Abstract
Background:
The TP53 pathway, in which TP53 and its negative regulator MDM2 are the central elements, has an important role in carcinogenesis, particularly in BRCA1- and BRCA2-mediated carcinogenesis. A single nucleotide polymorphism (SNP) in the promoter region of MDM2 (309T>G, rs2279744) and a coding SNP of TP53 (Arg72Pro, rs1042522) have been shown to be of functional significance.
Methods:
To investigate whether these SNPs modify breast cancer risk for BRCA1 and BRCA2 mutation carriers, we pooled genotype data on the TP53 Arg72Pro SNP in 7011 mutation carriers and on the MDM2 309T>G SNP in 2222 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Data were analysed using a Cox proportional hazards model within a retrospective likelihood framework.
Results:
No association was found between these SNPs and breast cancer risk for BRCA1 (TP53: per-allele hazard ratio (HR)=1.01, 95% confidence interval (CI): 0.93–1.10, Ptrend=0.77; MDM2: HR=0.96, 95%CI: 0.84–1.09, Ptrend=0.54) or for BRCA2 mutation carriers (TP53: HR=0.99, 95%CI: 0.87–1.12, Ptrend=0.83; MDM2: HR=0.98, 95%CI: 0.80–1.21, Ptrend=0.88). We also evaluated the potential combined effects of both SNPs on breast cancer risk, however, none of their combined genotypes showed any evidence of association.
Conclusion:
There was no evidence that TP53 Arg72Pro or MDM2 309T>G, either singly or in combination, influence breast cancer risk in BRCA1 or BRCA2 mutation carriers.
Keywords: TP53 , MDM2 , BRCA1/2 , breast cancer, polymorphism, risk
The TP53 pathway is crucial for tumour suppression, acting through regulation of cell-cycle control, apoptosis, senescence and DNA repair. The TP53 gene and its negative regulator MDM2 are central to this pathway, promoting polyubiquitination and degradation of TP53, and also controlling the TP53 synthesis (Toledo and Wahl, 2006; Candeias et al, 2008). Inactivation of the TP53 pathway has an important role in BRCA1- and BRCA2-associated tumourigenesis. BRCA1 and BRCA2 mutations are associated with genomic instability caused by defective cell-cycle checkpoint and DNA damage repair (Deng, 2006). Mouse model studies have highlighted functional links between these genes. Biallelic inactivation of BRCA1 and BRCA2 in mice have shown that embryonic lethality because of growth retardation can be partially rescued in a Trp53 null background (Evers and Jonkers, 2006). The development of mammary tumours in conditional BRCA1 and BRCA2 knockout mice was considerably accelerated in a Trp53 knockout background (Evers and Jonkers, 2006). In addition, a high incidence of TP53 mutations has been found in breast tumours of human BRCA1 and BRCA2 mutation carriers (Greenblatt et al, 2001; Manie et al, 2009). The observed interactions between TP53 and BRCA pathways are integral to the progression of tumourigenesis in breast cancer.
A TP53 polymorphism (rs1042522) has been found to be of functional significance, with the Pro72 allele being less efficient than Arg72 at inducing apoptosis, mainly due to weaker binding and ubiquitination by MDM2 of the Pro72 variant protein (Dumont et al, 2003; Osorio et al, 2006). An SNP in the promoter region of MDM2 (309T>G, rs2279744) has been shown to increase MDM2 transcriptional activity, thus attenuating the TP53 pathway (Bond et al, 2004). This latter SNP was associated with an earlier onset of breast cancer in Li–Fraumeni patients carrying TP53 mutations (Bougeard et al, 2006; Ruijs et al, 2007). The effect on breast cancer risk of the TP53 Arg72Pro and the MDM2 309T>G polymorphisms, separately and in combination, was investigated in a large case–control study by the Breast Cancer Association Consortium (BCAC), but no association was detected (Schmidt et al, 2007). However, several smaller studies examined these polymorphisms in BRCA1 and BRCA2 mutation carriers (Martin et al, 2003; Tommiska et al, 2005; Copson et al, 2006; Osorio et al, 2006; Wasielewski et al, 2007; Yarden et al, 2008), and some suggested an association between the TP53 Pro72 and the MDM2 309G alleles with an earlier age at breast cancer diagnosis (Martin et al, 2003; Tommiska et al, 2005; Osorio et al, 2006; Yarden et al, 2008). We therefore investigated the associations between breast cancer risk and these TP53 and MDM2 polymorphisms in a large series of BRCA1 and BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) (Chenevix-Trench et al, 2007).
