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Cancer

Genetic Polymorphisms in DNA Repair Genes XRCC4 and XRCC5 and Aflatoxin B1–related Hepatocellular Carcinoma

Long, Xi-Daia,b; Zhao, Donga; Wang, Chaob; Huang, Xiao-Yingb; Yao, Jin-Guangb; Ma, Yunc; Wei, Zhong-Huad; Liu, Mind; Zeng, Li-Xiaoc; Mo, Xiao-Qiangb; Zhang, Jian-Juna; Xue, Fenga; Zhai, Boa; Xia, Qianga

Author Information
doi: 10.1097/EDE.0b013e31829d2744

Abstract

Hepatocellular carcinoma (HCC) is highly malignant disease with an extremely poor prognosis. It is the most common cancer type in Guangxi Zhuang Autonomous Region, China, with an incidence rate of 53/10,000 per year and a death rate of 37–55/10,000 annually.1 Clinical epidemiologic evidence suggests aflatoxin B1 (AFB1) exposure is a major risk factor2 for liver cancer in Guangxi Region. AFB1, an important I-type chemical carcinogen, can induce various types of DNA damage, such as DNA double-strand breaks, DNA base damage, and oxidative damage.2–4 Among these DNA damage types, double-strand breaks are the most detrimental form because they may lead to both chromosomal breakage and rearrangement and ultimately lead to tumorigenesis.5–8

DNA repair genes “x-ray repair complementing group 4” (XRCC4) and “x-ray repair complementing group 5” (XRCC5) are necessary for DNA ligation in the nonhomologous end-joining pathway, which is responsible for repairing most double-strand breaks.6,9–12 Recently, several studies have shown that polymorphisms in these two genes, including XRCC4 codon 247 Ala>Ser (rs3734091, XRCC4P) and XRCC5 codon 180 Asp>Glu (rs80309960, XRCC5P), may be associated with DNA repair capacity and tumor risk.12–14 However, the association between them and HCC has not yet been elucidated. Here, we evaluated whether XRCC4P and XRCC5P modify AFB1-related liver cancer risk and prognosis.

METHODS

Subjects

We conducted a hospital-based case-control study that has been previously described.12,15,16 Briefly, cases were patients diagnosed with histopathologically confirmed HCC in the Affiliated Hospitals of the two main medical colleges in the Southwestern Guangxi, namely Guangxi Medical University and Youjiang Medical College for Nationalities, from January 2004 to December 2010. Both case and control recruitment is still ongoing. Controls without clinic evidence of hepatic diseases or tumors were randomly selected from a pool of healthy volunteers who visited the general health check up center of the same hospitals for routine scheduled physical exams. Controls were individually matched to cases on sex, ethnicity (Han, Minority), age (±5 years), and hepatitis B virus (HBV) and hepatitis C virus (HCV) infection. After giving written consent, participants provided demographic information (including age, race, medical history for themselves and their families, food consumption history, and migration history) using a standard interviewer-administered questionnaire. Clinical pathological data, including cirrhosis, tumor size, portal vein tumor (PVT), tumor stage, and medical treatment information, were obtained through the patients’ medical records.

A total of 1536 cases and 2074 controls, representing 95% of eligible cases and 98% of eligible controls, were enrolled and interviewed. At the same time, 4 mL of peripheral blood was obtained for DNA extraction. Surgically removed tumor samples of all cases were collected for immunohistochemistry and TP53M assay. Additionally, we collected 75 fresh cancer tissue specimens in which to assess levels of XRCC4 mRNA expression. Thirty-seven cases and 25 controls were excluded from the study because of low yield or poor quality of DNA samples, or lack of information on viral infection status, leaving 1499 cancer patients (including 1156 patients previously studied)15 and 2045 controls (including 1402 subjects previously studied)15 for final analysis. Those who were hepatitis B surface antigen (HBsAg)-positive and anti-HCV–positive were defined as infected with HBV and HCV. Liver cirrhosis was diagnosed by pathological examination, and tumor stages were confirmed according to the tumor nodes metastasis staging system. The protocol was approved by the Ethic Committees of the hospitals involved in this study.

