

  

[42]

endometrial

WHI

Asian

8/161

8/161

  

[42]

endometrial

MEC

Latino

104/673

104/673

  

[42]

endometrial

WHI

Latino

20/207

20/207

  

[42]

endometrial

MEC

Hawaiian

27/344

27/344

  

[43]

endometrial

Australia and the UK

Caucasian

3048/9528

3048/9528

  

Total

   

34,937/55969

21,305/42508

19,718/16337

12,439/10275

CAPS = CAncer Prostate in Sweden;JHH = The Johns Hopkins Hospital study; ATBC = Beta-Carotene Cancer Prevention Study;FPCC = CeRePP French Prostate Case-Control Study;HPFS = The Health Professionals Follow-up Study;PLCO = Prostate, Lung, Colon and Ovarian (PLCO) Cancer Screening Trial; MEC = Multiethnic Cohort Study; WHI = Women’s Health Initiative; CGEM = Cancer Genetic Markers of Susceptibility Study

aGenome-wide association study (GWAS)

Allelic associations

HNF1B variants and the risk of prostate cancer

rs4430796 G > A and the risk of prostate cancer

All 15 publications were included in the evaluation of the association between the HNF1B rs4430796 and prostate cancer (Allelic associations: 1). A strong significant association with risk of prostate cancer was observed (p = 2.21 × 10− 77, fixed effect OR = 1.247, 95% CI: 1.218, 1.276; Q = 21.98, p = 0.637, I2 = 0.0%, Fig. 2). Sensitivity analyses in Asians (p = 8.32 × 10− 8, fixed effect OR = 1.369, 95% CI: 1.221, 1.536; Q = 2.13, p = 0.712, I2 = 0.0%) and Caucasians (p = 1.21 × 10− 69, fixed effect OR = 1.241, 95% CI: 1.212, 1.271; Q = 17.09, p = 0.517, I2 = 0.0%) demonstrated a pattern similar to that of the full population. However, this effect was weak in the Africans (p = 0.002, fixed effect OR = 1.275, 95% CI: 1.093, 1.487; Q = 0.08, p = 0.777, I2 = 0.0%). No publication bias was found in the eligible studies (Harbord’s test p = 0.253).
Fig. 2
Fig. 2

a Fixed-effects meta-analysis of allele (A versus G) of the HNF1B rs4430796 G > A and prostate cancer. The OR of each study is represented by a square, and the size of the square represents the weight of each study with respect to the overall estimate. 95% CIs are represented by the horizontal lines, and the diamond represents the overall estimate and its 95% CI. b. Fixed-effects meta-analysis of allele (G versus A) of the HNF1B gene rs7501939 A > G and prostate cancer. c. Radom-effects meta-analysis of allele (G versus A) of the HNF1B gene rs11649743 A > G and prostate cancer. d. Fixed-effects meta-analysis of allele (C versus A) of the HNF1B gene rs3760511 A > C and prostate cancer

rs7501939 A > G and the risk of prostate cancer

Six publications were included in the evaluation of the association between the HNF1B rs7501939 and prostate cancer (Table 1). A strong significant association with risk of prostate cancer was observed (p = 9.31 × 10− 31, fixed effect OR = 1.201, 95% CI: 1.164, 1.239; Q = 8.24, p = 0.510, I2 = 0.0%, Fig. 2b). Sensitivity analyses in Caucasians demonstrated a pattern similar to that of the full population (p = 1.04 × 10− 29, fixed effect OR = 1.203, 95% CI: 1.165, 1.242; Q = 5.04, p = 0.539, I2 = 0.0%). No publication bias was found in the eligible studies (Harbord’s test p = 0.864).

rs11649743 A > G and the risk of prostate cancer

Two publications included data regarding the association between the HNF1B rs11649743 and prostate cancer (Table 1). There was a significant difference in the between-study heterogeneity among the eligible studies (Q = 15.1, p = 0.035, I2 = 53.6%). Strong significant association was observed with the prostate cancer risk (p = 1.08 × 10− 12, random effect OR = 1.138, 95% CI: 1.062, 1.219, Fig. 2c). No publication bias was found in the eligible studies (Harbord’s test p = 0.588).

