Association of Long Non-Coding RNA MEG3 Polymorphisms and Risk of Prostate Cancer in Chinese Han Population Bin Xu1,2, Minhao Zhang1,2, Chunhui Liu2, Can Wang1,2, Zonghao You1,2, Yali Wang1,2*, Ming Chen1,2** Purpose: To explore the association between MEG3 polymorphisms and the risk of prostate cancer in the Chinese Han population. Materials and Methods: Two MEG3 single-nucleotide polymorphisms (SNPs) (rs11627993 C >T rs7158663 A>G) were genotyped in a case-control study in which 165 prostate cancer patients and 200 healthy controls were recruited by a Real-Time Polymerase Chain Reaction (PCR) with the TaqMan assay. The odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the strength of association. Results: No statistically significant differences were found in the allele or genotype distributions of the MEG3 rs11627993 C >T and rs7158663 A > G polymorphisms among cases or healthy control subjects (rs11627993: CC vs CA: 95% CI = 0.54-1.95, ORs = 1.03; CC vs AA: 95% CI = 0.67-2.54, ORs = 1.30 ; CC/CA vs AA: 95% CI = 0.81-1.98, ORs = 1.26 , P = .29 ; C vs A: 95% CI = 0.85-1.57, ORs = 1.16, P = .35; rs7158663: AA vs AG: 95% CI = 0.76-5.08, ORs = 1.97, AA vs GG: 95% CI = 0.57-3.29, ORs = 1.37; AA/AG vs GG : 95% CI = 0.56-1.32, ORs = 0.86, P = .49; A vs G: 95% CI = 0.69-1.39, ORs = 0.98, P = .91) Further stratified analysis detected no significant association. Conclusion: The MEG3 polymorphisms (rs11627993 C>T and rs7158663 A>G) does not influence the suscepti- bility to prostate cancer. Keywords: maternal-expressed gene 3; polymorphism; susceptibility; prostate cancer; lncRNA INTRODUCTION According to recent reports, prostate cancer is the most common non-cutaneous malignancy and the second leading cause of cancer-related deaths of men in the developed world(1). The incidence and mortality of prostate cancer in the Chinese Han population have also been increasing in the last several decades(2). The 2019 China national cancer center reported that prostate cancer ranked sixth and tenth among male malignancies in terms of morbidity and mortality in 2015(2). To date, the mechanisms of prostate cancer remains largely un- known. LncRNAs are important for cancer initiation and pro- gression with the development of advanced genomic methods(3). The genome-wide association study have identified so many cancer risk SNPs which are locat- ed in noncoding regions(4). SNPs may affect the normal function of genes through various mechanisms, thereby affecting individual tumor susceptibility(5). MEG3 is abnormally expressed in various human can- 1Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, 210009, China. 2Surgical Research Center, Institute of Urology, Medical School of Southeast University, Nanjing, 210009, China. *Correspondence: Department of Urology, Affiliated Zhongda Hospital of Southeast University, 87 Dingjia qiao, Nanjing, Jiangsu Province,210009, People’s Republic of China. Tel: +86 150666260. E-mail: 15150666260@163.com **Department of Urology, Affiliated Zhongda Hospital of Southeast University, 87 Dingjia qiao, Nanjing, Jiangsu Province, 210009, People’s Republic of China. Tel: + 86 13913009977, E-mail: mingchenseu@126.com. Received September 2019 & Accepted May 2020 cers, such as hepatocellular carcinoma(6,7), bladder can- cer(8), glioma(7), and gastric cancer(9). Ribarska found low expression of MEG3 in prostate cancer(10). Luo found that MEG3 can inhibit the proliferation of pros- tate cancer cells and promote apoptosis(11). However, little is known about the association between SNPs in MEG3 and prostate cancer risk. Based on the previous findings mentioned above, we hypothesized that genetic variants of MEG3 may influ- ence the susceptibility of prostate cancer. To test the hypothesis, we carried out an association study