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. Author manuscript; available in PMC: 2007 Jun 1.
Published in final edited form as: Hum Mutat. 2006 Jun;27(6):538–544. doi: 10.1002/humu.20323

The ATM missense mutation Ser49Cys and risk of breast cancer

Denise L Stredrick 1, Montserrat Garcia-Closas 2, Marbin A Pineda 1, Parveen Bhatti 3, Bruce H Alexander 4, Michele M Doody 3, Jolanta Lissowska 5, Beata Peplonska 6, Louise A Brinton 2, Stephen J Chanock 7, Jeffery P Struewing 1,✉, Alice J Sigurdson 3
PMCID: PMC1850333  NIHMSID: NIHMS13666  PMID: 16652348

Abstract

Homozygous mutation in the ATM gene causes ataxia telangiectasia and heterozygous mutation carriers may be at increased risk of breast cancer. We studied a total of 22 ATM variants in two large population-based studies of 2856 breast cancer cases and 3344 controls from the U.S. and Poland. The missense mutation Ser49Cys (S49C), carried by approximately 2% of subjects, was more common in cases than controls in both study populations, combined odds ratio (OR) 1.69, 95% CI 1.19 – 2.40, P = 0.004. Another missense mutation at approximately 2% frequency, F858L, was associated with a significant increased risk in the U.S. study but not in Poland, combined OR of 1.44, 95% CI 0.98 – 2.11, P = 0.06. These analyses provide the most convincing evidence thus far that some missense mutations in ATM, particularly S49C, may be breast cancer susceptibility alleles. Because of their low frequency, even larger sample sizes are required to more firmly establish these associations.

Introduction

Ataxia telangiectasia (AT) is a rare autosomal recessive disease (frequency of 1/40,000 or less, heterozygote carrier frequency < ~ 1%) characterized predominantly by severe progressive cerebellar degeneration and increased rates of leukemia and lymphoma (McKinnon 2004). For nearly 20 years it has been suggested that obligate heterozygote mutation carriers, who are phenotypically normal, are at increased risk of breast cancer (Swift et al. 1987). Although somewhat controversial (Khanna 2000), epidemiologic studies among relatives of AT patients have generally confirmed a modest breast cancer risk among obligate heterozygotes (Swift et al. 1991; Geoffroy-Perez et al. 2001; Olsen et al. 2001; Thompson et al. 2005b).

The ATM (ataxia telangiectasia mutated) gene, cloned in 1995, is very large and mutations occur throughout its amino acid coding portions (Savitsky et al. 1995). Although somewhat biased, owing to the mutation screening methods applied to such a large gene, like the protein truncation test, most of the mutations identified thus far in AT patients are protein-truncating. The initial cancer observations in obligate carriers from AT families imply that AT-causing mutations underlie the increased breast cancer risk. Complete mutation screening of the ATM gene in breast cancer patients, however, has generally not identified a significant number of AT-related mutations in cases compared to controls, although the diversity and extremely low frequency of detected mutations has resulted in studies of insufficient power (FitzGerald et al. 1997). Additionally, haplotypes defined by common SNPs across the gene have not shown any association with breast cancer (Tamimi et al. 2004; Lee et al. 2005).

To explain the inability to identify protein-truncating ATM mutations in breast cancer patients, a model has been proposed suggesting that missense and truncating mutations could be associated with distinct phenotypes, namely, cancer and neurological diseases (Gatti et al. 1999). This reasoning is not entirely satisfactory, however, because it does not explain how the initial breast cancer risk association was discovered – namely that relatives of AT patients, who necessarily have mutations that are associated with severe neurological symptoms and are usually truncating, are at increased risk of breast cancer. None-the-less, recent evidence suggests that indeed some missense mutations are functionally relevant and predispose heterozygous carriers to breast cancer. For example, the rare missense mutation V2424G has been identified in two British AT patients who have a less severe level of cerebellar degeneration (Stankovic et al. 1998). It appears to confer an increased risk of breast cancer in these families, and shows “dominant-negative” biochemical effects (Stankovic et al. 1998; Chenevix-Trench et al. 2002; Scott et al. 2002; Thompson et al. 2005a). Missense mutations V2761A, R2849P, and G2876R, identified in AT patients, also showed dominant-negative effects, whereas of the missense mutations S2592C, A2274T, G2287A, C2464R, and G2772R, initially identified in breast cancer patients, only S2592 showed dominant-negative effects when studied biochemically (Scott et al. 2002). Although past studies have been underpowered for analysis of low frequency variants, several studies of breast cancer subjects have identified missense mutations more commonly in breast cancer patients, including the S49C mutation (Izatt et al. 1999; Atencio et al. 2001; Dork et al. 2001; Teraoka et al. 2001; Maillet et al. 2002; Rodriguez et al. 2002; Sommer et al. 2002; Bretsky et al. 2003; Buchholz et al. 2004).

