Skip Navigation


Carcinogenesis Advance Access originally published online on April 21, 2007
Carcinogenesis 2007 28(8):1680-1686; doi:10.1093/carcin/bgm097
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
28/8/1680    most recent
bgm097v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (9)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Sprague, B. L.
Right arrow Articles by Egan, K. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sprague, B. L.
Right arrow Articles by Egan, K. M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Genetic variation in TP53 and risk of breast cancer in a population-based case–control study

Brian L. Sprague1,2, Amy Trentham-Dietz1,2,*, Montserrat Garcia-Closas3, Polly A. Newcomb2,4, Linda Titus-Ernstoff5, John M. Hampton2, Stephen J. Chanock3, Jonathan L. Haines6 and Kathleen M. Egan7

1 Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI 53726, USA
2 University of Wisconsin Paul P. Carbone Comprehensive Cancer Center, Madison, WI 53726, USA
3 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20952, USA
4 Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
5 Dartmouth Medical School, Norris Cotton Cancer Center, Lebanon, NH 03756, USA
6 Center for Human Genetics Research, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
7 Division of Cancer Prevention and Control, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA

* To whom correspondence should be addressed. Tel: +1 608 263 1946; Fax: +1 608 265 5330; Email: trentham{at}wisc.edu


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Whereas germ line missense mutations in the tumor suppressor gene TP53 are associated with a marked predisposition to breast cancer, single-nucleotide polymorphisms (SNPs) may play a more modest role in breast cancer susceptibility. We examined genetic variation in TP53 in relation to breast cancer risk among women aged 20–74 years in a population-based case–control study in Wisconsin, Massachusetts and New Hampshire. Analyses were conducted separately for in situ (176 cases/581 controls) and invasive (1490 cases/1291 controls) breast cancer. Oral mucosal DNA samples were genotyped for the codon 72 polymorphism in exon 4 (rs1042522), seven intronic SNPs and three SNPs residing in the 3' untranslated region (UTR). Logistic regression was used to obtain age- and state-adjusted odds ratios for individual SNPs. Haplotypes were reconstructed using PHASE software, and the overall association with breast cancer risk was assessed using a global score test. None of the 11 individual SNPs or eight common haplotypes were significantly related to breast carcinoma in situ risk. Among all women, two linked SNPs (D' = 0.99, r2 = 0.95) on intron 7 (rs12951053, rs12947788) were associated with modest increases in invasive breast cancer risk; however, associations were only significant for heterozygous carriers. The data suggested that additional variants in the 3' UTR (rs9894946), and in two correlated SNPs (D' = 0.94, r2 = 0.81) in introns 6 (rs1625895) and 4 (rs2909430), were associated with reduced invasive breast cancer risk among women aged 50 and younger only (Pinteraction < 0.03). These results indicate that common variation in the TP53 gene could modify the risk of invasive breast cancer.

Abbreviations: 95% CI, 95% confidence interval; HWE, Hardy–Weinberg equilibrium; OR, odds ratio; SNP, single-nucleotide polymorphism; UTR, untranslated region


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
The human tumor suppressor gene TP53 encodes a transcription factor at the center of a network that inhibits cell growth and stimulates apoptosis in response to cellular stresses such as DNA damage (1–3). Over 20 000 alterations in TP53 have been discovered in human tumors (4,5), with an estimated 30% of breast cancers containing a TP53 mutation (6). Moreover, germ line mutations in the TP53 gene cause Li–Fraumeni syndrome, an autosomal dominant disorder characterized by inherited susceptibility to breast cancer, osteosarcoma, leukemia, brain and adrenocortical tumors at an early age (7–9). The excess risk of breast cancer associated with Li–Fraumeni syndrome is known to decline with increasing age (10); thus, it is possible that single-nucleotide polymorphisms (SNPs) in TP53 may affect breast cancer risk in a similar age-dependent manner.

At least 37 SNPs in the TP53 gene have been identified (11); yet few have been examined in relation to breast cancer risk. The most widely studied is the Ex4+119C>G polymorphism in codon 72 of exon 4 (TP53-01; rs1042522), which encodes an arginine–proline substitution. However, a recent pooled analysis of >8700 women with breast cancer and 10 000 controls indicated no overall association of the codon 72 polymorphism with breast cancer risk, and no evidence for modification by age at onset (12).

