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Effect of the TERT mutation on the prognosis of patients with urothelial carcinoma: a systematic review and meta-analysis



Telomerase reverse transcriptase (TERT) mutation represents the most prevalent genetic mutation found in urothelial carcinoma (UC) and holds potential as a prognostic indicator for tumor outcomes. However, the association between TERT mutation and prognosis in UC patients remains poorly elucidated due to conflicting findings in existing literature. Therefore, this study aimed to investigate the effect of the TERT mutation on the survival of UC patients.


We systematically searched the PubMed, Embase, and Cochrane Library databases for studies that investigated the relationship between the TERT mutation and the prognosis of UC patients. Endpoints included the 2-year and 5-year recurrence-free survival (RFS) and overall survival (OS). The Newcastle–Ottawa Scale (NOS) tool was used to assess the risk of bias in the included studies. Review Manager 5.3 was used for the meta-analysis.


Nine studies with a total of 1,552 patients were included in the analysis. Two studies were prospective, and seven were retrospective. The TERT promoter mutation was associated with a lower 2-year OS (relative risk [RR] = 0.92, 95% confidence interval [CI] 0.86–0.98; P = 0.007) and a lower 5-year OS (RR = 0.80, 95% CI 0.68–0.94; P = 0.008) compared with the TERT wild type. However, no significantly differences were found between two groups in terms of HR for OS (hazard ratio [HR] = 1.29, 95% CI 0.80–2.08; P = 0.29). Furthermore, we investigated the differences in RFS and disease-specific survival (DSS) between the two groups.


The TERT mutation increases the risk of death and decreases the survival time of UC patients. TERT may be a valuable marker with individual prognostic value.

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Urothelial carcinoma (UC) is the most common malignant tumor of the urinary system, with a high incidence of morbidity and mortality [1, 2]. It can be found anywhere in the urinary tract, from the renal pelvis to the urethra [3]. Known tumor markers such as p53, Aurora-A, and plasma fibrinogen are associated with the diagnosis and prognosis of UC [4, 5]. But they are also common in other tumors and lack specificity. Moreover, finding a biomarker to accurately diagnose and predict the prognosis of UC is challenging due to its molecular heterogeneity [6]. Therefore, it is imperative to investigate the cancer biology and pathogenesis in order to ascertain the prognosis of UC.

Telomeres are specialized structures located at the ends of chromosomes in eukaryotic cells. They are fundamentally DNA–protein complexes with significant biological functions, such as stabilizing chromosomes, preventing DNA fusion and degradation, protecting chromosomal structural genes, and regulating normal cell growth. Telomerase is a ribonucleoprotein that synthesizes telomere DNA at the ends of chromosomes, thereby compensating for terminal replication and allowing cells to proliferate indefinitely [7,8,9]. Telomerase is activated in the majority of human cancers, including bladder cancer and some urogenital tumors. Increased telomerase activity is attributed to the transcriptional regulation of TERT and is regarded as a hallmark of malignancy in humans [10, 11]. The TERT mutation is also the most common gene mutation in UC [3]. However, the association between TERT mutation and prognosis in UC patients remains poorly elucidated. Most studies have found that the TERT mutation shortens patient survival, which is related to disease progression and recurrence [1, 3, 12,13,14,15]. On the contrary, Jenny et al. reported that UC patients harboring the TERT mutation exhibit elevated rates of recurrence-free survival (RFS) at the 2-year and 5-year marks [6]. Likewise, TERT mutation improved PFS (HR 0.38, P = 0.012) and OS (HR 0.32, P = 0.037) in one study [16]. No difference was found between two groups regarding PFS and OS in Neal’s study [17].

Therefore, we conducted a systematic review and meta-analysis to determine the impact of the TERT mutation on the survival of UC patients and to aid in clinical treatment planning.


The systematic review and meta-analysis were based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [18], and the study has been registered on the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023430667).

Eligibility criteria

Eligibility criteria were formulated using the specific population, intervention, comparison, outcomes, and study design (PICOS) framework. This review included studies that fulfilled the following criteria: (P): adults aged over eighteen with UC; (I): gene sequencing identified the TERT mutant type; (C): gene sequencing identified the TERT wild type; (O): OS, RFS, and DSS; (S): retrospective and prospective cohort studies.