rs3760511 A > C and the risk of prostate cancer

Three publications were included in the evaluation of the association between the HNF1B rs3760511 and prostate cancer. There was a strong significant association between rs3760511 and the risk of prostate cancer, and moderate heterogeneity was found among the eligible studies (p = 1.57 × 10− 19, random effect OR = 1.214, 95% CI: 1.113, 1.325; Q = 4.57, p = 0.206, I2 = 34.3%, Fig. 2d). Sensitivity analyses in Caucasians demonstrated a pattern similar to that of the full population (p = 6.11 × 10− 19, random effect OR = 1.216, 95% CI: 1.125, 1.314; Q = 1.53, p = 0.216, I2 = 34.7%). No publication bias was found in the eligible studies (Harbord’s test p = 0.778).

HNF1B variants and the risk of endometrial cancer

rs4430796 G > A and the risk of endometrial cancer

Two publications were included in the evaluation of the association between the HNF1B rs4430796 A > G and endometrial cancer (Table 1). There was a strong significant association between rs4430796 and the endometrial cancer risk (p = 8.98 × 10− 16, fixed effect OR = 1.217, 95% CI: 1.160, 1.276; Q = 5.72, p = 0.768, I2 = 0.0%, Fig. 3). Similar patterns were found in the Caucasians (p = 3.73 × 10− 14, fixed effect OR = 1.215, 95% CI: 1.155, 1.277; Q = 0.57, p = 0.751, I2 = 0.0%). Lack of significant association was found in Africans (p = 0.235, fixed effect OR = 1.193, 95% CI: 0.891, 1.597; Q = 0.21, p = 0.645, I2 = 0.0%), the Asians (p = 0.058,fixed effect OR = 1.304, 95% CI: 0.992, 1.716; Q = 1.62, p = 0.203, I2 = 38.4%), and Latino and Hawaiian (p = 0.122, fixed effect OR = 1.217, 95% CI: 0.949, 1.562; Q = 3.07, p = 0.216, I2 = 34.8%). No publication bias was found in the eligible studies (Harbord’s test p = 0.950).
Fig. 3
Fig. 3

Fixed-effects meta-analysis of allele (A versus G) of the HNF1B gene rs4430796 G > A and endometrial cancer. The OR of each study is represented by a square, and the size of the square represents the weight of each study with respect to the overall estimate. 95% CIs are represented by the horizontal lines, and the diamond represents the overall estimate and its 95% CI

rs7501939 G > A and the risk of endometrial cancer

Two publications were included in the analysis of the association between the HNF1B rs7501939 and endometrial cancer (Table 1). Although the risk of endometrial cancer was increased in individuals carrying the G allele, compared to those with the A allele, lack of significant association was found with endometrial cancer risk (p = 0.258, random effect OR = 1.204, 95% CI: 0.873, 1.660). The same pattern was observed in Caucasians (p = 0.751, random effect OR = 1.104, 95% CI: 0.599, 2.036; Q = 190.13, p = 0.000, I2 = 98.9%), Africans (p = 0.122, random effect OR = 1.254, 95% CI: 0.942, 1.670; Q = 0.93, p = 0.336, I2 = 0.0%), Asians (p = 0.918, random effect OR = 1.040, 95% CI: 0.492, 2.196; Q = 2.23, p = 0.136, I2 = 55.1%)and Latino and Hawaiian (p = 0.262, random effect OR = 1.389, 95% CI: 0.783, 2.464; Q = 6.28, p = 0.043, I2 = 68.2%) (Data not shown).

Genotype comparison

rs4430796 G > A and the risk of prostate cancer

Of the 15 publications, only seven reported genotype information. The genotype distribution of the HNF1B rs4430796 among case and control groups is presented in Table 2. The genotype effects for AA versus GG (OR1) and AG versus GG (OR2) were calculated for each study. A multivariate meta-analysis was conducted to estimate the pooled risk. There was a significantly increased risk of prostate cancer among individuals with the homozygous AA genotype (p = 4.46 × 10− 22, fixed effect OR1 = 1.517, 95% CI: 1.394, 1.651; Q = 12.27, p = 0.424, I2 = 2.2%) and heterozygous AG genotype (p = 0.002, random effect OR2 = 1.180, 95% CI: 1.064, 1.309; Q = 17.50, p = 0.132, I2 = 31.4%).The pooled estimates were similar to those obtained after removal of the study with HW disequilibrium [10], i.e., fixed effect OR1 = 1.524 (p = 7.97 × 10− 18,95% CI: 1.384, 1.677; Q = 12.23, p = 0.347, I2 = 10.1%) and random effect OR2 = 1.198 (p = 0.003,95% CI: 1.064, 1.348;Q = 16.43, p = 0.126, I2 = 33.1%).
Table 2