Materials and methods
Study sample
Eligibility was restricted to female carriers with pathogenic mutations in BRCA1 or BRCA2 who were ⩾18 years. Data were obtained from 13 CIMBA studies (Table 1). The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and enrolled into national or regional studies. Information collected included the year of birth; mutation description; age at last followup; ages at breast and ovarian cancer diagnosis; and age at bilateral prophylactic mastectomy. Information was also available on the country of residence, which was defined to be the country of the clinic at which the carrier family was recruited for the study. Related individuals were identified through a unique family identifier. Further details of the information collected on the BRCA1 and BRCA2 mutation carriers and other details of the CIMBA initiative can be found elsewhere. Additional specific acknowledgements to the CIMBA collaborating centres are included in the Supplementary Appendix. (http://www.srl.cam.ac.uk/consortia/cimba/index.html) (Chenevix-Trench et al, 2007). All carriers participated in clinical and research studies at the host institutions under IRB-approved protocols.
Table 1. Number of BRCA1 and BRCA2 mutation carriers by study and by single nucleotide polymorphism (SNP).
| Study | Country | TP53 Arg72Pro (rs1042522) | MDM2 309T>G (rs2279744) | Genotyping platform |
|---|---|---|---|---|
| Spanish National Cancer Centre (CNIO) | Spain | 788 | 0 | Restriction enzyme digestion |
| Deutsches Krebsforschungszentrum (DKFZ) | Germany | 170 | 0 | PCR-based RFLP |
| Epidemiological study of BRCA1 and BRCA2 mutation carriers (EMBRACE) | U.K. and Eire | 1131 | 0 | iPLEX |
| Genetic Modifiers of cancer risk in BRCA1/2 mutation carriers (GEMO) | France and U.S.A. | 1405 | 1357 | Taqman |
| German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC) | Germany | 815 | 0 | Taqman |
| Helsinki Breast Cancer Study (HEBCS) | Finland | 188 | 187 | rs1042522: Amplifluor(tm) fluorescent genotyping (Kbiosciences); rs2279744: RFLP |
| HEreditary Breast and Ovarian study Netherlands (HEBON) | The Netherlands | 438 | 432 | Taqman |
| INterdisciplinary HEalth Research International Team BReast CAncer susceptibility (INHERIT BRCAs) | Quebec-Canada | 146 | 155 | Taqman |
| kConFab | Australia | 790 | 0 | iPLEX |
| National Cancer Institute (NCI) | USA | 190 | 0 | Taqman |
| National Israeli Cancer Control Center (NICCC) | Israel | 470 | 0 | Taqman |
| Ontario Cancer Genetics Network (OCGN) | Canada | 84 | 91 | Taqman |
| University of Pennsylvania (UPENN) | USA | 396 | 0 | iPLEX |
| Total | 7011 | 2222 |
Genotyping
We pooled genotype data from studies within CIMBA that had previously genotyped polymorphisms rs1042522 and rs2279744 (see Table 1). Deviation from Hardy–Weinberg equilibrium among unrelated subjects was evaluated separately for each SNP and study. There was evidence for deviation for only one study (P=0.03), but cluster plot examination did not show any unusual pattern and the study was included in the analysis. Where available study specific genotyping quality control data were examined and data were included if the call rate was over 95% and the concordance among duplicates was over 98%.
Statistical analysis
Mutation carriers were classified according to their age at diagnosis of breast cancer or their age at last follow up. For this purpose, individuals were censored at the age of first breast cancer diagnosis, ovarian cancer diagnosis, bilateral prophylactic mastectomy or the age at last observation. Only individuals censored at breast cancer diagnosis were assumed to be affected (Table 2).
