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Common Germline Genetic Variation in Antioxidant Defense Genes and Survival After Diagnosis of Breast Cancer

Miriam Udler, Ana-Teresa Maia, Arancha Cebrian, Clement Brown, David Greenberg, Mitul Shah, Carlos Caldas, Alison Dunning, Douglas Easton, Bruce Ponder, Paul Pharoah

From the Department of Public Health and Primary Care and the Department of Oncology, University of Cambridge; Cambridge Research Institute; and Eastern Cancer Registration and Information Centre, Unit C, Cambridge, United Kingdom

Address reprint requests to Miriam Udler, MPhil, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom; e-mail: miriam.udler{at}srl.cam.ac.uk

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
Purpose The prognosis of breast cancer varies considerably among individuals, and inherited genetic factors may help explain this variability. Of particular interest are genes involved in defense against reactive oxygen species (ROS) because ROS are thought to cause DNA damage and contribute to the pathogenesis of cancer.

Patients and Methods We examined associations between 54 polymorphisms that tag the known common variants (minor allele frequency > 0.05) in 10 genes involved in oxidative damage repair (CAT, SOD1, SOD2, GPX1, GPX4, GSR, TXN, TXN2, TXNRD1, and TXNRD2) and survival in 4,470 women with breast cancer.

Results Two single nucleotide polymorphisms (SNPs) in GPX4 (rs713041 and rs757229) were associated with all-cause mortality even after adjusting for multiple hypothesis testing (adjusted P = .0041 and P = .0035). These SNPs are correlated with each other (r² = 0.61). GPX4 rs713041 is located near the selenocysteine insertion sequence element in the GPX4 3' untranslated region, and the rare allele of this SNP is associated with an increased risk of death, with a hazard ratio of 1.27 per rare allele carried (95% CI, 1.13 to 11.43). This effect was not attenuated after adjusting for tumor stage, grade, or estrogen receptor status. We found that the common allele is preferentially expressed in normal lymphocytes, normal breast, and breast tumors compared with the rare allele, but there were no differences in total levels of GPX4 mRNA across genotypes.

Conclusion These data provide strong support for the hypothesis that common variation in GPX4 is associated with prognosis after a diagnosis of breast cancer.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
In the United Kingdom, breast cancer is one of the most common causes of death from cancer, with a death rate of approximately 29 per 100,000 women (National Statistics Cancer Registrations in England, 2003; http://www.statistics.gov.uk). Somatic genetic alterations have been shown to correlate with breast cancer prognosis,^1-3 but the effects of common inherited genetic variation are less well understood. Many studies have reported nominally significant association between common genetic variants and breast cancer survival,^4-22 but most of these studies were small, and none reached the level of statistical significance (P < .0001) that has been suggested as appropriate for genetic association studies in candidate genes.²³

The Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) breast cancer study was set up to investigate the role of common genetic variation in candidate genes in breast cancer susceptibility. However, genes that modify susceptibility to cancer may also influence progression after diagnosis. Therefore, we have linked the genetic data from the SEARCH breast study to outcome data from regional cancer registries to test the hypothesis that germline genetic variation affects survival after diagnosis of breast cancer.

Common variants in oxidative damage defense and repair genes are good candidates for both cancer susceptibility and prognosis. Reactive oxygen species (ROS) are produced as a natural byproduct during normal cellular respiration, as well as other normal cellular processes. ROS are known to be mitogenic because they cause lesions in DNA that may lead to malignant transformation.^24,25 To protect against cellular injury caused by ROS, cells have defense systems including antioxidant enzymes. Antioxidant enzyme levels are lower in most human and animal cancer cells than in the corresponding normal cells of origin, supporting a tumor suppressor role of these antioxidant enzymes in carcinogenesis.²⁶

Fifty-four single nucleotide polymorphisms (SNPs) in 10 genes (CAT, catalase; SOD1, SOD2, superoxide dismutases; GPX1, GPX4, glutathione peroxidases; GSR, glutathione reductase; TXN1, TXN2, theoredoxins; and TXNRD1, TXNRD2, theoredoxin reductase) involved in oxidative damage defense and repair have been investigated as part of SEARCH.²⁷ In the SEARCH breast cancer study, three borderline significant associations with breast cancer susceptibility were observed in CAT g27168a (P = .05), TXN-t2715c (P = .007), and TXNRD2-g23524a (P = .046).²⁷ Here, we report the results of an analysis of the association of the same 54 SNPs with breast cancer prognosis.