Since complete sequence analysis of the entire ATM gene is still prohibitively expensive for an adequately powered breast cancer case-control study, we analyzed 22 individual ATM variants, including AT-associated mutations, missense mutations, and non-coding variants, in two independent study populations in the U.S. and Poland.

Methods

Study Populations

United States Radiologic Technologist Study

The study of ATM was initiated in a nested breast cancer case-control study within the US Radiologic Technologist (USRT) cohort study, a group with occupational exposure to medical sources of ionizing radiation (Sigurdson et al. 2003; Sigurdson et al. 2004; Yoshinaga et al. 2004). Subjects included 861 prevalent breast cancer cases, both in situ and invasive, identified through questionnaires mailed during 1983–1988 and 1994–1998, and 1048 control subjects without breast cancer as of 1999, frequency matched to the cases on year of birth. Blood samples were collected between 1999 and 2004, with participation rates of 58% among cases and 48% among controls. Calendar year of breast cancer diagnoses ranged from 1955 to 2000.

Breast cancer case-control study in Poland

The second study is a case-control investigation of breast cancer conducted in Poland from 2000 – 2003 (Garcia-Closas, Submitted). Eligible cases were women 20–74 years of age, residents of Warsaw and Łódź, who were newly diagnosed with either histologically or cytologically confirmed in situ or invasive breast cancer. Population registries were used to randomly select controls, stratified by city and age in 5 year categories. We identified 3,037 eligible cases and 3,639 eligible controls through the study period. Of these, 2,386 (79%) cases and 2,503 (69%) controls agreed to participate in a personal interview on known and suspected breast cancer risk factors. The present study is limited to women with blood DNA samples: 1,995 cases (6% in situ) and 2,296 controls, which represent 84% and 92%, respectively, of those interviewed.

Both study protocols were reviewed and approved by local and NCI Institutional Review Boards. All participants provided written informed consent. Demographic characteristics of the two study populations are shown in Table S1.

Laboratory Methods & Variant Selection

We developed Taqman 5′-nuclease allele discrimination, denaturing high-performance liquid chromatography (dHPLC), or PCR-RFLP assays for the following types of nucleotide changes: AT-associated mutations (n=6) identified in five or more families of diverse ethnicity (as of 2002) or in British AT patients (http://www.vmresearch.org/investigators/concannon_patrick/atmut-t.htm); variants with functional significance by biochemical assay (n=4) (Scott et al. 2002); and non-conservative missense mutations with a minor allele frequency < 5% (n=5). A single silent mutation, P1526P, was also studied because its frequency differed between breast cancer cases and controls in a prior study (Teraoka et al. 2001).

Interim analyses of association with breast cancer in the USRT study (Struewing et al. 2004) identified four variants (S49C, S707P, F858L, and P1526P) with P ≤ 0.1, prompting us to evaluate these mutations in the Polish breast cancer study. In the Polish study, six additional non-coding SNPs, chosen from among those available at the National Cancer Institute’s Core Genotyping Facility (http://snp500cancer.nci.nih.gov), were also assayed (Bonnen et al. 2002; Packer et al. 2004; Tamimi et al. 2004; Lee et al. 2005). Additional details for all assays are available in Table S2.

Genotyping quality control (QC) was assessed with duplicated DNA samples intermixed with study samples (87 DNA aliquots from 8 non-study subjects in the USRT study, and 100 DNA pairs in the Polish study). Laboratory personnel were blinded as to the QC samples, which showed ≥ 99% concordance for all but one ATM assay (rs600329 in IVS31, 97% concordance). We observed no significant departures from Hardy-Weinberg equilibrium in the control populations for any of the assays.