Case series, surveys, letters, editorial comments, reviews, and animal studies were not included. In addition, studies without original data, those that did not explicitly report HR or Kaplan–Meier curves, and articles in languages other than English were excluded.

Information sources, search strategy, and selection process

A systematic search was conducted using Embase, PubMed, and the Cochrane Library. The search terms used were: (Telomerase OR TERT OR Telomerase Reverse Transcriptase OR Reverse Transcriptase; Telomerase OR Transcriptase; Telomerase Reverse OR Telomerase Catalytic Subunit) AND (Carcinoma; Transitional Cell OR Transitional Cell Carcinoma OR Transitional Cell Carcinomas OR Urothelial Carcinoma OR Urothelial Carcinomas). The search results were limited to humans. Studies published between January 1, 1990, and February 1, 2023, were included. Studies that meet our PICOS criteria were included.

Data collection process and data items

Two authors extracted data from the nine included studies. Data extracted included study type (prospective or retrospective study), first author, study duration, pathological type of tumor, number of patients, sex ratio, follow-up time, survival outcome, 2-year or 5-year survival rate (OS, RFS, and DSS), HR with 95% CI, and data source. The Engauge Digitizer was used to extract the survival rate from the Kaplan–Meier curves. We calculated HR for studies that did not present a 95% confidence interval (CI) employing the methodologies outlined in the literature of Jayne F. Tierney [19]. Three outcome measures were analyzed based on data availability and clinical correlation: OS, RFS, and DSS. Where disease-free survival (DFS) and failure-free survival were presented, these outcomes were deemed equivalent to RFS. The results could not be extracted if the study authors chose to stratify results based on a specific subgroup of the study rather than report results for the entire population.

Risk of bias assessment

The Newcastle–Ottawa Scale (NOS) [20, 21] was used to assess the quality of all studies. The NOS checklist includes three quality parameters: population selection (four points), comparability of cohorts (two points), and assessment of outcome for cohort studies (three points). Each study received a score ranging from zero to nine. Studies with a score of seven or higher were considered high-quality articles.

Synthesis methods

The meta-analysis included retrospective and prospective cohort studies and was performed using Review Manager 5.3 (Cochrane Collaboration, Oxford, UK). We pooled clinical effect estimates using the hazard ratio (HR), relative risk (RR), and their respective 95% CIs. The statistical significance level was set at P < 0.05. The Mantel–Haenszel effects model and inverse-variance effects model were used to combine the trials. We calculated and depicted forest plots with a 95% CI. The I2 test and Cochran’s Q test were used to assess the heterogeneity. Statistical heterogeneity was indicated by P < 0.1 in the Cochran’s Q test and I2 > 50% in the I2 test. If heterogeneity existed, a random effect model was adopted; otherwise, a fixed effect model was adopted. I2 values of 25%, 50%, and 75% indicate low, moderate, and high levels of inconsistency, respectively [22]. Various Kaplan–Meier curves described in the original literature were used to calculate the survival rate and HR with a 95% CI. Further sensitivity analyses were conducted to reduce heterogeneity and confirm the reliability of our findings.


Study selection, characteristics, and risk of bias

We found 455 articles, of which nine [1, 3, 6, 12,13,14,15,16,17] were selected for further analysis. Figure 1 depicts the search process (PRISMA flowchart). Two studies were prospective, and seven were retrospective. There were 1,552 participants. The follow-up period ranged from 5 to 25 years. Four studies focused on bladder cancer, one on upper tract urothelial cancer (UTUC), and four on urothelial carcinoma. Table 1 provides an overview of the patients and details of our study population. Furthermore, in the cohort study by Nakanishi et al. [14], DFS was the time between the initial radical operation and the subsequent appearance of recurrence. In this study, DFS is considered to be equivalent to RFS.

Fig. 1
figure 1

Flowchart illustrating the major steps of the review process in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement

Table 1 Characteristics of the included studies

Table 2 presents the variables from the included studies. The assessment of the effect of the TERT mutation on the prognosis of UC patients varied but included at least one of the following: OS, RFS, and DSS.

Table 2 The variables of the included studies

As shown in Table 2, all the included studies are of high quality.