The IVS6+62A>G polymorphism in intron 6 (TP53-16; rs1625895) has also been studied in relation to breast cancer risk. Although the results have been inconsistent (13,14), a few studies suggest an increased risk of breast cancer with the minor allele for this variant (15–18). Additionally, a number of studies have examined breast cancer risk in relation to TP53 haplotypes consisting of TP53-01 in codon 72 of exon 4, TP53-16 in intron 6 and a 16 bp insertion/deletion in intron 3, with mixed results (14–16,19–21). One study has reported that the association between this haplotype and breast cancer risk varies according to age at breast cancer onset (15).

The majority of studies of TP53 polymorphisms and breast cancer risk have been hospital based, evaluated only a few SNPs and were limited by a small sample size (<1000 cases). In this large population-based case–control study, we carried out a comprehensive evaluation of common variation in TP53 SNPs and risk of in situ (n = 176 cases) and invasive breast cancer (n = 1490 cases). The 11 SNPs evaluated were chosen based on their identification as having minor allele frequencies >0.03 in an NCI SNP500Cancer re-sequence project in 94 healthy Norwegian women (Table I) (11). The large sample size enabled us to consider whether the association between genetic variation in TP53 and breast cancer risk is modified by age of breast cancer onset and menopausal status.


View this table:
[in this window]
[in a new window]

  		Table I. TP53 SNP nomenclaturea

 

   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Study population
We genotyped DNA collected from women enrolled in a large population-based case–control study conducted in Wisconsin, Massachusetts and New Hampshire, details of which have been published previously (22,23). The study was conducted according to protocols approved by the institutional review boards at the University of Wisconsin (Madison, WI), Harvard University (Boston, MA), Dartmouth Medical School (Lebanon, NH) and the National Cancer Institute.

The study population has been described previously (22). Briefly, eligible cases were all English-speaking female residents of Massachusetts (excluding metropolitan Boston), New Hampshire and Wisconsin, with a new diagnosis of invasive (aged 20–69 years) or in situ breast cancer (aged 20–74 years, MA and NH only) reported to each state's mandatory cancer registry during 1996–2000. Eligibility was limited to cases with known dates of diagnosis, and for comparability with controls, listed telephone numbers and driver's licenses verified by self-report (if <65 years of age). Controls were randomly selected in each state from the community using two sampling frames: those under 65 years of age were selected from lists of licensed drivers and those 65–74 years of age were selected from a roster of Medicare beneficiaries compiled by the Centers for Medicare & Medicaid Services. Controls were selected at random within 5-year age strata to yield an age distribution similar to the cases enrolled in each state and were required to have no personal history of breast cancer, to have a listed telephone number and, if <65 years of age, to be a licensed driver.

At the conclusion of each interview, participants were asked if they would be willing to contribute a buccal sample. The present analysis is based on women interviewed between January 2000 and April 2001 who provided a DNA sample using an oral rinse protocol (23). A total of 204 (76%) in situ cases, 1708 (70%) invasive cases and 1527 (61%) controls returned a DNA sample. Interviewed women who did not provide a buccal swish sample were younger and were slightly more likely to be pre-menopausal when compared with those who returned a DNA sample.

TP53 SNP genotyping
We genotyped for all 11 TP53 SNPs with minor allele frequency >0.03 identified in a re-sequence project in 94 healthy Norwegian women (11). Thus, SNPs with very little degree of expected variation were not studied. The genotyped SNPs included the TP53-01 codon 72 polymorphism (Ex4+119C>G), seven intronic SNPs and three SNPs residing in the 3' untranslated region (UTR).

Collected swish samples were sent directly by subjects via priority mail to a National Cancer Institute-affiliated laboratory for processing. Collection, storage and DNA isolation were conducted according to protocols described previously (23). Whole genome amplification using multiple displacement amplification (Qiagen, Valencia, CA) was undertaken to increase the amount of DNA available for genetic analysis (24).

Genotypes were evaluated using validated Taqman or MGM Eclipse assays, which are described in detail for each SNP at http://snp500cancer.nci.nih.gov (11). Genomic DNA for 95 subjects was included randomly throughout the 11 whole genome amplification plates for quality control. Genotyping concordance with amplified paired DNA samples was 100% for eight SNPs; among the remaining TP53 SNPs, concordances were 97% for TP53-15 in the 3' UTR, 93% for TP53-16 in intron 6 and 76% for TP53-66 in intron 4.

