J Cancer 2017; 8(7):1162-1169. doi:10.7150/jca.18055

Research Paper

Association between SNPs in Long Non-coding RNAs and the Risk of Female Breast Cancer in a Chinese Population

Tao Xu1*, Xiu-Xiu Hu1, 2*, Xiang-Xiang Liu1, Han-Jin Wang3, Kang Lin1, Yu-Qin Pan1, Hui-Ling Sun1, Hong-Xin Peng1, 2, Xiao-Xiang Chen1, 2, Shu-Kui Wang1 Corresponding address, Bang-Shun He1 Corresponding address

1. General Clinical Research Center, Nanjing First Hospital, Nanjing Medical University, Nanjing, China;
2. Medical college, Southeast University, Nanjing, China;
3. Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
* These authors contributed equally to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) License. See http://ivyspring.com/terms for full terms and conditions.
How to cite this article:
Xu T, Hu XX, Liu XX, Wang HJ, Lin K, Pan YQ, Sun HL, Peng HX, Chen XX, Wang SK, He BS. Association between SNPs in Long Non-coding RNAs and the Risk of Female Breast Cancer in a Chinese Population. J Cancer 2017; 8(7):1162-1169. doi:10.7150/jca.18055. Available from http://www.jcancer.org/v08p1162.htm

Abstract

Long non-coding RNAs (LncRNAs) have been reported to be involved in tumorigenesis and tumor progression. Single nucleotide polymorphisms (SNPs) in the lncRNAs also play a vital role in carcinogenesis. The aim of this study was to assess the relationships between the four selected tagSNPs (rs944289, rs3787016, rs1456315, rs7463708) in the lncRNAs and the risk of female breast cancer in a Chinese population. A case-control study was carried out involving in a total of 439 breast cancer patients and 439 age-matched healthy controls. The genotyping was performed with Sequenom MassARRAY and the expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) in tumor tissues was measured by the immunohistochemistry (IHC) assay. We found that rs3787016 TT genotype (adjusted odds ratio (OR) = 1.62, 95% confidence interval (CI) = 1.09-2.41, P = 0.018) was associated with an increased risk of female breast cancer, especially among the patients with premenopausal status (adjusted OR = 2.55, 95% CI = 1.30-4.97, P = 0.006). Moreover, a statistically significant increased risk of the rs3787016 TT genotype was observed among the patients with advanced tumor stage (Ⅲ and Ⅳ), poor histological grade (G3-G4), positive lymph node involvement, positive expression of ER and PR and negative expression of HER-2; rs7463708 GT and GT/GG genotype were associated with decreased risk of breast cancer in the subgroup of patients with postmenopausal status (GT versus (vs.) TT: adjusted OR = 0.67, 95% CI = 0.46-0.99, P = 0.043; GT/GG vs. TT: adjusted OR = 0.68, 95% CI = 0.47-0.98, P = 0.041) and tumor late-stage (GT vs. TT: adjusted OR = 0.65, 95% CI = 0.43-0.97, P = 0.037; GT/GG vs. TT: adjusted OR = 0.65, 95% CI = 0.44-0.96, P = 0.029). In short, rs3787016 TT genotype was associated with increased breast cancer risk and clinicopathologic features of the tumor, especially among premenopausal women.

Keywords: Breast cancer, LncRNAs, SNPs

Introduction

Breast cancer (BC) is recognized as the most common malignant tumor and the leading cause of cancer-related death among females all over the world [1]. In China, breast cancer was responsible for around 268,600 new cases and 69,500 deaths in 2015 [2]. Studies have identified environmental factors as the risk for breast cancer, involving reproductive and hormonal factors including a long menstrual history, oral contraceptives use and never having children [1]. Also, genetic backgrounds play a vital role in the etiology of breast cancer. Previous researches have reported that a number of genetic variants were associated with the risk of BC [3-5]. However, the occurrence of BC is a complex multifactorial process and the molecular mechanism remains largely unclear.

