Genetic Variants in the TEP1 Gene Are Associated with Prostate Cancer Risk and Recurrence

ORIGINAL ARTICLE Genetic variants in the TEP1 gene are associated with prostate cancer risk and recurrence

CGu1,2,8,QLi2,3,4,8, Y Zhu1,2,8,YQu1,2, G Zhang1,2, M Wang2,3, Y Yang5,6, J Wang5,6, L Jin5,6,QWei3,7 and D Ye1,2

BACKGROUND: Telomere-related genes play an important role in carcinogenesis and progression of prostate cancer (PCa). It is not fully understood whether genetic variations in telomere-related genes are associated with development and progression in PCa patients. METHODS: Six potentially functional single-nucleotide polymorphisms (SNPs) of three key telomere-related genes were evaluated in 1015 PCa cases and 1052 cancer-free controls, to test their associations with risk of PCa. Among 426 PCa patients who underwent radical prostatectomy (RP), the prognostic significance of the studied SNPs on biochemical recurrence (BCR) was also assessed using the Kaplan–Meier analysis and Cox proportional hazards regression model. The relative telomere lengths (RTLs) were measured in peripheral blood leukocytes using real-time PCR in the RP patients. RESULTS: TEP1 rs1760904 AG/AA genotypes were significantly associated with a decreased risk of PCa (odds ratio (OR): 0.77, 95% confidence interval (CI): 0.64–0.93, P = 0.005) compared with the GG genotype. By using median RTL as a cutoff level, RP patients with TEP1 rs1760904 AG/AA genotypes tended to have a longer RTL than those with the GG genotype (OR: 1.55, 95% CI: 1.04–2.30, P = 0.031). A significant interaction between TEP1 rs1713418 and age in modifying PCa risk was observed (P = 0.005). After adjustment for clinicopathologic risk factors, the presence of heterozygotes or rare homozygotes of TEP1 rs1760904 and TNKS2 rs1539042 were associated with BCR in the RP cohorts (hazard ratio: 0.53, 95% CI: 0.36–0.79, P = 0.002 and hazard ratio: 1.67, 95% CI: 1.07–2.48, P = 0.017, respectively). CONCLUSIONS: These data suggest that genetic variations in the TEP1 gene may be biomarkers for risk of PCa and BCR after RP. Prostate Cancer and Prostatic Diseases (2015) 18, 310–316; doi:10.1038/pcan.2015.27; published online 4 August 2015

INTRODUCTION to the end-replication problem.8 Progressive telomere shortening Although prostate cancer (PCa) is the second most commonly from cell division provides a barrier for tumor progression. diagnosed cancer and the sixth most common cause of cancer- Mounting evidence indicates that by initiating chromosomal related mortality among men worldwide,1 only 10%–20% of instability, short and dysfunctional telomeres may be involved 9 diagnosed cases die from the disease,2 whereas more patients in prostate carcinogenesis. In addition to be involved in PCa live to develop recurrences. Patients with localized and locally development, telomeres may also have a role in disease advanced PCa are frequently treated with radical prostatec- progression and tumor telomere alteration may prove to be a – tomy (RP). However, it is estimated that 430% of men under- useful prognostic marker of post-prostatectomy BCR.10 12 going RP will have disease relapse, also referred to as biochemical Theoretically, functional genetic variants that affect telomere recurrence (BCR), defined as the first clinical indication of a rising elongation, activation of telomerase and configuration of telo- serum level of PSA.3 The risk of disease development greatly meric proteins could lead to some accelerated functional changes differs among individuals, and the heterogeneity in clinical responsible for cancer development and further growth advan- behavior despite similar clinicopathologic characteristics further tages. Cancer genome-wide association studies have shown emphasizes the need to identify novel markers for recurrence.4 that single-nucleotide polymorphisms (SNPs) in the telomere- – Germline variation has been associated with risk of PCa and the related genes are associated with risk of various cancers.13 15 In recent use of genetic information to predict outcome and to guide addition, previous studies have identified several PCa suscept- treatment has also been steadily increasing in oncologic research ibility loci located in the telomerase reverse transcriptase (TERT) and practice.5 gene, the catalytic subunit of the telomerase ribonucleoprotein Telomeres are terminal, tandem nucleotide repeats (5′-TTAGGG-3′), complex.16,17 However, the impact of functional genetic variants in complex with telomere-binding proteins located at the ends of associated with PCa risk and recurrence in other telomere-related every chromosome, and are key components in the maintenance genes remains unclear. of chromosomal stability.6,7 In somatic cells, telomeres are There are two telomere-length maintenance mechanisms, shortening by 30–200 base pairs after each mitotic division due including telomerase-based and alternative lengthening of

1Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China; 3Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China; 4Department of Pathology, First Affiliated Hospital, Xinjiang Medical University, Urumqi, China; 5Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; 6Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China and 7Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA. Correspondence: Dr Q Wei, Cancer Institute, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai 200032, China or Dr D Ye, Department of Urology, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai 200032, China. E-mail: [email protected] or [email protected] 8These authors contributed equally to this work. Received 11 September 2014; revised 8 April 2015; accepted 13 April 2015; published online 4 August 2015 TEP1 polymorphisms and prostate cancer CGuet al 311 telomeres recombinational mechanisms. TEP1 is a key component Patients were treated with radiation, androgen deprivation therapy and of the telomerase ribonucleoprotein complex, responsible for RP. A subset of clinically localized PCa patients who underwent RP (n = 441) telomerase activity.18 TEP1 also interacts directly with Bloom between 2006 and 2009 were followed up by PSA at least every 3 months syndrome protein and modulates its helicase activity, suggesting and disease-management information available from medical records; that TEP1 has an important function in the alternative lengthening subjects were excluded if their medical records were not available (n = 15). 19 The median follow-up time of the entire patient cohort was 37.7 months. of telomere pathways. TNKS and TNKS2 enhance the access of BCR was defined as two consecutive PSA measurements 40.2 ng ml − 1 at telomerase to telomeres, thereby having a role in telomere 4 fi 20 an interval of 3 months and the date of this event was set to the rst of maintenance. Variants in TEP1 and TNKS have also been found to these two test occasions.25 This study was approved by the Institutional 21,22 be regulators of telomere length. Review Board of Fudan University Shanghai Cancer Center. Thus, we designed a case–control study using a candidate-gene approach, to test the hypothesis that potentially functional SNP selection and genotyping polymorphisms in three key telomere-related genes (TEP1, TNKS We searched the National Center for Biotechnology Information dbSNP and TNKS2), which have previously been related to telomere database (http://www.ncbi.nlm.nih.gov/) for potentially functional SNPs length are associated with PCa risk. The relationship between and SNPinfo (http://snpinfo.niehs.nih.gov/), to identify the candidate SNPs these SNPs and BCR were further tested among a subset of based on the following three criteria: (1) located at the regulatory or patients who received RP. coding region of genes (that is, the 5′-near gene, 5′-untranslated regions (UTRs), exons, splice sites, 3′-UTR and 3′-near gene); (2) the minor allele frequency ⩾ 5% in Chinese Han, Beijing descendants reported in HapMap; MATERIALS AND METHODS (3) affecting the activities of microRNA-binding sites in the 3′-UTR and Study design and population transcription factor binding sites in the putative promoter region or changing the amino acid in the exons. The study subjects were mostly from previously published case–control For the TEP1 gene, we chose rs1713418 and rs1760904; the former is study.23 Briefly, 1115 eligible patients recruited into this study were newly located in the 3′-UTR region and the latter is located in the exon region. diagnosed and histopathologically confirmed primary prostate adenocar- For the TNKS gene, we chose rs17734024 and rs1055328, both located in cinoma from Fudan University Shanghai Cancer Center between January the 3′-UTR region. For the TNKS2 gene, we chose rs1539042 and 2005 and January 2012, of whom 1015 (92%) agreed to participate in this rs3758499; the former is located in the 3′-UTR region and the latter is study (Figure 1). All cases had received no prior chemotherapy or located in the exon region. All these six selected SNPs were genotyped by radiotherapy on recruitment. The tumor stage was determined according the TaqMan real-time PCR method as described previously.26 Briefly, DNA to criteria established by the American Joint Committee on Cancer tumor- isolation was performed by using the Qiagen Blood DNA Mini KIT (Qiagen, node-metastasis classification system (American Joint Committee on Valencia, CA, USA) with the buffy-coat fraction of the blood samples Cancer Staging Manual, sixth edition, 2002). Histopathological grading of donated by the participants. The results with 499% call rates and 100% the biopsy and RP specimens was performed according to the Gleason concordance for duplicated specimens were acceptable for further score system. The clinical information including Gleason score, serum PSA genotyping data analysis. level at diagnosis, lymph node involvement and disease stage were abstracted from the archival medical records. In addition, 1143 age (± 5 years)- and geographical region-matched cancer-free ethnic Han Chinese Measurement of relative telomere length controls were recruited from the Taizhou longitudinal study conducted Relative telomere length (RTL) measurements were available in 426 patients 24 during a similar time period. Taizhou longitudinal study was a large who received RP. RTL as represented by the telomere repeat copy number prospective cohort initiated to explore the environmental and genetic risk to single-copy gene (that is, 36B4) copy number (T/S) ratio was measured factors for common non-communicable diseases. The sample size of the using real-time quantitative PCR method described by Cawthon27 on an cohort will be at least 100 000 adults aged 30–80 years, drawn from the Applied Biosystems 7900HT. The PCR reaction mixture consisted of SYBR general residents of the districts of Taizhou. Baseline investigations Green Mastermix (Applied Biosystems, Grand Island, NY, USA), 100 nmol l − 1 included interviewer-administered questionnaire, anthropometric mea- Tel-1, 900 nmol l − 1 Tel-2, 400 nmol l − 1 36B4d, 400 nmol l − 1 36B4u and 7 ng surements and collection of buccal mucosal cells and blood specimens. of genomic DNA. The thermal cycling profile was 95 °C for 10 min followed −1 Individuals with a known test of serum PSA 44ngml present with or by 40 cycles of 95 °C for 15 s and at 56 °C (for telomere) or 58 °C (for 36B4) without abnormal digital rectal examination were excluded from the for 1 min. Following amplification, a dissociation curve confirmed the control group and those without response to the study participation were specificity of the reaction. During each run, negative and positive controls, a excluded (n = 91). All of the participants were interviewed with a calibrator DNA sample and a standard curve were included. For each questionnaire after a written informed consent was obtained. Blood standard curve, twofold serial dilutions of a reference DNA sample were samples were collected and processed as a routine practice by the Fudan used to produce a standard curve in each reaction. Two main steps were University Shanghai Cancer Center Tissue Bank (for cases) and the Taizhou involved in RTL quantification: first, the T/S ratio was determined for each longitudinal study (for controls). sample based on the standard curve. Second, the ratio for each sample was normalized to the calibrator DNA to standardize sample values across all reaction plates. The laboratory personnel were blinded to BCR status. R2 for each standard curve was ⩾ 0.99.