between SNPs in MEG3 and prostate cancer risk in a hospi- tal-based prostate cancer case-control study, in which 165 patients and 200 control subjects were recruited. PATIENTS AND METHODS Study subjects This study recruited 165 prostate cancer cases and 200 control subjects from the Affiliated Zhongda Hospital of Southeast University. CaP patients were diagnosed be- UROLOGICAL ONCOLOGY Urology Journal/Vol 18 No. 2/ March-April 2021/ pp. 176-180. [DOI: 10.22037/uj.v16i7.5585] tween July 2017 and July 2019 and were pathologically proven to have prostate adenocarcinoma after biopsy in the Affiliated Zhongda Hospital of Southeast Universi- ty. The control group was age-matched, and the subjects were healthy checkup examinees without cancer history and were collected in the same period. All the patients were southern Chinese Han population. Controls were excluded if they had an abnormal prostate-specific anti- gen (PSA) level, or abnormal digital rectal examination (DRE). After informed consent was obtained, 2ml of peripheral blood sample was collected and each subject was asked to finish a questionnaire including age, race, tobacco use, alcohol use, family history of cancer, and so on. In the present research, smoking more than five cigarettes per day for more than 5 years was defined as smoking. Drinking habit was defined as drinking at least three times per week and lasting more than 10 years. Family history of cancer was defined as cancer in first-degree relatives (parents, siblings, or children). Disease stage was determined by pathologic findings, pelvic computed tomography, magnetic resonance im- age, and radio-nucleotide bone scans. The tumor stage was determined using TNM classification and graded according to WHO guidelines. Pathologic grade was recorded as the Gleason score. All participants provided informed consent after the interview. This research protocol was approved by the Institutional Review Board of Affiliated Zhongda Hos- pital of Southeast University SNPs selection and genotyping We selected the SNPs of MEG3 with the minor al- lele frequency (MAF) > 0.05 in Han Chinese from the 1000 Genome Projects. As a result, rs11627993 and rs7158663 were selected. Genomic DNA was extract- ed from peripheral blood using the TIAN amp Blood DNA kit (Tian gen, China). Genotyping was performed by TaqMan SNP genotyping assay. Furthermore, about 3% of selected samples were blindly repeated for geno- typing to confirm the results. Statistical analysis Tests for the Hardy-Weinberg equilibrium in cases and controls were performed by the good-of-fit χ2 test. We estimated the association between genotypes and pros- tate cancer risk by odds ratios (ORs) and 95% confi- dence intervals (CIs) using the logistic regression. The ORs and 95%CIs were further adjusted for age, BMI (body mass index), and cigarette smoking, alcohol drinking, family history of cancers. All analyses were two-sided and P < .05 was considered significant. All statistical calculations were conducted with SPSS 13.0 software (SPSS Inc., Chicago, IL, USA). Association of MEG3 and risk of CaP-Xu et al. Urological Oncology 177 Characteristics Cases (n=165) Controls (n=200) P-valuea n % n % Age(years) ≤ 70 76 46.10 101 50.50 0.39 > 70 89 53.90 99 49.50 Body mass index (kg/m2) ≤ 23 56 33.90 68 34.00 0.99 > 23 109 66.10 132 66.00 Cigarette smoking Never 98 59.40 102 51.00 0.11 Ever 67 40.60 98 49.00 Alcohol drinking Never 100 60.60 132 66.00 0.29 Ever 65 39.40 68 34.00 Family history of cancers No 118 71.50 168 84.00 P < 0.01 Yes 47 28.50 32 16.00 aTwo-sided x2 test for the distributions between the cases and controls. Table 1. Demographic characteristics of CaP cases and controls characteristics. SNPs Genotypes Cases ,n(%) Controls ,n(%) P-valueb Adjusted OR (95% CI)c rs11627993a1 Total 