Long non-coding RNAs (LncRNAs) are a new class of regulatory non-coding RNAs with length longer than 200 nucleotides, lacking open reading frame and having no potential protein translation capacity [6]. Recently, many studies have revealed that aberrant expression of lncRNAs were significantly associated with tumorigenesis and tumor progression in different cancer types, indicating the lncRNAs act as proto-oncogene [7] or anti-oncogene [8]. In addition, lncRNAs are considered to be involved in complex pathogenesis of cancers, referring to the levels of epigenome, transcription and post-transcription [9]. LncRNAs have essential roles in multiple biological processes including chromatin remodeling, cell differentiation, cell cycle control, genome rearrangement, dosage compensation, gene imprinting and regulation of gene expression [10]. Study demonstrated that the lncRNA HOTAIR was overexpressed in BC tissues and participated in BC progression [9]. Also, up-regulated lncRNA MALAT1 was detected in lung adenocarcinoma, which predicted metastasis and poor prognosis in early-stage non-small cell lung cancer [11]. Additionally, research has shown that lncRNA MEG3 expression was down-regulated in gastric cancer tissues and cell lines, and was associated with metastasis of gastric cancer by its function as a competing endogenous RNA (ceRNA) of miR-181s to regulate gastric cancer progression [12].

SNPs in lncRNAs may affect the function of target genes through altering the process of splicing and stability of mRNA conformation, leading to the modification of their interacting partners [13]. To date, the susceptibility of lncRNA SNPs to cancer risk have been investigated by numerous researches, such as lncRNA HOTAIR rs920778 polymorphism cause HOTAIR up-regulated among T allele carriers, which enhancing esophageal squamous cell carcinoma (ESCC)[14] and cervical cancer [15] risk in a Chinese population. However, Bayram et al. [16] reported that HOTAIR rs920778 CC genotype significantly increased the BC risk in a Turkish population. In addition, it was identified that lncRNA HULC rs7763881 may decrease the risk of HBV-related hepatocellular carcinoma in a Chinese population [17]. Subsequently, genome-wide association studies (GWAS) have identified that the C allele carriers of rs12325489 in the lincRNA-ENST00000515084 are associated with increased BC risk [18].

Based on the above backgrounds, the SNPs in the lncRNAs were the susceptibility of BC, and could be invested as biomarkers for the risk of BC. To date, there is no research to evaluate the susceptibility of lncRNA PTCSC3 rs944289, lncRNA POLR2E rs3787016, lncRNA PRNCR1 rs1456315 and lncRNA PRNCR1 rs7463708 to BC risk. Therefore, in the current study, we selected these four tagSNPs in the lncRNAs and evaluated the relationships between the four SNPs and the risk of BC in a Chinese female population.

Materials and Methods

Study subjects

A total of 878 age-matched female subjects divided into case cohort with 439 BC patients and health cohort with 439 cancer-free individuals were enrolled in this population-based case-control study. All the patients were genetically unrelated and consecutively recruited starting from January 2008 to January 2016 in Nanjing First Hospital, Nanjing Medical University, China. Meanwhile, the health controls were randomly collected in the same hospital for their routine physical checkup at the same time period. For the cases and controls, a pretested questionnaire was used to record clinical information of each individual, such as tobacco smoking, alcohol consumption and other cancer history. Owing to less than ten individuals have the history of smoking and drinking, which may be attributed to the life style of Chinese female, and considering the very small size of participants has these two environmental factors, finally we adjusted inclusion criteria of cases as follows: (1) subjects were histologically diagnosed with primary BC; (2) with no history of smoking and drinking; (3) with no evidence of personal or family history of cancer. Selection criteria for controls included no prior history of cancer or other malignant conditions and without history of smoking and drinking. All participants have given written informed consents, and this study was approved by the Institutional Review Board of the Nanjing First Hospital.

SNPs genotyping

We collected these blood samples from each individual after their admission to the hospital. The whole blood samples of all participants collected in a test tube containing EDTA were used for genotyping assay. Genomic DNA was isolated from peripheral white blood and concentrated by using GoldMag-Mini Whole Blood Genomic DNA Purification Kit according to the manufacturer's directions (GoldMag Co. Ltd. Xian, China). The extracted DNA was stored at -80℃ until use. We adopted the spectrometry (DU530 UV/vis spectrophotometer, Beckman Instruments, Fullerton, CA, USA) to detect DNA purity. Sequenom MassARRAY Assay Design 3.0 Software was used to design Multiplexed SNP MassEXTEND assay[19]. PCR and extension primers were designed by Sequenom, Inc. Assay Design. EXO-SAP was used to digest PCR-amplified DNA, and then mixed the primer extended by IPLEX chemistry, desalted using Clean Resin (Sequenom) and spotted onto Spectrochip matrix chips. Finally, results were detected by Mass Spectrometer. All samples were genotyped by Sequenom MassARRAY RS1000 according to the manufacturer's protocol. The final data was managed and analysed by Sequenom Typer 4.0 Software [19, 20].

