Abstract
Background
Genetic loci within the major histocompatibility complex (MHC) have been associated with nasopharyngeal carcinoma (NPC), an Epstein-Barr virus (EBV)-associated cancer, in several GWAS. Results outside this region have varied.
Methods
We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases;3,740 controls). 43 noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of 4 independent case-control studies across 3 regions in Asia (4,716 cases;5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed.
Results
In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR=0.81;p-value 6.3*10−13). Our results also provide support for associations reported from published NPC GWAS - rs6774494 (p = 1.5*10−12;located in the MECOM gene region), rs9510787 (p = 5.0*10−10;located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (p = 2.8*10−8,p = 7.0*10−7,and p = 8.4*10−7 respectively;located in the CDKN2A/B gene region).
Conclusion
We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene is important for telomere maintenance and has been reported to be over-expressed in NPC, and an EBV protein expressed in NPC (LMP1) modulates TERT expression/telomerase activity.
Impact
Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis.
Keywords: Head and neck/oral cancers, Telomeres and telomerase, Polymorphisms in genes related to cell growth, differentiation, metastatic potential, apoptosis in cancer risk
Introduction
Nasopharyngeal carcinoma (NPC) is linked to EBV infection. While EBV infection is ubiquitous, NPC incidence varies considerably around the world [1]. It is hypothesized that genetic differences across populations partly explain the predilection of this cancer to individuals of Southeast Asian descent. Several lines of evidence support a role for genetic susceptibility in NPC. The disease clusters within families [1]. Also, numerous studies have implicated polymorphisms in candidate genes in NPC [2,3]. The most consistent evidence has been for an association between HLA and NPC, an association that is biologically plausible given the central role of EBV in NPC and of HLA in immune presentation/handling [4].
Several NPC GWAS have recently been published [5-9]; all provided support for the importance of genetic factors and clearly confirmed the involvement of genes in the MHC region (region where HLA genes reside) in NPC. Associations outside the MHC were also reported from these GWAS but were not as strong or consistent, suggesting the need for pooling across studies and larger efforts to identify novel genes involved in this disease [5-9].
We report a meta-analysis of four published GWAS (2,152 cases; 3,740 controls), followed by replication of noteworthy findings in case-control studies from the populations where the GWAS were conducted (4,716 cases; 5,379 controls). Our analysis identified a novel association between CLPTM1L/TERT and NPC and confirmed reported associations for SNPs located in the MECOM, TNFRSF19, and CDKN2A/2B gene regions.
Materials and Methods
The GWAS contributing to our meta-analysis included histologically confirmed NPC cases and region-specific controls restricted to individuals of Chinese ethnicity (Table 1) [5-8]. Genotyping for these four GWAS were performed using Illumina platforms. The two Malaysian GWAS were analyzed as one. All data included passed QC filtering criteria as described for the respective studies [5-8].
Table 1.
Summary of Studies Included in this Analysis
| Phase | Ref. # | Location | Genotyping Platform | # Cases | # Controls |
|---|---|---|---|---|---|
| GWAS | 6 | Southern China | Illumina Hap610 | 1583 | 2979 |
| GWAS | 7 | Taiwan | Illumina 600 Hap550v3_A BeadChips | 277 | 285 |
| GWAS | 5 | Malaysia (1) | Illumina Hap550v3 BeadChip | 108 | 240 |
| GWAS | 8 | Malaysia (2) | Illumina Human OmniExpress_12 v1.1 BeadChip | 184 | 236 |
| GWAS-SUM | 2152 | 3740 | |||
| Replication I | Southern China I | Sequenom custom array | 3525 | 4121 | |
| Replication I | Malaysia | Sequenom custom array | 335 | 405 | |
| Replication I | Taiwan I | Sequenom custom array | 352 | 312 | |
| Replication I | Taiwan II | Sequenom custom array | 504 | 541 | |
| Replication I - SUM | 4716 | 5379 | |||
| TOTAL | 6868 | 9119 | |||
To maximize coverage across studies, genome-wide imputations were performed for each study using typed SNPs. SNPs with call rates >90%, minor allele frequencies >3%, and that had genotype distributions that did not deviate from the expected by Hardy-Weinberg equilibrium (in controls; P>10−6) were retained for imputation using IMPUTE2. HapMap reference data were used (HapMap phase III, CHB+CHD+JPT data from IMPUTE2 website). Imputed genotypes with information score <90%, MAF <3% or missing >10% were excluded. GTOOL (http://www.well.ox.ac.uk/~cfreeman/software/gwas/gtool.html) was employed for data conversions.