Statistical analysis For all subjects, the χ2-test was used to assess differences in the frequency distributions of the selected demographic variables and genotypes of six SNPs between the cases and controls. The Hardy–Weinberg equilibrium for genotype distribution in controls was tested by a goodness-of-fit χ2-test. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by univariable and multivariable unconditional logistic regression models, to evaluate associations between the genotypes and risk of PCa without and with adjustment for confounding factors (age, smoking status and body mass index), respectively. Further stratification analyses were conducted to calculate the associations of SNP genotypes with PCa risk by demographic and clinicopathologic variables, followed by the homogeneity Q-tests. Based on the observed genotypes, haplotype frequencies were generated using Statistical Analysis Software PROC HAPLOTYPE (SAS Institute, Cary, Figure 1. Diagram showing the studying design. RP, radical NC, USA) to calculate ORs for haplotypes associated with PCa risk. The prostatectomy; RTL, relative telomere length; SNP, single-nucleotide interaction was also assessed by using a likelihood ratio test to compare polymorphism. models with and without the interaction terms.

© 2015 Macmillan Publishers Limited Prostate Cancer and Prostatic Diseases (2015), 310 – 316 TEP1 polymorphisms and prostate cancer CGuet al 312 For the 426 patients who received RP, the association between each SNP index did not differ significantly between BCR cases (median: and BCR of PCa was assessed with hazard ratios and 95% CI estimated by 24.1, range: 16.3–38.1) and non-BCR cases (median: 23.5, range: Cox proportional hazards regression analysis. The assumption of propor- 17.2–32.3, P = 0.106). tionality of the hazards was tested by using scaled Schoenfeld residuals. To evaluate the effects of genetic variations beyond the clinical factors to influence PSA recurrence, multivariate analyses were adjusted for Genetic variations and PCa risk stage, Gleason score, lymph node involvement and PSA at diagnosis. The genotype frequencies of the six SNPs and their associations The probability of freedom from the recurrence was estimated using the with PCa risk are summarized in Table 2. All the observed Kaplan–Meier method and the significance was determined using the genotype frequencies among the controls were in agreement log-rank test. For estimating recurrence risk, the time-dependent variable with Hardy–Weinberg equilibrium (P40.05). The genotype was defined as time from the date of RP to the first reported evidence of distribution of TEP1 rs1760904 was significantly different recurrence and patients without the event were censored at their last (P = 0.012) between the cases and controls. Compared with the follow-up update. Spearman’s rank correlation was used to investigate GG genotype, the TEP1 rs1760904 AG and AG/AA genotypes associations between RTL and age. RTL was categorized into dichotomies, were significantly associated with a decreased risk of PCa tertile and quartile, based on the distribution. (OR: 0.75 and 0.77, 95% CI: 0.62–0.91 and 0.64–0.93, respectively). Finally, the Bonferroni correction and false-positive report probability fi fi 28 However, no associations between variant genotypes of other ve were used to assess the false-positive ndings. All statistical analyses SNPs and PCa risk were observed. Three haplotype blocks were were performed with SAS software (version 9.1; SAS Institute). based on the observed genotype data (Supplementary Table 1) and the TNKS haplotype GG was significantly associated with the RESULTS PCa risk. The characteristics of all study participants are