Immunohistochemistry (IHC) assay

The immunohistochemistry (IHC) assay was applied to evaluate the expression of estrogen receptor (ER), progesterone receptor (PR) and the human epidermal growth factor receptor 2 (HER-2) in paraffin-embedded tumor tissue[21]. The immunohistochemical analysis was conducted following the instructions inside the kit. The monoclonal rabbit ER, PR and HER-2 antibody used in this study were purchased from Spring Bioscience (Pleasanton, CA, USA).

Statistical analysis

Hardy-Weinberg equilibrium (HWE) was assessed by a goodness of fit chi-square test among the healthy controls to compare the observed genotype frequencies with the expected ones. The two-sided χ2 test and independent t test were used to compare the selected variables between BC patients and healthy controls. Associations of the four SNPs with BC risks were estimated by a logistic regression model with odds ratios (ORs) and 95% confidence intervals (CIs), corresponding p values after adjustment for age and menopausal status. All statistical analysis was performed by using SPSS 23.0 for Windows (SPSS, Chicago, IL) and the P value < 0.05 was considered to be statistically significant.

Results

A total of 878 age-matched Chinese women subjects (439 BC patients and 439 healthy controls) were enrolled in this population-based case-control study to investigate the potential association between the four tagSNPs (rs944289, rs3787016, rs1456315, rs7463708) in the lncRNAs and BC risk. Clinicopathological features of patients with BC and healthy controls were summarized in Table 1, there were no statistically significant differences in age and menopausal status (mean age of patients vs. controls: 52.89±10.78 years vs. 52.95±10.89 years, P = 0.933; number of postmenopausal cases vs. controls: 241 vs. 229, P = 0.417). The observed genotype frequencies of the four SNPs in healthy controls were no significant deviations from the Hardy-Weinberg equilibrium (HWE) (P = 0.078 for rs944289, P = 0.144 for rs3787016, P = 0.167 for rs1456315 and P = 0.142 for rs7463708, respectively).

 Table 1 

Clinicopathological features of patients with breast cancer and healthy controls

VariablesCases, n (%)Controls, n (%)P valuea
Total participants439439
Age(Mean±SD, years)52.89±10.7852.95±10.890.933
Menopausal status0.417
Premenopausal198(45.10%)210(47.84%)
Postmenopausal241(54.90%)229(52.16%)
Tumor stage
0-Ⅱ306(69.70%)
Ⅲ-Ⅳ133(30.30%)
Tumor grade
G1-G2317(72.21%)
G3-G4122(27.79%)
Lymph node involvement
Negative211(48.06%)
Positive228(51.94%)
ER
Negative166(37.81%)
Positive273(62.19%)
PR
Negative205(46.70%)
Positive234(53.30%)
HER-2
Negative92(20.96%)
Positive347(79.04%)

aTwo-sided χ2 test and independent t test for the selected variables between cases and controls.

ER, estrogen receptor; PR, progesterone receptor; HER-2, human epidermal growth factor receptor-2

The genotypes and alleles distribution of the four tagSNPs in BC patients and healthy controls are presented in Table 2. Logistic regression analysis revealed that the rs3787016 TT homozygote (adjusted OR = 1.62, 95% CI: 1.09-2.41, P = 0.018) was associated with increased risk of BC when compared with the wild-type CC homozygote. Also, a borderline significantly increased risk was observed in the T allele of rs3787016 (adjusted OR = 1.21, 95% CI: 1.00-1.46, P = 0.052) for BC when compared with the C allele. However, no statistically significant association between rs944289, rs1456315 and rs7463708 and the risk of BC was observed among all participants, as shown in Table 2.