For each GWAS, SNPs were analyzed by logistic regression under a log additive model, adjusting for age and cryptic population stratification. To define population stratification adjustment factors, principal component analysis was performed (EIGENSTRAT) using a pruned set of 30,956 SNPs defined based on pairwise linkage disequilibrium (r2<0.05 among Chinese) and restricted to SNPs with MAF >3%. The top 10 eigenvectors were evaluated for their association with NPC (separately for each individual GWAS) and included in the final logistic models if p-value <0.05 by the Wald test.
Using results from individual GWAS, we identified the 500 SNPs with the lowest p-values from each of the studies after exclusion of SNPs that could not be imputed or failed QC filtering. We combined these study-specific lists of top-SNPs into a single list for consideration as part of the present meta-analysis. In total, 1,590 SNPs were identified through this process and these 1,590 SNPs comprised the basis for the present meta-analysis. Summary statistics (number cases/controls, genotype counts, beta coefficients , and standard deviations) were obtained from individual studies for selected SNPs and a meta-analysis was performed using a fixed effects model (R-program).
SNPs were selected for replication as follows. We arbitrarily ranked (by p-value) the top 200 hits (all with p-values <0.0167) from the meta-analysis for which the direction of the association was consistent across all individual studies. We then selected SNPs with p-values <1*10−5 that were 250kb+ from other selected SNPs. For SNPs within 250kb of another SNP on the list, we retained SNPs that had an r2 ≤ 0.80 (based on Chinese data from the 1k genome project) and the SNP with the smaller p-value when the r2 between SNPs was >0.80. Thirty SNPs were selected based on these criteria. We added 14 SNPs nominated by consortium members based on results from individual GWAS and other information from candidate-based studies and other studies in the published literature. One SNP that qualified based on the criteria above but failed in the design of the custom array described below was excluded (rs11865086). A second SNP that qualified but failed in the custom array design (rs6931820) was replaced with a SNP in strong LD with the original SNP (rs1324103; r2 = 0.88). In total, 43 SNPs were evaluated in the replication phase of our effort.
Replication studies were restricted to studies among individuals of Chinese descent. In total, we included 4,716 cases and 5,379 controls across four case-control studies in Mainland China, Malaysia, and Taiwan (Table 1). All four studies were hospital-based, recruiting NPC cases from selected hospitals in their respective geographical area. For the southern China study, cases were recruited from the Sun Yat-Sen University Cancer Center and the Southern Medical University Hospital. For the Malaysia study, cases were recruited from the University of Malaysia Medical Center and from a network of additional hospitals across the country. For the two Taiwan studies, cases were recruited form the National Taiwan University and MacKay Memorial hospitals and from the Chang Gung Memorial and Linkou hospitals, respectively. Cases were restricted to adults with histologically confirmed NPC. Geographically matched controls of Chinese descent were frequency (southern China, Malaysia and Taiwan II studies) or individually (Taiwan I study) matched to cases on age and gender. Controls did not have a history of NPC diagnosis. Studies were reviewed/approved by ethical committees and informed consent was obtained from participants.
A custom designed array containing the 43 SNPs selected for replication was developed using the Sequenome MassARRAY iPlex assay (Supplemental Table 1S). Testing was performed in one of two laboratories. To ensure comparable quality across laboratories, a common QC panel consisting of 94 HapMap samples was tested. Percent agreement across laboratories for the 43 SNPs tested was 97% (range: 82%-100%; Agreement was >85% for all but two SNPs: rs189897 and rs4714505).
To analyze the replication studies, individual genotyping results were pooled and an additive logistic regression model used to evaluate the effect of each SNP, adjusting for study. To summarize information across the GWAS and replication studies, we conducted a meta analysis using the fixed effect model to integrate estimates from all studies.