Table 2. Summary characteristics for the 7109 eligible BRCA1 and BRCA2 carriers used in the analysis and typed for either single nucleotide polymorphism (SNP).
| BRCA1 | BRCA2 | |||
|---|---|---|---|---|
| Characteristic | Unaffected | Breast cancer | Unaffected | Breast cancer |
| Number | 2055 | 2567 | 1051 | 1436 |
| Person-years follow-up | 87 571 | 104 679 | 46 315 | 63 080 |
| Median age at censure (IQR) | 41 (33–51) | 40 (34–46) | 42 (34–52) | 43 (37–50) |
| Age at censure (years), N (%) | ||||
| <30 | 327 (15.9) | 225 (8.8) | 139 (13.2) | 78 (5.4) |
| 30–39 | 584 (28.4) | 1052 (41.0) | 296 (28.1) | 462 (32.2) |
| 40–49 | 574 (27.9) | 880 (34.3) | 286 (27.2) | 511 (35.6) |
| 50–59 | 364 (17.7) | 296 (11.5) | 196 (18.7) | 278 (19.4) |
| 60–69 | 134 (6.5) | 87 (3.4) | 82 (7.8) | 81 (5.6) |
| 70+ | 72 (3.5) | 27 (1.0) | 52 (4.9) | 26 (1.8) |
| Year of birth, N (%) | ||||
| <1920 | 18 (0.9) | 32 (1.3) | 12 (1.1) | 10 (0.7) |
| 1920–29 | 63 (3.1) | 117 (4.6) | 39 (3.7) | 83 (5.8) |
| 1930–39 | 171 (8.3) | 267 (10.4) | 96 (9.1) | 196 (13.7) |
| 1940–49 | 326 (15.9) | 657 (25.6) | 143 (13.6) | 358 (24.9) |
| 1950–59 | 481 (23.4) | 820 (31.9) | 241 (22.9) | 459 (32.0) |
| 1960+ | 996 (48.5) | 674 (26.3) | 520 (49.5) | 330 (23.0) |
Abbreviation: IQR=interquartile range.
To correct for a potential bias related to the fact that BRCA1 and BRCA2 mutation carriers are not randomly sampled with respect to their disease status, the data were analysed within a survival analysis framework, by modelling the retrospective likelihood of the observed genotypes conditional on the disease phenotypes. A detailed description of the retrospective likelihood approach has been published (Antoniou et al, 2007). We used a Cox proportional hazards model, where the effect of each SNP was modelled either as a per-allele hazard ratio (HR) or using separate HRs for heterozygotes and homozygotes. To assess the combined effects of the SNPs, we fitted a model in which a separate HR parameter was estimated for each multilocus genotype. More details of the statistical analysis can be found elsewhere (Antoniou et al, 2008).
Results
In total, 7011 BRCA1 and BRCA2 mutation carriers were genotyped for TP53 Arg72Pro and 2222 mutation carriers were genotyped for MDM2 309T>G (Table 1). Table 2 shows summary statistics for the cohort of BRCA1 and BRCA2 mutation carriers with an observed genotype for either the TP53 or MDM2 polymorphism. There was no evidence of an association between either SNP and breast cancer risk in BRCA1 or BRCA2 mutation carriers combined or analysed separately (TP53 Arg72Pro: Ptrend=0.89, 0.77 and 0.83, respectively; MDM2 309T>G: Ptrend=0.60, 0.54 and 0.88, respectively) (Table 3). There was no evidence for heterogeneity in the HRs between studies (TP53 Arg72Pro: P=0.22 and 0.93, MDM2 309T>G: P=0.11 and 0.82 for BRCA1 or BRCA2 mutation carriers respectively). The HRs for the 9 TP53–MDM2 combined genotypes, estimated separately in BRCA1 and BRCA2 mutation carriers, ranged between 0.72 and 1.31, but none of them were significant.