The association between the HNF1B rs4430796 and prostate cancer (genotype distribution of case-control studies included in a meta-analysis)

Ref

Cases

Controls

HWE

AA vs GG

AG vs GG

GG

AG

AA

GG

AG

AA

OR1 (95% CI)

OR2 (95% CI)

[31]

16

60

119

77

73

10

0.889

1.494(1.249–1.786)

1.087(0.920–1.285)

[10]

446

1355

1073

316

883

509

a0.025

1.697(1.255-2.296)

1.285(0.984–1.679)

[10]

254

779

488

106

253

120

0.155

1.955(1.441–2.653)

1.433(1.060–1.937)

[10]

87

395

419

136

431

335

0.445

1.190(0.869–1.631)

1.077(0.820–1.415)

[10]

149

308

163

161

309

148

0.495

1.756(1.264–2.441)

1.304(0.974–1.746)

[10]

113

289

179

153

300

138

0.349

1.332(1.052–1.688)

0.998(0.808–1.233)

[10]

254

522

345

257

529

262

0.378

1.445(1.196–1.747)

1.206(1.018–1.428)

[10]

357

843

516

434

850

434

0.332

1.806(1.351–2.413)

1.543(1.187–2.006)

[37]

12

34

59

6

34

38

0.335

0.776(0.269–2.244)

0.500(0.168–1.486)

[38]

52

214

252

45

149

129

0.425

1.691(1.076–2.656)

1.243(0.792–1.950)

[39]

21

99

169

11

63

67

0.235

0.966(0.417–2.238)

0.514(0.217–1.215)

[32]

11

75

80

4

15

14

0.498

1.321(0.604–2.889)

0.823(0.372–1.823)

[41]

240

390

129

198

388

204

0.310

2.078(0.579–7.455)

1.818(0.510–6.484)

Pooled

       

1.517(1.394–1.651)

1.180(1.064–1.309)

HWE = p-value for Hardy–Weinberg equilibrium;

aHardy–Weinberg disequilibrium was observed in the control group

rs11649743 A > G and the risk of prostate cancer

Only one publication reported genotype information for rs11649743. However, this publication included relevant data for different populations and regions. The genotype distribution for the HNF1B rs11649743 among case and control groups is presented in Table 3. The genotype effects for GG versus AA (OR1) and GA versus AA (OR2) were calculated for each study. Multivariate meta-analysis was conducted to estimate the pooled risk. There was a significantly increased risk of prostate cancer among individuals with the homozygous GG genotype (p = 3.32 × 10− 6, fixed effect OR1 = 1.496, 95% CI: 1.262, 1.772) and heterozygous AG genotype (p = 7.82 × 10− 6, fixed effect OR2 = 1.276, 95% CI: 1.072, 1.519). No between-study heterogeneity was found for the homozygous GG genotype (Q = 2.19, p = 0.902, I2 = 0.0%) or for the heterozygous GA genotype (Q = 2.30, p = 0.891, I2 = 0.0%).
Table 3

Association between the HNF1B rs11649743 and prostate cancer (genotype distribution of case-control studies included in the meta-analysis)

Ref

Cases

Controls

HWE

GG vs AA

GA vs AA

AA

GA

GG

AA

GA

GG

OR1 (95% CI)

OR2 (95% CI)

[10]

115

895

1842

90

587

1009

0.292

1.460 (1.099–1.941)

1.220 (0.910–1.635)

[10]

40

395

1055

14

139

317

0.396

1.165 (0.626–2.168)

0.995 (0.525–1.884)

[10]

18

219

690

27

250

644

0.324

1.607 (0.877–2.946)

1.314 (0.704–2.451)

[10]

20

191

445

32

211

413

0.227

1.724 (0.971–3.062)

1.448 (0.801–2.618)

[10]

19

159

418

27

174

410

0.063

1.449 (0.793–2.646)

1.299 (0.695–2.426)

