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Carcinogenesis logoLink to Carcinogenesis
. 2010 Dec 1;32(3):327–330. doi: 10.1093/carcin/bgq256

The role of TP53 and MDM2 polymorphisms in TP53 mutagenesis and risk of non-melanoma skin cancer

Lindsay M Almquist 1,2, Margaret R Karagas 3,4, Brock C Christensen 5,6, Marleen M Welsh 7, Ann E Perry 8, Craig A Storm 8, Heather H Nelson 1,2,*
PMCID: PMC3105583  PMID: 21123835

Abstract

P53 is a key regulatory molecule in the cellular response to ultraviolet radiation, and TP53 mutation is the most common alteration in non-melanoma skin cancer. The MDM2 oncogene negatively regulates p53 protein levels, and both genes have functional polymorphisms that may modify skin cancer risk. Furthermore, prior research suggests that TP53 mutations preferentially occur on the arginine allele to selectively inactivate the p63 pathway. We tested these hypotheses of susceptibility and preferential mutation in non-melanoma skin cancer. The TP53 Arg72Pro and MDM2 309 polymorphisms were genotyped in a population-based case–control study of non-melanoma skin cancer, and TP53 alteration (mutation and immunohistochemistry staining) was evaluated in case tumors. In 902 cases of basal cell carcinoma (BCC), 676 cases of squamous cell carcinoma (SCC) and 812 controls, no association was found between the TP53 polymorphism and risk of non-melanoma skin cancer [odds ratio (OR)BCC 0.98, 95% confidence interval (CI) 0.80–1.20; ORSCC 0.93, 95% CI 0.75–1.16]. However, carriers of the MDM2 SNP309 G allele did have an elevated risk of non-melanoma skin cancer (ORBCC 1.15, 95% CI 0.93–1.42; ORSCC 1.29, 95% CI 1.02–1.63). We observed an association between TP53 alterations in the tumors and constitutive TP53 genotype (P < 0.01), with alterations preferentially occurring on the proline allele. Collectively, these data highlight the significant effects of genotype on gene-specific mutation events in carcinogenesis.

Introduction

Skin cancer remains the most common cancer in the USA (1). DNA damage that results from excess ultraviolet irradiation contributes to the development of non-melanoma skin cancer, and interindividual variability in the response to ultraviolet damage may alter disease risk. p53 is central to this DNA damage response and is a logical node for investigating genetic susceptibility to skin cancer.

p53 levels are negatively regulated by MDM2. This oncogenic protein normally promotes low levels of p53 through binding-mediated ubiquitination and subsequent protein degradation (2). High levels of MDM2 may result in insufficient p53 to respond to DNA damage. A common polymorphism in MDM2, SNP309, results in increased MDM2 levels, a pro-oncogenic phenotype (3).

In addition, a common polymorphism at codon 72 of p53 has been associated with several different phenotypes including transcriptional activity (4) and apoptotic potential (5). Although this cancer-promoting genotype has been investigated for many cancers, risk effects have been inconsistent. For instance, the codon 72 polymorphism has been positively associated with risk of basal cell carcinoma (BCC) but not squamous cell carcinoma (SCC) of the skin (68). Beyond contributing to cancer risk, it has been demonstrated that when TP53 mutations occur on the arginine allele of TP53 (A72), a dominant-negative phenotype for inactivation of p73 (and p63) is conferred (9). A selection bias for this phenotype might be especially relevant for skin cancer as the p63 protein is necessary for keratinocyte development (reviewed in ref. 10).

We hypothesized that the TP53 and MDM2 polymorphisms interact to increase risk of developing BCC and SCC. Furthermore, we investigated whether mutations in TP53 occurred selectively by genotype status.

Materials and methods

Study population

Newly diagnosed cases of histologically confirmed BCC and SCC in New Hampshire were identified using an incident survey established through the collaboration of dermatologists, dermatopathologists and pathology laboratories throughout the state and bordering regions, as described previously (11). Briefly, eligibility criteria for cases were as follows: (i) 25 and 74 years of age, (ii) had a listed telephone number and (iii) spoke English. Controls aged 25–64 years were identified from the New Hampshire State Department of Transportation files and those aged 65–74 years were obtained from enrollment lists from the Center for Medicaid and Medicare Services. Potential controls were frequency matched on age and gender to the combined distribution of case groups.