For each polymorphism, Hardy–Weinberg equilibrium (HWE) was tested by comparing the observed to expected genotype frequencies in controls. Genotypes for 9 of the 11 SNPs were consistent with HWE (P ≥ 0.10), whereas in two (TP53-09 in intron 1 and TP53-65 in intron 4) violation of HWE was suggested (P = 0.04); in both instances, the number of observed heterozygotes exceeded the expected number under HWE.

Reconstruction of the TP53 haplotype incorporating the 11 SNPs was accomplished using PHASE software (25,26). Eight distinct haplotypes were observed in the study population with a frequency >1%.

Statistical analysis
For each case, a reference date was defined as the registry-supplied date of breast cancer diagnosis. For comparability, the control subjects interviewed contemporaneously with cases were assigned an individual reference date. Using the anticipated interview date of the control and a random number based on the normal distribution of days from diagnosis to interview in the cases already interviewed (based on state and 5-year age group relative to the control), the individual control reference date was calculated. This was done to maintain comparability between cases and controls, and to maintain interviewer blinding to case–control disease status. Reference age was defined as the woman's age at the reference date. Only exposures that occurred at least a year prior to the assigned reference date were included in the analyses.

Two groups of overlapping controls were utilized in these analyses. For the analysis of breast carcinoma in situ, control women consisted of those aged 20–74 from Massachusetts and New Hampshire. For the analysis of invasive breast cancer, control women were those aged 20–69 from Massachusetts, New Hampshire and Wisconsin.

Multivariable logistic regression was used to obtain age- and state of residence-adjusted odds ratios (ORs) and 95% confidence intervals (95% CI) for individual SNPs and haplotypes. Tests for trend in breast cancer risk for each SNP were conducted by inclusion of an indicator term representing the number of minor alleles at the SNP (0, 1, 2). For each SNP, effect modification by age was evaluated by the inclusion of a cross-product term containing age (continuous) multiplied by the respective SNP (0, 1 or 2 minor alleles) in separate regression models. Each individual was assigned the ‘best pair’ of haplotypes estimated by PHASE software. A global score test was used to evaluate the age- and state of residence-adjusted differences in haplotype frequencies between cases and controls. For each haplotype, effect modification by age was evaluated by the inclusion of a cross-product term containing age (continuous) and the indicator variable (0, 1, 2) representing each specific haplotype. Effect modification by menopausal status was also considered by inclusion of a cross-product term containing menopausal status (pre-/post-menopausal) and the SNP or haplotype indicator variable. All regression analyses were performed using SAS Statistical Software (Version 9; SAS Institute, Cary, NC). ORs were further adjusted for potentially confounding variables selected a priori: age at reference date; family history of breast cancer in mother, sister or daughter; screening mammograms per year between 6 years and 1 year prior to the reference date; menopausal status; age at menarche; age at first full-term birth; parity; age at menopause; post-menopausal hormone use; weight at age 18; weight change since age 18 until 1 year prior to reference date; alcohol consumption; education and state. For each variable, an indicator term was incorporated in models for missing data. We observed little evidence of confounding of genetic associations by established breast cancer risk factors; therefore, results are shown from age-adjusted (20–49, 50–59 and 60–69 years) and state-adjusted (Massachusetts, New Hampshire and Wisconsin) models.

Amplified DNA was subject to routine quality control checks including the 16 allele IdentifilerTM test (Applied Biosystems, Foster City, CA). Samples missing data for at least one of the 16 test markers were excluded from the analysis due to concerns regarding DNA quality (n = 273). Ninty-six samples were excluded due to insufficient DNA. Finally, to limit heterogeneity of the study population, the analyses were restricted to women of self-reported European descent (97% of study participants). These exclusions left a total of 176 cases and 581 controls available for the analysis of breast carcinoma in situ, and 1490 cases and 1291 controls available for the analysis of invasive breast cancer.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
A comparison of cases and controls by selected breast cancer risk factors is shown in Table II. As expected, women with breast cancer were older at first birth and at menopause, had fewer children, had higher utilization of screening mammography and were more likely to have a family history of breast cancer and to have used post-menopausal hormones. Women with invasive breast cancer were younger at menarche than controls. The average age at diagnosis for in situ and invasive breast cancer cases was 56.7 and 54.2 years, respectively.