 Table 2 

Genotype and allele frequencies of the four SNPs between patients with breast cancer and healthy controls

GenotypeCases, n(%)Controls, n(%)Crude OR(95%CI)P valueAdjusted OR(95%CI)aP valuea
rs944289
CC127(28.93)115(26.20)ReferenceReference
CT229(52.16)237(53.99)0.88(0.64,1.19)0.4000.88(0.64,1.20)0.402
TT83(18.91)87(19.82)0.86(0.58,1.28)0.4650.86(0.58,1.28)0.453
CT/TT312(71.07)324(73.80)0.87(0.65,1.17)0.3650.87(0.65,1.17)0.368
Allele
C483(55.01)467(53.19)ReferenceReference
T395(44.99)411(46.81)0.93(0.77,1.12)0.4440.93(0.77,1.12)0.442
rs3787016
CC137(31.21)149(33.94)ReferenceReference
TC209(47.61)226(51.48)1.01(0.75,1.36)0.9701.02(0.76,1.38)0.894
TT93(21.18)64(14.58)1.58(1.07,2.34)0.0231.62(1.09,2.41)0.018
TC/TT302(68.79)290(66.06)1.13(0.85,1.50)0.3881.13(0.85,1.51)0.384
Allele
C483(55.01)524(59.68)ReferenceReference
T395(44.99)354(40.32)1.21(1.01,1.46)0.0481.21(1.00,1.46)0.052
rs1456315
AA234(53.30)244(55.58)ReferenceReference
GA165(37.59)159(36.22)1.08(0.82,1.44)0.5841.08(0.81,1.43)0.607
GG40(9.11)36(8.20)1.16(0.71,1.88)0.5521.16(0.71,1.88)0.555
GA/GG205(46.70)195(44.42)1.10(0.84,1.43)0.4981.09(0.84,1.43)0.511
Allele
A633(72.10)647(73.69)ReferenceReference
G245(27.90)231(26.31)1.08(0.88,1.34)0.4521.08(0.88,1.34)0.460
rs7463708
TT209(47.61)184(41.91)ReferenceReference
GT190(43.28)211(48.06)0.79(0.60,1.05)0.1030.79(0.60,1.05)0.102
GG40(9.11)44(10.02)0.80(0.50,1.28)0.3550.81(0.50,1.30)0.380
GT/GG230(52.39)255(58.09)0.79(0.61,1.04)0.0900.79(0.61,1.04)0.090
Allele
T608(69.25)579(65.95)ReferenceReference
G270(30.75)299(34.05)0.86(0.70,1.05)0.1390.86(0.70,1.05)0.139

aAdjusted by age and menopausal status in logistic regression analysis.

The bold values indicate statistically significant data

 Table 3 

Stratified effects of polymorphisms in lncRNAs on breast cancer risk by menopausal status

GenotypePremenopausalP valueaPostmenopausalP valuea
Patients/controlsOR(95%CI)aPatients/controlsOR(95%CI)a
rs944289
CC55/54Reference72/61Reference
CT110/1120.97(0.61,1.53)0.879119/1250.81(0.53,1.23)0.319
TT33/440.74(0.41,1.33)0.31250/430.97(0.56,1.66)0.903
CT/TT143/1560.90(0.58,1.40)0.638169/1680.85(0.57,1.27)0.428
rs3787016
CC61/65Reference76/84Reference
TC97/1280.79(0.51,1.23)0.304112/981.23(0.81,1.87)0.324
TT40/172.55(1.30,4.97)0.00653/471.25(0.75,2.08)0.387
TC/TT137/1451.01(0.66,1.54)0.970165/1451.24(0.85,1.82)0.272
rs1456315
AA99/113Reference135/131Reference
GA81/781.18(0.78,1.78)0.43184/810.99(0.67,1.47)0.971
GG18/191.08(0.54,2.17)0.83222/171.24(0.63,2.44)0.540
GA/GG99/971.16(0.79,1.72)0.444106/981.04(0.72,1.49)0.855
rs7463708
TT85/87Reference124/97Reference
GT93/1000.96(0.63,1.44)0.82697/1110.67(0.46,0.99)0.043
GG20/230.89(0.46,1.74)0.73320/210.74(0.38,1.43)0.366
GT/GG113/1230.94(0.64,1.39)0.760117/1320.68(0.47,0.98)0.041

aAdjusted by age

The results with significant difference are in bold

 Table 4 

Stratified effects of SNPs in lncRNAs on breast cancer risk by the pathological characteristics of patients

