ABSTRACT
Background:
Telomeres are protective DNA sequences at chromosome ends that shorten with cell division and regulate cellular lifespan. Dysregulation of telomere maintenance through telomerase activation is implicated in carcinogenesis, including ovarian cancer. This study aimed to systematically review and meta-analyze the association between telomere length and ovarian cancer risk and survival outcomes.
Methodology:
A systematic search of PubMed/MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library was conducted from inception to the final search date. Studies evaluating measured telomere length in relation to ovarian cancer risk or survival were included. Eligible observational studies reporting effect estimates were pooled using random-effects meta-analysis. Odds ratios (ORs) were synthesized for ovarian cancer risk, while hazard ratios (HRs) were pooled for survival outcomes. Heterogeneity was assessed using Cochran’s Q test and the I2 statistic.
Results:
Eleven studies were included in the systematic review, of which seven were eligible for meta-analysis (four risk studies and three survival studies). For ovarian cancer risk, the pooled common-effect estimate showed a modest association (OR = 1.17; 95% confidence interval [CI]: 1.02–1.34), but this was not statistically significant under the random-effects model (OR = 1.23; 95% CI: 0.70–2.16) with moderate heterogeneity (I2 = 66.8%, P = 0.0287). For survival outcomes, the common-effect model showed no significant association between telomere length and survival (HR = 0.98; 95% CI: 0.83–1.16), with substantial heterogeneity (I2 = 85.2%, P = 0.001). The random-effects estimate also showed no significant association (HR = 1.66; 95% CI: 0.21–12.87).
Conclusions:
Current evidence does not demonstrate a consistent association between telomere length and ovarian cancer risk or survival. Substantial heterogeneity across studies highlights the need for large, well-designed prospective studies with standardized telomere measurement methods to clarify the role of telomere dynamics in ovarian carcinogenesis.
KEYWORDS: Cancer risk, meta-analysis, ovarian cancer, survival, systematic review, telomere length
INTRODUCTION
Telomeres are repetitive DNA sequences (TTAGGG)n located at the ends of chromosomes that protect chromosomal integrity. With each cell division, telomeres gradually shorten, eventually signaling cellular senescence and limiting the proliferative capacity of normal somatic cells.[1,2] In contrast, cancer cells are able to maintain telomere length, allowing them to proliferate indefinitely. Shortened telomeres have been associated with several malignancies, including ovarian cancer, which is the most lethal gynecological cancer and is characterized by a high mortality rate and poor prognosis.[3,4]
Telomere length is primarily maintained by telomerase, a ribonucleoprotein enzyme with reverse transcriptase activity that synthesizes and elongates telomeric ends. Telomerase expression is very low or absent in most normal somatic cells, whereas its activation is commonly observed in malignant cells.[4,5] The human TERT gene, located at chromosome 5p13.33, encodes telomerase reverse transcriptase, the catalytic subunit of telomerase. As a key regulator of telomerase activity, TERT plays an important role in maintaining cellular immortality and promoting cancer development. Genetic variants in the TERT gene have been shown to increase susceptibility to several cancers.[6,7,8]
Telomerase activity has been detected in some normal ovarian and fallopian tube tissues, where it is thought to support oogenesis and fertility in a regulated manner. In contrast, telomerase activity is generally absent in premalignant ovarian lesions but is upregulated in most of ovarian cancers, suggesting that deregulation of telomerase is an important step in ovarian carcinogenesis.[9,10] These observations highlight the need for further research to better understand how changes in telomere length over time may influence the development and progression of ovarian cancer. Given the strong biological plausibility but inconsistent epidemiological evidence, a comprehensive synthesis of available data is warranted. The present study aimed to systematically review and meta-analyze the association between telomere length and ovarian cancer risk and overall survival, to clarify the direction and magnitude of these associations and to explore sources of heterogeneity across studies.
METHODOLOGY
Research question
Are telomere length associated with ovarian cancer risk, and is this association mediated by altered telomere length?
This systematic review and meta-analysis aimed to quantify the association between telomere length and ovarian cancer risk, and to explore whether altered telomere length may act as a biological mediator linking these to ovarian cancer susceptibility.
Protocol registration with PROSPERO
This systematic review has been prospectively registered with PROSPERO (International Prospective Register of Systematic Reviews). PROSPERO Registration Number: CRD420250631729.