Results
The initial meta-analysis across GWAS included a total of 2,152 cases and 3,740 controls. Results from the meta-analysis are summarized in Supplemental Table 2S. As described in the Materials and Methods section, we identified 43 SNPs for replication based on the GWAS meta-analysis. Replication was performed on a total of 4,716 cases and 5,379 controls across 4 studies (Table 1). Results from this replication effort are summarized in Table 2. In this analysis, the strongest evidence in support of an association with NPC was observed for rs31489 (OR=0.79; p-value=4.3*10−11), an intronic SNP within CLPTM1L in the CLPTM1L/TERT region (chr.5p15.33). This represents a locus not reported in previously published NPC GWAS. Findings for this SNP were consistent in the mainland Chinese and two Taiwanese replication studies and absent from the Malaysian replication study, the smallest of the replication efforts (Supplemental Figure 1S). A second SNP within the CLPTM1L/TERT locus (rs2853668; r2 = 0.108 and D′ = 0.917 with rs 31489 among controls in our replication studies) was also associated with NPC in the replication phase (OR=1.11; p-value=5.2*10−4), but the association was no longer statistically significant in analyses that conditioned on rs31489 (OR=1.05; p-value=0.15).
Table 2.
Results from GWAS Meta-Analysis and Replication Study for 43 SNPs Selected for Replication
| SNP | Gene Neighborhood | Chr | Location* | Selection Criteria** |
MAF (Ctrls)** | Major Allele |
Minor Allele |
GWAS Meta-Analysis | Replication Study | Combined | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR | P-value | OR | P-value | OR | P-value | ||||||||
| rs31489 | CLPTM1L/TERT | 5 | 1342714 | 2 | 0.22 | C | A | 0.85 | 1.8E-03 | 0.79 | 4.3E-11 | 0.81 | 6.3E-13 |
| rs6774494 | MECOM | 3 | 169082633 | 2 | 0.36 | A | G | 0.81 | 4.0E-07 | 0.86 | 3.4E-07 | 0.84 | 1.5E-12 |
| rs9510787 | TNFRSF19 | 13 | 24205195 | 2 | 0.35 | A | G | 1.2 | 1.9E-05 | 1.14 | 4.1E-06 | 1.16 | 5.0E-10 |
| rs1412829 | CDKN2A/2B | 9 | 22043926 | 1 | 0.11 | T | C | 0.72 | 2.8E-06 | 0.85 | 4.2E-04 | 0.80 | 2.8E-08 |
| rs4977756 | CDKN2A/2B | 9 | 22068652 | 1 | 0.22 | A | G | 0.8 | 9.7E-06 | 0.90 | 2.7E-03 | 0.87 | 7.0E-07 |
| rs1063192 | CDKN2A/2B | 9 | 22003367 | 1 | 0.17 | T | C | 0.77 | 2.4E-06 | 0.90 | 6.0E-03 | 0.86 | 8.4E-07 |
| rs2853668 | CLPTM1L/TERT | 5 | 1300025 | 2 | 0.31 | C | A | 1.15 | 1.7E-03 | 1.11 | 5.2E-04 | 1.12 | 3.6E-06 |
| rs3731239 | C9orf53,CDKN2A | 9 | 21974218 | 1 | 0.13 | T | C | 0.77 | 6.3E-05 | 0.87 | 1.6E-03 | 0.84 | 1.3E-06 |
| rs1572072 | TNFRSF19 | 13 | 24127210 | 2 | 0.26 | G | T | 0.89 | 1.3E-02 | 0.92 | 1.1E-02 | 0.91 | 4.8E-04 |
| rs3109384 | LOC646388 | 11 | 40118598 | 1 | 0.26 | C | T | 0.83 | 3.3E-05 | 0.93 | 1.8E-02 | 0.89 | 1.6E-05 |
| rs9928448 | ALDOA,PPP4C | 16 | 30072530 | 2 | 0.41 | T | C | 1.17 | 1.5E-04 | 1.07 | 2.4E-02 | 1.10 | 6.5E-05 |
| rs10120688 | RP11-145E5.4 | 9 | 22056499 | 2 | 0.28 | A | G | 0.84 | 1.8E-04 | 0.94 | 4.3E-02 | 0.91 | 1.5E-04 |
| rs2877822 | MUC13 | 3 | 124645034 | 2 | 0.04 | C | T | 0.68 | 1.1E-04 | 1.14 | 5.4E-02 | 0.96 | 5.2E-01 |
| rs6671127 | LOC100133029,GPR177 | 1 | 68571220 | 1 | 0.37 | A | C | 1.2 | 1.6E-05 | 1.05 | 8.5E-02 | 1.10 | 1.2E-04 |