AFB1 Exposure Data

AFB1 exposure, including exposure levels and length of exposure, was evaluated according to previously published methods.16,17 Briefly, exposure levels were ascertained by AFB1-DNA adduct levels in DNA samples from peripheral blood leukocytes. AFB1-DNA adduct levels were tested using a comparative enzyme-linked immunosorbent assay. For statistical analysis, aflatoxin exposure levels were divided into three groups according to the mean levels of AFB1-DNA adducts in cases and controls: low (≤1.00 μmol/mol DNA), medium (1.01–2.00 μmol/mol DNA), and high (≥2.01 μmol/mol DNA). In Guangxi, because food consumption is relatively simple and AFB1 mainly contaminates poorly stored food (especially corn and peanuts), the years in which participants ate food contaminated by aflatoxin were defined as aflatoxin-exposure years. Aflatoxin-exposure years were divided into three strata: short (<40 years), medium (40–48 years), and long (>48 years), according to the mean value of aflatoxin-exposure years among controls and cases.

Genotyping

Laboratory personnel were blinded to case and control status. Genomic DNA was isolated from peripheral blood leukocytes using standard phenol–chloroform extraction method for genotypic analyses of XRCC4 and XRCC5. Genotypes were analyzed using the TaqMan-PCR on iCycler iQ real-time PCR detection system (iQ5, Bio-Rad Laboratories Inc., Hercules, CA). Primer and probe sets and annealing temperatures used for TaqMan-PCR assay are shown in Supplemental Table S1 (http://links.lww.com/EDE/A691). Each PCR was carried out in a total volume of 25 μL consisting of 1 × Premix Ex Taq (catalog#DRR039A, TaKaRa Biotechnology [Dalian] Co., Ltd., Dalian, China), 0.2 μM of each probe, 0.2 μM of each primer, and 50–100 ng of genomic DNA. The PCR program had an initial denaturation step of 2 min at 95°C followed by 50 cycles of 10 sec at 95°C and 1 min at 60°C. For quality control, controls were included in each run, and repeated genotyping and sequencing of a random 10% subset yielded 100% identical genotypes.

The Hot-spot Mutation Analysis of TP53 Gene

Genomic DNA was isolated from cancer tissues using FFPE DNA Kit (catalog#CW0547) by Cowin Biotech Co., Ltd (Beijing, China) for the hot-spot mutation analysis of TP53 gene (at codon 249, TP53M). TP53M was tested by using the aforementioned TaqMan-PCR technique. The primers and probes sets used for TaqMan-PCR assay are shown in Supplemental Table S1 (http://links.lww.com/EDE/A691).

XRCC4 mRNA Expression Analysis

Total RNA was extracted from malignant tissues using E.Z.M.A. MicroElute Total RNA Kit with DNase I (catalog#R6831-02, Omega Bio-tek, Inc., Norcross, GA), and corresponding first-strand cDNA was synthesized using RevertAid First Strand cDNA Synthesis Kit (catalog#K1622, Fermentas Inc., Glen Burnie, MD). The relative quantitation of XRCC4 mRNA expressing levels using the comparative computed tomography method (2-ΔΔCt method)18 was carried out by above described TaqMan-PCR (with an internal control ubiquitin C mRNA).19 PCR primers and probes were shown in Supplemental Table S1 (http://links.lww.com/EDE/A691). Data analysis for the relative level of XRCC4 mRNA expression was performed with the iQ Optical System software Version 2.0 (Bio-Rad).

XRCC4 Protein Expression Assay

The expression levels of XRCC4 protein were analyzed by immunohistochemistry in tissue slides, as previously described.15 The corresponding anti-XRCC4 polyclonal antibody (dilution 1:500, catalog#sc-8285) and HRP-conjugated secondary antibody (catalog#KIT-9705) were obtained from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA), and Maixin Biotechnology, Inc., respectively. In this study, XRCC4 protein expressing levels were divided into three classifications: low (the immunoreactive score, <3), medium (3–6), and high (>6).12,20

HCC Patients Follow-up

Patients were followed and underwent serial monitoring of α-fetoprotein (AFP), ultrasonography, chest radiograph, and emission computed tomography every 2 months for the first 2 years and semiannually thereafter for detection of recurrence. Recurrence was confirmed by imaging techniques, either intrahepatically or extrahepatically (lymph nodes, distant metastases). An increase of AFP without radiologic evidence of a new tumor was not regarded as recurrence until confirmed by imaging. The last follow-up day was set on 31 August 2011, and the survival status was confirmed by means of clinic records and patient or family contact. We defined the duration of overall survival as from the date of curative treatment to the date of death or last known date alive. The duration of recurrence-free survival was defined as the date of curative treatment to the date of tumor recurrence or last known date alive.12

Statistical Methods

To assess differences between groups, demographic characteristics, AFB1 exposure information, and XRCC4P and XRCC5P genotypes were compared using Student t test and the χ2 test. Because of the individually matched design, we did conditional logistic regression (with multivariate factors including known causes of hepatocellular among the Guangxi population) to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for risk of liver cancer.