GenotypeCoStage(0-Ⅱ)P valueaStage(Ⅲ-Ⅳ)P valueaGrade(G1-G2)P valueaGrade(G3-G4)P valueaLymph node involvement(-)P valueaLymph node involvement(+)P valuea
CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)
rs944289
CC11592Reference35Reference92Reference35Reference62Reference65Reference
CT2371590.84(0.60,1.18)0.314700.97(0.61,1.53)0.8791660.88(0.62,1.23)0.440630.87(0.55,1.40)0.5681100.86(0.59,1.26)0.4421190.89(0.61,1.29)0.536
TT87550.79(0.51,1.23)0.300281.06(0.60,1.88)0.851590.85(0.55,1.31)0.454240.91(0.50,1.64)0.741390.84(0.51,1.37)0.478440.89(0.55,1.44)0.633
CT/TT3242140.83(0.60,1.14)0.252980.99(0.64,1.54)0.9542250.87(0.63,1.20)0.393870.88(0.56,1.37)0.5701490.85(0.59,1.22)0.3821630.89(0.62,1.27)0.520
rs3787016
CC149103Reference34Reference101Reference36Reference70Reference67Reference
TC2261450.95(0.69,1.32)0.769641.24(0.78,1.98)0.3711511.00(0.72,1.39)0.994581.09(0.68,1.74)0.716980.94(0.64,1.36)0.7231111.11(0.77,1.61)0.580
TT64581.34(0.86,2.07)0.194352.57(1.45,4.56)0.001651.53(1.00,2.36)0.053281.92(1.07,3.46)0.029431.47(0.90,2.38)0.121501.79(1.11,2.89)0.016
TC/TT2902031.02(0.75,1.39)0.911991.48(0.96,2.29)0.0802161.10(0.81,1.50)0.549861.23(0.79,1.90)0.3611411.03(0.73,1.46)0.8581611.23(0.87,1.75)0.239
rs1456315
AA244157Reference77Reference164Reference70Reference112Reference122Reference
GA1591191.16(0.85,1.59)0.344460.90(0.59,1.37)0.6201221.13(0.83,1.54)0.451430.94(0.61,1.45)0.794771.05(0.74,1.50)0.781881.09(0.78,1.54)0.610
GG36301.29(0.76,2.19)0.340100.87(0.41,1.83)0.707311.28(0.76,2.16)0.35090.86(0.39,1.88)0.708221.33(0.75,2.37)0.335181.01(0.55,1.85)0.982
GA/GG1951491.19(0.89,1.60)0.248560.90(0.61,1.33)0.5881531.16(0.86,1.55)0.330520.93(0.62,1.40)0.735991.11(0.80,1.54)0.5521061.08(0.78,1.49)0.657
rs7463708
TT184139Reference70Reference148Reference61Reference98Reference111Reference
GT2111380.87(0.64,1.18)0.357520.65(0.43,0.97)0.0371380.81(0.59,1.09)0.164520.75(0.49,1.14)0.172920.82(0.58,1.16)0.261980.77(0.55,1.07)0.120
GG44290.89(0.53,1.49)0.653110.65(0.32,1.33)0.240310.89(0.53,1.48)0.64590.61(0.28,1.33)0.212210.90(0.51,1.60)0.723190.72(0.40,1.31)0.282
GT/GG2551670.87(0.65,1.17)0.344630.65(0.44,0.96)0.0291690.82(0.61,1.09)0.174610.72(0.48,1.08)0.1161130.83(0.60,1.16)0.2761170.76(0.55,1.04)0.090

aAdjusted by age and menopausal status

The bold values indicate statistically significant data

 Table 5 

Stratified effects of SNPs in lncRNAs on breast cancer risk by the expression of ER,PR and HER-2

