Association between telomere length and survival in cancer patients: a meta-analysis and review of literature

Abstract

The relationship between telomere length and cancer survival has been widely studied. To gain a deeper insight, we reviewed the published studies. A total of 29 studies evaluated telomere length in the peripheral blood; 22 studies evaluated telomere length in the tumor tissue. First, in the peripheral blood studies, for solid tumor patients with shortened telomere length, the combined hazard ratios (HRs) for mortality and tumor progression were 1.21 (95%CI, 1.10–1.32) and 1.71 (95%CI, 1.37–2.13), respectively. Meanwhile, in hematology malignancy, the combined HRs for mortality and tumor progression were 2.83 (95%CI, 2.14–3.74) and 2.65 (95%CI, 2.18–3.22), respectively. Second, in the studies that use tumor tissue, for patients with shortened telomeres, the combined HRs for mortality and tumor progression were 1.26 (95%CI, 0.95–1.66) and 1.65 (95%CI, 1.26–2.15), respectively. In the studies that calculate the telomere length ratios of tumor tissue to adjacent normal mucosa, for patients with lower telomere length ratios, the combined HRs were 0.66 (95%CI, 0.53–0.83) and 0.74 (95%CI, 0.41–1.32) for mortality and tumor progression, respectively. In conclusion, shortened telomere in peripheral blood and tumor tissue might indicate poor survival for cancer patients. However, by calculating the telomere length ratios of tumor tissue to adjacent normal mucosa, the lower ratio might indicate better survival.

Keywords

telomere / survival / cancer / meta-analysis

Introduction

Telomeres are “tandem repeats of TTAGGG nucleotides.” It protects genome stability by capping chromosomes [ 1]. Because the lagging strand replicates incompletely, telomeres will shorten when cell divides. When telomeres significantly shortened with impaired genome stability, Rb and p53 signaling pathways are activated to initiate cell senescence or apoptosis [ 2]. However, in tumor cells, on the contrary, telomerase is activated to keep telomere length and maintain cell divisions [ 3].

Certain studies suggest that telomere maintenance indicates a survival advantage for tumor growth, and suggests poor prognosis for those cancer patients [ 4]. However, although telomere maintenance is common in advanced malignancies, evidence suggests that short telomeres with concurrent chromosomal instability would result in malignant transformation in normal cells [ 5, 6]. Thus, telomere alterations in tumor are likely to contribute to the aggressive features of tumor, which might be a predictor for poor clinical outcome. Previously, Ma et al. summarized that shortened telomere increased the risk of cancer development [ 7]. However, with respect to cancer survival, the results are conflicting.

Materials and methods

Literature review and study selection

We performed literature review using the EMBASE, PubMed, and Cochrane Library database until August 22, 2015, by two authors (QK and PQ) independently. We used the search terms ((telomere or telomeric or TRF) and (prognosis or prognostic or survival or recurrence or progression) and “cancer”). Only English-language literature and human studies were included. Bibliographies of the identified articles were reviewed to search for any missing papers. Non-related studies were firstly excluded by checking titles and abstracts. Then full-text papers were retrieved and examined thoroughly according to the inclusion and exclusion criteria. Consensus with a third reviewer (WZX) was performed to resolve discrepancies.

Study inclusion/exclusion criteria

The inclusion criteria was as follows: (1) original studies that assessed telomere length in patient samples and provided the cutoff value of shortened telomere length; (2) studies that utilized overall survival or progression-free survival as clinical outcome; (3) studies that reported a hazard ratio (HR) and 95% confidence interval (95%CI) related telomere length to death or tumor progression, either using cox regression analysis directly or providing relevant data to estimate the HR and 95%CI; (4) sample size was larger than 20 individuals. Studies that only investigate telomere length, but without survival analysis, were excluded. In order to exclude duplicate data, we only selected the largest patient cohort, if there is significant overlap of the patient series in several studies.

Data extraction and quality assessment

Pre-specified data elements included: first author, publication year, origin country, cancer type, study center, study type, treatment, sample size, median age, DNA source, methods for telomere length measurement, and survival data including overall survival and progression-free survival. The quality of each study was assessed according to the REMARK guidelines [ 8– 10]. By using a checklist in which one point was allocated to each reported item (introduction, materials and methods, results, and discussion, altogether with multiple sub-items), high-quality studies were represented by the high awarding points.

Data synthesis and statistical analysis

Included studies were divided into two groups for analysis: those with telomere length data obtained from peripheral blood samples and those with telomere length data obtained from tissue samples. The primary outcome for analysis was the HR and the corresponding 95%CI that related shortened telomere length to death or tumor progression. An HR of greater than 1 indicated an adverse outcome. If such data were not reported directly from the original study, we calculated the HR and 95%CI according to the methods suggested by Tierney et al. [ 11]. If the same study provided several estimates, the most adjusted one was included for analysis (i.e., multivariate cox regression was better than univariate regression, and Kaplan-Meier analysis was the last option).