	PATIENTS AND METHODS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
Study Population
The SEARCH breast cancer study is an ongoing population-based study of women with breast cancer diagnosed in the region of England currently covered by the Eastern Cancer Registry (population = approximately 2.2 million). Eligible patients were either patients with invasive breast cancer diagnosed at less than 70 years of age since the beginning of the study on July 1, 1996 (incident patients), or patients diagnosed with breast cancer at age 55 or younger since January 1, 1991, who were still alive at the beginning of the study (prevalent patients). Some of the prevalent patients diagnosed before 1995 were identified by the Thames Cancer Registry as a result of registry boundary changes. All participants in the study gave informed consent, provided a blood sample, and completed a comprehensive epidemiologic questionnaire. Sixty-seven percent of eligible breast cancer patients returned a questionnaire, and 64% provided a blood sample. DNA from 4,470 participants has been genotyped. Data on tumor characteristics (TNM stage,²⁸ grade, and histopathologic type) and on patient first-line treatment were collected by the cancer registries by review of the patient case notes.

The samples have been split into two sets to save DNA and reduce genotyping costs. The first set (n = 2,270 patients) was genotyped for all SNPs, and the second set (n = 2,200 patients) was only genotyped for those SNPs that showed marginally significant associations in set 1 (P heterogeneity or P trend < .1 for univariate analyses). This staged approach substantially reduces genotyping costs without significantly affecting statistical power and has been described in greater detail elsewhere.²⁷ The study was approved by the Eastern Multicenter Research Ethics Committee.

Follow-Up
Both the East Anglian Cancer Registry and the Thames Cancer Registry have active follow-up at 3 and 5 years after diagnosis and then at 5-year intervals by searching hospital information systems for recent visits. If a patient has not had a recent visit, his or her general practitioner is contacted. The registries are also notified by death certificate flagging with the Office for National Statistics. There is a lag time with this process of a few weeks for cancer deaths and 2 months to 1 year for noncancer deaths.

Laboratory Methods
The 10 genes were originally selected as candidate genes for breast cancer susceptibility but are also candidates for prognosis. We used a comprehensive SNP tagging approach in which tag SNPs were chosen to capture all the known common genetic variation in each gene with a minimum correlation coefficient (r²) of 0.8. Data from the International Hap Map Project (http://www.hapmap.org) and resequencing data from the Environmental Genome Project (http://pga.gs.washington.edu/finished_genes.html) were used to select tag SNPs. In total, 54 SNPs were chosen to tag 290 common variants (Table 1; see Cebrian et al²⁷ for details). Genotyping was carried out using a fluorescent 5' exonuclease assay (TaqMan) and the ABI PRISM 7900 Sequence Detection Sequence (Applied Biosystems, Foster City, CA) implemented in 384-well format. Each 384-well plate included duplicate samples, and only assays where concordance was 100% were included for analysis. Assays were not repeated for failed genotype calls.

The SNPs significantly associated with survival at the 5% level were retested in models to adjust for age at diagnosis, tumor stage, and tumor grade, all of which are known prognostic factors. Factors were grouped as follows: age at diagnosis: < 45, 45 to 49, 50 to 54, and > 54 years; tumor stage group: TNM I, II, III, and IV; and grade: well differentiated, moderately differentiated, and poorly/undifferentiated.

Cause of death was available for 555 (97.5%) of the 569 deaths. Of these, 505 patients had breast cancer (International Classification of Diseases–10th revision [ICD-10] code 50), a secondary neoplasm (ICD-10 codes 78 and 79), or a malignant neoplasm without specification of site (ICD-10 code 80). Cause-specific analysis was performed on SNPs significant at the 5% level in the univariate analyses. All analyses were performed with Intercooled Stata version 9 (STATA Corp, College Station, TX).