presented in Table 1. Cases had a higher percentage of body mass index Stratification and interaction analysis ⩽ 24 versus controls (Po0.001), which was further adjusted for in We detected a statistically significant interaction between age subsequent multivariable logistic regression analyses. Body mass and TEP1 rs1713418 variant genotypes in the stratification analysis (Supplementary Table 2). Overall, the TEP1 rs1713418 AG/GG genotypes were associated with a 32% increased risk of PCa among younger individuals but was associated with 29% reduced Table 1. Characteristics of PCa cases and controls risk of PCa among older ones, a finding of heterogeneity supported by additional homogeneity tests and confirmed by Variables Cases (%) Controls (%) P-values the interaction analyses (Supplementary Table 3). Such a statistical N = 1015 N = 1052 evidence of SNP–age interaction was not observed for other SNPs. Age (years) 69.1 ± 8.2 68.6 ± 8.9 0.828 To account for chance associations from multiple comparisons, ⩽ 64 291 (28.7) 308 (29.3) the Bonferroni correction was performed and false-positive report 65–75 496 (48.9) 500 (47.5) probability values for significant findings at different prior 475 228 (22.5) 244 (23.2) probability levels were shown in Supplementary Table 4.

2 BMI (kg/m ) Genetic variations and risk of PCa BCR ⩽ 24 579 (57.0) 508 (48.3) 0.001 424 436 (43.0) 544 (51.7) Telomere erosion has been reported to be a prognostic predictor of early likelihood of post-RP BCR.12–14 Here we evaluated the Smoking status effects of genetic variants in telomere-related genes in a cohort of Never 406 (40.0) 412 (39.2) 0.697 426 clinical localized PCa patients who underwent RP. Among 100 Ever 609 (60.0) 640 (60.8) (23.5%) men who experienced unfavorable outcomes, the median time to the BCR was 28.4 months (range, 2.1–55.7 months). PSA PSA value (ng ml − 1) o levels, pathologic stage, lymph node involvement and Gleason 10 180 (19.4) fi o 10–20 195 (21.0) score were signi cantly associated with the BCR (P 0.01) 420 552 (59.6) (Supplementary Table 5). We performed multivariable analyses Missing 88 (8.7) for each SNP and found significant associations of TEP1 rs1760904 and TNKS2 rs1539042 genotypes with risk of PCa BCR (Table 3). Gleason score The TEP1 rs1760904 displayed the most significant association, ⩽ 7 (3+4) 317 (31.2) with a 0.53-fold decreased risk (95% CI: 0.36–0.79) of PCa pro- ⩾ 7 (4+3) 606 (59.7) gression associated with the AG/AA genotypes, compared with Missing 92 (9.1) the GG genotype. Kaplan–Meier curves and log-rank tests were used to show the probability of BCR stratified by TEP1 rs1760904 Stage of disease fi I 5 (0.5) genotypes (P = 0.005, Figure 2). No statistically signi cant asso- II 434 (42.8) ciations were found for the other SNPs analyzed. III 142 (14.0) IV 356 (35.1) Genetic variations and RTL Missing 78 (7.7) To investigate whether the RTL had prognostic significance, PCa Treatment patients who underwent RP were categorized into dichotomies, RP 441 (43.4) tertiles and quartiles based on their RTL distribution (range, 0.06– Radiation with or 224 (22.1) 2.06). RTL was inversely associated with age (r = − 0.40, Po0.001). without ADT When participants were dichotomized according to the median ADT 344 (33.9) RTL value, significant differences in RTL by genotype of TEP1 Other treatment 6 (0.6) rs1760904 were observed (Table 4). Longer RTL showed a fi Abbreviations: ADT, androgen-deprivation therapy; BMI, body mass index; signi cantly higher proportion of the AG/AA genotypes, compared PCa, prostate cancer; RP, radical prostatectomy. with that of the GG genotype (OR: 1.55, 95% CI: 1.04–2.30). The association between RTL and risk of BCR did not differ significantly