The Spearman r test was used to analyze the correlation between XRCC4 genotypes and XRCC4 protein expression. Kaplan–Meier survival analysis with the log-rank test was used to evaluate the relationship between XRCC4P and HCC prognosis. Risk factors for liver cancer prognosis were firstly selected using Cox multivariate regression model (including all possible multiplicatively interactive variables) with stepwise forward selection based on likelihood ratio test. Hazard ratios (HRs) and 95% CIs for risk factors were then calculated from multivariate Cox regression model. All statistical analyses were done using the statistical package for social science version 18 (SPSS Institute, Chicago, IL).

RESULTS

Our final analysis included 1499 liver cancer cases and 2045 controls (Table 1). There were no differences between cases and controls in terms of the distribution of age, sex, race, and HBV and HCV status because these were individually matched.

TABLE 1
TABLE 1:
Demographic and Etiologic Characteristics of HCC Cases and Controls

Table 2 summarizes information on aflatoxin exposure for the entire study population. Aflatoxin-exposure years were associated with an increased risk for liver cancer (OR = 2.56 for medium-exposure years and OR = 5.95 for long-exposure years). Cases had higher levels of AFB1-DNA adducts than controls (1.98 ± 0.03 compared with 1.03 ± 0.01 μmol/mol DNA). To investigate whether the levels of DNA adducts reflect aflatoxin exposure levels, we analyzed the association between AFB1-DNA adduct levels in peripheral blood leukocytes’ and another important AFB1 exposure biomarker AFB1-albumin adducts in serum21 among 129 cases. AFB1-DNA adduct levels were positively related to AFB1-albumin adduct levels (data not shown). Furthermore, to investigate the episodic nature of aflatoxin exposure, we collected peripheral blood samples from 91 controls at various times (spring, summer, autumn, and winter) and analyzed the kinetics of adduct levels (Supplementary Figure 1, http://links.lww.com/EDE/A691). A relative higher level of aflatoxin-DNA adduct levels was found in summer than in winter (Supplementary Figure 1, http://links.lww.com/EDE/A691). For the estimate of cumulative risk value of aflatoxin exposure, the season of sample collection was treated as an ordinal variable (winter coded as 0, spring as 1, autumn as 2, and summer as 3) and incorporated into multivariable logistic regression. Liver cancer risk gradually increased with exposure level (adjusted OR = 2.03–6.43, Table 2).

TABLE 2
TABLE 2:
AFB1 Exposure and the Risk of HCC

XRCC4 and XRCC5 genotypes from peripheral blood DNA samples are listed in Table 3. The genotype distributions of XRCC4 codon 247 and XRCC5 codon 180 polymorphisms in controls were consistent with Hardy–Weinberg equilibrium. Logistic regression analysis showed that only XRCC4P modified liver cancer risk. The adjusted OR for HCC among those heterozygous for XRCC4 codon 247 Ala and Ser allele (XRCC4-AS) versus those homozygous for XRCC4 codon 247 Ala alleles (XRCC4-AA) was 1.35 (95% CI = 1.08–1.70). The corresponding OR for those homozygous for XRCC4 codon Ser alleles (XRCC4-SS) was 2.02 (95% CI = 1.44–2.83). Thus, liver cancer risk was associated with the number of XRCC4 codon 247 Ser alleles.

TABLE 3
TABLE 3:
Polymorphisms of XRCC4, XRCC5, and Ligase IV and Risk of HCC

To assess possible interactive effects of matching factors and XRCC4P on liver cancer risk, we analyzed this polymorphism stratified by matching factors such as HBV and HCV infection, age, race, and sex. These factors did not substantially modulate the effect of this polymorphism on cancer risk (Supplemental Table S2, http://links.lww.com/EDE/A691).

The joint effects of aflatoxin-exposure years and XRCC4 genotypes on liver cancer risk are provided in Table 4 and Supplemental Table S3 (http://links.lww.com/EDE/A691). More years of aflatoxin exposure consistently increased liver cancer risk; moreover, this risk was more pronounced among subjects with XRCC4 risk genotypes. There was evidence of multiplicatively interactive effects of genotypes and exposure years on liver cancer risk (30.06 > [5.41 × 1.92]) according to the previously published formula (OReg > [OReg’ × ORe’g]).22 A similar increased-risk trend was also observed in the joint effects analysis of this polymorphism and aflatoxin exposure levels for liver cancer risk (14.43 > [6.12 × 1.55], Table 2 and Supplemental Table S3, http://links.lww.com/EDE/A691).