Definition of exposure
For this review, the primary exposure of interest was measured telomere length, quantified in peripheral blood leukocytes (leukocyte telomere length [LTL]) or tumor tissue. Telomere length was measured using methods such as quantitative polymerase chain reaction (tumor-to-stromal [T/S] ratio), Southern blot (kilobase length), or telomere index (T/S ratio).
Studies were classified into the following exposure categories:
LTL measured prior to diagnosis or at baseline
Peripheral blood telomere length in ovarian cancer patients
Tumor telomere length or telomere index.
Studies evaluating only telomere-related lncRNA signatures, or other molecular proxies without measured telomere length, were included in the systematic review for descriptive synthesis but were not combined with measured telomere length studies in quantitative analyses.
PICO statement
Population (P): Women with ovarian cancer and/or women evaluated for ovarian cancer risk (cases and controls)
Intervention/Exposure (I/E): Measured telomere length (leukocyte or tumor tissue)
Comparison (C): Women without ovarian cancer (healthy or benign-disease controls)
-
Outcome (O):
Association between telomere length and ovarian cancer risk (e.g., pooled odds ratio [OR]/relative risks [RR])
Differences in telomere length (or direction of genetically predicted telomere length) linked to ovarian cancer susceptibility
Search strategy
A comprehensive literature search was performed to identify studies assessing the association between telomere length and ovarian cancer risk and survival. The search was conducted across PubMed/MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library from inception to the final search date. Both controlled vocabulary (e.g., MeSH/Emtree) and free-text terms were used, combining three main concept domains: “ovarian cancer,” “ovarian carcinoma,” “epithelial ovarian cancer,” “ovarian neoplasm,” “telomere,” “telomere length,” and “leukocyte telomere length.” Boolean operators (AND/OR) were applied to combine synonyms within each domain and to link the domains together. Filters were applied to limit results to human studies published in English, and eligible study designs included genetic association studies and observational designs such as case–control and cohort studies. Reference lists of included studies and relevant reviews were additionally screened manually to capture any further eligible articles, and the search and reporting were documented in accordance with PRISMA-S guidelines.
Selection of studies
Following the database search, all retrieved records were compiled and imported into EndNote, and duplicate citations were identified and removed. Two reviewers then independently screened the titles and abstracts of all unique records against the predefined inclusion and exclusion criteria for studies evaluating telomere length in relation to ovarian cancer. Articles considered potentially eligible were obtained as full texts and assessed independently by the same two reviewers for final inclusion. Reasons for exclusion at the full-text stage (e.g., irrelevant outcomes, nonhuman studies, insufficient data, duplicate cohorts, review/editorial, or noneligible study design) were documented and reported. Any disagreements between reviewers at any stage were resolved through discussion and consensus; if unresolved, a third reviewer adjudicated. The overall screening and selection process was summarized using a PRISMA flow diagram.
Data extraction
Two reviewers independently extracted data from all included studies using a standardized form. Extracted items included author/year, country/ethnicity, study design, sample size (cases/controls), ovarian cancer type, telomere length, genotype/allele frequencies, and effect estimates (OR/RR/hazard ratio [HR] with 95% confidence interval [CI]). Telomere length measurement details were extracted when available. Any disagreements were resolved by discussion, with a third reviewer adjudicating if needed.
Eligibility criteria
Studies were eligible for quantitative synthesis if they reported measured telomere length (leukocyte or tumor) and provided effect estimates (OR/HR) for ovarian cancer risk or survival outcomes. Studies without measured telomere length but involving telomere length and ovarian cancer were included in the systematic review but were not pooled in the primary meta-analysis.
Statistical Analysis-Separate meta-analyses were conducted for:
Ovarian cancer risk and measured LTL
Overall or cancer-specific survival and measured telomere length
For risk analyses, ORs comparing extreme telomere length categories (e.g., shortest vs. longest or Q4 vs. Q1) were pooled using random-effects models. For survival analyses, HRs comparing predefined telomere length categories were pooled separately. Heterogeneity was assessed using the I2 statistic and Cochran’s Q test.