165 200 0.62 CC 24(14.55) 27(13.50) 1.00(reference) CA 85(51.51) 94(47.00) 1.03(0.54-1.95) AA 56(33.94) 79(39.50) 1.30(0.667-2.54) CC/CA 109(66.06) 121(60.50) 0.29 1.00(reference) AA 56(33.94) 79(39.50) 1.26(0.81-1.98) Allele 0.35 C allele 133(40.30) 148(37.00) 1.00(reference) A allele 197(59.70) 252(63.00) 1.16(0.85-1.57) rs7158663a2 0.34 AA 13(7.88) 11(5.50) 1.00(reference) AG 54(32.73) 78(39.00) 1.97(0.76-5.08) GG 98(59.39) 111(55.50) 1.37(0.57-3.29) AA/AG 67(40.61) 89(44.50) 0.49 1.00(reference) GG 98(59.39) 111(55.50) 0.86(0.56-1.32) Allele 0.91 A allele 80(24.20) 100(25.00) 1.00(reference) G allele 250(75.80) 300(75.00) 0.98(0.69-1.39) aThe genotype frequencies among the control subjects were in agreement with the Hardy–Weinberg equilibrium (a1:x2 =0.003 p=0.99 a2:x2 =0.24 p = 0.89). bTwo-sided x2test for the distributions or allele frequencies between the cases and controls. cOdds ratios (ORs) were obtained from a logistic regression model with adjusting for age, BMI, cigarette smoking, alcohol drinking, family history of cancers. Table 2. Genotypes in patients with CaP and controls. RESULTS Characteristics of the study population The demographic characteristics of participants are de- scribed in Table 1. There was no significant difference in age (P = .39), BMI (P = .99), cigarette smoking (P = .11), and alcohol drinking distribution (P = .29). How- ever, there was a significant difference in the family history of cancer between cases and controls (P < .001), which may suggest the incidence of prostate cancer is related to genetic factors. Genotype distributions of MEG3 polymorphism and risk of CaP Both of polymorphisms (rs11627993 C>T and Table3. MEG3 polymorphisms and clinicopathological characteristics in patients with CaP. Variables rs11627993 CC/CA,n(%) AA,n(%) P-valuea Adjusted OR (95% CI)b Clinical stagec Localized(84) 53(63.10) 31(36.90) 0.75 1.00(reference) Advanced(81) 56(69.14) 25(30.86) 0.91(0.51-1.62) Gleason score < 7(14) 13(92.86) 1(7.14) 1.00(reference) = 7(64) 39(60.94) 25(39.06) 0.05 8.33(1.03-67.71) > 7 (87) 57(65.52) 30(34.48) 0.07 6.84(0.85-54.85) PSA ≤20 (74) 48(64.86) 26(35.14) 0.75 1.00(reference) > 29(91) 61(67.03) 30(32.97) 0.90(0.47-1.73) rs7158663 AA/AG,n(%) GG,n(%) Clinical stagec Localized(84) 33(39.29) 51(60.71) 0.67 1.00(reference) Advanced(81) 34(41.98) 47(58.02) 0.87(0.45-1.66) Gleason score < 7 (14) 5(35.71) 9(64.29) 1.00(reference) = 7 (64) 22(34.38) 42(65.62) 0.75 1.23(0.36-4.24) > 7 (87) 40(45.98) 47(54.02) 0.60 0.72(0.22-2.42) PSA ≤ 20 (74) 27(36.49) 47(63.51) 0.32 1.00(reference) > 29(91) 40(43.96) 51(56.04) 0.72(0.38-1.36) aTwo-sided w2 test for the distributions or allele frequencies between the cases and controls. bOdds ratios (ORs) were obtained from a logistic regression model with adjusting for age, BMI, cigarette smoking, alcohol drinking, family history of cancers. cLocalized: T1–2N0M0; Advanced: T3–4NxMx or TxN1Mx or TxNxM1 [according to the international tumor–node–metastasis (TNM) staging system for CaP.] Table 4. Association and stratification analysis between MEG3 polymorphism and risk of CaP. rs11627993(Cases/Controls) N (Cases /Controls) CC/CA AA Variables N % n % P-valuea Adjusted OR (95% CI)b Total 165/200 109/121 66.06/60.50 56/79 33.94/39.50 0.29 1.27(0.82-1.98) Age (years) ≤ 70 76/101 52/62 68.42/61.39 24/39 31.58/38.61 0.40 1.32(0.69-2.53) > 70 89/99 57/59 64.04/60.00 32/40 35.96/40.00 0.21 0.66(0.35-1.26) Body mass index (kg/m2) ≤ 23 56/68 35/42 62.50/61.76 21/26 37.50/38.24 0.86 1.07(0.51-2.24) > 23 109/132 74/79 67.89/59.85 35/53 32.11/40.15 0.17 1.49(0.85-2.62) Cigarette smoking Never 98/102 68/63 69.39/61.76 30/39 30.61/38.24 0.37 1.32(0.72-2.41) Ever 67/98 41/58 61.19/59.18 26/40 38.81/40.82 0.70 1.14(0.59-2.22) Alcohol drinking Never 100/132 68/83 0.68/62.88 