TABLE 4
TABLE 4:
Joint Effects of AFB1 Exposure and XRCC4P on HCC Risk

To investigate the potential effects of XRCC4P on XRCC4 expression, we analyzed the association between this polymorphism and XRCC4 protein using immunohistochemistry in the cancer tissues of 1499 HCC cases. Genotypes with XRCC4 codon 247 Ser alleles significantly downregulated XRCC4 expression in hepatocellular tumor tissues compared with XRCC4-AA (Figure 1A). Furthermore, XRCC4P was negatively related to the levels of XRCC4 protein (r = −0.314, Supplemental Table S4, http://links.lww.com/EDE/A691). Representative photographs show the correlation between genotype and expression levels (Figure 1B). mRNA levels of XRCC4 in malignant tissues with XRCC4-AS or -SS were substantially lower than those with XRCC4-AA (Figure 1C). Together, these results suggest this polymorphism downregulates XRCC4 expression.

FIGURE 1
FIGURE 1:
XRCC4 codon 247 polymorphism (XRCC4P) downregulates XRCC4 expression and modifies the DNA repair capacity. A, XRCC4 protein expression was evaluated using the immunohistochemical scores of immunoreactive score (IRS) system.18 XRCC4 expression scores are shown as box plots, with the vertical bars representing the range of data. B, Representative images showing that XRCC4 expression levels in tumor cells varied by XRCC4 genotypes. C, Quantitative XRCC4 mRNA levels in tumor tissues from 75 subjects. Data are shown as means ± S.E. of three independent experiments. D, Association between XRCC4P and aflatoxin-DNA adduct levels (means ± S.E). E, The percent of TP53M-positive tumors in three groups with different genotypes of XRCC4 (1499 subjects).

To investigate whether XRCC4P affects DNA repair capacity, we explored the correlation between this polymorphism and AFB1-DNA adduct levels (Figure 1D). We found that persons with risk genotypes had higher levels of AFB1-DNA adducts (1.74 ± 0.07 μmol/mol DNA for XRCC4-SS; 1.56 ± 0.05 μmol/mol DNA for XRCC4-AS) compared with those with XRCC4-AA (1.39 ± 0.02 μmol/mol DNA, Figure 1D). Because TP53M is the most important molecular signature of AFB1-induced HCC,23 we investigated whether XRCC4P modified this mutation in the 1499 cancer cases. Genotypes of XRCC4 increased the frequency of TP53M (Figure 1E); the corresponding risk values were 2.64 and 5.29 for XRCC4-AS and XRCC4-SS, respectively (Table 5). Taken together, these findings suggest XRCC4P correlates with DNA repair capacity for the repair of DNA damage caused by aflatoxin.

TABLE 5
TABLE 5:
XRCC4P and TP53M Risk

In order to assess the clinical relevance of XRCC4P, we analyzed the survival follow-up information of all liver cancer patients. Among these subjects, 1092 received the same curative treatment. Association analysis between risk genotypes (namely genotypes with XRCC4 codon 247 Ser alleles [XRCC4-AS/SS]) or nonrisk genotype (XRCC4-AA) and the pathologic characteristics of HCC were first performed separately (Supplemental Table S5, http://links.lww.com/EDE/A691). We observed substantial differences in the distribution of genotypes among various aflatoxin exposure levels, tumor size, and recurrence status, but not among strata of aflatoxin-exposure years, sex, minority status, HBsAg, cirrhosis, or tumor stage (Supplemental Table S5, http://links.lww.com/EDE/A691). Survival analysis showed liver cancer cases who carried XRCC4-SS (compared with those with XRCC4-AA) had shorter recurrence-free survival (median recurrence-free survival time was 12 months vs. 39 months, Figure 2A) and higher recurring risk (adjusted HR = 5.05, Supplemental Table S6, http://links.lww.com/EDE/A691), particularly under conditions of high aflatoxin exposure (Figure 2B and C). Additionally, this polymorphism was related to the overall survival of liver cancer cases (Figure 3), with some evidence of multiplicative interaction for XRCC4-SS and long AFB1 exposure years (Pinteraction = 0.035; Supplemental Table S7, http://links.lww.com/EDE/A691).