Table 2. Genotype frequencies of TEP1, TNKS and TNKS2 polymorphisms and their associations with PCa risk

SNP HWE Cases (%) Controls (%) P-value OR (95% CI) P-valuea

TEP1 rs1713418 AA 0.28 373 (36.8) 381 (36.2) 0.941 1.00 AG 465 (45.8) 490 (46.6) 0.97 (0.80–1.17) 0.740 GG 177 (17.4) 181 (17.2) 1.01 (0.78–1.29) 0.971 AG/GG 642 (63.3) 671 (63.8) 0.802 0.98 (0.82–1.17) 0.807

TEP1 rs1760904 GG 0.37 386 (38.0) 338 (32.1) 0.012 1.00 AG 451 (44.4) 529 (50.3) 0.75 (0.62–0.91) 0.003 AA 178 (17.5) 185 (17.6) 0.84 (0.65–1.09) 0.184 AG/AA 629 (62.0) 714 (67.9) 0.005 0.77 (0.64–0.93) 0.005

TNKS rs17734024 GG 0.12 659 (64.9) 647 (61.5) 0.222 1.00 AG 309 (30.4) 345 (32.8) 0.87 (0.72–1.05) 0.145 AA 47 (4.6) 60 (5.7) 0.75 (0.50–1.11) 0.152 AG/AA 356 (35.1) 405 (38.5) 0.107 0.85 (0.71–1.02) 0.079

TNKS rs1055328 CC 0.63 468 (46.1) 514 (48.9) 0.209 1.00 CG 461 (45.4) 438 (41.6) 1.16 (0.97–1.39) 0.104 GG 86 (8.5) 100 (9.5) 0.94 (0.69–1.29) 0.714 CG/GG 547 (53.9) 538 (51.1) 0.211 1.12 (0.94–1.33) 0.195

TNKS2 rs1539042 GG 0.19 482 (47.5) 515 (49.0) 0.793 1.00 CG 424 (41.8) 429 (40.8) 1.05 (0.88–1.26) 0.598 CC 109 (10.7) 108 (10.3) 1.08 (0.80–1.44) 0.627 CG/CC 533 (52.5) 537 (51.1) 0.505 1.06 (0.89–1.26) 0.540

TNKS2 rs3758499 GG 0.57 278 (27.4) 301 (28.6) 0.363 1.00 AG 544 (53.6) 532 (50.6) 1.10 (0.90–1.35) 0.366 AA 193 (19.0) 219 (20.8) 0.95 (0.73–1.22) 0.665 AG/AA 737 (72.6) 751 (71.4) 0.536 1.05 (0.87–1.28) 0.596 Abbreviations: BMI, body mass index; CI, conﬁdence interval; HWE, Hardy–Weinberg equilibrium; OR, odds ratio; PCa, prostate cancer; SNP, single-nucleotide polymorphism. aAdjusted for age, smoking status and BMI. Bold values indicate Po0.05.