RESULTS
A total of eleven studies evaluating the association between telomere biology and ovarian cancer were included in the systematic review [Figure 1]. Of these, eight studies were eligible for quantitative synthesis (meta-analysis) as they reported comparable effect estimates (ORs or HRs) with corresponding 95% CIs for defined telomere length comparisons. These included five studies assessing ovarian cancer risk using ORs[11,12,13,14,15] and three studies evaluating survival outcomes using HRs.[16,17,18] Studies not included in the meta-analysis were excluded due to heterogeneity in exposure definitions, molecular endpoints, or lack of extractable effect estimates. Separate meta-analyses were performed for risk and survival outcomes to ensure methodological consistency.
Figure 1.
PRISMA flow diagram showing the selection process of studies evaluating the association between telomere length and ovarian cancer risk and survival
Risk of bias
Overall, the included studies demonstrate good methodological quality, with the majority achieving high NOS scores (8-9), indicating low risk of bias. Studies with slightly lower scores (NOS 7) were mainly limited by selection constraints, histology-restricted or trial-based populations, and reduced comparability across groups, rather than flaws in outcome assessment [Table 1]. Collectively, the evidence base is methodologically robust and suitable for synthesis, with only minor concerns related to generalizability and confounding control in a few studies.
Table 1.
Risk of bias analysis of included telomere length studies using the Newcastle–Ottawa Scale
| Study (year) | Study design | Selection (Max - 4) | Comparability (Max – 2) | Outcome (Max – 3) | Total score (Max - 9) | Interpretation |
|---|---|---|---|---|---|---|
| Shi et al. (2025)[11] | Two-sample Mendelian randomization | 3 | 2 | 3 | 8 | Low risk |
| Yang et al. (2017)[12] | Prospective nested case–control | 4 | 2 | 3 | 9 | Low risk |
| Kotsopoulos et al. (2014)[17] | Population-based cohort (prognostic survival) | 4 | 2 | 2 | 8 | Low risk |
| Terry et al. (2012)[14] | Population-based case–control + genetic association | 4 | 2 | 2 | 8 | Low risk |
| Mirabello et al. (2010)[15] | Population-based pilot case–control | 3 | 1 | 2 | 6 | Moderate risk |
| Zhang et al. (2015)[13] | Mendelian randomization (GWAS consortia) | 3 | 2 | 3 | 8 | Low risk |
| Falandry et al. (2015)[16] | Prospective trial-based prognostic biomarker (ancillary) | 3 | 1 | 3 | 7 | Low–moderate |
| Kuhn et al. (2011)[18] | Tissue-based cohort (qFISH; histotypes + survival) | 3 | 2 | 2 | 7 | Low–moderate |
GWAS: Genome-wide association studies, qFISH: Quantitative fluorescence in situ hybridization
Studies included in the systematic review
The included studies evaluated telomere biology in ovarian cancer across diverse clinical contexts, including risk, prognosis, treatment response, and survival. Prospective and case–control studies assessing LTL showed inconsistent associations with risk: Yang et al.[12] reported reduced ovarian cancer risk with longer pre-diagnostic TL (OR 0.67, 95% CI 0.46-0.97), whereas Mirabello et al.[15] found increased risk with shorter TL (OR 3.39); large population-based studies such as Terry et al.[14] and Kotsopoulos et al.[17] observed no significant associations with risk or survival. Prognostic studies suggested a more subtype-and tissue-specific pattern: Kuhn et al.[18] demonstrated markedly worse survival in clear cell carcinoma with higher tumor telomere index (HR 4.93, 95% CI 1.64–14.86), and Falandry et al.[16] reported poorer outcomes among elderly patients with shorter peripheral blood TL. Tomasova et al.[19] further highlighted tissue-specific effects, linking shorter blood TL to better platinum sensitivity but longer tumor TL to poorer survival [Table 2].
Table 2.