Analysis of GPX4 Gene Expression
Analysis of the expression of GPX4 was performed in a different set of B lymphocytes from healthy blood donors, normal breast tissue, and breast tumor tissue. Breast tumor patients were selected on the basis of having normal copy number, as determined by oligonucleotide-based array comparative genomic hybridization analysis (data kindly provided by Dr S.F. Chin), which is a high-resolution method for measuring chromosomal copy number change. DNA and total RNA were extracted from these samples, and cDNA was prepared with the TaqMan Reverse Transcription Reagents kit (Applied Biosystems) using random hexamers, according to the manufacturer's instructions. DNA from all samples was genotyped by TaqMan analysis using the genotyping assay for rs713041, which includes two different label probes, each annealing specifically to either allele. Because this assay included primers and probes within the coding region, it was also suitable to use it for the analysis of cDNA. Allele-specific gene expression was determined in heterozygous samples using three replicates per assay. For quantification, a dilution series of a heterozygote DNA sample was analyzed for quantitative polymerase chain reaction. Ct (cycle at threshold) values were exported using the appropriate software and were used to calculate a standard curve for quantification. In this way, when we calculated the ratios in cDNA samples, these came automatically normalized for the Ct corresponding to the 1:1 ratio of the two alleles in the reference DNA samples. Allelic expression ratios were calculated as log₂{[c allele (VIC)]/[t allele (FAM)]}. Total expression levels of all samples heterozygous and homozygous for both alleles were determined using a TaqMan Gene Expression Assay (Applied Biosystems; assay ID: Hs00157812_m1). Results were normalized with the total levels of expression of actin-beta.

To investigate the stability of the allelic mRNAs (half-life), their decay was measured in a heterozygote cell line after treatment with dactinomycin, an inhibitor of transcription. In brief, KPL-1 cells (human breast carcinoma cell line) were plated in growth medium, and 24 hours later, they were treated with dactinomycin 10 µg/mL. Total RNA was isolated from cells treated for different time intervals.

	RESULTS

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Association of Genotype With Survival
The characteristics of the SEARCH breast study participants for whom genotyping and vital status data were available are listed in Table 2 (see also Appendix Tables A1 and A2, online only, for characteristics of prevalent and incident patients and characteristics of patients by set number, respectively). No significant difference in survival was found between incident and prevalent patients (P = .19). During the 20,953 person-years at risk, there were 569 deaths before 10 years of follow-up.

View larger version (10K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 1. Cumulative hazard by GPX4-06 (rs757229) genotype.

The Cox regression model for GPX4-06 fits the data better than the model for GPX4-02, and in a stepwise regression model including both SNPs, only GPX4-06 remained in the final model; however, the difference in fit between the two models was small (Akaike Information Criterion scores of 8,395.93 and 8,396.42, respectively). Furthermore, other molecular data suggest that GPX4-02 is a better candidate for a functional effect than GPX4-06 (see next section). Therefore, we further investigated GPX4-02 for evidence of an interaction with treatment. Data on whether or not the patients had been treated with radiotherapy, chemotherapy, and adjuvant hormone therapy were available for 96% of patients. The hazard associated with GPX4-02 was higher in patients receiving radiotherapy or adjuvant hormone therapy compared with patients not receiving the respective treatments. However, tests for interaction were not significant. There was no difference in the prognosis of patients who carried the rare allele of GPX4-02 according to whether or not they had been treated with chemotherapy. Likewise, the effect of GPX4-02 was similar in early- and advanced-stage disease. When stratified by ER status, the hazard associated with GPX4-02 was greater in ER-negative patients (HR = 1.49; 95% CI, 1.16 to 1.92) compared with ER-positive patients (HR = 1.23; 95% CI, 0.99 to 1.52), but again, the difference was not significant (P = .20). As expected, similar results were observed for GPX4-06 (data not shown).