| rs10796139 | FRMD4A | 10 | 13892298 | 1 | 0.36 | A | G | 0.82 | 1.3E-05 | 0.96 | 1.2E-01 | 0.91 | 2.1E-04 |
| rs1331627 | NTNG2 | 9 | 135091879 | 1 | 0.42 | C | T | 0.84 | 4.7E-05 | 1.04 | 1.3E-01 | 0.98 | 2.9E-01 |
| rs11672613 | C3 | 19 | 6705246 | 1 | 0.42 | T | C | 0.83 | 1.1E-05 | 0.96 | 1.5E-01 | 0.92 | 2.4E-04 |
| rs6468749 | YWHAZ | 8 | 102008828 | 1 | 0.37 | T | C | 1.21 | 1.0E-05 | 1.04 | 1.5E-01 | 1.09 | 2.2E-04 |
| rs12577139 | BARX2 | 11 | 129301284 | 2 | 0.15 | C | T | 0.84 | 2.1E-03 | 1.06 | 1.5E-01 | 0.98 | 5.7E-01 |
| rs7119879 | BARX2 | 11 | 129305687 | 2 | 0.16 | G | A | 0.84 | 1.6E-03 | 1.05 | 1.9E-01 | 0.98 | 4.8E-01 |
| rs1991007 | 5 | 55968018 | 1 | 0.08 | C | A | 1.38 | 2.5E-05 | 1.05 | 3.2E-01 | 1.15 | 1.3E-03 | |
| rs12570170 | HK1 | 10 | 70801833 | 1 | 0.37 | G | A | 1.19 | 5.3E-05 | 1.03 | 3.5E-01 | 1.08 | 2.1E-03 |
| rs2886189 | ZBTB16 | 11 | 113501655 | 1 | 0.30 | T | C | 0.83 | 4.3E-05 | 0.97 | 3.8E-01 | 0.93 | 2.4E-03 |
| rs9820110 | 3 | 70469958 | 1 | 0.29 | G | T | 1.24 | 2.6E-06 | 1.03 | 3.8E-01 | 1.09 | 7.1E-04 | |
| rs17801001 | EPHA3 | 3 | 89414555 | 1 | 0.12 | A | C | 1.32 | 7.7E-06 | 1.03 | 4.4E-01 | 1.11 | 1.7E-03 |
| rs11209216 | LOC100133029,GPR177 | 1 | 68571431 | 1 | 0.44 | C | T | 1.18 | 5.5E-05 | 1.02 | 4.9E-01 | 1.07 | 4.6E-03 |
| rs6795074 | EPHA3 | 3 | 89516652 | 1 | 0.10 | T | C | 1.38 | 3.3E-06 | 1.03 | 5.1E-01 | 1.13 | 1.7E-03 |
| rs9538032 | 13 | 58985847 | 1 | 0.25 | T | C | 1.21 | 5.5E-05 | 0.98 | 5.1E-01 | 1.05 | 8.2E-02 | |
| rs3181088 | VCAM1 | 1 | 101198708 | 2 | 0.11 | C | T | 1.28 | 2.6E-04 | 1.03 | 5.8E-01 | 1.10 | 1.2E-02 |
| rs6800118 | MIRN138-1, hsa-mir-138-1 | 3 | 44141157 | 2 | 0.28 | A | G | 0.84 | 1.2E-04 | 1.02 | 6.2E-01 | 0.96 | 8.0E-02 |
| rs7702277 | 5 | 14020756 | 1 | 0.12 | G | T | 1.39 | 8.0E-08 | 0.98 | 6.6E-01 | 1.10 | 6.5E-03 | |
| rs1296284 | 5 | 55934938 | 1 | 0.33 | G | A | 1.21 | 2.9E-05 | 1.01 | 7.0E-01 | 1.07 | 7.9E-03 | |
| rs2802402 | ITM2B | 13 | 47685360 | 1 | 0.16 | C | T | 0.77 | 2.9E-06 | 0.99 | 8.1E-01 | 0.91 | 4.4E-03 |
| rs695207 | MIR3134, ROD1 | 9 | 114056169 | 1 | 0.27 | T | G | 1.2 | 7.3E-05 | 0.99 | 8.2E-01 | 1.06 | 3.5E-02 |
| rs189897 | ITGA9 | 3 | 37518545 | 2 | 0.04 | A | T | N/A | N/A | 1.02 | 8.3E-01 | 1.02 | 8.3E-01 |
| rs2158250 | ITGB8 | 7 | 20425446 | 2 | 0.41 | A | G | 0.86 | 4.8E-04 | 1.00 | 8.7E-01 | 0.95 | 3.7E-02 |
| rs1286041 | 6 | 6839192 | 1 | 0.17 | A | G | 1.26 | 3.1E-05 | 1.01 | 8.9E-01 | 1.08 | 1.4E-02 | |
| rs4714505 | LOC100130606,TFEB | 6 | 41648147 | 1 | 0.11 | C | T | 0.71 | 1.7E-07 | 1.00 | 9.3E-01 | 0.90 | 4.3E-03 |
| rs7014115 | ASPH | 8 | 62649567 | 1 | 0.12 | T | G | 1.33 | 6.1E-06 | 1.00 | 9.5E-01 | 1.09 | 1.3E-02 |
| rs4936612 | 11 | 121203120 | 1 | 0.40 | A | G | 0.85 | 6.3E-05 | 1.00 | 9.5E-01 | 0.95 | 2.7E-02 | |
| rs11637457 | AGBL1 | 15 | 87572506 | 1 | 0.16 | C | T | 0.8 | 7.7E-05 | 1.00 | 9.5E-01 | 0.93 | 3.1E-02 |
| rs1324103**** | 6 | 93901016 | 1 | 0.42 | A | G | 0.84 | 1.4E-05 | 1.00 | 9.6E-01 | 0.94 | 1.2E-02 | |
| rs9924017 | HS3ST4 | 16 | 25849321 | 1 | 0.36 | A | G | 1.19 | 4.7E-05 | 1.00 | 9.7E-01 | 1.06 | 2.2E-02 |
Based on hg19.