Studies included in the systematic review assessing association between telomere length and ovarian cancer
| Study ID (Author, Year) | Country/Region | Study design | Sample size (Cases) | Telomere marker | Stage/Setting (risk/diagnosis/treatment/survival/histotypes) | Comparison Group (s) | Direction of association | Key findings |
|---|---|---|---|---|---|---|---|---|
| Tomasova et al., 2024[19] | Czech Republic | Observational cohort | 212 OvC (184 PBL; 56 tumor TL) | Relative TL (T/S) in PBL and tumor tissue | Newly diagnosed OvC, FIGO I–IV; endpoints: Platinum response (PFI) and 10-year OS | PBL TL: Platinum-sensitive (PFI ≥12 months) versus resistant (PFI ≤6–12 months); Tumor TL: > median versus≤median | Shorter PBL TL → better platinum sensitivity; longer tumor TL→poorer OS; no association with histotype, FIGO, grade, residual tumor, age | Therapy response (PBL TL) P=0.037; OS (tumor TL) log-rank P=0.006; other comparisons P>0.05 |
| Xu et al., 2024[23] | China+TCGA | Bioinformatic + lab validation | 370 TCGA cases; 88 controls | Telomere-related lncRNAs | Serous OC prognosis | High versus low TRL-risk | High TRL-risk=worse OS | Independent prognostic factors (P<0.05), and FAM27E3 (better OS) and PTPRD-AS1 (worse OS) were each linked to survival (P=0.036) |
| Yang et al., 2017[12] | USA and Sweden (NHS, NHSII, NSHDS) | Pooled nested case–control within prospective cohorts | 442 incident epithelial OvCa cases; 727 controls | Prediagnosis leukocyte TL (relative T/S, z-score) | Risk of incident invasive epithelial OvCa overall; subtypes: Serous/poorly diff versus non-serous; rapidly fatal (≤3 years) versus less aggressive | Main: TL quartiles (Q4 vs. Q1); per 1 SD TL; subtype-specific Q4 versus Q1 | Longer prediagnosis TL associated with lower overall OvCa risk; subtype patterns explored | Overall risk Q4 versus Q1 OR 0.67 (95% CI 0.46–0.97), P<0.05; per 1 SD OR 0.89 (0.78–1.01, borderline); subtype P values not fully reported in excerpt |
| Sun et al., 2017[21] | USA | Case–control genetic study | 417 cases; 417 controls | TEP1, TERT, TNKS, PINX1, TERF2IP SNPs | Risk; OS; platinum response | Genotype versus reference; cumulative alleles | Many SNPs↑risk, ↓ OS, ↓ platinum response | TEP1 rs2228026 was significant for risk (P<0.001; Q=0.028), while TNKS rs10093972 and therapy-response SNPs were only suggestive (no Q <0.05) |
| Falandry et al., 2015[16] | GINECO Trial 3 (multicenter) | Ancillary analysis of prospective trial | 111 advanced OvCa (109 with TL) | Peripheral blood TL in kb | Elderly FIGO III–IV OvCa; outcomes: Treatment completion, toxicity, geriatric vulnerability, OS (adjusted for FIGO, age, GVS) | TL quartiles; Short TL (<5.77 kb) versus Long TL; TL<6.0 versus ≥6.0 kb for OS | Short TL unfavorable: Lower completion, more serious AEs; trend to higher mortality with TL<6 kb | OS TL <6 versus ≥6 kb: HR 1.57, P=0.06; treatment completion short versus long TL P=0.020; serious AEs P=0.019 |
| Kotsopoulos et al., 2014[17] | Ontario, Canada | Population-based cohort of invasive epithelial OvCa; survival | 1,042 epithelial OvCa cases | Leukocyte TL (T/S, z-score quartiles) | Ovarian-cancer–specific survival; overall and by histology (serous vs. non-serous) | TL quartiles (Q2–Q4 vs. Q1 short TL); combined Q2–4 versus Q1; stratified by histology | No significant association between leukocyte TL and mortality overall or by histotype | Overall Q2–4 versus Q1 HR 0.88 (0.77–1.10), P=0.25, trend P=0.83; serous and non-serous also NS (P>0.28) |
| Bojesen et al., 2013[20] | International (OCAC, mainly Europe) | Large multi-center case–control (genetic) | 986 serous LMP OvCa; 23,491 controls | TERT polymorphism (Peak 2), associated with longer TL | Risk of serous LMP ovarian cancer | Per-allele log-additive model (minor vs. major allele) | Minor allele associated with increased serous LMP risk and longer TL | OR 1.51 (95% CI 1.36–1.67); P=1.34×10−15 |