View this table:
[in this window]
[in a new window]

  		Table II. Characteristics of breast cancer cases and controls

 
Results for the 11 individual TP53 SNPs are shown in Table III. None of the investigated SNPs were related to risk of breast carcinoma in situ at a statistically significant level. These results were not modified by age at diagnosis or menopausal status (data not shown). Five of the SNPs (TP53-71 in the 3' UTR, TP53-11 and TP53-10 in intron 7, TP53-65 in intron 4 and TP53-09 in intron 1) were uncommon in this population and no homozygotes for the minor allele were observed among those with in situ breast cancers.


View this table:
[in this window]
[in a new window]

  		Table III. Polymorphisms in TP53 and ORs for breast carcinoma in situ and invasive breast cancer

 
Three TP53 SNPs had borderline statistically significant associations with invasive breast cancer risk (Table III). Women heterozygous for the TP53-15 polymorphism in the 3' UTR had a modestly decreased risk of invasive breast cancer compared with women homozygous for the major allele (OR: 0.84; 95% CI: 0.71–1.00). In contrast, heterozygosity at two linked SNPs (TP53-11 and TP53-10; D' = 0.99, r2 = 0.95) on intron 7 was associated with ~25% increased risk of invasive breast cancer. The test for trend in risk with number of minor alleles reached statistical significance only for TP53-11 (Ptrend = 0.05). The sequence changing TP53-01 polymorphism on exon 4 had no overall association with invasive breast cancer risk (CC/CG versus GG, OR: 0.99; 95% CI: 0.86–1.16).

We considered whether age at diagnosis modified the associations of TP53 SNPs with invasive breast cancer risk (Table IV). Among women <50 years of age (491 cases, 427 controls), carriers of the minor allele for three of the SNPs (TP53-15 in the 3' UTR, TP53-16 in intron 6 and TP53-66 in intron 4) had a reduced risk of invasive breast cancer (Pinteraction < 0.01; D' = 0.78, r2 = 0.47 for TP53-15 and TP53-16; D' = 0.87, r2 = 0.52 for TP53-15 and TP53-66; D' = 0.94, r2 = 0.81 for TP53-16 and TP53-66). In each instance, a statistically significant trend in risk was observed with increasing number of minor alleles (Ptrend < 0.01). Conversely, among women aged 50 years and older (999 cases, 864 controls), for each of the three SNPs, risk was modestly and non-significantly elevated among women homozygous for the minor allele. Similar findings were observed in analyses stratified by age with a cut-point of 45 years, although the results were less precise (data not shown).


View this table:
[in this window]
[in a new window]

  		Table IV. Polymorphisms in TP53 and ORs for invasive breast cancer, by age at diagnosis

 
We examined all TP53 SNP associations for potential interaction by menopausal status and the results were essentially similar to those shown for age at breast cancer onset; specifically, the reduction in invasive breast cancer risk associated with the minor alleles at TP53-15 in the 3' UTR, TP53-16 in intron 6 and TP53-66 in intron 4 was limited to pre-menopausal women (Pinteraction < 0.04).

Eight common TP53 haplotypes with frequencies >1% were identified (Table V). None of the eight haplotypes for TP53 (based on the best pair assignments) were significantly associated with risk of breast carcinoma in situ, overall (global test: P = 0.93) or by age or menopausal status (data not shown). Similarly, none of the haplotypes were associated with risk of invasive breast cancer overall. However, in analyses stratified on age, one haplotype (ID no. 7 in the table) was significantly under-represented among younger women with breast cancer (OR: 0.65; 95% CI: 0.46–0.91), whereas this haplotype had no significant association with breast cancer risk among older women (Pinteraction = 0.03). This haplotype included the minor alleles at TP53-15 in the 3' UTR, TP53-16 in intron 6 and TP53-66 in intron 4, which were all individually associated with reduced breast cancer risk among younger women. There were no substantial changes to these results when the haplotype analyses were weighted based on the probability of the haplotype pair assignment, rather than using the best pairs; the OR for haplotype number 7 among women <50 years of age was 0.64 (95% CI: 0.45–0.90) in the weighted analysis (Pinteraction = 0.01). Finally, the group of rare haplotypes with frequencies each <1% was associated with a reduced risk of invasive breast cancer among women <50 years old (OR = 0.68, 95% CI: 0.46–0.99). Global tests for a haplotype association with invasive breast cancer risk were significant in the younger (P = 0.03) but not the older (P = 0.72) women.


