MNS16A polymorphism of the TERT gene on cancer risk: a systematic review and meta-analysis

Abstract Some studies have suggested that MNS16A polymorphism in telomerase reverse transcriptase (TERT) gene is associated with cancer risk in various populations and types of cancer. However, the results of previous studies exploring this link have been inconclusive. To be able to accurately assess the association between TERT MNS16A polymorphism and cancer risk, we performed a meta-analysis based on 17 studies described in 12 articles, including 13,764 controls and 7,132 cases. Combined odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were estimated to assess the strength of the association in either a fixed-effects model or, if applicable, a random-effects model. Heterogeneity between articles and their publication bias were also tested. Overall, pooled results showed that no significant association between this polymorphism and cancer was found in the five gene models tested. Considering that there may be too many negative studies in the included studies, diluting the results of the total sample size, we stratified these studies according to ethnicity, source of controls and cancer type. In the stratified analysis, a statistically significant association was observed between Asians and population-based studies. We also analyzed by cancer type and found a significantly increased risk of brain cancer in five genetic models. Our results suggest that TERT MNS16A polymorphism is likely to contribute to increased cancer risk.


Introduction
Cancer is increasingly becoming one of the leading causes of death worldwide and has become one of the most challenging modern health problems, placing a huge burden on public health systems worldwide. [1]However, the exact pathogenesis of tumors has not been fully expounded.Like other complex diseases, cancer is a multifactorial disease caused by complex genetic factors. [2]Therefore, genetic factors, such as genetic polymorphisms, play a non-negligible role in the occurrence and development of cancer. [3]elomeres (a distinctive DNA-protein structure at the distal end of eukaryotic chromosomes) are highly conserved functional structures located at the ends of eukaryotes' chromosomes, with functions that protect chromosomes from degradation, end-to-end fusion, and rearrangement. [4]omatic cells gradually shorten the length of telomeres after each cell division, however, in immortal tumor cells, telomeres reach a critical length and lose their capping function during the aging phase.Uncapped chromosomal ends trigger DNA-damage-like responses. [5]The activity of telomerase in normal human tissues is suppressed, reactivated in tumors, and thus may be involved in malignant transformation. [6,7]Human telomerase reverse transcriptase (hTERT), an important component of telomerase, is highly expressed in almost all immortal tumor cells but is limited in normal tissues, leading researchers to suggest that hTERT is involved in cancer susceptibility. [8]MNS16A is a small polymorphic tandem repeat satellite located downstream of hTERT gene, which was first reported to affect the promoter activity of lung cancer cell lines. [9]In recent years, there has been more and more studies on the MNS16A polymorphism, and researchers are increasingly aware of the importance of this polymorphism in cancer.Many new studies have discovered inconsistent conclusions.Currently, there is no definitive conclusion on the relationship between this polymorphism and tumor, so META analysis is needed to clarify this association.Variants containing short tandem repeats (S allele) had stronger promoter activity than long repeats (L allele), suggesting that the number of tandem repeats is associated with lung cancer risk.Subsequently, several malignancies such as brain, [10,11] lung, [12,13] breast, [14,15] urinary system, [16][17][18] colorectal, [19] hematology, [20,21] and one meta-analysis [22] had investigated MNS16A in the etiology of cancer but with inconsistent results.Considering the important role of MNS16A in promoter activity of hTERT gene, we therefore conduct a meta-analysis on eligible articles to estimate association of MNS16A with cancer risk.

Identification and eligibility of relevant studies
We carried out a systematic literature search in PubMed and Web of Science to identify studies investigating the association between the MNS16A polymorphism in the TERT gene and cancer risk, using the following search terms: TERT OR hTERT OR "telomerase reverse transcriptase" AND "polymorphism".Studies published before April 2023 were selected, the search was limited to English.The reference lists of reviews and retrieved articles were hand searched by the two authors independently, and abstracts or unpublished reports were not considered.
Studies that were included in the current meta-analysis had to contain all of the following: (a) an evaluation of the TERT MNS16A polymorphism and cancer risk, (b) a case-control design, and (c) sufficient published data for estimating an odds ratio (OR) with a 95% confidence interval (CI), and (d) the tissue of origin must be peripheral blood.Studies were excluded from the analysis if they were (a) not about cancer research, (b) not human case-control design, (c) lacking usable data on genotype frequencies, and (d) not consistent with Hardy-Weinberg equilibrium.