1 = Selected based on GWAS meta-analysis results; 2 = Selected as an additional candidate based on a-priori literature.
Based on frequency observed among controls in the replication study.
Replaced rs6931820 w/ p-value = 3.47E-06 in GWAS Meta
In analyses that combined the GWAS and replication studies, findings for rs31489 were strengthened (OR across GWA+replication studies = 0.81; p-value = 6.3*10−13) (Table 2). Some evidence for heterogeneity across studies was observed (p-heterogeneity = 0.035). Additional associations (p ≤ 1*10−7) were observed in our combined GWA plus replication studies meta-analysis for rs6774494 (p = 1.5*10−12; MECOM gene region), rs9510787 (p = 5.0*10−10; TNFRSF19 gene region), rs1412829, rs4977756, and rs1063192 (p = 2.8*10−8, p = 7.0*10−7, and p = 8.4*10−7 respectively; CDKN2A/2B gene region) (Table 2; Supplemental Figure 1S).
Discussion
We report herein results from a meta-analysis of NPC GWAS followed by replication studies across three regions in Asia. A novel association was observed within the CLPTM1L/TERT locus. This finding is of note given that SNPs in this region were reported from GWAS conducted for numerous other cancers, including lung, bladder, pancreas, testis and central nervous system [10]. A recent meta-analysis of 85 studies including over 490,000 subjects that evaluated 67 TERT/CLPTM1L locus polymorphisms and 24 tumor types identified 11 SNPs with strong cumulative evidence for an association with at least one cancer type. rs31489 was one of these SNPs and was found to have strong cumulative evidence for association with testicular cancer among Caucasians and moderate cumulative evidence for association with Asian lung cancer [10]. Furthermore, a review of the literature identified candidate gene studies (two that evaluated SNPs and a third that evaluated a microsatellite marker) that reported an association between polymorphisms within the CLPTM1L/TERT locus and NPC [11-13]. Two of the three SNPs evaluated in these studies are in LD with rs31489 (rs401681 r2 = 0.427 in 1kG ASN and 0.512 in 1kG CHB; rs402710 r2 = 0.433 in 1kG ASN and 0.569 in 1kG CHB). The third SNP is not in LD with rs31489, suggesting the possibility for the existence of greater than one independent susceptibility variant within the CLPTM1L/TERT locus (rs2736098 r2 = 0.016 in 1kG ASN and 0.049 in 1kG CHB). Our findings in the CLPTM1L/TERT locus gain added significance given the role of TERT in telomere length regulation [14], the finding that telomerase overexpression is observed in NPC [15], and that the EBV proteins LMP1, a protein frequently expressed in NPC, activates TERT expression and enhances telomerase activity [16,17]. We did observe evidence for possible heterogeneity in effect observed for rs31489 across study populations (p-heterogeneity = 0.035). The evidence for heterogeneity was of marginal statistical significance and was driven primarily by the two Malaysian studies included in our effort. It is unclear at this time whether our findings reflect true heterogeneity, differential misclassification of ethnicity in the Malaysian studies, or a chance finding. This observation deserves further consideration in future studies.