[10]

28

361

777

47

359

687

0.200

1.898 (1.176–3.065)

1.688 (1.034–2.756)

[10]

48

495

1216

62

546

1167

0.425

1.346 (0.916–1.979)

1.171 (0.788–1.740)

Pooled

       

1.496 (1.262–1.772)

1.276 (1.072–1.519)

Cumulative evidence of association

Epidemiological credibility of significant associations

Venice criteria were applied to evaluate these significant associations. Details of protection from bias for genetic variants significantly associated with prostate and endometrial cancer risk in meta-analyses are shown in Table 4. Grades of A were given to all these meta-analyses for amount of evidence, replication of association, and protection from bias. Therefore, strong evidence of true association with cancer risk is assigned to rs4430796, rs7501939, rs11649743, and rs3760511 for prostate cancer and rs4430796 for endometrial cancer.
Table 4

Details of protection from bias for genetic variants significantly associated with prostate and endometrial cancers risk in meta-analyses

Variants

Cancer site

Cancer risk

Venice criteria grade

Protection from bias

Reason for bias

Reason for bias exemption

Initial study influence

Deviation from HWE

OR < 1.15

p value for publication bias

p value for small study bias

OR (95% CI)

p value

OR (95% CI)

p value

rs4430796

prostate

1.247 (1.218–1.276)

2.21 × 10−77

AAA

A

NA

Identified by GWAS

1.244 (1.215–1.273)

2.07 × 10−74

No

No

0.253

0.248

rs7501939

prostate

1.201 (1.164–1.239)

9.31 × 10−31

AAA

A

NA

Identified by GWAS

1.200 (1.162–1.238)

1.31 × 10−29

No

No

0.864

0.868

rs11649743

prostate

1.138 (1.062–1.219)

1.08 × 10−12

AAA

A

Low OR

Identified by GWAS

1.136(1.053–1.226)

0.001

No

Yes

0.588

0.580

rs3760511

prostate

1.214 (1.113–1.325)

1.57 × 10−19

AAA

A

NA

Identified by GWAS

1.228 (1.139–1.224)

1.04 × 10−7

No

No

0.778

0.770

rs4430796

endometrium

1.217 (1.160–1.276)

8.98 × 10−16

AAA

A

NA

Identified by GWAS

1.202 (1.105–1.308)

1.87 × 10−5

No

No

0.950

0.943

HWE = P value for Hardy-Weinberg equilibrium;

Probability of true association with cancer risk

To evaluate the probability of true association with cancer risk for the nominally significant variants, FPRP value was calculated. All associations with cancer risk had a FPRP value < 0.001. Thus, all the cumulative epidemiological evidence of associations was graded as strong.

Discussion

To our knowledge, this is the first general overview of the association between HNF1B variants and susceptibility to prostate and endometrial cancers. Our primary analysis revealed that, rs4430796 A, showed strong significant associations with risk of both prostate cancer (OR = 1.247, p = 2.21 × 10− 77,) and endometrial cancer (OR = 1.217, p = 8.98 × 10− 16); the AA, AG genotypes also showed strong significant associations with risk of prostate cancer (OR1 = 1.517, p = 4.46 × 10− 22; OR2 = 1.180, p = 0.002). Sensitivity analyses in Caucasians demonstrated patterns similar to that of the full population. However, lack of significant association was found in Africans, which is likely due to the considerably smaller sample size. There was a strong significant association between rs7501939 A and the risk of prostate cancer (OR = 1.201, p = 9.31 × 10− 31); however, lack of significant association with endometrial cancer risk was observed (OR = 1.104, p = 0.751. For rs11649743 G, strong significant association was found with the prostate cancer risk (OR = 1.138, p = 1.08 × 10− 12), and the GG, AG genotypes also showed strong significant associations with the risk of prostate cancer (OR1 = 1.496, p = 3.32 × 10− 6; OR2 = 1.276, p = 7.82 × 10− 6). Strong significant association was also found between rs3760511 C and the risk of prostate cancer (OR = 1.214, p = 1.57 × 10− 19). Using the Venice criteria and false-positive report probability tests, we graded all the cumulative evidence of significant associations with prostate and endometrial cancers risk as strong.