Data extraction
Two investigators independently abstracted the data from eligible studies selected according to the inclusion criteria listed above, and the results were compared.Any disagreement was resolved by discussion.If a disagreement persisted despite the discussion, a third author was invited to assess the articles in question.The following information was collected for each study: the first author's name, year of publication, country, patient ethnicity, cancer type, source of control groups, genotyping method, total number of cases and controls and number of cases and controls with LL, LS, and SS genotypes.For studies investigating two or more cancer types, data will be extracted as separate studies.

Statistical analysis
The summary odds ratios (ORs) corresponding to a 95% confidence interval (CI) were calculated to assess the strength of the association between the TERT MNS16A polymorphism and cancer risk.The OR and the 95% CI in each comparison were assessed in a homozygote comparison model (SS versus LL), a heterozygote comparison model (SL versus LL), a dominant model (SS + SL versus LL), a recessive model (SS versus SL + LL) and an allele comparison model (2SS + SL versus 2LL + SL).Our subgroup analysis was based on type of cancer, source of control, and race.The Hardy-Weinberg equilibrium (HWE) in the control group of each study was calculated using goodness of fit tests (Chi square test or Fisher precision test), and studies with p < 0.05 were excluded.
Between-study heterogeneity was assessed by x2-based Cochran Q statistical test and I2 metric.Heterogeneity was considered significant at p < 0.05 for Q statistics (evaluating whether the observed variance exceeded the expected variance).For I2metric, the following cutoff points were used: I2 = 0-25%, without heterogeneity; I2 = 25-50%, moderate heterogeneity; I2 = 50-75%, with large heterogeneity; I2 = 75-100%, extreme heterogeneity. [23]If the heterogeneity test results are p < 0. 05.Then the random effects model (DerSimonian and Laird methods) [24] was used to analyze the combined ORs.Otherwise, if the result of heterogeneity test is p > 0. 05 (indicating no significant heterogeneity between studies), and then the fixed effects model (Mantel-Haenszel method) [25] was selected.The Z test was used to determine the pooled OR, and the significance was set at p < 0.05.
Sensitivity analyses were performed to assess the impact of each independent case-control study.In addition, Begg test and Egger regression test were performed to evaluate publication bias, and p < 0.05 was considered to be representative of statistically significant publication bias.
All statistical analysis was conducted using STATA software (version 12; Stata Corporation, College Station, Texas).Two-sided P-values <0.05 were considered to be statistically significant.

Main characteristics of the enrolled studies
The study selection processes were presented in Figure 1.For MNS16A polymorphism of TERT gene, a total of 12 articles (including 17 casecontrol studies) with 7132 cases and 13,764 controls met the inclusion criteria.A total of 11 studies were performed in Caucasians, 3 studies were performed in Asians, 2 studies in Iranians, and one study in African.Controls of 11 studies were population-based controls and 6 studies were hospital-based controls.All studies were incompliance with HWE.Table 1 showed the characteristics of all the eligible studies and genotype frequency distributions of the MNS16A polymorphism included in our meta-analysis.Newcastle-Ottawa scale (NOS) was used to evaluate the quality of the enrolled studies, as shown in Table 3.

Main meta-analysis results
Table 2 lists the main results of a meta-analysis of TERT MNS16A polymorphism.Pooled results based on all eligible studies show that the overall OR value is invalid after enlarging the sample size.However, this does not necessarily indicate that TERT MNS16A is not associated with cancer.

Sensitivity analysis
Sensitivity analyses were performed to assess the impact of each individual study on the aggregate study, or by sequentially omitting the individual qualifying study (Figure 3).The results showed that in the genetic model of the relationship between MNS16A polymorphism of TERT gene and cancer susceptibility, none of the studies changed the overall significance of ORs, indicating the stability and reliability of our overall results.

Publication bias assessment
A funnel plot and Egger's test were conducted to evaluate the publication bias of the literature (Figure 4).The shape of the funnel plot did not reveal any obvious evidence of asymmetry.Similarly, the statistical results still did not show publication bias under the recessive effects model   (t = 0.62, p = 0.544).Additionally, in all other genetic models, the results did not show evidence of publication bias (data not shown).

Trial sequential analysis
To assess random errors, we performed TSA.The analysis [26,27] showed that the cumulative Z-curve had crossed the trial sequence monitoring boundary and the size of the information required, indicating that enough evidence has validated the conclusions.