GenotypeCoER(-)P valueaER(+)P valueaPR(-)P valueaPR(+)P valueaHER-2(-)P valueaHER-2(+)P valuea
CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)CaOR(95%CI)
rs944289
CC11548Reference79Reference63Reference64Reference28Reference99Reference
CT237880.89(0.58,1.35)0.5721410.87(0.61,1.23)0.4221000.77(0.52,1.13)0.1751290.97(0.67,1.42)0.890460.79(0.47,1.33)0.3671830.90(0.65,1.25)0.526
TT87300.83(0.48,1.41)0.483530.89(0.57,1.41)0.629420.87(0.54,1.41)0.579410.86(0.53,1.40)0.544180.86(0.44,1.65)0.640650.87(0.57,1.32)0.510
CT/TT3241180.87(0.58,1.29)0.4791940.88(0.62,1.23)0.4371420.79(0.55,1.14)0.2081700.94(0.66,1.35)0.750640.80(0.49,1.31)0.3812480.89(0.65,1.22)0.472
rs3787016
CC14949Reference88Reference62Reference75Reference31Reference106Reference
TC226851.19(0.79,1.80)0.4041240.93(0.66,1.32)0.6951031.14(0.78,1.67)0.4951060.93(0.65,1.34)0.707350.72(0.42,1.22)0.2241741.11(0.81,1.53)0.524
TT64321.53(0.90,2.63)0.119611.69(1.08,2.64)0.021401.51(0.91,2.49)0.108531.75(1.10,2.79)0.019262.10(1.14,3.88)0.017671.49(0.97,2.28)0.069
TC/TT2901171.24(0.84,1.82)0.2871851.08(0.78,1.49)0.6491431.20(0.84,1.72)0.3241591.09(0.77,1.52)0.638611.00(0.62,1.60)0.9862411.17(0.87,1.59)0.303
rs1456315
AA24487Reference147Reference108Reference126Reference48Reference186Reference
GA159671.18(0.81,1.71)0.403981.02(0.73,1.41)0.928831.16(0.82,1.65)0.397820.99(0.71,1.40)0.974361.13(0.70,1.82)0.6221291.06(0.79,1.44)0.699
GG36120.95(0.47,1.91)0.879281.27(0.74,2.17)0.390140.89(0.46,1.72)0.725261.38(0.80,2.40)0.24781.06(0.46,2.43)0.897321.18(0.71,1.98)0.526
GA/GG195791.14(0.80,1.63)0.4801261.06(0.78,1.44)0.696971.12(0.80,1.56)0.5131081.07(0.78,1.47)0.691441.12(0.71,1.76)0.6211611.09(0.82,1.44)0.575
rs7463708
TT18480Reference129Reference98Reference111Reference44Reference165Reference
GT211740.81(0.56,1.17)0.2581160.78(0.57,1.08)0.130920.82(0.58,1.16)0.251980.77(0.55,1.08)0.124400.79(0.49,1.27)0.3281500.79(0.59,1.07)0.127
GG44120.64(0.32,1.27)0.201280.91(0.53,1.54)0.711150.65(0.34,1.23)0.185250.94(0.55,1.63)0.83480.71(0.31,1.63)0.416320.83(0.50,1.38)0.479
GT/GG255860.78(0.54,1.11)0.1701440.80(0.59,1.09)0.1521070.79(0.56,1.10)0.1621230.80(0.58,1.10)0.162480.78(0.50,1.22)0.2781820.80(0.60,1.06)0.120

aAdjusted by age and menopausal status

The bold values indicate statistically significant data

To identify the stratified effects of SNPs in lncRNAs on BC risk, subgroup analysis based on the menopausal status was performed and logistic regression analysis revealed that rs3787016 TT genotype carriers (adjusted OR = 2.55, 95% CI: 1.30-4.97, P = 0.006) have higher BC risk than those with wild-type CC in the premenopausal sub-cohort; in contrast, in the subgroup of postmenopausal women, rs7463708 GT genotype (adjusted OR = 0.67, 95% CI: 0.46-0.99, P = 0.043) or rs7463708 GT/GG genotype (adjusted OR = 0.68, 95% CI: 0.47-0.98, P = 0.041) was associated with decreased risk of BC when compared with the wild-type TT, as summarized in Table 3.