| Terry et al., 2012[14] | USA (NECC, NHS) | Large population-based case–control + nested case–control | NECC RTL: 911 cases, 961 controls; SNP set: 1173 cases, 1200 controls | Leukocyte RTL (T/S) + telomere-gene SNPs (TERT, TRF1/2, POT1, TNKS) | Ovarian cancer risk overall and by histotype; modifiers: BMI, smoking, OC use, parity, ovulatory cycles | RTL tertiles (T1 shortest vs. T2, T3 longest); SNP log-additive per allele; histology-specific | RTL: No overall association with OC risk. Several TERT SNPs show modest ↑ risk; POT1 variants affect RTL but not risk | RTL overall NS (e.g.,, T1 vs. T3 OR ≈1.0, P>0.05); TERT gene-level PCA P=0.00008; individual SNP P values nominal but lose significance after multiple testing |
| Harris et al., 2012[22] | USA (MA and NH) | Population-based ovarian cancer cohort: genetic association and survival | 1480 invasive epithelial OvCa cases | SNPs in telomere genes: TERT, POT1, TNKS, TRF1, TRF2 | Outcomes: Survival, relapse, chemo-refractory disease; analyses by histotype and treatment | Per-allele genetic model; SNP dosage versus survival/relapse; stratified by histology, chemo, BMI, smoking | No SNPs met P<0.001; some TERT variants suggest ↑ mortality/relapse (not robust after adjustment) | Most SNPs P>0.001 (NS); some nominal P<0.05 (e.g., rs2853676 for relapse) but >0.001 |
| Kuhn et al., 2011[18] | USA, Taiwan | Observational Study | 219 ovarian carcinoma tumors | Tumor Telomere Index (TI=tumor TL÷stromal TL) | 4 histotypes: HGSC, CCC, EMC, LGSC; survival; HGSC primary versus recurrent | TI ≤1 versus TI >1; histologic subtype; primary versus recurrent HGSC | TI >1 in clear cell carcinoma associated with worse survival | Clear cell: HR 4.93 (95% CI 1.64–14.86), P=0.005; TI across histotypes P=0.007; TI >1 CCC versus others P=0.01; HGSC primary versus recurrent TI change P=0.09 |
| Mirabello et al., 2010[15] | Poland | Population-based case–control | 99 serous OvCa cases, 100 matched controls | Leukocyte TL (T/S ratio) | Risk of serous adenocarcinoma; tumor grade; FIGO I–III | TL tertiles (short/medium/long); short versus long; stratified by grade, HRT, other factors | Shorter TL associated with increased serous ovarian cancer risk | Overall TL difference P=0.002; individual ORs significant (values not detailed here) |
PFI: Platinum-free interval, FIGO: International Federation of Gynecology and Obstetrics, PBL: peripheral blood leukocytes, OS: Overall survival, TCGA: The Cancer Genome Atlas, AEs: Adverse Events, LMP: Low malignant potential, SNPs: Single nucleotide polymorphisms, BMI: Body mass index, RTL: Relative telomere length, HGSC: High-grade serous carcinoma, LGSC: Low-grade serous carcinoma, EMC: Endometrioid carcinoma, CCC: Clear cell carcinoma, HRT: Hormone replacement therapy, CI: Confidence interval, OR: Odds ratio, HR: Hazard ratio, OvCa: Ovarian carcinoma, TL: Telomere length, TI: Telomere index
Meta-analysis-interpretation of forest plots
In the survival analysis, three studies evaluating telomere length and survival outcomes showed heterogeneous results [Table 3]. One study reported a markedly increased hazard of death with higher tumor telomere index, while others demonstrated either a modest or no association. The pooled estimate from the common-effect model showed no significant association between telomere length and survival (HR = 0.98; 95% CI: 0.83–1.16). However, substantial heterogeneity was observed (I2 = 85.2%, P = 0.001). Under the random-effects model, the pooled HR was 1.66 (95% CI: 0.21–12.87), indicating no statistically significant association but with wide CIs reflecting considerable between-study variability [Figure 2].
Table 3.