FIGURE 2
FIGURE 2:
XRCC4P correlated with recurrence-free survival of liver cancer related to aflatoxin exposure. A, The association between recurrence-free survival and XRCC4P in liver cancer cases receiving curative treatment (n = 1,092). B, Recurrence-free survival and XRCC4P in strata of aflatoxin-exposure years. C, Recurrence-free survival and XRCC4P within strata of aflatoxin exposure. MRT indicates median recurrence-free survival time.
FIGURE 3
FIGURE 3:
XRCC4P correlated with overall survival related to aflatoxin exposure. A, The association between overall survival and XRCC4P in cases receiving curative treatment (n = 1,092). B, Recurrence-free survival and XRCC4P within strata of aflatoxin-exposure years. C, The association between overall survival and XRCC4P within strata of aflatoxin. MST indicates median survival time.

A recent report showed that the dysregulation of XRCC4 is related to tumor metastasis.24 We therefore investigated whether XRCC4P influenced risk of PVTs, the most common metastasic type of liver cancer,25,26 by assessing 1092 HCC cases during follow-up after curative treatment (Table 6). Carriers of XRCC4 codon 247 Ser alleles had substantially higher risk of PVTs (OR = 2.08 for XRCC4-AS; 6.67 for XRCC4-SS).

TABLE 6
TABLE 6:
XRCC4P and PVT Risk

DISCUSSION

AFB1 is an important toxic metabolite produced by fungi of the Aspergillus spp. that grows readily on such foodstuffs as corn and groundnuts stored in damp conditions.3 Once ingested, this toxin is metabolized mainly by cytochrome P450 into the genotoxic metabolic AFB1-exo-8,9-epoxide (AFB1-epoxide). AFB1-epoxide is able to bind to DNA, causes the formation of AFB1-DNA adducts, and induces hepatocellular cancer.3,21 In our study, AFB1 exposure status was associated with liver cancer. However, only a relatively small proportion of those with chronic AFB1 exposure develop liver cancer.27–30 This suggests possible individual susceptibility related to genetic factors such as DNA repair capacity.

The nonhomologous end-joining genes (NHEJ) are a cancer-correlated genetic factor that plays an important role in the repair of double-strand breaks resulting from exogenous attacks such as AFB1.31–33 XRCC4 and XRCC5 are two important DNA repair genes involved in the NHEJ pathway. The encoded protein of XRCC4 consists of 336 amino acid residues and interacts directly with Ku70/Ku80.34 In the repair of double-strand breaks by NHEJ, this encoded protein serves as a flexible join between Ku70/Ku80 and its associated protein ligase IV.34 XRCC4 is required for precise end-joining of blunt double-stranded breaks in mammalian cells, and the mutant XRCC4 reduces NHEJ capacity.35–37 XRCC5 encoding protein is the 80-kDa subunit (Ku80) of Ku70/Ku80 heterodimer complex, the DNA-binding component of the DNA-dependent protein kinase.6 This complex can bind to the DNA ends at a double-stranded break and then recruit and activate the DNA-dependent protein kinase.11 XRCC5 knockout mice are growth retarded, radiosensitive, and severely immunodeficient, suggesting that XRCC5 plays an important role in NHEJ and in the maintenance of genomic stability.38 Therefore, XRCC4 and XRCC5 are essential for DNA repair capacity of NHEJ, and deficiencies in their function might result in tumors.11,13

More than one hundred polymorphisms have been reported in XRCC4 and XRCC5, some of which are correlated with malignant tumors such as myeloma, oral cancer, gastric cancer, and bladder cancer.12–14,39 We investigated only two polymorphisms, namely XRCC4P and XRCC5P, because these two polymorphisms localize at conserved sites of these two genes and change the amino acids coded. This suggests that they may be associated with decreased DNA repair capacity and increased cancer risk.14 We found that XRCC4P was not only associates with liver cancer but also modified aflatoxin’s association with liver cancer. Tseng et al14 investigated the effects of XRCC4P on oral cancer in Taiwan (another Chinese population) and found that persons carrying XRCC4-AS had higher cancer risk than those with XRCC4-AA (adjusted OR = 2.04, P = 0.023). They also observed some evidence of gene–environment interaction on cancer risk. These data suggest this polymorphism may be an important genetic susceptibility factor in cancer risk.