For the meta-analysis, the combined HRs were firstly summarized, using a random effects model based on the forest plots. Subgroup and meta-regression analyses were conducted to explore the heterogeneity, and to identify potential factors that alter the pooled HR value. Only one covariate was included in per meta-regression model. Publication bias was assessed by the Egger’s bias indicator test. A P value that was less than 0.05 were considered significant. All analyses were conducted using Stata 12 (StataCorp, College Station, Texas, USA).

Results

Eligible studies

The abstracts and titles of 3360 primary studies were identified for initial review using recognized search terms ((telomere or telomeric or TRF) and (prognosis or prognostic or survival or recurrence or progression) and “cancer”), of which 68 examined the association between telomere length and cancer prognosis. Upon further review by full text studies, 16 were eliminated based on insufficient survival data [ 12– 27]. One study was also excluded because of the duplicated patients [ 28]. Thus, after the application of the inclusion and exclusion criteria, 51 studies were included in the analysis, with 29 studies focused on peripheral blood telomere length and 22 studies focused on tissue telomere length (Fig. 1). Of the studies focusing on peripheral blood telomere length, 13 were from solid tumor patients [ 29– 41], and the other 16 were from hematology malignancy patients [ 42– 58]. With respect to the studies focusing on tissue telomere length, 10 were measured in tumor tissue [ 59– 68], and the other 12 were ratios measured by tumor/normal tissue [ 4, 69– 79].

The main features of the 51 studies included in the meta-analysis were summarized in Table 1. The total study population was 14 464, with a mean of 283 subjects per study (range, 32 to 3142). The mean age of the subjects was 54.4 years, with a range of 2 to 72 years old. The publication year ranged from 1997 to 2015. The trials were conducted in Asia (14), Europe (28), America (8), and Oceania (1). The tumor types in our analysis included leukemia (14), breast cancer (6), colorectal cancer (5), esophagus cancer (3), ovarian cancer (2), lung cancer (3), gastric cancer (1), liver cancer (1), renal cancer (1), prostate cancer (1), bladder cancer (2), head and neck cancer (1), oral cancer (1), neuroblastoma (2), glioblastoma (1), glioma (1), myelodysplastic syndromes (1), myeloproliferative neoplasms (1), Ewing sarcoma (1), lymphoma (1), and two cohort studies including multiple cancer types. In these analyses, telomere lengths were evaluated by different types of methods, such as realtime PCR (24), Southern blot (9), TeloTAGGG telomere length (Telo) assay (9), fluorescent in situ hybridization (flow-FISH) (6), slot blot (2), and single telomere length analysis (STELA) assay (1). Given that we checked all the included studies, few studies adjusted for age and gender in these studies, except for those that calculated the telomere length ratios of tumor tissue to adjacent normal mucosa.

Quality assessment using the REMARK guidelines was performed on all 51 studies included for meta-analysis. The mean scores were 14.4±1.7 and 14.8±1.5 for the peripheral blood study and tissue study, respectively. Of the 51 included studies, 40 directly reported HRs. However, back-calculation from available data using statistical methods described above was necessary in the remaining studies. During this process, data were segregated according to either overall survival or progression-free survival.

Assessment of telomere length methodologies

Methods used to determine telomere length included PCR amplification of telomere repeats relative to a single copy gene (T/S), Southern blot, slot blot, flow-FISH, Telo assay, and STELA.

All peripheral blood telomere studies in solid tumors were evaluated by PCR(T/S) for telomere length in peripheral blood. The amplification threshold used to dichotomize telomere length varied between these studies. The threshold was set as median in six studies [ 30, 33, 34, 38– 40], as quartile in four studies [ 29, 32, 36, 37], as tertile in one study [ 35], and was determined by ROC curve in two studies [ 31, 41]. However, of all peripheral blood telomere studies in hematology malignancy study Southern blot was the most popular way for evaluating telomere length, which was utilized in six studies [ 46, 47, 50, 54– 56]. The remaining evaluation methods include PCR(T/S), flow-FISH, Telo assay, and STELA assay. The median was the most used threshold in these studies; it was used in seven studies [ 42, 44, 48, 52– 55]. Other thresholds used included ROC curve analysis and CART technique.