Allelic Gene Expression Analysis of GPX4-02 (rs713041)
The existence of SNPs in the coding region of genes has led to the observation that differences in allelic expression are common.^29,30 Differences in allelic expression could be a mechanism that links germline variation with altered function of gene products because of preferential expression of alleles with different stabilities or that encode for amino acid changes. The SNP GPX4-02 (rs713041) has been previously reported to have functional effects, with common homozygotes (cc) having an increased activity of lipoxygenase metabolism of approximately 36% and 44% compared with rare homozygotes (tt) and heterozygotes (ct), respectively.³¹ Therefore, we analyzed the allelic gene expression ratios (c allele/t allele) in heterozygotes identified in 57 blood samples from normal individuals, six normal breast tissue samples, and 33 samples of tumor tissues from breast cancer patients (37, five, and 13 were heterozygotes, respectively). Mean ratios obtained indicated that the common c allele is preferentially expressed in all types of samples analyzed, ranging from five- to eight-fold of the rare allele expression level (Fig 2A). The expression ratio was somewhat greater in ER-negative patients (Fig 2B), but this was not statistically significant (P = .59). The allelic imbalance does not lead to a difference in the total amount of GPX4 mRNA across the three genotypes (Fig 2C). One explanation for this is that expression may be controlled by a feedback loop that is dependent on total levels whatever the relative expression of the two alleles. We did observe small differences in expression of GPX4 between the three different tissues analyzed (P = .00053 and .013 for normal breast v normal blood and normal breast v breast tumor, respectively; Fig 2D). In an attempt to elucidate the mechanism responsible for the allelic gene expression imbalance, we investigated the stability of the two variant mRNAs and found that they have different half-lives (46 minutes for the c allele and 1 hour and 28 minutes for the t allele in KPL-1 cells; Fig 2E). Because it is the less stable variant that is in higher quantity in the analyzed samples, we suggest that the differences detected in the amount of the two variants is most likely a result of differences in the gene expression rate, rather than a reflection of the different stabilities.

View larger version (18K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 2. Expression analysis of GPX4 in normal tissue (blood and breast) and breast tumors. (A) Log2 ratio of allelic expression for GPX4-02 (rs713041), with ratio calculated as (c allele)/(t allele). Number of heterozygote samples analyzed is indicated for each tissue source. (B) Log2 ratio of allelic expression in breast tumors by estrogen receptor (ER) expression status. (C) Total level of GPX4 expression compared between different genotypes for GPX4-02 (rs713041) in blood from normal controls and breast tumors. (D) Comparison of total levels of GPX4 expression between different tissues and between normal breast versus breast tumors. Number of samples analyzed is indicated for each tissue source. (E) Half-life determination for the two variant mRNAs of GPX4 and 18S mRNA in KPL-1 cells. Cells were treated with Actinomycin-D to block synthesis of new mRNA. Values represent the mean, from triplicate points, of the percentage of mRNA existing at each time point. Half-life was extrapolated from the trend line equations (displayed for each mRNA) as the time necessary to observe 50% decay.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
We have evaluated the impact of 54 tagging SNPs in 10 oxidative repair genes on breast cancer survival among white women from the East Anglian region of the United Kingdom. The major strengths of this study are its large size, the fact that it is population based, the length and systematic approach of the follow-up, and the systematic approach to tagging the known common genetic variation in the genes of interest. However, missing data on ER status and lack of detail for treatment data, such as specific chemotherapeutic agent used or duration of treatment, limit the interpretation of our results.

We have found no evidence that common variations in CAT, SOD1, SOD2, GPX1, GSR, TXN1, TXN2, TXNRD1, or TXNRD2 are associated with outcome after a diagnosis of breast cancer. Recently, Ambrosone et al¹⁰ found that the tt genotype of rs1001179 (CAT-01) was associated with a reduced risk of death, although the finding was not statistically significant. We also found that the rare allele of this SNP was associated with improved survival, but again, the association was not significant (HR for tt v cc = 0.90; 95% CI, 0.53 to 1.52). The SNPs under study were not selected because of their predicted effects on structure and function but, instead, because they tag all known common variants and are expected to tag any unknown variants. Nevertheless, it is possible that important, unidentified variants in the genes were not efficiently tagged.²⁷ It is also possible that rare variants in these genes are important predictors of outcome. We may also have failed to detect any association with survival because of lack of statistical power to detect modest effects. Despite our large sample size, there were just 569 deaths in our cohort. Assuming a type I error rate of 0.001, we had only 20% power to detect a codominant allele of frequency 0.1 that confers a relative hazard of 1.3% and 70% power to detect a similar allele with a frequency of 0.3. Power to detect recessive alleles with similar effects was poor.