Discussion
Telomeres are functional structures at the ends of chromosomes that protect chromosomes from end-to-end fusion.When telomere erosion falls below a certain length, it can trigger a crisis. [28]Telomeres shorten gradually throughout a person's life.A hallmark of advanced malignancy is the ability of cells to divide continuously, an ability almost universally associated with telomerase reactivation to stabilize telomere length.Inhibition of telomerase and shorter telomeres in humans may have evolved, in part, as a protective mechanism against cancer.Although there is still much we do not know about the regulation of telomerase, it remains a very attractive and novel target for cancer diagnosis. [29]The activation of telomerase is closely related to human aging and the pathogenesis of cancer cells.Telomerase is considered to be a key factor in cancer cell biology, and its re-expression enables malignant cells to proliferate indefinitely. [30]MNS16A was first identified as a tandem repeat satellite of TERT polymorphism in a study of lung cancer patients. [9]In this meta-analysis, we sought to determine whether polymorphic TERT MNS16A polymorphism is closely associated with cancer risk in a larger sample size.MNS16A polymorphism did not appear to be associated with cancer risk in any of the gene models.However, considering the possible dilution of the overall effect size due to the inclusion of too many meaningless negative results in the studies, we performed a stratified analysis.The results showed that in a subgroup analysis by cancer type, the risk of brain cancer was significantly increased in all five genetic models; Hematological tumors followed, showing increased risk in all four genetic models.However, no increased risk of lung cancer, breast cancer, urinary cancer, or other cancers associated with this polymorphism was observed.In a subgroup analysis by ethnicity, in three genetic models, the risk of cancer increased significantly in Asians, but not in Caucasians and Iranians.This suggests that the mechanism of cancer may be different in different races.When subgroup analyses were performed according to control group sources, significant correlations were observed in population-based studies, but not in hospital-based studies.
Heterogeneity analysis is an important part of meta-analysis.In this study, significant heterogeneity was found in all five gene models.However, when subgroups were analyzed by cancer type, heterogeneity disappeared in brain cancer and was not found in the three model species of lung cancer.The three gene models of breast cancer show extreme heterogeneity.None of the five gene models of hematological tumors showed heterogeneity, presumably due to the small number of studies included on this cancer.In subgroup analyses stratified by race, Asian heterogeneity disappeared.Heterogeneity can be attributed to differences in patient characteristics, genetic background, or living environment, it might be attributed to differences in genotyping methods for polymorphisms.Sensitivity analysis shows that our results are robust and reliable.In addition, neither the shape of funnel plots nor the statistical results showed publication bias in our meta-analysis.
However, this meta-analysis has several limitations to consider.First, the small sample size limits the reliability of the results.Second, we only evaluated studies published in English, which may affect the comprehensiveness of the data collected.Third, we did not test the relationship between polymorphisms and the environment, and specific environmental factors may affect the risk association between genetic polymorphisms and cancer.Fourth, although bias is not shown in publication bias testing, we cannot ignore the possibility of unpublished due to some unexpected factors, which may bias our results.Fifth, we mainly evaluated the relationship between MNS16A polymorphism with various cancers, and we couldn't get enough data for some cancer types.Sixth, we were unable to determine the effect of this polymorphism on the mRNA expression of TERT gene.Seventh, we didn't assess the linkage disequilibrium, which might not reflect the real function correctly.Despite these shortcomings, there are also some advantages to our study, and we have spent some effort to find qualified case-control studies that meet our carefully designed criteria for inclusion.
Taken together, this meta-analysis provides convincing support that TERT MNS16A polymorphism may greatly improve cancer susceptibility, particularly brain and hematologic tumors.
There has been a previous meta-analysis [22] focused on this topic in 2013.Years have passed, there has been some new studies, many of which have found different conclusions than before.A new and more comprehensive meta-analysis is needed.At the same time, our study completed the findings of previous meta-analyses.In some ways, we came up with different results than previous meta-analysis.
We were trying to discover the relationship between MNS16A polymorphism and cancer.And we do find that MNS16A polymorphism was correlated with brain cancer and hematologic tumors.Screening of MNS16A polymorphism would provide clinical value for early diagnosis of brain cancer and hematologic tumors.

Figure 1 .
Figure 1.Flow chart of studies selection process for MNS16A gene polymorphisms.

Figure 2 .
Figure 2. overall association between the TERT MNs16A polymorphism and cancer risk for all subjects in the homozygote comparison model (fixed-effects model).

Figure 3 .
Figure 3. Results of the sensitivity analysis examining the association between the TERT MNs16A polymorphism and cancer risk in the recessive model.

Figure 4 .
Figure 4. Funnel plot to determine publication bias of the meta-analysis of the association between cancer risk and the TERT MNs16A polymorphism.

Figure 5 .
Figure 5. tsA for MNs16A polymorphism under the allele contrast model.

Table 1 .
characteristics of studies included in the meta-analysis.

Table 2 .
total and stratified analysis of TERT MNs16A polymorphism on cancer risk.

Table 3 .
Methodological quality of the enrolled studies according to the Newcastle-ottawa scale.