A personal interview was conducted with consenting cases and controls. The interviews, usually conducted in the participant’s home, covered demographic factors, pigmentation characteristics, sun exposure and sensitivity and other factors. Blood draws and/or buccal samples were obtained from 85% of study participants. All study protocol and materials were approved by the Dartmouth College Committee for the Protection of Human Subjects, and all participants provided informed consent.

Genotyping

DNA was extracted from peripheral blood lymphocytes using Qiagen Genomic DNA extraction kits (Valencia, CA). Genotyping for the TP53 codon 72 polymorphism (rs1042522) was performed by polymerase chain reaction–restriction fragment length polymorphism (12). Genotyping of the MDM2 polymorphism (rs2279744) was done on the Sequenom platform by the University of Minnesota Biomedical Genomics Center. Overall, 10% of samples were embedded duplicates, and concordant genotypes were achieved for 99% of the paired samples. Both single nucleotide polymorphisms (SNPs) were in Hardy-Weinberg equilibrium among controls.

TP53 mutation analysis

Among the genotyped cases, 291 tumors had p53 mutation analysis, and 249 tumors had immunohistochemistry (IHC) data. A comprehensive pathology review was conducted by a single pathologist. Tumor DNA was extracted as described previously (13). Single-strand conformation polymorphism analysis of TP53 exons 5 through 9 was performed on tumor-derived DNA. Exons were amplified by polymerase chain reaction containing fluorescence dye-labeled primers. Previously reported primer sequences and annealing temperatures for each exon were used (14). All samples were then run on 2% agarose gels to confirm sample amplification. Following a denaturing step and cooling to 4°C, a capillary based DNA autosequencer ABI 310 (PE Applied Biosystems, Foster City, CA) was used to run SSCP and identify samples with band shifts [using Gene Scan 3.1 software (PE Applied Biosystems)]. Samples with SSCP band shifts were again polymerase chain reaction amplified using unlabeled primers described above and then run on 3% Supra Seive (American Bioanalytical, Natick, MA) low melting agarose gels. Amplicon bands corresponding to fragment sizes for each exon were excised for gel extraction with QIAquick Gel Extraction Kit (Qiagen). Cycle sequencing of gel-extracted samples was performed using forward primers and Dye Terminator v1.1 Cycle Sequencing Kit (PE Applied Biosystems). Cycle sequencing products were purified using Centrisep purification columns (Princeton Separations, Freehold, NJ), denatured and cooled to 4°C prior to sequencing on the capillary based ABI 310 (PE Applied Biosystems). Sequencing analysis was performed with DNA Sequencing Analysis Software v3.4.5 (PE Applied Biosystems).

P53 IHC staining

Additionally, we performed immunohistochemical analysis of p53 on a subset of tumors using avidin–biotin techniques as described in Kelsey et al. (15). Using a standardized form, a study dermatopathologist (C.S.) scored the stained slides for intensity and percent of tumor cells staining positively. We considered a tumor positive with a score of 3+ intensity in >10% of the tumorous cells.

Logistic regression

Analysis was restricted to Caucasian subjects. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for each SNP were obtained using unconditional logistic regression adjusting for age at diagnosis (continuous), gender and skin type (tan/mild burn versus severe burns/blisters). To test for statistical interaction between genotypes, models were generated that included separate main effect terms for each of the genotypes as well as additional crossproduct interaction terms. The log-likelihood was then compared with the log-likelihood derived from a similar model that did not contain the cross product terms. Associations between genotype and tumor p53 status were tested using a chi-square test of independence. All tests were two sided.

Results

We studied 902 cases of BCC, 676 cases of SCC and 812 population-based controls described in Table I. The prevalence of the TP53 Pro allele was 24.0% and the prevalence of the MDM2 G was 33.0%. Among those with an MDM2 G allele, we observed a slightly elevated risk of BCC (OR: 1.15, 95% CI: 0.93–1.42) that did not reach statistical significance and an increased risk of SCC (OR: 1.29, 95% CI: 1.02–1.63, Table II). However, we did not observe an association with either BCC (OR: 0.98, 95% CI: 0.80–1.20) or SCC (OR: 0.93, 95% CI: 0.75–1.16) and TP53 genotype. In addition, we did not observe any statistically significant interactions between these polymorphisms and sex, number of lifetime sunburns or skin reaction to acute sun exposure (data not shown).

Table I.