Moreover, we demonstrated the association of the four SNPs with the pathological characteristics (tumor stage, tumor grade and lymph node involvement) and patient's tumor tissue characteristics (expression of ER, PR and HER-2). As shown in Table 4, we found that rs3787016 TT genotype was associated with advanced TNM (Ⅲ and Ⅳ) classification (adjusted OR = 2.57, 95% CI: 1.45-4.56, P = 0.001), poor histological grade (G3-G4) (adjusted OR = 1.92, 95% CI: 1.07-3.46, P = 0.029) and positive lymph node involvement (adjusted OR = 1.79, 95% CI: 1.11-2.89, P = 0.016). In addition, a marginal significance of increased risk for BC with early differentiation (G1-G2) (adjusted OR = 1.53, 95% CI: 1.00-2.36, P = 0.053) was noticed. Also, we determined a statistically significant inverse relationship between the GT genotype (adjusted OR = 0.65, 95% CI: 0.43-0.97, P = 0.037) or GT/GG genotype (adjusted OR = 0.65, 95% CI: 0.44-0.96, P = 0.029) of rs7463708 polymorphism and tumor late-stage (Ⅲ and Ⅳ). Furthermore, subgroup analysis based on expression of ER, PR and HER-2 was presented in the Table 5. Similarly, we observed that rs3787016 TT genotype was associated with increased BC risk of positive expression of ER (adjusted OR = 1.69, 95% CI: 1.08-2.64, P = 0.021) and PR (adjusted OR = 1.75, 95% CI: 1.10-2.79, P = 0.019) and negative expression of HER-2 (adjusted OR = 2.10, 95% CI: 1.14-3.88, P = 0.017), respectively. However, there was no significant association for the three SNPs (rs944289, rs1456315, rs7463708) in all subgroups, as shown in Table 5.

Discussion

In this population-based case-control study, we investigated the association between the four selected SNPs in the lncRNAs and the risk of female BC in a Chinese population. We observed that rs3787016 TT genotype was associated with an increased risk of female BC and clinicopathologic features of the tumor, especially among premenopausal women.

The SNP rs3787016 is in a lncRNA which located in an intron region of RNA polymerase Ⅱ subunit E (POLR2E) gene, which encodes the fifth largest subunit of RNA polymerase II and is responsible for synthesizing messenger RNA (mRNA) in eukaryotes. Previous study suggested the functional genetic variants in lncRNA regions may contribute to carcinogenesis [22]. Moreover, the rs3787016 TT genotype was investigated to be associated with increased risk of prostate cancer in an eastern Chinese population [23], which was consistent with the result of the study containing a meta-analysis of two GWAS and a case-control study [22]; however, such a significant association could not be duplicated in a Serbian population [24]. This study indicated that the rs3787016 TT genotype is a risk factor for female BC in a Chinese population. In contrast, a case-control study of ESCC demonstrated that POLR2E rs3787016 CT or CT/TT genotype had a decreased risk of ESCC [25]. The different findings in the above studies might be explained as follow. Firstly, the results of association studies may vary among different cancer types. Secondly, owing to ancestral backgrounds, inter-population genetic differences including differences in allele frequencies could lead to inconsistent results. Finally, ESCC is considered to be affected by multiple environmental factors exposures and the interaction of the genetic backgrounds and environmental factors contributes to the risk of cancer, so the association of genetic variants and ESCC risk should be validated by more researches. Subsequently, subgroup analysis of this study revealed that the carriers of rs3787016 TT genotype have more evident risk effect on patients with positive expression of ER and PR. As we known, the expression of these two receptors is closely related to the menopausal status of females, and women in the premenopausal status have more estrogen and progesterone, which may be attributed to the result concluded by this study that patients with rs3787016 TT genotype have higher BC risk in the premenopausal sub-cohort.

The SNP rs1456315 is located in the prostate cancer associated noncoding RNA 1 (PRNCR1), which is a ~13kb lncRNA transcribed from the “gene desert” region of chromosome 8q24 (128.14-128.28Mb). SNPs in the lncRNA PRNCR1 have been reported to influence the secondary structure of PRNCR1 mRNA and the stability of the mRNA conformation, resulting in the occurrence and development of human diseases [26]; in addition, rs1456315 positioned in the region 2 of 8q24 was significantly associated with prostate cancer susceptibility [26]. Subsequently, study reported that rs1456315 AG genotype may contribute to a decreased risk of colorectal cancer [27]. However, in the present study, no statistically significant association was observed between the rs1456315 and the risk of BC. The inconsistent conclusions may be attributed to the different kinds of cancer. Also, this is the first study investigated the relationship between the rs1456315 and BC risk, so further large-scale studies in different populations still need to be done.