Statistical Methods

We compared genotype frequencies between cases and controls using contingency table analyses and unconditional logistic regression modeling, adjusting for age and study site. Adjustment for additional variables, such as age at menarche, parity, and age at first birth within the individual study groups did not appreciably alter the estimated genotype odds ratios. For age-adjusted analyses, age was considered the age at diagnosis for cases; for controls from Poland, age was considered the age at interview, and in the USRT study, the age as of 1999. For variants where all three genotype possibilities were observed, we tested for overall differences in genotype frequency between cases and controls using a likelihood ratio chi-square test with 2 degrees of freedom (does not assume dominant or recessive inheritance model). We tested for homogeneity of odds ratios between study groups using the Breslow-Day test as implemented in SAS 9.1 (SAS Institute, Inc., Cary, NC).

We calculated the probability of a false association, or false positive report probability (FPRP) (Wacholder et al. 2004), to assess whether our findings were “noteworthy” and reflect true associations. The FPRP was calculated for prior probabilities ranging from 0.1 to 0.0001, based on the statistical power to detect a true OR of 1.5. This range of probabilities was chosen to reflect our priors for the SNPs under study, i.e. 0.1 for the AT-related and missense mutations and 0.0001 for the non-coding mutations. We considered associations with an FPRP below 0.20 (i.e. less than 20% probability of being false positive findings) to be noteworthy.

Genotype frequencies were compared for cases with various survival times in the USRT study and there were no statistically significant differences. For example, the prevalence of S49C heterozygotes was 3.6% in subjects recruited within 10 years of their breast cancer diagnosis and 4.1% among those diagnosed more than 10 years prior to recruitment and blood collection (P = 0.8). We also noted no statistically significant differences in the genotype frequencies for any variant between invasive and in situ cases for either study group (data not shown). Therefore, estimates of relative risk are presented for both types of tumors combined.

Results

We observed a significantly increased risk of breast cancer among women who were heterozygous carriers of the rare missense mutation S49C (Table 1). Among USRT subjects, 3.9% of cases and 2.6% of controls were heterozygous for S49C, while in Polish subjects 2.3% of cases and 1.2% of controls carried this mutation. Estimated ORs were not significantly different between the two study populations (P = 0.5), and the adjusted OR for the combined data was 1.69 (95% CI 1.19 – 2.40, P = 0.004). S49C heterozygotes were found more commonly among cases under age 50 than among older cases, whereas the frequency was similar among controls (Table 2), resulting in a stronger association with breast cancer risk in younger (OR = 2.21, 95% CI 1.09 – 4.46) than older (OR 1.53, 95% CI 0.99 – 2.38) women (P = 0.1 for heterogeneity of ORs). The F858L missense mutation was associated with significantly increased breast cancer risk in the USRT study, being carried by 3.5% of cases and 1.8% of controls (P = 0.03) (Table 1). Its frequency did not vary significantly between cases and controls in the Polish study. The study-specific ORs for F858L were not significantly different from each other (P=0.2), however, and the combined OR was 1.44 (95% CI 0.98 – 2.11, P = 0.06).

Table 1.

Association between four ATM SNPs and breast cancer.

USRT
Poland
Combined
SNP Name Cases Controls Cases Controls Cases Controls
(rs numa) Genotypeb N N OR (95% CI) c P N N OR (95% CI) c P N % N % OR (95% CI)d Pe
S49C (1800054) Hz WT 821 1013 1.0 1933 2258 1.0 2754 97.2 3271 98.4 1.0 0.5
Het 33 27 1.60 (0.88 – 2.90) 0.1 45 28 1.88 (1.17 – 3.02) 0.009 78 2.8 55 1.7 1.69 (1.19 – 2.40) 0.004
S707P (4986761) Hz WT 837 999 1.0 1923 2231 1.0 2760 98.0 3230 97.8 1.0 0.02
Het 14 34 0.47 (0.23 – 0.93) 0.03 42 39 1.25 (0.80 – 1.94) 0.3 56 2.0 73 2.2 0.92 (0.65 – 1.32) 0.7
F858L (1800056) Hz WT 826 1023 1.0 1924 2230 1.0 2750 97.9 3253 98.5 1.0 0.2
Het 30 19 2.03 (1.05 – 3.90) 0.03 30 31 1.12 (0.67 – 1.86) 0.7 60 2.1 50 1.5 1.44 (0.98 – 2.11) 0.06
P1526P (1800889) Hz WT 791 951 1.0 1702 1962 1.0 2493 88.3 2913 87.7 1.0 0.2
Het 47 87 0.75 (0.49 – 1.13) 273 308 1.02 (0.86 – 1.22) 320 11.3 395 11.9 0.93 (0.79 – 1.09)
Hz Var 2 0 Inf. 7 14 0.58 (0.23 – 1.43) 9 0.3 14 0.4 0.75 (0.32 – 1.74)
0.4 (df=2)f 0.5 (df=2)f 0.5 (df=2)f
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b