Studies included in the meta-analysis for ovarian cancer risk and overall survival
| Study | Biospecimen | Measurement method | Operational contrast used for meta-analysis | Outcome type | Comparison used for meta-analysis | Effect type | Value of effect type | 95% CI |
|---|---|---|---|---|---|---|---|---|
| Shi et al., 2025[11] | Leukocytes | qPCR (T/S) | Short versus long TL | Risk of OvCa | Short versus long TL | OR | 1.27 | 1.01–1.60 |
| Yang et al., 2017[12] | Leukocytes (pre-dx) | qPCR (T/S; z-score) | Q4 versus Q1 | Risk of incident OvCa | Q4 (longest) versus Q1 (shortest) | OR | 0.68 | 0.47–0.97 |
| Zhang et al., 2015[13] | Leukocytes | qPCR (T/S) | Short versus long TL | Risk of OvCa | Short versus long TL | OR | 1.13 | 0.87–1.47 |
| Falandry et al., 2015[16] | Peripheral blood | Southern blot (kb) | TL <6.0 kb versus ≥6.0 kb | Overall survival | TL <6.0 kb versus ≥6.0 kb | HR | 1.57 | 0.98–2.51 |
| Kotsopoulos et al., 2014[17] | Leukocytes | qPCR (T/S; z-score) | Q2–Q4 versus Q1 | Cancer-specific survival | Q2–Q4 versus Q1 (shortest TL) | HR | 0.88 | 0.77–1.10 |
| Terry et al., 2012[14] | Leukocytes | qPCR (T/S) | T1 (shortest) versus T3 (longest) | Risk of OvCa | T1 (shortest) versus T3 (longest) | OR | 1.01 | 0.80–1.28 |
| Kuhn et al., 2011[18] | Tumor versus stroma | TI ratio | TI >1 versus ≤1 (clear cell only) | Survival (clear cell carcinoma) | TI >1 versus TI ≤1 (clear cell only) | HR | 4.93 | 1.64–14.86 |
| Mirabello et al., 2010[15] | Leukocytes | qPCR (T/S) | Short versus long tertile | Risk of OvCa | Short versus long TL | OR | 3.39 | 1.54–7.46 |
CI: Confidence interval, OR: Odds ratio, qPCR: Quantitative polymerase chain reaction, HR: Hazard ratio, OvCa: Ovarian carcinoma, TL: Telomere length, TI: Telomere index
Figure 2.
Forest plot showing the association between telomere length and ovarian cancer overall survival
For ovarian cancer risk, four studies reported inconsistent associations between telomere length and disease risk [Table 3]. While some studies suggested a protective effect of longer telomeres or increased risk with shorter telomeres, others showed null associations. Four studies assessed the association between measured telomere length and ovarian cancer risk, yielding inconsistent results. The pooled common-effect estimate indicated a statistically significant association (OR = 1.17; 95% CI: 1.02–1.34). However, moderate to substantial heterogeneity was present (I2 = 66.8%, P = 0.0287). Using the more conservative random-effects (Hartung–Knapp) model, the pooled OR was 1.23 (95% CI: 0.70–2.16), which did not demonstrate a statistically significant association [Figure 3].
Figure 3.
Forest plot showing the association between telomere length and ovarian cancer risk
Interpretation of heterogeneity and sensitivity analysis
Moderate to substantial heterogeneity was observed in the ovarian cancer risk meta-analysis (I2 = 66.8%), suggesting considerable between-study variability. This heterogeneity likely reflects differences in study design, telomere measurement methods, timing of measurement (pre-diagnosis vs post-diagnosis), tissue source, and ovarian cancer subtypes. The wide CIs observed under the random-effects (Hartung–Knapp) model highlight the imprecision of pooled estimates and underscore the need for cautious interpretation.
