Introduction
Radiotherapy is commonly used in cancer treatment. At least half of cancer patients will require radiotherapy with either curative or palliative intent [
1]. However, the adverse effect induced by radiotherapy restricts this modality from playing a larger role in the multidisciplinary therapy of cancer. It has been widely noticed that patients were not homogeneous in the reaction of normal tissue following radiotherapy [
2,
3]. The standard radiotherapy schedule was recommended treating the cancer patients as a whole, which was actually miscellaneous with patients of different radio-sensitivity. So the radio-resistive patients who can bear more doses of radiotherapy were confined in the protocol of standard radiotherapy with the radio-sensitive patients who may even fail the cost-benefit evaluation of receiving radiotherapy. Consequently, the likelihood of a cure was to some extent reduced for some patients. On the other hand, for some others, the standard radiotherapy was still too harmful to the balance between the therapeutic effect and the normal tissue injury. It is believed that a genetic basis plays an important role in this heterogeneous response to radiation [
4,
5].
‘Radiogenomics’ is the study of genetic variation associated with response to radiotherapy, with a main purpose of establishing single nucleotide polymorphism (SNP) based risk models that can stratify patients according to radio-sensitivity [
6,
7]. In the last decade, candidate gene association studies have identified several potential predictors for radio-sensitivity. Due to the insufficient sample size of these studies and relatively small effects conferred by relevant SNPs, it makes much sense to systematically synthesize the previous evidence. Recently, we have reviewed several SNPs in radiogenomics, including ATM [
8], XRCC3 [
9] and XRCC1. The aim of the present meta-analysis is to evaluate the effect of excision repair cross-complementing 2 (ERCC2, also known as XPD, xeroderma pigmentosum group D ) polymorphisms on radiotoxicity.
ERCC2 protein is an essential component of the general transcription factor TFIIH complex that plays a key role in nucleotide excision repair (NER) and basal transcription [
10‐
14]. Besides a 5’-3’ helicase activity, ERCC2 also plays a bridging function within the TFIIH complex [
13,
15]. Mutations in ERCC2/XPD have been associated with three hereditary diseases, namely Xeroderma pigmentosum (XP), Cockayne Syndrome and Trichothyodystrophy (TTD) [
10,
13,
16]. However,
in vitro studies failed to relate the polymorphisms of ERCC2 to DNA repair capacity [
13,
17‐
19].
Discussion
Radiogenomics has entered the era of big data [
31]. However, for the last decade candidate gene approach was predominant, and inconsistent results have been reported due to most studies were underpowered with a relatively small information size. Besides, some single SNP may confer only slightly elevated risk of radiotoxicity, so it is difficult to identify this true effect without an enough sample size. Hence, systematically summarizing the previous data benefits of identifying a relatively small but significant effect of relevant SNPs. In fact, meta-analysis has played an important role in radiogenomics.
The present meta-analysis systematically summarized the previous data of ERCC2 in radiogenomics. A significant association between rs13181 and radiotoxicity was identified by conventional meta-analysis. Our data revealed that the major allele of rs13181 presents as a risk allele, which means the minor allele confers a protect effect against the appearance of radiotoxicity. However, we should notice that this association was still borderline (95 % CI: 0.55-0.93), and one study made the original significance vanish in leave-one-out sensitivity analysis. In addition, this conventional significance failed to get the confirmation of TSA. We applied TSA with the intention of drawing out more specific conclusions. TSA revealed that the z-curve failed to further cross the α-spending boundary after crossing the conventional boundary of z = −1.96, which means the correlation between rs13181 polymorphism and radiotoxicity risk still need the confirmation of subsequent studies. To safely conclude an effect of OR = 0.71, additional 1400 patients were needed.