Additional associations (p ≤ 1*10−7) were observed in our combined GWA plus replication studies meta-analysis for rs6774494 (p = 1.5*10−12; MECOM gene region), rs9510787 (p = 5.0*10−10; TNFRSF19 gene region), rs1412829, rs4977756, and rs1063192 (p = 2.8*10−8, p = 7.0*10−7, and p = 8.4*10−7 respectively; CDKN2A/2B gene region) (Table 2; Supplemental Figure 1S). These associations were previously reported from the Mainland China NPC GWAS and their potential biological implications discussed [6]; our data provide support for these associations.
Strengths of our study include the fact that it evaluated associations with NPC across multiple GWAS and the large size of its replication effort. Limitations include the inability to further investigate potential heterogeneity of effects by exposure status or geographic/ethnic groups. Future studies should explore the associations reported herein in additional populations with differing ethnic makeup.
In conclusion, our GWAS meta-analysis and replication effort has identified an additional susceptibility locus for NPC within the CLPTM1L/TERT region of chromosome 5p15.33 and provides support for several previously reported NPC susceptibility loci.
Supplementary Material
Acknowledgements
We would like to recognize the full membership of the International NPC Genetics Working Group who contributed to this publication. They include:
Jin-Xin Bei (State Key Laboratory of Oncology in Southern China, Sun Yat-sen University Cancer Center, Guangzhou, China)
Kai-Ping Chang (Department of Otolaryngology, Chang Gung Memorial Hospital at Lin-Kou, Taoyuan, Taiwan)
Yu-Sun Chang (Chang Gung Molecular Medicine Research Center and Graduate Institute of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan)
Chien-Jen Chen (Graduate Institute of Epidemiology, College of Public Health, National Taiwan University and Genomics Research Center, Academia Sinica, Taipei, Taiwan)
Yoon-Ming Chin (Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia)
Charles Chung (Center for Genomics Research, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA)
Allan Hildesheim (Infections and Immunoepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA)
Wan-Lun Hsu (Graduate Institute of Epidemiology, College of Public Health, National Taiwan University and Genomics Research Center, Academia Sinica, Taipei, Taiwan)
Alan Soo-Beng Khoo (Molecular Pathology Unit, Cancer Research Centre, Institute for Medical Research, Kuala Lumpur, Malaysia)
Jian-Jun Liu (Genome Institute of Singapore, Singapore)
Pei-Jen Lou (Department of Otolaryngology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan)
James McKay (Genetic Epidemiology Unity, International Agency for Research on Cancer, Lyon, France)
Ching-Ching Ng (Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia)
Kin-Choo Pua (Department of Otorhinolaryngology, Hospital Pulau Pinang, Penang, Malaysia)
Lee-Chu See (Department of Biostatistics and Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan)
Wen-Hui Su (Department of Biomedical Sciences, Graduate Institute of Biomedical Sciences, College of Medicine and Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan)
Soo-Hwang Teo (Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, Selangor, Malaysia)
Ngan-Ming Tsang (Department of Radiation Oncology, Chang Gung Memorial Hospital at Lin-Kou, Taoyuan, Taiwan)
Ka-Po Tse (Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan)
Meredith Yeager (Center for Genomics Research, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA)
Chia-Jung Yu (Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan)
Kai Yu (Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA)
Yi-Xin Zeng (State Key Laboratory of Oncology in Southern China, Sun Yat-sen University Cancer Center, Guangzhou, China and Peking Union Medical College, Beijing, China)
The mainland China NPC Study Group: Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center – M.Y. Chen, H.Q. Mai, Y.F. Xia, X. Guo, H.Y. Mo, M.Y. Chen, C.N. Qian; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center – W.H. Jia, Y.X. Zeng, Q.S. Feng, L.Z. Chen, X.H. Zheng, Y. Zhang, Q. Cui, Y.M. Guo, F.T. Feng, W.S. Liu, J.X. Bei, J. Li; Department of Genomics & Proteomics, Beijing Institute of Radiation Medicine – G.Q. Zhou, F. He, H. Zhang; Beijing Proteome Research Center – G.Q. Zhou, F. He, H. Zhang; Department of Otorhinolaryngology and Head Surgery, First Affiliated Hospital of Guangxi Medical University – G.W. Huang, Z. Zhang; Department of Cancer Prevention Research, Cancer Prevention Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in Southern China – S.M. Cao; Clinical Trail Study Center, Sun Yat-sen University Cancer Center – M.H. Hong.