Description of the population studied

Characteristics Controls, n (%) BCC, n (%) SCC, n (%)
Sex
    Male 493 (60.7) 509 (56.4) 427 (63.2)
    Female 319 (39.3) 393 (43.6) 249 (36.8)
Mean age (years ± SD) 61.2 ± 10.6 58.8 ± 11.1 64.0 ± 8.8
Severe sunburnsa
    0–1 413 (51.7) 346 (38.9) 267 (40.2)
    ≥2 386 (48.3) 545 (61.2) 398 (59.8)
Reaction to acute sun exposureb
    Tan or mild burn, tan later 560 (69.1) 516 (57.2) 372 (55.1)
    Severe burn, peel or blister 250 (30.9) 386 (42.8) 303 (44.9)

aMissing for 13 controls, 11 BCC and 11 SCC.

bMissing for 2 controls and 1 SCC.

Table II.

Association of MDM2 and TP53 polymorphisms with BCC and SCC

Controls (%) BCC (%) OR (95% CI) SCC (%) OR (95% CI)
MDM2a
    TT 323 (47.9) 345 (45.0) Referent 234 (41.9) Referent
    GT 284 (42.1) 331 (43.2) 1.14 (0.91–1.42) 261 (46.7) 1.28 (1.00–1.63)
    GG 67 (9.9) 90 (11.7) 1.22 (0.86–1.74) 64 (11.4) 1.35 (0.91–2.00)
    Any G allele 351 (52.1) 421 (55.0) 1.15 (0.93–1.42) 325 (58.1) 1.29 (1.02–1.63)
TP53b
    Arg/Arg 446 (58.1) 485 (57.9) Referent 366 (58.7) Referent
    Arg/Pro 274 (35.7) 295 (35.2) 0.96 (0.7 8–1.19) 220 (35.3) 0.93 (0.74–1.17)
    Pro/Pro 47 (6.1) 57 (6.8) 1.13 (0.75–1.72) 37 (5.9) 0.93 (0.58–1.49)
    Any Pro allele 321 (41.9) 352 (42.1) 0.98 (0.80–1.20) 257 (41.3) 0.93 (0.75–1.16)

aMissing for 138 controls, 136 BCC and 117 SCC.

bMissing for 45 controls, 65 BCC, and 535 SCC.

Next, we investigated potential interactions between MDM2 and TP53 polymorphisms. For BCC, the risk associated with the MDM2 G genotype was somewhat elevated among those with a TP53 Pro allele [OR = 1.27 (95% CI 0.91–1.78)] relative to those with the TP53 Arg/Arg genotype [OR = 1.12 (95% CI 0.84–1.49)]. Similarly, among SCC, there was evidence for modest effect modification of the TP53 genotype on the MDM2 disease association, with those having a TP53 Pro allele demonstrating elevated risk of SCC with MDM2 genotype [OR = 1.56 (95% CI 1.06–2.29)] relative to those with the Pro/Pro genotype [OR = 1.22 (0.89–1.67)]. However, interaction terms for MDM2 and TP53 genotype were not statistically significant (Pinteraction = 0.46 and 0.28 for BCC and SCC, respectively).

We next evaluated the relationship of genotype and tumor p53 status among a subset of cases with tumor data (Table III). The prevalence of TP53 mutation was highest among the TP53 Pro/Pro group (53%) compared with those carrying an Arg allele (30%). IHC results were consistent with the mutation data; 54% of Pro/Pro cases stained positive, whereas only 29% of Arg/Arg and 22% of Arg/Pro were positive. When considering evidence for any p53 alteration (mutation or altered IHC), there was a strong association with TP53 genotype (Table III, P < 0.01). There was a nonsignificant trend for decreasing TP53 mutation prevalence and aberrant p53 IHC staining with MDM2 G alleles. The associations between genotypes and any p53 alteration were similar in the two histologies (data not shown).

Table III.

TP53 polymorphism, but not MDM2 polymorphism, is associated with tumor alteration of p53

IHC staining
Mutation
Either mutation or abnormal staining
Normal Heavy Wild-type Mutant No Yes
P53 genotype
Arg/Arg 96 39 (28.9%) 106 50 (32.1%) 85 71 (45.5%)
Arg/Pro 43 12 (21.8%) 47 17 (26.6%) 40 24 (37.5%)
Pro/Pro 6 7 (53.8%) 7 8 (53.3%) 3 12 (80%)
P-value 0.07 0.13 0.01
MDM2 genotype
TT 65 26 (28.6%) 69 36 (34.3%) 58 47 (44.8%)
TG 76 24 (24.0%) 77 38 (33.6%) 66 50 (43.1%)
GG 18 4 (18%) 25 5 (19.4%) 22 9 (29%)
P-value 0.55 0.26 0.28

Discussion

We evaluated the impact of polymorphisms in the MDM2 and TP53 genes on both non-melanoma skin cancer risk and TP53 somatic alteration in case tumors. MDM2 was associated with a modestly elevated risk of BCC and SCC. There was some evidence that the TP53 polymorphism enhanced the observed risk associated with the MDM2 G allele, but the interaction was not statistically significant. Nevertheless, this observation is consistent with data from Li-Fraumeni patients for whom the variant MDM2 allele is associated with an earlier onset of tumors (16,17).