Synthesis results

Overall survival

The meta-analysis included eight studies with a total of 1,458 patients [1, 6, 12,13,14,15,16,17]. Figure 2 depicts the pooled results of overall survival. Forest plots revealed that the TERT promoter mutation was associated with a lower 2-year OS (RR = 0.92, 95% CI 0.86–0.98; P = 0.007) and a lower 5-year OS (RR = 0.80, 95% CI 0.68–0.94; P = 0.008) compared to the TERT wild type. However, pooled results from eight studies showed no significant differences in the HR for OS (P = 0.29). These results suggest that patients without the TERT mutation may have a significant overall survival advantage.

Fig. 2
figure 2

Forest plot comparing the overall survival of the TERT mutation and control groups

Recurrence-free survival

The meta-analysis included three studies with a total of 291 patients [3, 6, 14]. Figure 3 depicts the pooled results of recurrence-free survival. Meta-analysis demonstrates that the pooled estimates of 5-year RFS (RR 0.77, 95% CI 0.62–0.96; P = 0.02) was lower in TERT mutation group than those in control group. However, pooled results from three studies showed no significant differences in the HR for RFS and 2-year RFS. Furthermore, in the study conducted by Yang CH et al., HR for RFS was not available and thus was not incorporated into the meta-analysis. Therefore, pooled HR was not consistent with pooled 2-year and 5-year RFS.

Fig. 3
figure 3

Forest plot comparing the recurrence-free survival of the TERT mutation and control groups

Disease-specific survival

Figure 4 depicts the overall pooled results of the preliminary analysis of disease-specific survival. 2-year DSS and 5-year DSS results were available from three studies with a pooled OR of 0.89 (95% CI 0.80–0.99; P = 0.03), 0.85 (95% CI 0.74–0.97; P = 0.02), respectively. And pooled HR for DSS was 2.23 (95% CI 1.41–3.53; P < 0.001). There was no obvious heterogeneity between the included studies, and pooled analysis showed significant differences in the 2-year DSS, 5-year DSS, and HR for DSS. Therefore, these results indicate that patients without the TERT mutation have a DSS advantage.

Fig. 4
figure 4

Forest plot comparing the disease-specific survival of the TERT mutation and control groups

Sensitivity analysis and heterogeneity

Sensitivity analysis was carried out only when more than three studies were compared. When the studies conducted by Neal and Rachakonda were excluded from the OS analysis, the pooled 5-year OS was 0.74 (95% CI 0.65–0.84; p < 0.001). Meanwhile, the heterogeneity was also changed (I2 = 40%, P = 0.14). Rachakonda’s study was excluded because its outcome differed significantly from other studies (RR = 0.93, 95% CI 0.79–1.09; p > 0.05) and it had a high weight. Neal’s study was excluded because of analogous reasons. Furthermore, after running the leave-one-out test, the leave-one-out sensitivity analysis showed no significant differences in terms of HR for OS. Although there was still heterogeneity among the included studies, this is not surprising given global economic, cultural, and ethnic differences.

Assessment of publication bias

We were unable to assess publication bias because the testing ability was insufficient when there were 10 or fewer studies [23, 24].


We present the first systematic review and meta-analysis investigating the effect of the TERT mutation on the prognosis of UC patients. The analysis included nine studies with a total of 1,552 patients. OS and RFS are the most extensively studied survival outcomes that have been investigated in multiple studies. In contrast, MFS has only been the subject of one study [15].

Several key findings are reported in our pooled study analysis. First, the TERT mutation is found in the majority of UC patients, and some studies have demonstrated that such a mutation is an early event in the progression of UC [13]. Second, the TERT mutation is associated with a higher risk of mortality and recurrence, even though there is no statistical significance in the HR for OS and RFS. Third, compared to the 2-year survival rate, a more pronounced disparity is observed in the 5-year survival rates between the mutant type and the wild type. This observation signifies that UC patients with the TERT mutation experience an inferior long-term survival outcome. The consistency of these findings indicates their reliability and robustness as a whole.