DISCUSSION
Our findings support the biological relevance of telomere length in ovarian cancer while showing that its measurable association with risk and prognosis is inconsistent across studies. Telomeres maintain chromosomal stability, and telomere attrition can promote genomic instability, whereas preserved/elongated telomeres may facilitate tumor cell survival and progression.[1,20,21,22,23,24]
Several studies have demonstrated that tumor cells and their precursor lesions exhibit shorter telomeres compared with surrounding nonmalignant cells.[25,26,27] In a small case–control study, telomere length in plasma-derived free DNA was significantly shorter in ovarian cancer patients than in healthy controls and showed a positive correlation with telomere length in ovarian tumor tissue.[28] Furthermore, increased telomerase activity accompanied by shortened telomeres has been observed in ovarian cancer tissue, with the highest telomerase activity detected in poorly differentiated tumors.[29]
In our meta-analysis, the pooled association was not statistically significant for either survival (common-effect HR = 0.98, 95% CI 0.83–1.16; I2 = 85.2%) or ovarian cancer risk (common-effect OR = 1.09, 95% CI 0.96–1.24; I2 = 75.9%), indicating substantial between-study variability. At the individual-study level, strong subtype-and tissue-specific signals were evident, such as markedly worse survival in clear cell carcinoma with a higher tumor telomere index:[18] (HR = 4.93, 95% CI 1.64–14.86) and a reduced risk of incident ovarian cancer with longer pre-diagnostic leukocyte TL:[12] (OR = 0.68, 95% CI 0.47–0.97), whereas other large studies were null:[14,17] (HR = 0.88, 95% CI 0.77–1.10; OR = 1.01, 95% CI 0.80–1.28).
These patterns are consistent with Harris et al.[22] who genotyped telomere maintenance genes in 1,480 invasive epithelial ovarian cancer cases which evaluated telomere-maintenance gene rather than telomere length, and did not provide directly comparable HR/OR estimates for telomere length–based exposure categories. They found no robust survival associations after clinical adjustment; although one rare TERT variant showed a high covariate-adjusted mortality estimate (HR = 3.49, 95% CI 1.11–11.00), this attenuated after adding clinical characteristics (HR = 2.06, 95% CI 0.65–6.53), and no gene-level associations were observed. Collectively, these comparisons suggest that telomere biology may exert context-dependent effects, with leukocyte TL potentially reflecting susceptibility in some settings and tumor-specific telomere maintenance more closely linked to prognosis or treatment resistance, warranting larger standardized studies stratified by histotype, tissue source, and study design.
Our findings also align with the systematic review and meta-analysis by Wentzensen et al.,[30] which reported a strong association between short telomere length and overall cancer risk in retrospective studies (pooled OR = 2.90, 95% CI 1.73–4.80, P < 0.0001), but no significant association in prospective cohorts (pooled OR = 1.16, 95% CI 0.87–1.54, P = 0.32). Similarly, when all study designs were combined, Wentzensen et al.[30] observed substantial heterogeneity with a pooled OR of 1.96 (95% CI 1.37–2.81) and high inconsistency (I2 > 90%). These findings mirror the divergent results observed among ovarian cancer studies included in our analysis, where prospective studies suggested either null or modest associations, while some retrospective studies reported stronger effects.
Epidemiological studies evaluating LTL and ovarian cancer risk have yielded inconsistent results. In a small retrospective pilot study, women in the shortest tertile of LTL had an approximately three-fold increased risk of serous ovarian carcinoma compared with those in the longest tertile (OR 3.4, 95% CI 1.5–7.5), with the strongest association observed among poorly differentiated tumors.[31] Subsequent studies reported weaker but statistically significant associations between shorter LTL and increased ovarian cancer risk.[32] However, the largest population-based case–control study conducted within the New England Case–Control Study did not observe a significant overall association between LTL and ovarian cancer risk or by histologic subtype, although an inverse association in the expected direction was noted after excluding recently treated cases.[14] As blood samples in these retrospective studies were collected after cancer diagnosis, telomere shortening may reflect disease-related physiological stress, cancer treatment, or psychological factors rather than prediagnostic susceptibility.
Consistent with this variability, our pooled analysis showed no significant overall association between telomere length and ovarian cancer risk (OR = 1.09, 95% CI 0.96–1.24; I2 = 75.9%). However, individual studies demonstrated context-specific effects, including a reduced risk with longer prediagnostic LTL (OR = 0.68, 95% CI 0.47–0.97) and markedly poorer survival associated with tumor-based telomere alterations in clear cell carcinoma (HR = 4.93, 95% CI 1.64–14.86), while other large studies were null. These findings suggest that previously reported positive associations likely reflect study design, timing of telomere assessment, or histological subtype rather than a consistent etiologic role of LTL, supporting the null pooled estimates observed in our meta-analysis.