Our findings were based on several gene-association studies, including several thousand participants, and were robust in terms of study design and sensitivity analyses. We found no evidence of publication bias or small study bias based on funnel plots. Between-study heterogeneity was found in allelic association studies (G versus A) of rs7501939, and in allelic (G versus A) of rs11649743 for prostate cancer. When HWE was examined, one study showed deviation. Our results were robust to the removal of this study.

HNF1B encodes three isoforms: isoforms (A, B and C); isoform A and B act as transcriptional activators and isoform C acts as a transcriptional repressor [44]. HNF1B is involved in the regulation of cell proliferation, and genetic variation in HNF1B might modulate the risk of cancer [45]. However, the precise pathomechanism by which the genetic variation affects susceptibility to cancers is still unclear. In a recent GWAS, rs4430796 and rs7501939 in HNF1B were associated with the risks of both endometrial cancer in women of European background [43] and prostate cancer [28] . Several studies examined the associations between HNF1B and prostate cancer and endometrial cancer across various populations [12, 46, 47]. According to these studies, the two variants are associated with the risks of prostate cancer and endometrial cancer. Moreover, the rs4430796 G allele is significantly associated with an increased risk of lung cancer [13] . In 2013, Pharoah et al. identified that the HNF1B rs757210 is specific to serous epithelial ovarian cancer by pooling data from GWAS and follow-up genotyping; the analysis included 43 studies from the Ovarian Cancer Association Consortium [18]. At the same time, Shen et al. found evidence for a differential effect of HNF1B on the serious and clear cell subtypes of ovarian cancer. They found that HNF1B loss-of-function role and gain-of-function are related to serous and clear cell ovarian cancers, respectively [20]. Another research discovered HNF1B rs7501939 was a susceptibility locus for testicular germ cell tumor [48]. Taken together, these studies suggest that specific HNF1B variants predispose individuals to clear cell ovarian, endometrial, lung and prostate cancers, et al.

There are several limitations of the study. First, it is likely that some publications were overlooked although we conducted an exhaustive literature search, some relevant published studies with null results were not identified. Second, due to insufficient data, we were unable to evaluate publication bias for associations between several variants in 8q24 region and prostate and endometrial cancer. Third, a unified analysis standard across studies could not be defined for lack of raw data from the original publications. Therefore, future studies with larger sample size are warranted to confirm these associations.

Conclusions

Given the relevance of HNF1B variants to cancer biology, we attempted to estimate the strength of the genetic associations between these variants and prostate and endometrial cancers. This Human Genome Epidemiology (HuGE) systematic review presents strong evidence for an association between HNF1B variants and prostate and endometrial cancers, both overall and in Caucasians, Asians, Africans, and Indians, suggesting a multiplicative genetic model for variants of HNF1B among different ethnic populations. Our study results also suggest that HNF1B plays an important role in prostate and endometrial cancers, and these variations may serve as efficient and economical biomarkers for the diagnosis of prostate and endometrial cancers.

Abbreviations

CNKI: 

Chinese National Knowledge Infrastructure

GWAS: 

genome-wide association studies

HNF1B: 

hepatocyte nuclear factor-1 beta

SNP: 

single-nucleotide polymorphism

Declarations

Acknowledgments

We are grateful to Editage Company for help in revising this paper.

Funding

Data collection, design and analysis of the study was supported by National Natural Science Foundation of China: 81401238, 81330016, 81630038; Grants from the Ministry of Education of China: 313037, 20110181130002; Grant from State Commission of Science Technology of China: 2012BAI04B04; Grants from the Science and Technology Bureau of Sichuan province: 2012SZ0010, 2014SZ0149, 2016JY0028; Grant from the clinical discipline program (Neonatology) from the Ministry of Health of China: 1311200003303.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

Data were extracted independently by YT and YW, YT, SL, FZ and DM contributed to writing the manuscript. Data with any disagreement was adjudicated by YQ. All authors were responsible for drafting the manuscript, read and approved the final version.

Ethics approval and consent to participate

This study has not directly involved humans, though is based on retrospectively analyzed pre-existing data.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Pediatrics, West China Second University Hospital, Sichuan University, No.17, Section 3, Renmin Nan Road, Chengdu, 610041, Sichuan Province, China
(2)
Key Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, No.17, Section 3, Renmin Nan Road, Chengdu, 610041, Sichuan Province, China

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