View this table:
[in this window]
[in a new window]

  		Table V. Haplotypes of TP53 polymorphisms and risk of breast carcinoma in situ and invasive breast cancer

 
Similarly, an interaction between haplotype number 7 and menopausal status was detected (Pinteraction = 0.04), although the reduced risk of invasive breast cancer among pre-menopausal women did not reach statistical significance (OR: 0.75; 95% CI: 0.54–1.05). The group of rare haplotypes was associated with reduced invasive breast cancer risk in pre-menopausal women only, though this also failed to reach statistical significance (OR: 0.77; 95% CI: 0.55–1.09).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
The results of this large population-based case–control study suggest that genetic variation in the tumor suppressor gene TP53 may alter risk of invasive breast cancer. Minor alleles for two linked SNPs in intron 7 (TP53-11 and TP53-10) were associated with increased risk of invasive breast cancer among all women, although these were of borderline statistical significance. Minor alleles for three additional SNPs (TP53-15 in the 3' UTR, TP53-16 in intron 6 and TP53-66 in intron 4) and one haplotype carrying variant alleles for these SNPs were associated with reduced risk among younger women only (aged 50 years and younger). Results for in situ breast cancer were null, though the analyses had less power to detect association. Overall, the results are consistent with a modest influence of TP53 genetic variation on the risk of invasive breast cancer, particularly those arising in younger women.

To our knowledge, only 2 of the 11 SNPs we investigated have been studied previously in relation to breast cancer risk. A recently published pooled analysis that included data from nine studies indicated no overall association of the Arg72Pro polymorphism in exon 4 (TP53-01) with breast cancer risk (12). Our overall results for the Arg72Pro variant were consistent with estimates from the pooled analysis.

TP53-16 on intron 6 has been studied previously in relation to breast cancer risk (13–18). Four studies reported an increased risk associated with the minor allele (15–18), whereas two studies found no evidence for association with this variant (13,14). In contrast, the present data suggest ~40% reduction in risk among younger women carrying the minor A allele (as well as the minor allele of a correlated SNP TP53-66 on intron 4). Likewise, in the present data, heterozygosity at TP53-15 in the 3' UTR was associated with ~40% reduction in invasive breast cancer risk among women <50 years. However, neither of these associations was observed in two large study populations in Norway and Poland (27).

It is difficult to distinguish between an interaction by age versus menopausal status. Menopausal status appeared to modify the association between breast cancer risk and variants in TP53-15 in the 3' UTR, TP53-16 in intron 6 and TP53-66 in intron 4 (Pinteraction = 0.02, 0.04, 0.02, respectively), but in each instance the risk reductions were stronger among younger women than among pre-menopausal women.

Several associations detected in these data involved SNPs occurring in non-coding regions. These associations may have occurred by chance given the many associations tested. However, variations in intronic structure have been proposed to influence cancer susceptibility via regulation of gene expression, gene splicing or mRNA stability (18,28,29). It is also possible that these polymorphisms are in linkage disequilibrium with other functional polymorphisms that may affect breast cancer risk.

The observation that genetic variation in TP53 may be more relevant to younger onset breast cancer is consistent with observations that TP53 mutations in Li–Fraumeni syndrome disproportionately increase cancer risk at younger ages. In one study, women under the age of 45 with Li–Fraumeni syndrome had an 18-fold higher risk of breast cancer compared with women in the general population, whereas the relative risk was 1.8 for women over the age of 45 (10). Therefore, our results appear consistent with the notion that variation in the TP53 gene may be more influential in early onset breast cancer, though this result needs confirmation.