32/49 0.32/37.12 0.71 1.12(0.63-1.98) Ever 65/68 41/38 63.08/55.88 24/30 36.92/44.12 0.32 1.44(0.70-2.93) Family history of cancers No 118/168 76/103 64.41/61.31 42/65 35.59/38.69 0.64 1.12(0.69-1.84) Yes 47/32 33/18 70.21/56.25 14/14 29.79/43.75 0.21 1.83(0.72-4.68) rs7158663(Cases/Controls) AA/AG GG n % n % Total 165/200 67/89 40.61/44.50 98/111 59.39/55.50 0.51 0.87(0.56-1.33) Age (years) ≤70 76/101 33/53 43.42/52.48 43/48 56.58/47.52 0.27 0.71(0.38-1.31) >70 89/99 34/36 38.20/36.36 55/63 61.80/63.64 0.87 1.05(0.57-1.93) Body mass index (kg/m2) ≤23 56/68 20/28 35.71/41.18 36/40 64.29/58.82 0.48 0.77(0.37-1.60) ＞23 109/132 47/61 43.12/46.21 62/71 56.88/53.79 0.86 0.95(0.56-1.64) Cigarette smoking Never 98/102 39/42 39.80/41.18 59/60 60.20/58.82 0.73 0.91(0.50-1.63) Ever 67/98 28/47 41.79/47.96 39/51 58.21/52.04 0.41 0.76(0.39-1.46) Alcohol drinking Never 100/132 38/58 38.00/43.94 62/74 62.00/56.06 0.60 0.86(0.49-1.51) Ever 65/68 29/31 44.62/45.59 36/37 55.38/54.41 0.71 0.87(0.43-1.78) Family history of cancers No 118/168 43/76 36.44/45.24 75/92 63.56/54.76 0.27 0.76(0.46-1.24) Yes 47/32 24/13 51.06/40.63 23/19 48.94/59.37 0.42 1.46(0.58-3.65) a Two-sided w2 test for the distributions between the cases and controls. b Odds ratios (ORs) were obtained from a logistic regression model with adjusting for age, BMI, cigarette smoking, alcohol drinking, family history of cancers. Association of MEG3 and risk of CaP-Xu et al. Vol 18 No 2 March-April 2021 178 Urological Oncology 179 rs7158663 A>G) were in accordance with Hardy-Wein- berg equilibrium (HWE) in the control subjects (rs11627993:x2 = 0.003 P = .99 rs7158663:x2 = 0.24 P = .89). However, neither of the two MEG3 polymor- phisms was associated with prostate cancer suscepti- bility, even after being adjusted for potential covariates (age, BMI, cigarette smoking, alcohol drinking, family history of cancers). We next evaluated the effects of combined risk genotypes on prostate cancer suscepti- bility. Similarly, no significant association was found (Table 2). For rs11627993, after adjusting for potential covariates, compared with CC homozygotes, subjects carrying CA heterozygotes (95% CI = 0.54-1.95, ORs = 1.03) or AA homozygotes (95%CI = 0.67-2.54, ORs = 1.30) had a decreased risk of CaP. In addition, subjects carrying AA homozygotes had a 1.26-fold reduced risk (95%CI = 0.81–1.98 , P = .29) than these carrying CC/CA gen- otypes, and the A allele displayed a higher prevalence of CaP compared with the C allele (95%CI = 0.85–1.57, ORs = 1.16, P = 0.35). Similarly, for rs7158663, af- ter adjusting for potential covariates, compared with AA homozygotes, subjects carrying AG heterozygotes (95%CI = 0.76-5.08, ORs = 1.97) or GG homozygotes (95%CI=0.57-3.29, ORs=1.37) had an increased risk of CaP (Table 3). The G allele displayed a lower prev- alence of CaP compared with the A allele (95%CI = 0.69–1.39, ORs = 0.98, P = .91). Stratified analyses We next evaluated the stratified association of rs11627993 and rs7158663 with prostate cancer risk by clinical stage (Localized: T1–2N0M0; Advanced: T3–4NxMx or TxN1Mx or TxNxM1), pathologic grade (Gleason score <7, 7, and >7) and serum PSA level (≤ 20 and >20) (Table3), potential covariates(Table 4). No association with rs11627993 or rs7158663 and pros- tate cancer was found. DISCUSSION It is well known that environmental and genetic fac- tors such as genetic mutations and polymorphisms contribute to prostate cancer carcinogenesis(12,13). Long non-coding RNAs are molecules larger than 200 nucle- otides, which do not code protein(14). It has been report- ed that lncRNAs affect not only biologic processes such as metabolism, proliferation, tissue differentiation, cell type identity maintenance, apoptosis, cell signal regu- lation, organ development, and aging