Experimental and genetic studies further suggest that disruption of shelterin components, such as POT1, can influence tumorigenicity and treatment response in ovarian cancer cells,[33] while GWAS have identified multiple variants in telomere-related genes (POT1, hTERT, hTERC-CLPTM1 L) associated with OvC risk.[34] In contrast to this strong biological and molecular rationale, our meta-analysis of epidemiological studies found no statistically significant pooled association between telomere length and ovarian cancer risk (OR = 1.09, 95% CI 0.96–1.24) or survival (HR = 0.98, 95% CI 0.83–1.16), with substantial heterogeneity across studies. However, context-specific associations were evident at the individual-study level, including markedly worse survival associated with tumor-based telomere alterations in clear cell carcinoma and a reduced risk of incident ovarian cancer with longer pre-diagnostic LTL.
Telomere length can serve as a prognostic biomarker because it reflects genomic stability and cellular replicative capacity, both of which influence tumor aggressiveness and patient outcomes. In ovarian cancer, tumor-specific telomere maintenance (e.g., longer or stabilized telomeres via telomerase activation) is associated with enhanced tumor survival and poorer prognosis, while short telomeres can drive genomic instability and disease progression. Additionally, LTL may reflect host biological aging and treatment tolerance, further affecting survival.[16]
The survival meta-analysis should be interpreted with considerable caution. The three included studies differed substantially in biological specimen (tumor telomere index vs. LTL), patient population (clear cell carcinoma subtype vs. unselected epithelial ovarian cancer vs. elderly advanced-stage cohort), and outcome definitions. In particular, the study by Kuhn et al. evaluated tumor telomere index exclusively in clear cell carcinoma and reported a markedly elevated HR 4.93, whereas the other studies assessed LTL in broader populations and demonstrated modest or null associations. Pooling these clinically and methodologically heterogeneous studies likely contributed to the high statistical heterogeneity (I2 = 85.2%) and the imprecision of the random-effects estimate. Therefore, the pooled survival result should be regarded as exploratory rather than definitive.
This meta-analysis has some important limitations. First, there was high variation between studies, mainly because the studies differed in their design, the type of sample used to measure telomere length (blood or tumor tissue), the methods of measurement, and how outcomes were defined. Second, only a small number of studies could be included in the meta-analysis, especially for survival outcomes, which limited the strength of the pooled results. Third, in several studies, telomere length was measured after cancer diagnosis, so the shortening of telomeres may have been influenced by the disease itself or by cancer treatment, rather than reflecting true risk. Fourth, differences in ovarian cancer subtypes and survival definitions may have affected comparability across studies. Finally, because of the limited number of studies, publication bias could not be properly assessed. These limitations suggest that the results should be interpreted cautiously and highlight the need for larger, well-designed prospective studies.
CONCLUSION
This systematic review and meta-analysis evaluated the association between telomere length and ovarian cancer risk, survival, and prognosis across diverse study designs and biological contexts. The pooled epidemiological data did not demonstrate a statistically significant overall association between telomere length and either ovarian cancer risk or survival. Substantial heterogeneity across studies was observed, reflecting differences in tissue source, timing of telomere assessment, outcome definitions, and histological subtypes. Notably, context-specific associations were evident at the individual-study level, with tumor-based telomere alterations linked to poorer survival in certain subtypes and longer prediagnostic LTL associated with reduced ovarian cancer risk in prospective settings. These findings suggest that telomere length is not a uniform biomarker but may have prognostic and etiologic relevance in specific clinical and biological contexts. Future large-scale, well-designed prospective studies with standardized telomere measurement and subtype-specific analyses are warranted to clarify the role of telomere biology in ovarian cancer risk stratification and prognostication.
Future directions and recommendations
Future research should prioritize large, well-designed prospective studies with prediagnostic assessment of telomere length to minimize reverse causation and better clarify its etiologic role in ovarian cancer. Standardization of telomere measurement techniques and exposure definitions is essential to improve comparability across studies and reduce heterogeneity. Given the context-dependent associations observed, analyses should be stratified by histological subtype, disease stage, and tissue source (tumor vs peripheral blood), with parallel evaluation of telomerase activity and shelterin complex alterations. Integrating telomere length with molecular, genetic, and clinical parameters, including treatment response and geriatric vulnerability indices, may enhance its prognostic utility. Finally, functional and translational studies are needed to elucidate the mechanistic links between telomere maintenance pathways and ovarian cancer progression, which could inform the development of telomere-targeted biomarkers and therapeutic strategies.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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