At present, next-generation sequencing technology enables us to gain a comprehensive understanding of cancer biology and the pathogenesis of UC [25]. UC has a higher frequency of mutations than other human tumors. These include mutations of tumor suppressor genes (TP53, RB1), the RAS/RAF pathway, the mTOR pathway, and the TERT gene promoter [25, 26]. TERT mutations are typically found in two hotspots of the promoter region: chromosome 5: -124G > A and -146G > A [1, 6, 12, 13, 15]. Recent studies have linked TERT promoter mutations with tumorigenesis in UC. TERT promoter mutations also have a high potential for UC diagnosis and prognosis [27].

The TERT promoter mutation is one of the most common gene mutations in UC [3, 28]. In the study conducted by Boaz Kurtis et al. [28,29,30], TERT mutation status did not correlate with age, sex, tumor location, histological grade, pathological stage, or invasiveness. Therefore, TERT can be used as an independent predictor of prognosis in UC patients. In other words, regardless of tumor grade or stage, TERT can be used as a predictor of the prognosis of the tumor. However, in the study conducted by Ping Yuan et al. [31], TERT non-mutation carriers in cancer patients were younger than carriers, and female patients were less likely to carry the TERT mutation. Therefore, there is a contradiction between the studies of Boaz Kurtis and Ping Yuan. Furthermore, one study found that TERT promoter mutations are rarer in patients under 39 years of age [32]. This is consistent with the study conducted by Ping Yuan. However, the predictive value of TERT would not be affected because the age at diagnosis in UC patients is mostly greater than 60 years [2].

This review has several limitations. The relationship between the TERT mutation and MFS cannot be estimated due to the lack of positive events. Furthermore, the small sample size of the included studies makes it difficult to draw a reliable conclusion. In the study conducted by Sumit et al. [15], the TERT mutation decreased MFS in UC patients. Therefore, more high-quality research is required to evaluate the relationship between the TERT mutation and MFS in UC patients. Moreover, Ismail et al. showed that gender, age at diagnosis, tumor grade and stage, type of disease, and lymph node metastasis were all independently associated with poor patient survival [1, 13, 15]. Unfortunately, because some clinical information was missing in the included studies, we were unable to perform a subgroup analysis based on sex, age, tumor grade, or tumor stage. Similarly, HR values with 95% CI were missing in some studies. We used the method mentioned in the study conducted by Jayne F. Tierney [19] to calculate HR with a 95% CI. Some errors were inevitable in this process.

Additional research is required to evaluate the TERT gene mutation and determine its effect on the prognosis of a more explicitly defined population. This population should include patients with bladder cancer, ureteral cancer, and renal pelvis cancer. Such studies should be prospective and multicenter, and they should compare the TERT mutant to the wild type. These studies should include both baseline characteristics (gender, age at diagnosis, tumor stage, grade, and type of disease) and survival outcomes (OS, RFS, DSS, and MFS). In addition, although TERT showed clinically relevant values in urothelial carcinoma, a rapid and cost-effective method needs to be developed before routine use.


In conclusion, this meta-analysis provides pooled estimates of the effect of the TERT mutation on the prognosis of UC patients. TERT mutations in UC patients are associated with poor survival and prognosis. TERT may be a unique marker with individual prognostic value. To further determine the effect of the TERT mutation on UC patients, prospective multicenter large-cohort studies are needed.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.



Telomerase reverse transcriptase


Urothelial carcinoma


Overall survival


Recurrence-free survival


Hazard ratio


Relative risk


Confidence interval


Disease-specific survival


Metastasis-free survival


Carbohydrate antigen 19–9


Upper tract urothelial cancer


  1. Hosen I, Rachakonda PS, Heidenreich B, de Verdier PJ, Ryk C, Steineck G, Hemminki K, Kumar R. Mutations in TERT promoter and FGFR3 and telomere length in bladder cancer. Int J Cancer. 2015;137(7):1621–9.

    Article  CAS  PubMed  Google Scholar 

  2. Miyazaki J, Nishiyama H. Epidemiology of urothelial carcinoma. Int J Urology : Official J Japanese Urological Assoc. 2017;24(10):730–4.

    Article  Google Scholar 

  3. Yang CH, Hung WC, Wang SL, Kang WY, Chen WT, Huang YC, Su YC, Chai CY. Immunoexpression and prognostic role of hTERT and cyclin D1 in urothelial carcinoma. APMIS: Acta Pathologica, Microbiologica, et Immunologica Scandinavica. 2008;116(4):309–16.