but also tumor- igenesis(15,16). Maternally expressed gene 3 (MEG3) is a lncRNA which is expressed in many normal tissues, and located on chromosome 14q32.3(17). It is the first lncRNA identified as a tumor suppressor, preventing cancer initiation and development(18). Recent stud- ies demonstrated decreased MEG3 levels in a variety of primary human cancer(19). MEG3 expression lev- el is decreased in lung cancer(20). The downregulation of MEG3 usually led to more aggressive cancers and MEG3 expression level correlated with tumor grade and prognosis in colorectal cancer, and gastric cancer(21,22). Yin et al. analyzed 62 CRC cases and demonstrated that a lower MEG3 level correlates with lower pathologi- cal grade, deeper tumor invasion, and advanced TNM stage(23). Sun et al. reported that downregulated MEG3 is associated with poor prognosis and promotes cell proliferation in gastric cancer(24). Li et al. found MEG3 expression level is significantly lower in invasive NF- PAs compared to noninvasive NFPAs(25). SNPs play important roles in carcinogenesis by affecting gene ex- pression and function(26). Some polymorphisms may af- fect the expression and secondary structure of lncRNA, which contribute to the development of cancer(27-29). Cao et al. genotyped five tagSNPs in the MEG3(rs3087918, rs11160608, rs4081134, rs10144253, and rs7158663) to investigate their role in colorectal cancer risk in a case-control study. They demonstrated that rs7158663 may be associated with colorectal cancer risk(23). Anoth- er study reported that MEG3 rs4081134 was associated with the risk of neuroblastoma in Chinese children(30). However, no studies on the association between MEG3 polymorphisms and the risk of the prostate cancer have been conducted until now. This is the first study to explore the correlation between the MEG3 polymorphisms and prostate cancer suscep- tibility in China. The results showed that a family histo- ry of cancer increases the risk of prostate cancer. But no significant association was found between MEG3 pol- ymorphisms and the risk of prostate cancer. Our study had several limitations. The primary limitation was a small sample size, which may impair the strength of the statistical power, especially for the stratification anal- ysis. Secondly, only two MEG3 polymorphisms were genotyped. More potentially functionally polymor- phisms in MEG3 needed to be studied \ CONCLUSIONS In conclusion, our study showed that the MEG3 poly- morphisms (rs11627993 and rs7158663) have no im- pacts on the risk of prostate cancer. A study based on multi-hospitals with larger sample should be conducted. Moreover, in vitro and in vivo functional analysis to re- veal the mechanism how the genetic polymorphisms in MEG3 affect the prostate cancer risk also need to be studied. ACKNOWLEDGEMENTS This study was funded by The National Natural Sci- ence Foundation of China (No. 81872089, 81370849, 81672551, 81300472, 81070592, 81202268, 81202034), Natural Science Foundation of Jiangsu Province (BK20161434, BL2013032, BK20150642 and BK2012336), Six talent peaks project in Jiangsu Province (WSW-034) CONFLICT OF INTEREST The authors report no conflicts of interest in this work. REFERENCES 1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7- 34. 2. Chen W, Sun K, Zheng R, et al. Cancer incidence and mortality in China, 2014. Chin J Cancer Res. 2018;30:1-12. 3. Kumar V, Westra HJ, Karjalainen J, et al. Human disease-associated genetic variation impacts large intergenic non-coding RNA expression. PLoS Genet. 2013;9:e1003201. 4. Frazer KA, Murray SS, Schork NJ, Topol EJ. Human genetic variation and its contribution to complex traits. Nat Rev Genet. 2009;10:241- Association of MEG3 and risk of CaP-Xu et al. 51. 5. 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