Table 3. Genotype frequencies by mutant gene and breast cancer status with hazard ratio (HR) estimates.
| Unaffected (%) | Affected (%) | HR | 95% CI | P-value | |
|---|---|---|---|---|---|
| TP53 Arg72Pro (rs1042522) | |||||
| BRCA1/2 | |||||
| GG | 1660 (54.4) | 2164 (54.7) | 1.00 | ||
| GC | 1178 (38.6) | 1508 (38.1) | 1.00 | 0.92–1.10 | |
| CC | 214 (7.0) | 287 (7.3) | 1.01 | 0.85–1.20 | |
| 2-df test | 0.99 | ||||
| Per allele | 1.01 | 0.94–1.08 | 0.89 | ||
| BRCA1 | |||||
| GG | 1127 (56.0) | 1399 (55.2) | 1.00 | ||
| GC | 748 (37.2) | 947 (37.4) | 1.01 | 0.90–1.13 | |
| CC | 138 (6.9) | 188 (7.4) | 1.03 | 0.84–1.27 | |
| 2-df test | 0.96 | ||||
| Per allele | 1.01 | 0.93–1.10 | 0.77 | ||
| BRCA2 | |||||
| GG | 533 (51.3) | 765 (53.7) | 1.00 | ||
| GC | 430 (41.4) | 561 (39.4) | 0.98 | 0.84–1.14 | |
| CC | 76 (7.3) | 99 (6.9) | 0.99 | 0.72–1.36 | |
| 2-df test | 0.95 | ||||
| Per allele | 0.99 | 0.87–1.12 | 0.83 | ||
| MDM2 309T>G (rs2279744) | |||||
| BRCA1/2 | |||||
| TT | 358 (40.3) | 530 (39.8) | 1.00 | ||
| TG | 405 (45.6) | 615 (46.1) | 0.99 | 0.84–1.18 | |
| GG | 126 (14.2) | 188 (14.1) | 0.93 | 0.73–1.17 | |
| 2-df test | 0.79 | ||||
| Per allele | 0.97 | 0.87–1.08 | 0.60 | ||
| BRCA1 | |||||
| TT | 275 (39.7) | 369 (39.5) | 1.00 | ||
| TG | 323 (46.6) | 443 (47.4) | 0.98 | 0.81–1.19 | |
| GG | 95 (13.7) | 123 (13.2) | 0.91 | 0.67–1.19 | |
| 2-df test | 0.78 | ||||
| Per allele | 0.96 | 0.84–1.09 | 0.54 | ||
| BRCA2 | |||||
| TT | 83 (42.4) | 161 (40.5) | 1.00 | ||
| TG | 82 (41.8) | 172 (43.2) | 1.07 | 0.77–1.50 | |
| GG | 31 (15.8) | 65 (16.3) | 0.93 | 0.60–1.44 | |
| 2-df test | 0.83 | ||||
| Per allele | 0.98 | 0.80–1.21 | 0.88 | ||
Discussion
To our knowledge, this is the largest study to investigate the hypothesis that TP53 Arg72Pro and MDM2 309T>G influence breast cancer risk in BRCA1 and BRCA2 mutation carriers individually or in combination. Our findings of no association for these SNPs suggest that they have little or no effect on BRCA-related breast cancer risk. These results are consistent with the absence of risk association in the recent TP53 haplotype analysis, involving Arg72Pro and an intronic polymorphism c.97-147ins16 bp, in a series of 2932 BRCA1 and BRCA2 carriers from CIMBA (Osorio et al, 2008). Our sample of mutation carriers had power of approximately 75% for TP53 and 40% for MDM2 to detect significant associations (P<0.05) for a per-allele HR of 1.1 and power of 100 and 90% respectively for a HR of 1.2, suggesting that we can reliably dismiss previously suggested associations (Martin et al, 2003; Osorio et al, 2006; Yarden et al, 2008).
Yarden et al showed that the MDM2 GG genotype among Ashkenazi BRCA1/2 mutations carriers was significantly associated with breast cancer diagnosed <age 51 (P=0.019) (Yarden et al, 2008). However, we did not find any evidence of an increased risk for the GG homozygotes among the 217 carriers of the BRCA1 Ashkenazi mutations 185delAG and 5382insC (HR=0.98, 95%CI 0.48–2.01) in this series.