The most significant results were for two correlated SNPs in GPX4. This gene is a member of the GPX gene family and encodes glutathione peroxidase, a selenoprotein that catalyzes the reduction of hydrogen peroxide, organic hydroperoxide, and lipid peroxides by reduced glutathione. Glutathione peroxidase functions in the protection of cells against oxidative damage. We looked at GPX1 and GPX4 because they are the most active intracellular forms of this superfamily and have previously been associated with cancer.^32-34 It has also been suggested that GPX4 plays a role in regulation of leukotriene biosynthesis and inflammation because GPX4 has been found to upregulate arachidonate metabolism in an epidermoid carcinoma tumor cell line.³⁵ Given that most patients in our study mostly had ER-positive and lymph node–negative tumors, it is possible that the association we found is most applicable to this good-outcome subset of breast cancer patients. Indeed, there was a suggestion that the effects varied by ER status of the tumors and according to treatment, but none of these subgroup effects was significant, and much larger sample sizes would be needed for confirmation.

GPX4-06 and GPX4-02 were chosen as tagging SNPs rather than as known functional variants. However, GPX4-02 (rs713041) is in the 3' untranslated region, and in eukaryotes, selenium is incorporated into selenoproteins as the amino acid selenocysteine in a process requiring a stem-loop within the 3' untranslated region of the mRNA. Furthermore, genotype at this SNP has been shown to be associated with levels of lymphocyte 5-lipoxygenase metabolites. These data suggest that this SNP or another correlated SNP has functional effects and support the hypothesis that GPX4 plays a regulatory role in leukotriene biosynthesis.³¹ Further evidence comes from our findings that the alleles of GPX4-02 are differentially expressed in normal breast tissue and blood, as well as in breast tumors. Allelic variation in gene expression, or allelic expression imbalance, is a common event across the genome, and it has been implicated in cancer susceptibility (see review in Yan and Zhou³⁶). AEI might be expected to alter function by reducing total expression, but we found no evidence for expression differences by genotype in either lymphocytes or breast tissue. However, the total sample size was small, and a much larger sample size would be needed to detect potentially important, small genotype-specific differences in expression, particularly if any difference was tissue specific.

Taken together, these data support the hypothesis that common variation in GPX4 is associated with prognosis after a diagnosis of breast cancer. Further studies to test this hypothesis are warranted.

	AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
The author(s) indicated no potential conflicts of interest.

	AUTHOR CONTRIBUTIONS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
Conception and design: Arancha Cebrian, Carlos Caldas, Alison Dunning, Douglas Easton, Bruce Ponder, Paul Pharoah

Administrative support: Carlos Caldas, Alison Dunning, Douglas Easton, Bruce Ponder

Provision of study materials or patients: Clement Brown, David Greenberg, Mitul Shah

Collection and assembly of data: Ana-Teresa Maia, Arancha Cebrian, Clement Brown, David Greenberg, Mitul Shah

Data analysis and interpretation: Miriam Udler, Ana-Teresa Maia

Manuscript writing: Miriam Udler, Ana-Teresa Maia, Carlos Caldas, Bruce Ponder, Paul Pharoah

Final approval of manuscript: Miriam Udler, Ana-Teresa Maia, Arancha Cebrian, Clement Brown, David Greenberg, Mitul Shah, Carlos Caldas, Alison Dunning, Douglas Easton, Bruce Ponder, Paul Pharoah

	Appendix

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	ACKNOWLEDGMENTS

 
We thank S.F. Chin for expression data on some of the cancer patients; J. Marioni for help in expression data analysis; the women who have taken part in the study; the Studies of Epidemiology and Risk Factors in Cancer Heredity study team; the consultants and general practitioners throughout East Anglia for their help in recruiting patients; and Warren Carmody of the East Anglian Cancer Registry and Vivian Mak at the Thames Cancer Registry for providing outcome and clinical data.

	NOTES

 
Supported by a program grant from Cancer Research UK. B.P. is a Gibb Fellow, D.E. is a Principal Research Fellow, and P.P. is a Senior Clinical Research Fellow of Cancer Research UK.

M.U. and A.-T.M. contributed equally to this work.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
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Submitted January 4, 2007; accepted April 17, 2007.

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