between cases with longer RTL compared with those with shorter between genetic variations in the TEP1 gene and PCa recurrence. ones (hazard ratio: 1.26, 95% CI: 0.85–1.87). Results were similar Subsequent real-time quantitative PCR assays consistently showed when considering tertiles or quartiles cutpoints (Supplementary TEP1 rs1760904 was associated with RTL in 426 RP patients. Table 5). Although this association became borderline after Bonferroni correction was applied, the current study showed evidence of men with the AG/AA genotypes tended to have longer DISCUSSION telomeres than the men with the GG genotype. This finding may In the present study, we identified that the TEP1 rs1760904 variant contribute to a more accurate prediction of clinical outcome and genotypes were significantly associated with PCa risk. Individuals enhance the selection of the high-risk patients who may benefit with one or two copies of the TEP1 rs1760904 A allele were at from more aggressive adjuvant therapy and more intensive 0.77-fold lower PCa risk than the GG homozygotes. Genetic follow-up. variants of TEP1 have been previously examined in relation to In addition to age, smoking and obesity also accelerate telo- bladder, hepatocellular and breast cancer risk.18,22,29 This SNP is mere shortening by increasing systemic oxidative burden.30,31 non-synonymous and causes a substitution of proline to serine Thus, we conducted exploratory analyses of SNP–environment (Ser1195Pro), which is likely to affect TEP1 structure and influence interactions with smoking, body mass index and age. It is telomerase, as well as BLM helicase activity. Telomere shortening noteworthy that there was a significant interaction between can initiate tumor growth and constrain PCa progression. There- TEP1 rs1713418 and age. Mounting evidence suggests that cancer fore, it is a likely candidate for the source of the complex genetic is an aging-associated disease, and that cancer and aging share changes underlying the phenotypic diversity of PCa.9 many molecular pathways.32 Physiologically, telomeres undergo Moreover, we found that the TEP1 rs1760904 might be an shortening with each cell division and consequently telomeres independent predictive factor for post RP BCR in the study shorten with age. An age-related decline in telomere length may population. In the Kaplan–Meier and multivariable Cox hazards promote genetic instability and affect the risk of malignancies.33 regression analyses, this SNP predicted BCR risk in patients with TEP1 codes for protein that has a key role in telomerase that is localized PCa treated by RP after adjustment for the known clinical responsible for catalyzing the addition of new telomeres to predictors of recurrence. Although TEP1 has not been functionally chromosomes.18 These results support the presence of biological implicated in PCa to date, we speculated that telomere length interactions between telomere attrition and age on PCa develop- was a physiological modulator involved in the association ment and recurrence (Figure 3). Accounting for risk factors and

Table 3. Association between TEP1, TNKS and TNKS2 polymorphisms and PCa BCR

SNP Genotype BCR, n (%) Non-BCR, n (%) HR (95% CI) HR (95% CI)a P-values

TEP1 rs1713418 AA 32 (32.0) 114 (35.0) 1.00 1.00 AG 48 (48.0) 148 (45.4) 1.09 (0.70–1.70) 1.24 (0.79–1.94) 0.361 GG 20 (20.0) 64 (19.6) 1.06 (0.61–1.86) 1.08 (0.61–1.89) 0.802 AG/GG 68 (68.0) 212 (65.0) 1.08 (0.71–1.65) 1.18 (0.77–1.81) 0.438 TEP1 rs1760904 GG 51 (51.0) 116 (35.6) 1.00 1.00 AG 36 (36.0) 153 (46.9) 0.51 (0.31–1.05) 0.54 (0.35–0.83) 0.005 AA 13 (13.0) 57 (17.5) 0.55 (0.37–0.88) 0.51 (0.27–0.94) 0.032 AG/AA 49 (49.0) 210 (64.4) 0.57 (0.39–0.85) 0.53 (0.36–0.79) 0.002 TNKS rs17734024 GG 71 (71.0) 202 (62.0) 1.00 1.00 AG 26 (26.0) 111 (34.0) 0.77 (0.49–1.21) 0.74 (0.47–1.17) 0.198 AA 3 (3.0) 13 (4.0) 0.55 (0.17–1.77) 0.34 (0.10–1.10) 0.072 AG/AA 29 (29.0) 124 (38.0) 0.74 (0.48–1.15) 0.83 (0.52–1.32) 0.147 TNKS rs1055328 CC 57 (57.0) 164 (50.3) 1.00 1.00 CG 36 (36.0) 132 (40.5) 0.81 (0.53–1.23) 0.86 (0.56–1.33) 0.503 GG 7 (7.0) 30 (9.2) 0.79 (0.36–1.74) 0.91 (0.41–2.00) 0.810 CG/GG 43 (43.0) 162 (49.7) 0.81 (0.54–1.20) 0.87 (0.58–1.31) 0.517 TNKS2 rs1539042 GG 41 (41.0) 155 (47.5) 1.00 1.00 CG 47 (47.0) 134 (41.1) 1.31 (1.02–2.60) 1.62 (1.05–2.41) 0.032 CC 12 (12.0) 37 (11.4) 1.37 (0.72–2.60) 1.91 (0.89–3.42) 0.071 CG/CC 59 (59.0) 171 (52.5) 1.36 (1.02–1.97) 1.67 (1.07–2.48) 0.020 TNKS2 rs3758499 GG 27 (27.0) 93 (28.5) 1.00 1.00 AG 59 (59.0) 177 (54.3) 1.02 (0.64–1.61) 1.12 (0.71–1.78) 0.620 AA 14 (14.0) 56 (17.2) 0.82 (0.43–1.56) 0.85 (0.44–1.63) 0.628 AG/AA 73 (73.0) 233 (71.5) 0.97 (0.62–1.51) 0.95 (0.60–1.48) 0.803 Abbreviations: BCR, biochemical recurrence; CI, conﬁdence interval; HR, hazard ratio; PCa, prostate cancer; SNP, single-nucleotide polymorphism. aAdjusted for age, PSA, Gleason score, lymph node involvement, tumor stage and year of surgery. Bold values indicate Po0.05.