Hz WT subjects are homozygous for the reference/wild-type allele; Het subjects are heterozygous for the variation; Hz Var subjects are homozygous for the non-reference/variant allele.

c

Odds ratio, adjusted for age (below 50, 50–59, 60–69, 70+).

d

Adjusted for study group (USRT or Poland) and age (below 50, 50–59, 60–69, 70+).

e

P value for Breslow-Day test for homogeneity of the ORs across study groups (USRT vs Poland).

f

P value for unadjusted likelihood ratio chi square test with 2 degrees of freedom for overall difference in genotype frequencies between cases and controls.

Table 2.

Heterozygote frequencies for the two ATM missense mutations S49C & F858L among subgroups of study subjects.

ATM SNP
S49C
F858L
Breast Cancer Case/Control Subgroup Total N No. Het % Het Total N No. Het % Het
Cases All 2832 78 2.8 2810 60 2.1
Controls All 3326 55 1.7 3303 50 1.5
Cases USRTa 854 33 3.9 856 30 3.5
Warsawb 1255 31 2.5 1242 18 1.4
Łódź b 723 14 1.9 712 12 1.7
Controls USRT 1040 27 2.6 1042 19 1.8
Warsaw 1467 20 1.4 1450 17 1.2
Łódź 819 8 1.0 811 14 1.7
Cases Age <50 1095 37 3.4 1089 27 2.5
Age 50+ 1736 41 2.4 1720 33 1.9
Controls Age <50 807 11 1.4 803 11 1.4
Age 50+ 2519 44 1.7 2500 39 1.6
Cases FH +c 398 10 2.5 395 10 2.5
FH − 2432 68 2.8 2413 50 2.1
Controls FH + 296 5 1.7 294 5 1.7
FH − 3028 50 1.7 3007 45 1.5
Cases Invasive-USRT 729 28 3.8 731 28 3.8
In situ- USRT 125 5 4.0 125 2 1.6
Invasive-Poland 1862 41 2.2 1839 30 1.6
In situ- Poland 116 4 3.4 115 0 0.0
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a

U.S. Radiologic Technologist Study subjects.

b

Warsaw and Łódź are the two study sites for the Polish Breast Cancer Case-control Study.

c

FH + subjects report at least one first degree relative with breast cancer. FH – subjects have no first degree relatives with breast cancer.

Table 2 shows S49C and F858L heterozygote frequencies for various subgroups of subjects. The two SNPs were slightly more common in the US subjects, but generally showed consistency in their association with breast cancer. Heterozygote frequencies for F858L were slightly higher in subjects with a first degree relative with breast cancer compared to those with a negative family history, but S49C did not vary by family history.

The FPRP, or probability that the observed association with S49C is a false positive finding, was 11% for a prior probability of 0.1 and a true effect size of 1.5. Lower prior probabilities, down to 0.05, yielded FPRP values of 20% or below, while a prior probability of 0.01 results in a FPRP of 57%. The FPRP for the borderline significant association for F858L was above 20%, even for high priors (FPRPs 49% to >99% for priors of 0.1 to 0.0001, respectively, and true OR of 1.5), indicating that this finding is likely to be a false positive.

The S49C and F858L mutations were two of four coding mutations genotyped in both the USRT and Poland study groups because they showed some evidence of association (P ≤ 0.1) in an interim analysis of the USRT data (Struewing et al. 2004). (Tables S3 & S4) The P1526P silent mutation, observed commonly in a previous series of breast cancer cases (Teraoka et al. 2001), was somewhat less common among cases in USRT but was at the same frequency among the Polish cases and controls. The S707P missense mutation was significantly less common among USRT cases compared to controls (OR = 0.47, 95% CI 0.23 – 0.93) but showed the opposite effect in the Polish study group (OR = 1.25, 95% CI 0.80 – 1.94). Overall, there was no significant association between S707P with breast cancer risk, but there was evidence for significant heterogeneity in the OR between study groups (P=0.02).