    Article  PubMed  Google Scholar 

  4. Liu R, Zhou X, Zou L, Chen Q, Hu Y, Hu J, Wu X, Jiang H. Clinicopathological and prognostic significance of preoperative plasma fibrinogen level in patients with upper urinary tract urothelial carcinoma: A retrospective tumor marker prognostic study. Int J Surg (London, England). 2019;65:88–93.

    Article  Google Scholar 

  5. Scarpini S. Rouprц╙t M, Renard-Penna R, Camparo P, Cussenot O, Compц╘rat E: Impact of the expression of Aurora-A, p53, and MIB-1 on the prognosis of urothelial carcinomas of the upper urinary tract. Urol Oncol. 2012;30(2):182–7.

    Article  CAS  PubMed  Google Scholar 

  6. Roggisch J, Ecke T, Koch S. Molecular identification of telomerase reverse transcriptase (TERT) promotor mutations in primary and recurrent tumors of invasive and noninvasive urothelial bladder cancer. Urol Oncol. 2020;38(3):77.e17-77.e25.

    Article  CAS  PubMed  Google Scholar 

  7. Blackburn EH. Structure and function of telomeres. Nature. 1991;350(6319):569–73.

    Article  CAS  PubMed  Google Scholar 

  8. Counter CM, Avilion AA, LeFeuvre CE, Stewart NG, Greider CW, Harley CB, Bacchetti S. Telomere shortening associated with chromosome instability is arrested in immortal cells which express telomerase activity. EMBO J. 1992;11(5):1921–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Blasco MA, Funk W, Villeponteau B, Greider CW. Functional characterization and developmental regulation of mouse telomerase RNA. Scie (New York, NY). 1995;269(5228):1267–70.

    Article  CAS  Google Scholar 

  10. Daniel M, Peek GW, Tollefsbol TO. Regulation of the human catalytic subunit of telomerase (hTERT). Gene. 2012;498(2):135–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–74.

    Article  CAS  PubMed  Google Scholar 

  12. Wu S, Huang P, Li C, Huang Y, Li X, Wang Y, Chen C, Lv Z, Tang A, Sun X, et al. Telomerase reverse transcriptase gene promoter mutations help discern the origin of urogenital tumors: a genomic and molecular study. Eur Urol. 2014;65(2):274–7.

    Article  CAS  PubMed  Google Scholar 

  13. Rachakonda PS, Hosen I, de Verdier PJ, Fallah M, Heidenreich B, Ryk C, Wiklund NP, Steineck G, Schadendorf D, Hemminki K, et al. TERT promoter mutations in bladder cancer affect patient survival and disease recurrence through modification by a common polymorphism. Proc Natl Acad Sci USA. 2013;110(43):17426–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Nakanishi K, Kawai T, Hiroi S, Kumaki F, Torikata C, Aurues T, Ikeda T. Expression of telomerase mRNA component (hTR) in transitional cell carcinoma of the upper urinary tract. Cancer. 1999;86(10):2109–16.

    Article  CAS  PubMed  Google Scholar 

  15. Isharwal S, Audenet F, Drill E, Pietzak EJ, Iyer G, Ostrovnaya I, Cha E, Donahue T, Arcila M, Jayakumaran G, et al. Prognostic value of TERT alterations, mutational and copy number alterations burden in urothelial carcinoma. Eur Urol Focus. 2019;5(2):201–4.

    Article  PubMed  Google Scholar 

  16. de Kouchkovsky I, Zhang L, Philip EJ, Wright F, Kim DM, Natesan D, et al. TERT promoter mutations and other prognostic factors in patients with advanced urothelial carcinoma treated with an immune checkpoint inhibitor. J Immunother Cancer. 2021;9(5):e002127. Erratum in: J Immunother Cancer. 2021;9(9).

  17. Chawla NS, Sayegh N, Tripathi N, Govindarajan A, Zengin ZB, Phillip EJ, Dizman N, Meza L, Muddasani R, Chehrazi-Raffle A, et al. Genomic and clinical prognostic factors in patients with advanced urothelial carcinoma Receiving immune checkpoint inhibitors. Clin Genitourin Cancer. 2023;21(1):69–75.

    Article  PubMed  Google Scholar 

  18. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed). 2021;372:n71.