and the results have not been entirely consistent.18,36–38 However, only one study has investigated the effect of TNKS2 polymorphisms on cancer prognosis. In this study, TNKS2 rs2066276 located in the promoter of the TNKS2 gene, in partial linkage disequili- brium with rs1539042 (r2 = 0.41 and D’ = 1), showed a significant correlation with histologic grade of but not susceptibility to breast cancer.36 These data support the hypothesis that clinical outcomes may benefit from TNKS2 inhibition in the treatment of PCa. Germline genetic variation has the potential to be a marker for predisposition to aggressive disease and may provide insights into biological pathways of initiation and progression of PCa.39 Given the potential genetic heterogeneity existing in tumor tissues, the use of inherited variation to predict treatment response is appealing, which could potentially allow for more tailored PCa therapies. Several SNPs have yet been identified, Figure 2. Kaplan–Meier analysis of time to biochemical recurrence which adds clinically significant increment to the prognostic after radical prostatectomy, stratified by genotypes of TEP1 power of currently used clinical indicators and seem to improve rs1760904. BCR, biochemical recurrence. the predictive accuracy of preoperative nomograms for tumor progression.39,40 As initial studies investigating prognostic end- points were inconsistent,39,41,42 we chose the clinical endpoint of BCR when designing the study. Although BCR itself portends their potential interactions with genetic factors could result in a variable prognosis and does not always predict systemic improved discrimination in risk stratification. recurrence,3 its use as a primary outcome after RP is significant, TNKS2 regulates telomere homeostasis by binding to TRF1, the because BCR is the primary trigger for further intervention with negative regulator of telomere length.20 Discovery of roles for salvage radiation therapy or androgen-deprivation therapy.43 TNKS2 in cellular processes involved in proliferation and survival Moreover, in light of the relatively high proportion of men has raised the possibility of using TNKS2 inhibitors as novel anti- experiencing BCR,3 a prognostic biomarker that accurately reflects cancer therapeutics.34 In multivariable analyses, heterozygotes the risk of BCR would have a direct clinical impact by determining or rare homozygotes of the TNKS2 rs1539042 variant allele were which patients are at highest risk of BCR for further treatment. at 1.55-fold increased risk for BCR. An SNP located specifically in With this information, an informed conversation can be held the 3′-UTR of the TNKS2 gene, such as rs1539042, may change the between patients and physicians on whether or not to initiate the affinity of a miRNA-binding site so as to repress translation or needed therapy immediately due to an increased risk or whether destabilize mRNA. In fact, miR-20a had been shown to modulate or not an observation period is preferable. Indeed, these findings the translation of TNKS2 mRNA via the binding sites in the 3′-UTR that variations in TEP1 rs1713449 and TNKS2 rs1539042 may help and promote colony formation, cellular invasion and migration of to accurately define the patient population that would benefit cancer cells.35 Four previous studies have examined the associa- from adjuvant therapy in men receiving RP is intriguing and tion between genetic variants in the TNKS2 genes and cancer risk, worthy of further studies.