We performed subgroup analyses by adverse effect. Radiation-induced adverse effects can be classified as early or late effects according to the time before the manifestation of relevant clinical symptoms. Most radiogenomics studies reported early and late effects separately, and some SNPs exert inconformity effect on early and late effects. For instance, the pooled data of XRCC1 revealed that Arg399Gln (rs25487) polymorphism significantly correlated with an elevated risk of early radiotoxicity, while this SNP was ruled out any clinical relevance with late radiotoxicity (Song YZ: The XRCC1 Arg399Gln Polymorphism and Radiation-Induced Adverse Effects on Normal Tissue: Systematic Review with Meta-analysis and Trial Sequential Analysis. Submitted). Meta-analysis of XRCC3 Thr241Met (rs861539) polymorphism also reported a similar result, that is a significant association with early radiotoxicity rather than late radiotoxicity [
9]. In the present meta-analysis, most studies evaluated early radiotoxicity, and only one study involved late radiotoxicity, so it is noteworthy that the pooled result of the present meta-analysis mainly reflects the effect on early radiotoxicity. Within early radiotoxicity, a significant association between rs13181 polymorphism and acute esophageal toxicity was also identified. However, this association should not be over interpreted, due to only two studies were included in this subgroup. The most evaluated radiotoxicity was acute skin toxicity in the present meta-analysis, and four studies evaluated this reaction following radiotherapy. The association between rs13181 polymorphism and acute skin toxicity was not significant.
For interpreting the pooled result of a meta-analysis, adequate evaluation on the heterogeneity between studies is crucial (as was previously described in detail [
9]). One of the most important source of heterogeneity derived from the heterogeneous treatment protocols among the included studies. For instance, the radiotherapy parameters, such as total dose, dose per fraction and irradiation volume, were not identical among the included studies. Some treatment protocols of included studies involved chemotherapy as a component of multidisciplinary therapy, while some were basing on radiotherapy alone. Toxicity evaluation was another important source of heterogeneity. Both the criteria applied and the division grade were not consistent among included studies. Nevertheless, statistical calculations did not identify obvious heterogeneity, we believed that the influence of these potential heterogeneity factors were at an acceptable level.
Based on the radiogenomics studies throughout the last decade, it is safe to conclude that no SNP alone possesses the power to accurately predict the radio-sensitivity prior radiotherapy [
6,
31]. A study aiming to validate the associations previously reported between candidate SNPs and radiotoxicity did not confirm any significant association [
32]. To date, six genome-wide association studies (GWASs) have been published on radiogenomics [
33‐
38]. The SNPs which were identified with a genome-wide significance were not located in the region supposed by candidate gene association studies. However, statically significant conclusions were constantly reported by meta-analyses of candidate gene association studies. Through combining information of all the relevant studies, more statistical power was acquired [
39]. Evidence of meta-analysis has revealed that XRCC1 rs25487, XRCC3 rs861539, ATM rs1801516 and ERCC2 rs13181 polymorphisms significantly associated with early radiotoxicity, though the effect size was relatively small [
8,
9]. While an individual candidate SNP was not expected to confer a large effect on radiotoxicity. Instead, composing a synthesized risk model is the major modality how the relevant SNPs play a role on the prediction of radio-sensitivity. Despite a relatively small effect (with odds radios of 1.2 to 1.5) exerted on radiotoxicity by individual SNP, an enough prediction power can be accrued by involving multiple such SNPs.
Conclusions
Although the minor allele of rs13181 polymorphism was identified with a protect effect against radiotoxicity, it is noteworthy that the correlation was borderline, and one included study made the overall meta-analysis loss the statistical significance in leave-one-out sensitivity analysis. In addition, this significant association identified by traditional meta-analysis failed to get the conformation of TSA. More studies with additional 1400 patients were needed to draw the firm conclusion at the level of OR = 0.71.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
DLH conceived of the study, participated in its design and critically reviewed the manuscript. SYZ, DMN and ZYY performed publication screening & data extraction and drafted the manuscript. SWY and XCC performed the statistical analysis and participated in the design of the study. All authors read and approved the final manuscript.