    PubMed  Google Scholar 

  19. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007;8:16.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ottawa Hospital Research Institute. (2021). Coding manual for cohort studies. [Accessed Jan 03, 2022].

  21. Ottawa Hospital Research Institute. (2021). Newcastle-Ottawa quality assessment scale cohort studies. [Accessed Jan 03, 2022].

  22. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ (Clinical research ed). 2003;327(7414):557–60.

    Article  PubMed  Google Scholar 

  23. Sterne JA, Gavaghan D, Egger M. Publication and related bias in meta-analysis: power of statistical tests and prevalence in the literature. J Clin Epidemiol. 2000;53(11):1119–29.

    Article  CAS  PubMed  Google Scholar 

  24. Lau J, Ioannidis JP, Terrin N, Schmid CH, Olkin I. The case of the misleading funnel plot. BMJ (Clinical research ed). 2006;333(7568):597–600.

    Article  PubMed  Google Scholar 

  25. Audenet F, Attalla K, Sfakianos JP. The evolution of bladder cancer genomics: What have we learned and how can we use it? Urol Oncol. 2018;36(7):313–20.

    Article  CAS  PubMed  Google Scholar 

  26. Mikhailenko DS, Nemtsova MV. Point somatic mutations in bladder cancer: key carcinogenesis events, diagnostic markers and therapeutic targets. Urologiia (Moscow, Russia: 1999). 2016;1:100–5.

    Google Scholar 

  27. Hayashi Y, Fujita K, Netto GJ, Nonomura N. Clinical application of TERT promoter mutations in urothelial carcinoma. Front Oncol. 2021;11:705440.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kurtis B, Zhuge J, Ojaimi C, Ye F, Cai D, Zhang D, Fallon JT, Zhong M. Recurrent TERT promoter mutations in urothelial carcinoma and potential clinical applications. Ann Diagn Pathol. 2016;21:7–11.

    Article  PubMed  Google Scholar 

  29. Cheng L, Davidson DD, Wang M, Lopez-Beltran A, Montironi R, Wang L, Tan PH, MacLennan GT, Williamson SR, Zhang S. Telomerase reverse transcriptase (TERT) promoter mutation analysis of benign, malignant and reactive urothelial lesions reveals a subpopulation of inverted papilloma with immortalizing genetic change. Histopathology. 2016;69(1):107–13.

    Article  PubMed  Google Scholar 

  30. Allory Y, Beukers W, Sagrera A, Flández M, Marqués M, Márquez M, van der Keur KA, Dyrskjot L, Lurkin I, Vermeij M, et al. Telomerase reverse transcriptase promoter mutations in bladder cancer: high frequency across stages, detection in urine, and lack of association with outcome. Eur Urol. 2014;65(2):360–6.

    Article  CAS  PubMed  Google Scholar 

  31. Yuan P, Cao JL, Abuduwufuer A, Wang LM, Yuan XS, Lv W, Hu J. Clinical characteristics and prognostic significance of TERT promoter mutations in cancer: a cohort study and a meta-analysis. PLoS ONE. 2016;11(1):e0146803.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Giedl J, Rogler A, Wild A, Riener MO, Filbeck T, Burger M, Rümmele P, Hurst C, Knowles M, Hartmann A, et al. TERT core promotor mutations in early-onset bladder cancer. J Cancer. 2016;7(8):915–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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This work was supported by the City of Nanchong Strategic Cooperation with the Local Universities Foundation of Technology (20SXQT0305, 18SXHZ0321); the Application and Basic Research Program of the Sichuan Science and Technology Department (2020YJ0185, 2022NSFSC0804); the Primary Health Development Research Center of Sichuan Province Program (SWFZ21-C-98); and the Medical Research Project of the Sichuan Medical Association (S21061).

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WT had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: WT, SH. Administrative support: WT. Provision of study materials: SH, DX. Collection and assembly of data: SH, DX, ZJJ. Data analysis and interpretation: SH, DX, LY. Manuscript writing: All authors. Final approval of manuscript: All authors.

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Correspondence to Tao Wu.

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Shuai, H., Duan, X., Zhou, JJ. et al. Effect of the TERT mutation on the prognosis of patients with urothelial carcinoma: a systematic review and meta-analysis. BMC Urol 23, 177 (2023).

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