Of the 10 AT-related mutations studied in the USRT population, only four were heterozygous in at least one subject: one case carried the 1563delG and one carried the 7636del9 mutation, while three cases and four controls were heterozygous for IVS10-6T>G and four cases and three controls carried S1691R. In total, nine cases and seven controls carried one of these mutations specified a priori as likely to be causally related to the AT phenotype, an insignificant difference. The frequency of all variants studied in the USRT study group are shown in Table S3. In the Poland study group, there were no differences in genotype frequency between cases and controls for the non-coding variants, as shown in Table S4.

Discussion

We have analyzed a number of rare (heterozygote frequencies < 10%) coding variants in the ATM gene in two large breast cancer studies of 2856 breast cancer cases and 3344 controls from the U.S. and Poland. We provide evidence that at least one of them, S49C, may be a breast cancer susceptibility allele. The S49C missense mutation, carried by less than 3% of subjects, was associated with a significantly elevated odds ratio of 1.69 (95% CI 1.19 – 2.40, P = 0.004). False positive report probability calculations indicated that this association is unlikely to be a false positive finding. The variant was slightly more common in US compared to Polish subjects, but the association with breast cancer risk was consistent between the two study populations. The variant was more common among early-onset breast cancer cases (diagnosed before age 50), but there was little difference for subjects with and without a first degree relative with breast cancer.

F858L, another missense mutation at about the same frequency as S49C, was also more common among cases but the association did not reach even nominal statistical significance. The association was mostly driven by the US study group, although the test for heterogeneity of the ORs between studies was not statistically significant. The S707P mutation was significantly less common in cases than controls in the USRT study, but is was more common in cases than controls in the Polish study. The P1526P variant was significantly lower in cases from the USRT study in an interim analysis, but upon analysis of the complete data set and when combined with the Polish data, was not associated with breast cancer risk.

Because complete sequence analysis of the ATM gene is prohibitively expensive in large epidemiologic studies, we developed assays for a set of individual AT-causing mutations. While individually rare, we hoped that combining less frequent AT-related mutations would permit us to determine whether they are associated with breast cancer. Most of the mutations we assayed were not detected in any of the USRT subjects and the summed frequency of AT-related mutations was not different between cases and controls. Two of the mutations included in our a priori list, S1691R and the intron 10 splicing mutation, were detected in more than one subject, but it may be that neither of them are true mutations: a study of the intron 10 splicing mutation published since we initiated our analyses suggests it may not increase the risk of breast cancer (Szabo et al. 2004), and the S1691R was studied because it was identified in a single British AT patient, which may, in fact, not be the AT-causing mutation in this subject. Excluding these two variants, we detected two clear AT-causing mutations in cases and none in controls. We thus were not able to contribute much information on whether truncating, AT-causing mutations are more common in breast cancer patients compared to controls.

Our most interesting association was S49C and breast cancer. This mutation, initially identified in a small series of 38 sporadic breast cancer cases (Vorechovsky et al. 1996), has also been detected in 1.6% of 192 hospital-based breast cancer cases (Dork et al. 2001) and in a study of 92 North American AT patients (Castellvi-Bel et al. 1999). It has been evaluated in at least two previous epidemiologic studies of breast cancer. It’s frequency did not differ between breast cancer cases and controls in the Multiethnic Cohort study (Bretsky et al. 2003), although there were two or fewer carriers in each of the four ethnic groups. S49C was significantly more common among 75 Caucasian breast cancer patients, enriched for second cancers and positive breast cancer family history, studied at M. D. Anderson Cancer Center compared to 940 blood bank donor controls (6.7% vs 1.3%) (Buchholz et al. 2004).

The Ser -> Cys mutation is a non-conservative amino acid substitution at residue 49, but there have been no biochemical studies of its effect on ATM function. This amino acid maps to the recently described chromatin association domain (Young et al. 2005), but does not map to the well-known functional domains of this protein. In silico analysis of the potential functional significance of this and other missense mutations were inconclusive: the S49C has a potentially intolerant “Sorting Intolerant from Tolerant” (SIFT) score, but is not predicted to be pathological with PolyPhen, while the F858L was possibly damaging in PolyPhen analyses but tolerated in SIFT analyses (Ng and Henikoff 2001; Ramensky et al. 2002).