The two SNPs under investigation have an established in vitro phenotype and can potentially interact in the development of cancer. They are well-studied polymorphisms that have been associated with many different malignancies. Still the epidemiologic literature contains many inconsistent results. In a recent large pooling study, there was no evidence for an association of the MDM2 SNP with either breast or colorectal cancer; however, there was evidence for increased risk of lung cancer among G allele carriers (18). For non-melanoma skin cancer, prior studies investigating the MDM2 polymorphism have not observed increases in cancer risk (19,20). The TP53 polymorphism has been associated with BCC in two studies (6,7), whereas a third study found no association of the TP53 polymorphism with either BCC or SCC (8). Additionally, McGregor et al. (21) observed an association between the TP53 polymorphism and both BCC and SCC in renal transplant recipients, but not immune competent patients. Nan et al. (20) specifically addressed gene–gene interaction between these two SNPs in a prospective cohort of women. They observed a borderline statistically significant interaction with SCC (but not BCC) with an enhanced MDM2 risk among those with the TP53 Pro genotype, similar to the results we report here. These studies, along with our results, indicate that any risk effects or gene–gene interactions in immune competent populations are probably modest. This is perhaps a surprising result given the established phenotypes of the two polymorphisms.

Although these gene variants do not have a dramatic effect on disease risk, it is possible that they influence the accumulation of genetic damage and tumor phenotype. Marin et al. (9) demonstrated that a TP53 mutation on the Arg allele not only has a null p53 phenotype, it confers a dominant-negative phenotype on p73 and p63. In our tumor series, we observe preferential mutation on the rare proline allele, as indicated by the elevated mutation prevalence in the homozgote Pro/Pro group relative to the other genotype groups. This observation suggests selection bias against this dominant-negative phenotype. In 2002, McGregor et al. (21) investigated the relationship between the TP53 polymorphism and mutation in a small number of immune competent and immune-compromised individuals. No homozygote Pro/Pro individuals were included, but the prevalence of mutation among heterozygotes was 70%, compared with 47% among Arg/Arg cases. This is consistent with our interpretation of preferential mutation on proline alleles. Interestingly, they also observed that there was a very strong relationship between genotype and deletion (as measured by loss of heterozygosity), with a much higher prevalence of loss among carriers of a proline allele. This pattern is highly consistent with our previous work in lung cancer where we observed no difference in TP53 mutation prevalence by codon 72 polymorphism, but a strong selection for loss of proline (22).

A priori, we might have assumed that mutations would be selected for on the Arg allele, potentially giving them a ‘super’ phenotype. However, p63 is an essential protein in the skin, as evidenced by the lack of epidermis in p63-null mice (23,24). Therefore, it is possible that particularly at early stages of tumor development, there is selective pressure for TP53 mutation to occur on the Pro allele, thus limiting interference with the vital p63 pathway and maintaining aberrant cell outgrowth.

As in all research, our study has limitations. First, our study population consists of individuals from New Hampshire, and the results might not be generalizable to other Caucasian populations in regions that experience more or less exposure to ultraviolet. Also, as p53 somatic alteration data were not available for all cases, our statistical power was limited. Additional experiments investigating the relationship of TP53 allelism, mutation and p63 status in skin cancer tumors are necessary to definitely determine whether there is selection bias in tumorigenesis with regards to the codon 72 polymorphism. Collectively, these data highlight the significant affects of genotype on gene-specific mutation events in carcinogenesis.

Funding

National Institutes of Health (CA082354 and CA057494).

Acknowledgments

Conflict of Interest Statement: None declared.

Glossary

Abbreviations

BCC

basal cell carcinoma

CI

confidence interval

IHC

immunohistochemistry

SCC

squamous cell carcinoma

SNP

single nucleotide polymorphism

OR

odds ratio

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