Telomerase Reverse Transcriptase Locus Polymorphisms and Cancer Risk

A Field Synopsis and Meta-analysis

Simone Mocellin; Daunia Verdi; Karen A. Pooley; Maria T. Landi; Kathleen M. Egan; Duncan M. Baird; Jennifer Prescott; Immaculata De Vivo; Donato Nitti


J Natl Cancer Inst. 2012;104(11):840-854. 

In This Article


This work, to our knowledge, is the first synopsis of the literature on the role of polymorphisms at the TERT locus (5p15.33) in cancer predisposition. Upon systematic review and meta-analysis of the data from 85 molecular epidemiology studies, enrolling almost half a million people tested for one or more of 67 polymorphisms, which generated 494 allelic contrasts, we found that 22 polymorphisms were associated with the risk of developing one or more types of cancer but only 11 showed strong cumulative evidence for association, according to the Venice criteria.

The risks were relatively low, with odds ratios for risk alleles ranging between 1.05 and 1.61 and those for protective alleles between 0.92 and 0.75. Accordingly, PAR, which takes into account both magnitude of the risk and risk allele frequency in the general population, varied from 4% to 36%. Although these figures might suggest at first glance that the TERT locus does not play a major role in cancer susceptibility, a couple of considerations should be made. First, it is widely recognized that single common polymorphisms are generally associated with low risks (ie, OR < 1.5),[20] which calls for considering the effect of combinations of multiple polymorphisms. A few studies[29,37,54,63] addressed this issue by assessing the effect of TERT locus haplotypes on cancer risk: However, the haplotypes considered by different authors are heterogeneous, and thus no meta-analysis could be performed. Other investigators have verified that some polymorphisms (eg, rs2736100 and rs2736098) carry a risk independently of others [eg, rs402710,[29] rs4635969,[40] and rs401681[41]] using multivariable logistic regression analysis, but unfortunately, the models (ie, the combination of included covariates) are not equal and thus their results cannot be merged. Nevertheless, to provide readers with an idea of the potential predictive value of multiple polymorphisms, we considered three unrelated (based on pairwise correlation coefficient r 2 <0.1 and multivariable analysis) polymorphisms (ie TERT rs2736100, intergenic rs4635969, and CLPTM1L rs402710) with a strong cumulative evidence for association with lung adenocarcinoma, and we found that the estimated joint PAR defined by these polymorphisms is 41% (see Figure 1), which corresponds to a 0.5% attributable community risk (considering a 1.2% lifetime risk of lung adenocarcinoma). Although we could calculate only a per-allele PAR (ie, only the codominant model was tested), this result highlights the pivotal role that TERT locus polymorphisms play in the determination of the most frequent histological subtype of lung cancer and exemplifies the importance of further investigation on the 5p15.33 region with regard to cancer predisposition in general.

Another key point is that the TERT gene alone (without considering the rest of the TERT locus) has more than 500 known SNPs, whereas thus far the relationship with cancer risk has been investigated only for 67 SNPs, which is a minority of these polymorphisms. It should also be remembered that only 24 tumor types were investigated and that on average, each polymorphism was tested for about three tumor types (range = 1–23) (see the heat map in Supplementary Figure 3, available online). Furthermore, as we reported above, for many polymorphisms, some evidence of association with cancer risk already exists, although more data are necessary to conclusively define their role (see Table 1 for polymorphisms with moderate or weak cumulative evidence and Supplementary Table 1, available online, for polymorphisms with statistically significant association in a single study). In contrast, only for a minority of the polymorphisms investigated to date (5 [7%] of 67) the available results are compatible with no relevance for the susceptibility of three tumor types (see Table 2 for strong cumulative evidence), which does not rule out that these SNPs might be associated with the risk of other tumor types. Therefore, this synopsis, which strongly supports the relevance of the TERT locus to define the genetic architecture of cancer predisposition, also underscores that much work remains to be done before we can entirely appreciate the importance of this DNA region in cancer development.

The 5p15.33 locus is characterized by a 62-kb LD block including the 5′-end of TERT, its promoter, and the entire gene CLPTM1L (Supplementary Figure 2, available online); consequently, there are two genes that can be involved in the tumor promoting effects epidemiologically linked to the above described polymorphisms. Certainly, TERT is the more appealing candidate because of its well-known role in telomere and tumor biology. However, we must underscore the discrepancy between the epidemiological findings associating TERT polymorphisms to cancer risk and the relatively scarce[29] and sometime conflicting evidence[59,87] associating the same polymorphisms to telomere length, a key aspect linking these chromosomal structures to cancer biology. In light of these controversies, more work is warranted to elucidate the molecular mechanisms possibly responsible for these epidemiological observations. For example, rs2736100 and other SNP in the locus are close to mutations known to alter telomerase activity.[88] The complete sequencing of this locus in cancer patients will help investigators to fully elucidate the relationship between the TERT locus polymorphisms and cancer risk.

For the other gene in this region, CLPTM1L might be relevant not only because it is in LD with TERT but also in the light of its own biological activity; its product (cleft lip and palate transmembrane protein 1-like protein) is known to induce cisplatin resistance in ovarian cancer cells (the CLPTM1L product is also called cisplatin resistance related protein [CRR9]).[89] Moreover, its SNP rs402710 has been recently associated with higher levels of bulky aromatic and hydrophobic DNA adducts,[47] a typical product of lung cancer carcinogens such as polycyclic aromatic hydrocarbons and tobacco-specific nitrosamines.