With respect to the telomere studies in tumor tissue, the methods for telomere length measurement also varied among these studies, with two measured by PCR(T/S) [ 59, 60], two by Telo assay [ 62, 64], two by slot blot [ 61, 63], and one by Southern blot [ 65]. The median was the most used threshold to dichotomize telomere length in these studies [ 59, 60, 64, 65]. Other thresholds used included ROC curve analysis and the reported values.

Telomere length in blood or normal tissue might be shorter when people age; telemore length is sign of senescence. Thus, in some tissue studies, to adjust the age-dependent variation of telomere length in the tumor tissue studies, some authors might calculate the telomere length ratios of tumor tissue to adjacent normal mucosa. In these studies that calculate the telomere length ratio, Telo assay was the most popular evaluation of telomere length [ 4, 51, 73, 74, 76, 77, 79]. Given that the telomere length was recorded as the ratio between tumor tissue and normal tissue, the most common threshold used in these studies was 1 [ 70– 72, 74, 78].

Telomere length in peripheral blood and survival outcome in solid tumor patients

Meta-analysis was conducted to analyze the studies that evaluated the telomere length in peripheral blood for the survival outcome in solid cancer patients. Using the random-effects model because of significant heterogeneity of the studies, significant higher mortality and more tumor-progression were observed for these patients with short telomere. The pooled HR of 1.21 (95%CI, 1.10–1.32) and 1.71 (95%CI, 1.37–2.13) indicated that short telomere length significantly affects overall survival and progression-free survival, with I² values of 87% and 60%, respectively (Fig. 2A and 2B).

With respect to the overall survival, because of the high heterogeneity exhibited in the trials, meta-regression was conducted to explore the heterogeneity of the covariates; these include the study population (general population vs. special cancer types), sample size (≥1000 vs.<1000), telomere length cutoff value (median vs. other cutoff values), quality score (≥15 vs.<15), study area (Asia vs. Europe and America), age (≥60 vs.<60) and center (multi-center vs. single-center) (Table 2). Almost all subgroups showed poor overall survival of patients with shortened telomere length. However, covariates were not a statistically significant source of heterogeneity (P>0.05). Publication bias was not significant for overall survival and progression-free survival (Egger’s test, P = 0.772 and P = 0.232, respectively, funnel plots in Supplementary Fig. 1A and 1B).

Telomere length in peripheral blood and survival outcome in hematology malignancy patients

For studies that evaluate the telomere length in peripheral blood of hematology malignancy patients, shortened telomere length was significantly correlated with the mortality and tumor progression, with the pooled HR estimate of 2.83 (95%CI, 2.14–3.74, I² = 74%, P<0.001) and 2.65 (95% CI: 2.18–3.22, I² = 48%, P = 0.051), respectively (Fig. 2C and 2D). We could see from the forest plot that Borssen’s study was the only one that reported the better overall survival in patients with shortened telomere length; perhaps it was the only study that focused on the childhood acute lymphoblastic leukemia [ 58]. After excluding this study, the pooled HR estimate for mortality was 3.26 (95%CI: 2.44–4.34, I² = 63%, P = 0.003).

Meta-regression was conducted to explore the heterogeneity of the covariates including the sample size (≥200 vs.<200), telomere length cutoff value (median vs. other cutoff values), quality score (≥15 vs.<15), study area (Asia vs. Europe and Oceania), age (≥60 vs.<60), center (multi-center vs. single-center) and method (PCR vs. non-PCR) (Table 3). All subgroups showed poor overall survival of patients with shortened telomere length. The HR of mortality was 13.2 (95%CI, 6.06–27.99; I² = 0) of patients with shortened telomere length when the quality score was over 15 in the studies. The covariate of quality score and evaluation method were statistically significant sources of heterogeneity (P = 0.036). We found that studies with higher qualities had more strict study design and more detailed survival analysis; thus, the results of these studies were more consistent. Publication bias was not significant, both in the overall survival study (P = 0.686 for Egger’s test), and in the progression-free survival study (P = 0.137 for Egger’s test) (funnel plots in Supplementary Fig. 1C and 1D).

Telomere length in tumor tissue and survival outcome in solid cancer patients

For studies evaluating the telomere length in tumor tissue of solid cancer patients, the pooled HR estimate for mortality and tumor progression was 1.26 (95%CI, 0.95–1.66) and 1.65 (95%CI, 1.26–2.15), respectively. Forest plots revealed substantial heterogeneity for mortality and tumor progression studies (I² = 79% and I² = 75, respectively) (Fig. 3A and 3B). As seen from the forest plot, only the study from Pezzolo et al. showed the hazard ratio for better overall survival and tumor-free survival (HR= 0.13 and 0.25, respectively) [ 68]. After excluding this study, the pooled HR estimate for mortality and tumor progression was 1.44 (95%CI, 1.08–1.92; I² = 57%) and 1.96 (95%CI, 1.48–2.59; I² = 45%), respectively. Publication bias was not significant in the overall survival study (P = 0.137 for Egger’s test) or the progression-free survival study (P = 0.359 for Egger’s test) (funnel plots in Supplementary Fig. 1E and 1F).