To our knowledge, this is the first study to evaluate the relation between TP53 polymorphisms and risk of breast carcinoma in situ. The results were generally null, although the number of women studied was relatively limited, particularly for evaluations by age and menopausal status. In haplotype analyses, no significant associations were found between any of the eight common haplotypes and risk of breast carcinoma in situ. TP53 mutations have been identified both in breast carcinoma in situ and invasive tumors (30). As TP53 may influence progression and malignant potential of tumors, further studies of these associations are warranted in preinvasive breast cancer.

The study had several potential limitations to consider. Although this population-based study was among the largest to date of TP53 polymorphisms and breast cancer risk, power was limited to detect age-specific associations and associations for homozygous minor allele genotypes for variants of low prevalence in the population. Multiple tests were performed raising the possibility that some associations emerged by chance. Finally, the study was based on whole genome amplified DNA, and results may be subject to systematic loss of heterozygotes due to imbalanced allele amplification (24). However, tests for HWE indicated no significant loss of heterozygotes in the TP53 SNPs examined. In addition, with the exception of one SNP (TP53-66 in intron 4), we observed high concordance of genotypes with replicate genomic DNA samples included for quality control. These results indicate that effects of allele amplification bias on results, if any, would have been minimal.

In summary, the present study suggests that TP53 SNPs may have a modest influence on breast cancer risk. Age at onset appears from these data to be a potential effect modifier and should be considered in future studies of the TP53 tumor suppressor gene in relation to breast cancer risk.


   Acknowledgments
 
The authors are grateful to Drs Patrick Remington, Henry Anderson, Meir Stampfer and Walter Willett for their expert advice throughout the case–control study. We wish to thank the study staff, tumor registrars and all the participants in the Collaborative Breast Cancer Study for their contributions. This study was supported by grants CA105197, CA47147, CA47305, CA69664, CA67338 and CA67264 from the National Institutes of Health.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