With regard to XRCC5P, there were no associations between this polymorphism and disease susceptibility in the Public Library of Medicine PubMed database as of September 2012. This may be related to a low frequency of XRCC5 codon 180 Glu alleles. In our study, the Glu allele was observed in about 4.5% of the Guangxi population; however, XRCC5P did not modify liver cancer risk. These results need to be confirmed in other populations.

To further explore possible biological pathways by which XRCC4P might increase aflatoxin-related liver cancer risk, we analyzed the effects of this polymorphism on XRCC4 expression and DNA repair function. We found XRCC4 codon 247 Ser alleles downregulated the levels of XRCC4 expression, including protein and mRNA expression. Regarding the association of between XRCC4P and DNA repair capacity, we explored this association using the levels of AFB1-DNA adduct and the frequency of TP53M. This was done primarily because DNA adducts are a major type of DNA damage induced by aflatoxin exposure, and adduct levels are related not only to aflatoxin exposure but also to DNA repair capacity,3,40 whereas TP53M is the characteristic genetic change correlated with aflatoxin exposure.23,40 This suggests that AFB1-DNA adduct and TP53M could be regarded as biomarkers of DNA repair function related to aflatoxin exposure. Our results showed XRCC4P increased the level of aflatoxin-DNA adducts and the frequency of TP53M. Together, these findings suggest that this polymorphism may decrease DNA repair capacity through modulating XRCC4 expression levels and function. The DNA damage induced by aflatoxin cannot be repaired effectively, with higher adduct levels leading to induction of mutations such as in the p53 gene and higher risk of hepatocellular carcinogenesis. Therefore, XRCC4P may play an important role in the production of liver cancer by aflatoxin.

Another interesting finding is that XRCC4P was associated with poor prognosis, possibly because this polymorphism increased the risk of metastasis to the portal vein. Supporting our results, recent studies have shown that dysfunction of XRCC4 relates to tumor metastasis.24

When investigating the association between genetic polymorphisms and aflatoxin-related liver cancer, it is important to collect sufficiently large samples to test for gene–environment interaction, to avoid the effects of confounders, and to evaluate aflatoxin exposure information.22 In the present study, the effects of possible confounder, including age, sex, race, and HBV and HCV infection status, were controlled with an individually matched design. In the stratified analysis, no interactive effects were found, suggesting that these factors do not modify the correlation between XRCC4P and liver cancer related to aflatoxin exposure.

We evaluated aflatoxin exposure levels from aflatoxin-DNA adduct levels in DNA samples from peripheral blood leukocytes. Adduct levels in peripheral blood leukocytes are positively and linearly related to adduct levels in liver tumor tissue.16 Furthermore, adduct levels were also correlated with serum levels of aflatoxin-albumin adducts in this study. Given the seasonal changes in levels of this adduct, the estimate of cumulative aflatoxin exposure in present study may more correctly integrate levels over time. We estimated cumulative aflatoxin exposure by means of an analysis of aflatoxin-DNA adduct levels.

This study had several limitations. Selection bias might have occurred through the selection of hospital-based control subjects. Also, liver disease itself may affect the metabolism of aflatoxin and modify the levels of aflatoxin-DNA adducts. Thus, the increased risk with aflatoxin exposure seen in this study was probably underestimated. In spite of the relatively large sample size, the power to elucidate gene–environment interactions was limited because of the small magnitudes of the overall associations and the relatively low frequency of high-risk genotypes. Although the status of TP53M was investigated in liver cancer cases, other mutations of the TP53 gene were not. Additionally, while we assessed XRCC4P and XRCC5P, we did not analyze polymorphisms of other genes involved in the NHEJ pathway, polymorphisms that might be able to further modify the effect of aflatoxin on liver cancer.6,8 More genes deserve elucidation based on large samples and a combination of genes and aflatoxin exposure.

To conclude, we report an association between XRCC4P and aflatoxin-related liver cancer risk and prognosis, with possible modification of liver cancer risk and prognosis related to aflatoxin. The gene–environment interactions were stronger than the gene or aflatoxin exposure alone. Given that liver cancer is a highly fatal tumor, the finding of a genetic susceptibility (if confirmed) may have implications for screening and prevention.

ACKNOWLEDGMENTS

We thank Qiu-Xiang Liang, Yun Yi, and Yuan-Feng Zhou for sample collection and management and Hua Huang for molecular biochemical technique. We also thank all members of Department of Medical Test and Infective Control, Affiliated Hospital of Youjiang Medical College for Nationalities, for their help.

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