The Malaysia NPC Study Group: Hospital Pulau Pinang: K.C. Pua -Project Leader, S. Subathra, N. Punithavati, B.S. Tan, Y.S. Ee, L.M. Ong, R.A. Hamid, M. Goh, J.C.T. Quah, J. Lim; Hospital Kuala Lumpur/Universiti Putra Malaysia: Y.Y. Yap, B.D. Dipak, R. Deepak, F.N. Lau, P.V. Kam, S. Shri Devi; Queen Elizabeth Hospital: C.A. Ong, C.L. Lum, Ahmad N.A., Halimuddin S., M. Somasundran, A. Kam, M. Wodjin; Sarawak General Hospital/ Universiti Malaysia Sarawak: S.K. Subramaniam, T.S. Tiong, T.Y. Tan, U.H. Sim, T.W. Tharumalingam, D. Norlida, M. Zulkarnaen, W.H. Lai; University of Malaya: G. Gopala Krishnan, C.C. Ng, A.Z. Bustam, S. Marniza, P. Shahfinaz, O. Hashim, S. Shamshinder, N. Prepageran, L.M. Looi, O. Rahmat, J. Amin, J. Maznan, L.Y. Yap; Hospital Universiti Sains Malaysia: S. Hassan, B. Biswal; Cancer Research Initiatives Foundation: S.H. Teo; Institute for Medical Research: A.S.B. Khoo - Program Leader, A. Munirah, A. Subasri, L.P. Tan, N.M. Kumaran, M.S. Nurul Ashikin, M.S. Nursyazwani, B. Norhasimah, R. Sasela Devi, S. Shri Devi, C.Y. Koh
Funding Sources: This project was supported by the National High Technology Research and Development Program of China (863) (2012AA02A501, 2012AA02A206) (J. Bei & Y. Zheng), the Major State Basic Research Development Program of China (973) (2011CB504302) (J. Bei & Y. Zheng), the National Natural Science Foundation of China (81222035, 81101544) (J. Bei & Y. Zheng), the Pearl River Nova Program and the Agency for Science, Technology and Research of Singapore (J. Bei and J. Liu), the Ministry of Education of Taiwan, the Malaysian Ministry of Higher Education-High Impact Research (H-50001-A000023) (C. Ng and Y. Chin), and by the Intramural Research Program of the U.S. National Cancer Institute (A. Hildesheim and K. Yu).
Abbreviations List
- CDKN2A/B gene region
Cyclin-Dependent Kinase Inhibitor 2A/B
- CLPTM1L/TERT locus
Cleft Lip and Palate Transmembrane Protein 1 Telomerase reverse transcriptase locus
- EBV
Epstein-Barr virus
- GWAS
genome-wide association study
- HLA
human leukocyte antigen
- LD
linkage disequilibrium
- LMP1
latent membrane protein 1
- MAF
Minor allele frequency
- MECOM
MDS1 and EVI1 complex locus
- NPC
nasopharyngeal carcinoma
- SNPs
Single Nucleotide Polymorphism
- TNFRSF19
Tumor Necrosis Factor Receptor Superfamily, Member 19
Footnotes
Conflict of Interest Statement: The authors have no conflicts of interest to report.
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