Table 4. Association between TEP1 rs1760904 and RTL

SNP Genotype Short RTL, n (%) Long RTL, n (%) OR (95% CI)a P-values

TEP1 rs1713418 AA 67 (32.2) 79 (36.2) 1.00 AG 100 (48.1) 96 (44.1) 0.82 (0.53–1.26) 0.358 GG 41 (19.7) 43 (19.7) 0.87 (0.51–1.50) 0.692 AG/GG 141 (67.8) 139 (63.8) 0.83 (0.56–1.25) 0.374 TEP1 rs1760904 GG 92 (44.3) 75 (34.4) 1.00 AG 81 (38.9) 108 (49.5) 1.67 (1.10–2.56) 0.017 AA 35 (16.8) 35 (16.1) 1.26 (0.72–2.21) 0.425 AG/AA 116 (55.7) 143 (65.6) 1.55 (1.04–2.30) 0.031 TNKS rs17734024 GG 129 (62.0) 144 (66.1) 1.00 AG 73 (35.1) 64 (29.4) 0.77 (0.51–1.17) 0.225 AA 6 (2.9) 10 (4.5) 1.50 (0.53–4.24) 0.446 AG/AA 79 (38.0) 74 (33.9) 1.21 (0.81–1.80) 0.358 TNKS rs1055328 CC 113 (54.3) 108 (49.5) 1.00 CG 76 (36.5) 92 (42.2) 1.28 (0.85–1.92) 0.232 GG 19 (9.2) 18 (8.3) 0.99 (0.50–2.01) 0.996 CG/GG 95 (45.7) 110 (50.5) 1.22 (0.83–1.79) 0.302 TNKS2 rs1539042 GG 98 (47.1) 98 (45.0) 1.00 CG 92 (44.2) 89 (40.8) 0.97 (0.64–1.46) 0.895 CC 18 (8.7) 31 (14.2) 1.72 (0.90–3.29) 0.098 CG/CC 110 (52.9) 120 (55.0) 0.91 (0.62–1.33) 0.630 TNKS2 rs3758499 GG 54 (26.0) 66 (30.3) 1.00 AG 114 (54.8) 122 (56.0) 0.87 (0.56–1.35) 0.535 AA 40 (19.2) 30 (13.7) 0.61 (0.34–1.12) 0.105 AG+AA 154 (74.0) 153 (69.7) 0.80 (0.53–1.23) 0.309 Abbreviation: BMI, body mass index; CI, conﬁdence interval; OR, odds ratio; RTL, relative telomere length; SNP, single-nucleotide polymorphisms. aAdjusted for age, BMI and smoking status. Bold values indicate Po0.05.

may be explained by the limited sample size and further studies would be needed to definitively evaluate these relationships in larger sample sizes. Furthermore, this study did not have sufficient statistical power to identify the associations between telomere- related gene SNPs and outcome after prostate radiotherapy; a larger study focus on the radiation therapy would be necessary to answer this question. Finally, our study was based on the leukocytes telomere length only and not on the prostate tissue telomere length. As there is an intra-individual synchrony in telomere length across the somatic tissues of humans as evidenced by the strong correlations between the telomere lengths in all tissue types.46 Moreover, the rates of telomere shortening are similar in the somatic tissues.46 However, future work aims to directly describe the relationships between prostate tissue, leukocytes Figure 3. Model depicting the effect of genetic variants and aging telomere lengths and PCa BCR cases. on prostate cancer growth and progression underlying telomere attrition. Risk genetic variants and aging lead to progressive telomere shortening, which allows the proliferation of cells with telomere dysfunction-induced genomic instability and gene aberra- CONCLUSIONS tions, resulting in carcinogensis. In addition, telomere attrition promotes telomerase reactivation, leading to tumor progression. In conclusion, we identified that TEP1 rs1760904 was associated with both risk of PCa and RTL. In addition, SNPs of TEP1 and TNKS2 also influenced risk of tumor progression independent of the known clinicopathologic predictors. This work was built on the In agreement with previous studies,2,3,40 we found that PSA, importance of telomere-related genetic variants in the PCa Gleason score, lymph node involvement and disease stage fi were among the most important predictors of BCR. Thus, the biology and it is essential that our ndings are replicated in results of this study are strengthened by these well-known independent studies with longer follow-up periods for cancer prognostic factors of PCa recurrence. However, there were some outcomes. Relevant functional studies will clarify the link between limitations to consider in interpreting these results. One potential telomere-related genes and PCa risk and recurrence. If confirmed, drawback of the current study was that we did not investigate these findings will further advance the understanding of PCa all genes involved in the telomere pathway and some possible occurrence and prognosis, with the ultimate goal of better significant SNPs of other telomere-related genes might be missed. individualizing treatment for PCa. Additional studies of the role of other telomere-related gene variants in PCa are warranted. In addition, several studies have indicated a relationship between smoking and telomere shortening,30,44,45 whereas we found no interaction between CONFLICT OF INTEREST smoking and telomere length in the present study. This finding The authors declare no conflicts of interest.

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