The BCAC study of 5191 cases and 3834 controls found no evidence of an association of TP53 Arg72Pro and MDM2 309T>G either with breast cancer overall or with oestrogen receptor (ER) status of tumours (Schmidt et al, 2007). As the majority of BRCA1 mutation-associated breast tumours are ER-negative (Lakhani et al, 2005), the absence of an association in our study of breast cancer with the TP53 and MDM2 SNPs in BRCA1 mutation carriers is consistent with the lack of an association with ER-negative cancers in the general population.
Acknowledgments
The CIMBA data management, DE, LM, SP, MC and EMBRACE are supported by Cancer Research UK Grants C1287/A10118 and C1287/A8874. CL is supported by Cancer Research UK Grant C8197/A10123. ACA is a Cancer Research – UK Senior Cancer Research Fellow.
Jacques Simard is Chairholder of the Canada Research Chair in Oncogenetics. This work was supported by the Canadian Institutes of Health Research for the ‘CIHR Team of Prediction and Communication of Familial Risks of Breast Cancer’ program. Daniel Sinnett holds the François-Karl Viau Chair in Pediatric Oncogenomics and is a scholar of the Fonds de la Recherche en Santé du Québec (FRSQ).
We thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by grants from the National Breast Cancer Foundation, the National Health and Medical Research Council (NHMRC) and by the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. The kConFab Clinical Follow Up Study has been funded by NHMRC grants 145684, 288704 and 454508. ABS and GCT are NHMRC fellows.
We gratefully acknowledge the contribution of Dr Jeffery P Struewing and Marbin Pineda for their laboratory support of this project. Drs Greene and Loud were supported by funding from the Intramural Research Program of the US National Cancer Institute, and from research contracts NO2-CP-11019-50 and N02-CP-65504 with Westat, Rockville, MD, USA.
The NICCC thanks the laboratory technicians Mrs. Irena Rimon and Mrs. Ana Gurtovnik for their technical support.
OCGN: We thank Mona Gill and Nayana Weerasooriya for assistance and we acknowledge funding from Cancer Care Ontario.
We thank Alicia Barroso, Concepción Hernandez and Anna Gonzalez for their technical support. The CNIO study was partially funded by the Asociación Española Contra el Cáncer (AECC), the Fundación Marató and the project PI081120 from the Ministry of Science and Innovation.
We thank Diana Torres and Muhammad U Rashid for providing DNA samples and supplying data. We thank Antje Seidel-Renkert for expert technical assistance. The DKFZ study was supported by the DKFZ.
The HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, NKI 2007-3756.
The investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. RE, EB and L D'M are also supported by Cancer Research UK Grant C5047/A8385. DGE and FL are supported the NIHR Biomedical Research Centre, Manchester.
We wish to thank all the GEMO collaborating members (Cancer Genetics Network ‘Groupe Génétique et Cancer’, Fédération Nationale des Centres de Lutte Contre le Cancer, France) for their contribution to this study. The GEMO study was supported by the Ligue National Contre le Cancer and the Association ‘Le cancer du sein, parlons-en!’ Award.
We thank Juliane Koehler for her excellent technical assistance and the 12 centers of the GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) for providing samples and clinical data. GC-HBOC is supported by a grant of the German Cancer Aid (grant 107054) and the Center for Molecular Medicine Cologne (grant TV93) to Rita K Schmutzler.
We thank Drs Kirsimari Aaltonen, Carl Blomqvist and RN Hanna Jäntti for their help with the patient data and Dr Johanna Tommiska for her kind help with the genetic analyses. The Finnish Cancer registry is gratefully acknowledged for the cancer data. The HEBCS study has been financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (110663), Finnish Cancer Society and the Sigrid Juselius Foundation.
Footnotes
Supplementary Information accompanies the paper on British Journal of Cancer website (http://www.nature.com/bjc)
Supplementary Material
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