Considering that, for both genes, virtually all polymorphisms have no effect on protein sequence (all polymorphisms for which a meta-analysis could be performed were either intronic or exonic-synonymous or intergenic) (Supplementary Table 1, available online), the association of these polymorphisms with cancer susceptibility might derive from either their LD with still undetected functional polymorphisms (ie, exonic non-synonymous) or from their effect on protein expression (although the latter hypothesis does not appear to be supported by the evidence collected thus far, as mentioned above). Overall, the findings collected in this synopsis, which are virtually always based on tagging SNP, might tip the balance in favor of gene-centric strategies, that is, studies based on the use of polymorphisms known to affect protein sequence. However, some investigators have recently reported no meaningful results adopting this approach and have hypothesized that natural selection has rendered non-synonymous alleles so rare (ie, MAF < 5%) that sample sizes greater than those used for common alleles should be used to detect statistically significant associations.[90] Remembering that in this synopsis, where virtually all studies regarded polymorphisms with MAF greater than 5%, the mean sample size is approximately 6000 subjects, the practical difficulty of carrying out gene-centric research is self-evident.

An intriguing finding of our work is that the association between a given polymorphism and cancer risk can be very specific not only in terms of ethnicity/histology but also in terms of effect direction (Table 1). Indeed, we found that some 5p15.33 locus polymorphisms correlate (with strong evidence) with cancer risk only in whites (eg, rs2736100 in lung adenocarcinoma) or Asians (eg, rs402710 in lung cancer), and that others predispose to a specific histological subtype of cancer (eg, rs2736100 and rs4027100 in lung adenocarcinoma). More surprisingly, the same polymorphism (eg, rs2736100, rs401681) can result in an increased risk for some cancer types (eg, lung cancer, BCC) and a reduced risk for others (eg, TGCC, melanoma). In the case of melanoma and BCC, this finding, apparently contradictory, is in line with the opposite effect that telomere shortening [which is accelerated in rs401681[C] carriers[41]] can have on the two tumor types.[91,92] On the other hand, our observation lends support to a double hypothesis: 1) no common molecular pathway leads to the development of all cancer types, and 2) some pathways favoring the development of some tumor types might even oppose the genesis of others. Some clinical epidemiology evidence is in the same direction: for example, women taking tamoxifen (a drug interfering with the estrogen receptor pathway) are at lower risk of breast cancer but at higher risk of endometrial cancer; and people affected with skin melanoma (and thus with a genetic background predisposing to this tumor) are at higher risk of secondary melanoma but also at lower risk of gastrointestinal and lung tumors.[93] Though appealing, this hypothesis clearly warrants further investigation to be validated and thus to be exploitable on the clinical ground.

Finally, the limitations of this synopsis must be addressed. For example, although an exhaustive literature search was performed, it is possible that some publications were overlooked; moreover, not all the GWAS authors we contacted agreed to provide their data; finally, only for a minority of studies genotype data (either as raw or summary data) were provided, which enabled us to test only the codominant model (per-allele risk analysis). We hope that this large collection of data on TERT locus polymorphisms and cancer risk will prompt investigators to share their knowledge in this field, also exploiting the dedicated online data repository above mentioned (available at[13] Furthermore, we used allele counts and crude estimates of effect, rather than association estimates adjusted by other polymorphisms, genes, or even environmental factors. As discussed above, for interaction between polymorphisms, the models used in single eligible studies differ in most cases and were therefore unsuitable for pooling. Lung cancer was the only tumor type for which investigators often reported data adjustment for smoking, the most common environmental risk factor. In this case, the impact of TERT locus polymorphisms was generally unaffected by smoking,[80] which strengthens the findings of our meta-analysis, although it does not rule out other confounding factors [eg, chronic obstructive pulmonary disease.[84]] Again, even for lung cancer, the adjustment for smoking was reported in different ways (eg, as a single OR adjusted by including smoking behavior in a logistic regression model or by providing multiple ORs obtained separately in smoking and nonsmoking subjects), which precluded any meaningful pooling of summary data.

For gene–gene interactions, it should be remembered that tens of genes are currently known to contribute to telomere biology[94] and thus may contribute to modulate cancer susceptibility. However, to date, only a few authors investigated the relationship between polymorphisms of telomere-related genes (other than TERT) and predisposition to few tumor types,[24,28,37,45,60,62,75] and because the available results are sparse (different tumor types), no data merging could be performed, which calls for further research in this field.

Multiple testing is another possible concern. We performed a total of 118 meta-analyses (including ethnicity-specific and cancer subtype–specific analyses): Considering a Bonferroni adjustment, the P value threshold for statistical significance would be .0004, which would reduce statistically significant associations from 75 to 47 (Table 1, P values tagged with symbols). Nevertheless, it should be noted that this P value is overly conservative because many tests were performed in independent datasets. Furthermore, lowering the alpha level of significance increases the possibility of type II error (ie, reduces statistical power). More importantly, polymorphisms statistically significantly associated with cancer risk were graded according to the Venice criteria, providing evidence over and above statistical P values.

In conclusion, this synopsis demonstrates that genetic variation in the TERT locus is likely to play a relevant role in cancer development. However, it also underscores that much work still needs to be done to clarify the molecular mechanisms underlying this epidemiological observation and to define the interactions of this evidence with the other pieces of the cancer predisposition puzzle.


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