The other coding SNPs that we evaluated have been studied previously in epidemiologic settings, but owing largely to their small sample size, the results have been inconsistent. For example, F858L has sometimes been observed more frequently in breast cancer cases than controls (3.6% vs 2.6%, 1500 total subjects) (Dork et al. 2001) while in another setting it was less frequent (2.1% vs 7.4%, 223 total subjects) (Teraoka et al. 2001). In the Multiethnic Cohort study, its frequency was similar between cases and controls (1.3% vs 1.1%, 854 total subjects) but there were only nine heterozygote carriers (Bretsky et al. 2003). The S707P mutation has usually been observed more frequently in breast cancer cases than controls (Dork et al. 2001; Teraoka et al. 2001; Bretsky et al. 2003), but it was significantly less frequent in cases from our USRT study. Whether the observed differences in our two study populations might reflect true differences in the effect of S707P on breast cancer risk due to different environmental or genetic backgrounds is unknown. We did not find any evidence for associations with two of the more common missense variants, P1054R and L1420F, which have shown inconsistent results in previous studies, nor with the very common non-coding polymorphisms studied previously (Dork et al. 2001; Teraoka et al. 2001; Bretsky et al. 2003; Tamimi et al. 2004; Lee et al. 2005).

In summary, we find that the ATM missense mutation S49C is likely to be a breast cancer susceptibility allele. The mutation is rare, and even in our combined study population of 6200 subjects, we observed it in only 133. It will be important to confirm this association in even larger study populations that can be attained through data pooling efforts, such as the Breast Cancer Association Consortium.

Supplementary Material

Supplementary Tables 1-4

Acknowledgments

This research was supported in part by the Intramural Research Program of the NIH, Division of Cancer Epidemiology and Genetics and the Center for Cancer Research, National Cancer Institute, U.S. Department of Health and Human Services. The authors would like to acknowledge Diane Kampa (University of Minnesota) for USRT study coordination; Elisha Peterson and Sarah Hardy (Laboratory of Population Genetics) and Robert Welch and Meredith Yeager (NCI Core Genotyping Facility) for laboratory and bioinformatics assistance; Anita Soni (Westat, Inc., Rockville, MD), Christopher McClure (RTI International, Research Triangle Park, NC), and Pei Chao and Laura Bowen (IMS, Inc., Silver Spring, MD) for data and sample management.

Footnotes

Participating Centers in Poland

Cancer Center and M. Skodowska-Curie Institute of Oncology in Warsaw: Departments of Epidemiology (Coordinating center: Dr. Jolanta Lissowska, Mrs. Alicja Bardin-Mikolajczak, Dr. Witold Zatonski), Breast Cancer Treatment and Reconstruction (Drs. Edward Towpik and Jerzy Giermek), Departments of Surgical Oncology (Dr. Pawel Kukawski) Pathology (Drs. Grzegorz Rymkiewicz, Marcin Ligaj, Joanna Barawska, Agnieszka Turowicz, Wlodzimierz Olszewski).

Polish Oncological Foundation in Warsaw: Pathology (Drs. Dorota Mazepa-Sikora, Wlodzimierz Olszewski ).

Nofer Institute of Occupational Medicine in Łódź (Drs. Neonila Szeszenia-Dybrowska, Beata Peplonska).

Medical University, Community Copernicus Hospital in Łódź: Departments of Surgical Oncology (Drs. Arkadiusz Jeziorski, Janusz Piekarski), and Pathology (Drs. Radzislaw Kordek, Pasz-Walczak, Kubiak, Kupnicka, Olborski).

Polish Mother’s Health Memorial Hospital in Łódź: Departments Surgical Oncology and Breast Diseases (Drs. Marcin Faflik, Magdalena Baklinska, Marek Zadrozny, Boguslaw Westfal) and Clinical Pathomorphology (Drs. Stanislaw Lukaszek, Andrzej Kulig).

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Supplementary Materials

Supplementary Tables 1-4
NIHMS13666-supplement-Supp.pdf (100.7KB, pdf)

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