Telomere length ratios of tumor tissue to adjacent normal mucosa and survival outcome in solid cancer patients

The pooled HRs of mortality and tumor progression were 0.66 (95%CI, 0.53–0.83) and 0.74 (95%CI, 0.41–1.32), respectively (Fig. 3C and 3D). Heterogeneity was present, mainly from the study by Frias et al., which estimated the risk of lung cancer death by dichotomous telomere length ratio as all other studies did [ 74]. However, their result (HR, 1.89; 95%CI, 1.15–3.10) contrasted with the result of Hsu et al. (HR, 0.39; 95%CI, 0.19–0.83), who also studied the telomere length in lung cancer [ 77]. Upon exclusion of this study, the I² value decreased to 55% in the overall survival. Egger’s test was significant in the overall survival study (P = 0.001); however, it was not significant in the progression-free survival study (P = 0.59) (funnel plots in Supplementary Fig. 1G and 1H).

Discussion

The hypothesis that telomere length variation is a determinant of prognosis is attractive to explain the heterogeneity in clinical outcome. Previously, Zhang et al. reported that short telomere length indicated a significant association with poor cancer survival. However, they did not consider that serum telomere length and tumor tissue telomere length represent different mechanisms and should be analyzed separately [ 80]. The 51 eligible studies that included 14 464 patients pooled in our meta-analysis support the significant associations between telomere length changes and cancer survival.

First, in peripheral blood studies of solid cancer patients, shortened telomere is predictive for poor mortality and tumor-progression. In patients with hematology malignancy, shortened telomere is also predictive for poor mortality and tumor-progression.

Secondly, in the tissue-based studies, the shortened telomere was shown to indicate poor mortality and tumor-progression. However, when calculating the telomere length ratios of tumor tissue to adjacent normal mucosa to adjust the age-dependent variation of telomere length, the shortened telomere indicated reduced mortality and tumor-progression.

Conflicting results were observed between tissue ratio studies and other studies. Certain researchers are truly concerned with the age-dependent telomere length variation and wish to exclude the age effect on the telomere length. Thus, telomere length ratios of tumor tissue to adjacent normal mucosa were a good choice. In these tissue ratio studies, telomere length ratio reflects the cumulative impact of tumor-associated factors on genomic homeostasis [ 81]. Sufficient telomere maintenance, as indicated by larger telomere length ratio, might represent poor survival in these patients.

However, peripheral blood telomere length is often representative of other healthy tissue. Telomere length might represent the biological “age.” Thus, patients with shortened telomere length are biologically older, and might indicate poor survival. Consistently, in most studies, the group of patients with shorter telomere lengths was also older than the other group. In tumor tissue studies and hematology malignancy studies, although tumors themselves might have some effect on telomere length, we suppose that age might still have the main impact. Duggan et al. also suggested that progressive telomere shortening with cell division is a hallmark of aging [ 30]. Furthermore, they demonstrated that the risk of cancer mortality is not related to baseline telomere length, but rather to rate of length change over time, which may be amenable to intervention.

Different methods were used to determine telomere length. Southern blot, the traditional method to determine telomere length, is the most widely used. Furthermore, flow-FISH is also a useful approach. However, when DNA sample is of poor quality, a slot blot methodology has been proposed as an alternative to estimate the total telomere DNA content. The use of PCR (T/S) for telomere length, as described by Cawthon et al. in 2002, has become increasingly popular in recent years [ 82]. Peripheral blood studies of telomere length in solid cancer patients was first initiated in 2008, and the PCR was the only method to evaluate telomere length in these studies. Moreover, Baird et al. developed a PCR-based technique for detection of individual telomeres, STELA, in which very short telomeres can be visualized [ 83]. Svenson et al. reported that the PCR method retained a good correlation with Southern blot data when applied to DNA from bone marrow and lymph node samples, but was not successful for solid cancer [ 81]. To date, no consensus has been reached on the optimal method of assessing telomere length.

The main factors we considered responsible for the inconsistency results were as follows: tumor type, representing different pathological characteristics; variability in the detection method; absence of a uniform cutoff value of the shortened telomere length. In addition, inconsistency in the inclusion of clinical factors predicting overall survival and progression-free survival in multivariate analysis might also be a contributing factor. Studies that are better designed and use standardized unbiased methods and prospectively homogeneous cohorts, are required to assess the precise prognostic roles of telomere length in cancer patients.

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