Rs7463708 overlaps with the lncRNA PRNCR1 and is located in an enhancer of prostate cancer associated transcript 1 (PCAT1) 78 kb away, which is a lncRNA positioned in the 8q24 “gene desert” region and overexpressed in prostate cancer. It was reported that the PCAT1 promoter strongly interacted with the T allele of rs7463708, suggesting that rs7463708 regulated the activation of PCAT1 enhancer and resulted in increased PCAT1 expression [28, 29]. In addition, PCAT1 plays an important role in the carcinogenesis through interacting with the GNMT gene involving in prostate cancer [29] and modulating mTOR signaling pathway in hepatocellular carcinoma [30], which also participating in the development of BC [31]. Thus, it is possible that the rs7463708 have potential association with BC risk. Also, our study drew a conclusion that in the sub-cohort analysis, rs7463708 GT and GT/GG genotypes were protective factors for female BC among postmenopausal status and tumor late-stage. To date, there was no study investigated the association between the rs7463708 and cancer risk except for prostate cancer risk. This is the first time investigating the association of rs7463708 and BC risk; therefore, more researches should be conducted for further study.

The SNP rs944289 at 14q13.3 is located 3.2 kb upstream of a long intergenic noncoding RNA (lincRNA) named Papillary Thyroid Carcinoma Susceptibility Candidate 3 (PTCSC3) and positioned in the binding site of the CCAAT/enhancer binding proteins (C/EBP) α and β [32]. The rs944289 T allele can affect binding sequence and results in missense variant and amino acid substitution (valine instead of alanine at codon 339), which may be induce multinodular goiter and papillary thyroid cancer (PTC)[33]. Up to now, all published researches were assessed the relationships between the rs944289 and differentiated thyroid carcinoma (DTC) [34-37]; however, to date, no associaion of other cancer types was discussed with the SNP, which may be due to the specific suseptibility of the SNP to the risk of DTC, and in this study, we also abserved no significant relationships between the rs944289 and BC risk.

To our knowledge, in the present study, we investigated the association between the four selected SNPs and BC risk for the first time. Although there were some important discoveries revealed in the study, several limitations also need to be addressed. Firstly, the four selected SNPs of lncRNAs in our study may not be comprehensive because we were limited by those have been identified to have risk effect on other cancers. Also, the biological function of these lncRNAs remains largely unknown and has not been validated in experimental models, so it is difficult to explain our results. Secondly, the number of subjects in our study is not enough large and the small size in subgroup analysis may not provide statistical power to show significant results. Moreover, the clinical information of each individual is not fully reliable and detailed, which might influence the accuracy of the results. Thirdly, BC is a complex and multifactorial disease, this is not a large size population based case-control study, and the samples was not enough for the sub-group analysis, therefore, to confirm our findings, studies with more large-scale samples including different ethnic populations and detailed clinical information should be conducted. In addition, properly functional assessments also should be performed to illuminate the etiology of the BC.

In summary, this study demonstrated that rs3787016 TT genotype was associated with BC risk and clinicopathologic features of the tumor, especially among premenopausal women. Nevertheless, the results of this preliminary study need to be validated by further larger and well-designed researches.

Acknowledgements

This project was supported by grants from the National Nature Science Foundation of China (No. 81472027, 81501820) to S.W and Y.P; Jiangsu Provincial Medical Youth Talent to B.H (QNRC2016066) and Y.P (QNRC2016074); Nanjing Medical Science and Technique Development Foundation to B.H (JQX13003, QRX11254, and QYK11175) and Y.P (QRX11255); Jiangsu Provincial Medical Innovation Team to S.W.

Competing Interests

The authors have declared that no competing interest exists.

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Author contact

Corresponding address Corresponding authors: Shu-Kui Wang Email: sk_wangedu.cn; Bang-Shun He Email: hebangshuncom


Received 2016-10-24
Accepted 2016-12-19
Published 2017-4-9