  1. Vogelstein B, et al. Surfing the p53 network. Nature (2000) 408:307–310.[CrossRef][Medline]
  2. Prives C, et al. The p53 pathway. J. Pathol. (1999) 187:112–126.[CrossRef][Web of Science][Medline]
  3. Vogelstein B, et al. Cancer genes and the pathways they control. Nat. Med. (2004) 10:789–799.[CrossRef][Web of Science][Medline]
  4. Olivier M, et al. The IARC TP53 database: new online mutation analysis and recommendations to users. Hum. Mutat. (2002) 19:607–614.[CrossRef][Web of Science][Medline]
  5. Hamroun D, et al. The UMD TP53 database and website: update and revisions. Hum. Mutat. (2006) 27:14–20.[CrossRef][Web of Science][Medline]
  6. Borresen-Dale AL. TP53 and breast cancer. Hum. Mutat. (2003) 21:292–300.[CrossRef][Web of Science][Medline]
  7. Srivastava S, et al. Germ-line transmission of a mutated p53 gene in a cancer-prone family with Li-Fraumeni syndrome. Nature (1990) 348:747–749.[CrossRef][Medline]
  8. Malkin D, et al. Germ line p53 mutations in a familial syndrome of breast cancer, sarcomas, and other neoplasms. Science (1990) 250:1233–1238.[Abstract/Free Full Text]
  9. Varley JM. Germline TP53 mutations and Li-Fraumeni syndrome. Hum. Mutat. (2003) 21:313–320.[CrossRef][Web of Science][Medline]
  10. Garber JE, et al. Follow-up study of twenty-four families with Li-Fraumeni syndrome. Cancer Res. (1991) 51:6094–6097.[Abstract/Free Full Text]
  11. Packer BR, et al. SNP500Cancer: a public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes. Nucleic Acids Res. (2006) 34:D617–D621.[Abstract/Free Full Text]
  12. The Breast Cancer Association Consortium. Commonly studied single-nucleotide polymorphisms and breast cancer: results from the breast cancer association consortium. J. Natl Cancer Inst. (2006) 98:1382–1396.[Abstract/Free Full Text]
  13. Mavridou D, et al. TP53 intron 6 polymorphism and the risk of ovarian and breast cancer. Br. J. Cancer (1998) 77:676–677.[Web of Science][Medline]
  14. Sjalander A, et al. p53 polymorphisms and haplotypes in breast cancer. Carcinogenesis (1996) 17:1313–1316.[Abstract/Free Full Text]
  15. Weston A, et al. p53 haplotype determination in breast cancer. Cancer Epidemiol. Biomarkers Prev. (1997) 6:105–112.[Abstract]
  16. Wang-Gohrke S, et al. p53 germline polymorphisms are associated with an increased risk for breast cancer in German women. Anticancer Res. (1998) 18:2095–2099.[Web of Science][Medline]
  17. Wang-Gohrke S, et al. Intron 3 16 bp duplication polymorphism of p53 is associated with an increased risk for breast cancer by the age of 50 years. Pharmacogenetics (2002) 12:269–272.[CrossRef][Web of Science][Medline]
  18. Peller S, et al. A novel polymorphism in intron 6 of the human p53 gene: a possible association with cancer predisposition and susceptibility. DNA Cell Biol. (1995) 14:983–990.[Web of Science][Medline]
  19. Khaliq S, et al. P53 mutations, polymorphisms, and haplotypes in Pakistani ethnic groups and breast cancer patients. Genet. Test. (2000) 4:23–29.[CrossRef][Web of Science][Medline]
  20. Weston A, et al. True extended haplotypes of p53: indicators of breast cancer risk. Cancer Genet. Cytogenet. (1998) 102:153–154.[CrossRef][Web of Science][Medline]
  21. Keshava C, et al. Waf-1 (p21) and p53 polymorphisms in breast cancer. Cancer Epidemiol. Biomarkers Prev. (2002) 11:127–130.[Abstract/Free Full Text]
  22. Garcia-Closas M, et al. Polymorphisms in DNA double-strand break repair genes and risk of breast cancer: two population-based studies in USA and Poland, and meta-analyses. Hum. Genet. (2006) 119:376–388.[CrossRef][Web of Science][Medline]
  23. Garcia-Closas M, et al. Collection of genomic DNA from adults in epidemiological studies by buccal cytobrush and mouthwash. Cancer Epidemiol. Biomarkers Prev. (2001) 10:687–696.[Abstract/Free Full Text]
  24. Liang X, et al. Whole genome amplification of oral rinse self-collected DNA in a population-based case-control study of breast cancer. Cancer Epidemiol Biomarkers Prev. (In Press).
  25. Stephens M, et al. A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. (2001) 68:978–989.[CrossRef][Web of Science][Medline]
  26. Stephens M, et al. Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am. J. Hum. Genet. (2005) 76:449–462.[CrossRef][Web of Science][Medline]
  27. Garcia-Closas M, et al. Common genetic variation inTP53 and its flanking genes, WDR79 and susceptibility to breast cancer. In: Int. J. Cancer. (In Press).
  28. Malkinson AM, et al. The intronic structure of cancer-related genes regulates susceptibility to cancer. Mol. Carcinog. (1994) 10:61–65.[Web of Science][Medline]
  29. Tabor HK, et al. Opinion: candidate-gene approaches for studying complex genetic traits: practical considerations. Nat. Rev. Genet. (2002) 3:391–397.[Web of Science][Medline]
  30. Lukas J, et al. p53 mutations and expression in breast carcinoma in situ. Am. J. Pathol. (2000) 156:183–191.[Abstract/Free Full Text]
Received February 1, 2007; revised April 9, 2007; accepted April 11, 2007.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Clin. Cancer Res.Home page
M. E. Sehl, L. R. Langer, J. C. Papp, L. Kwan, J. L. Seldon, G. Arellano, J. Reiss, E. F. Reed, S. Dandekar, Y. Korin, et al.
Associations between Single Nucleotide Polymorphisms in Double-Stranded DNA Repair Pathway Genes and Familial Breast Cancer
Clin. Cancer Res., March 15, 2009; 15(6): 2192 - 2203.
[Abstract] [Full Text] [PDF]

Home page
 BloodHome page
N. A. Ellis, D. Huo, O. Yildiz, L. J. Worrillow, M. Banerjee, M. M. Le Beau, R. A. Larson, J. M. Allan, and K. Onel
MDM2 SNP309 and TP53 Arg72Pro interact to alter therapy-related acute myeloid leukemia susceptibility
Blood, August 1, 2008; 112(3): 741 - 749.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
28/8/1680    most recent
bgm097v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (9)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Sprague, B. L.
Right arrow Articles by Egan, K. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sprague, B. L.
Right arrow Articles by Egan, K. M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?