Abstract
Background
Altered expression or function of mouse double minute-2 (MDM2) protein could contribute to lung carcinogenesis; thus, this study investigated MDM2-rs2279744 polymorphism together with other epidemiologic factors for their association with lung cancer risk.
Methods
A total of 500 lung cancer patients and 500 age and gender-matched healthy controls living in Northeastern China were recruited for genotyping of MDM2-rs2279744. Clinicopathological data was collected and subjected to univariate and multivariate analyses.
Results
In univariate analysis, the MDM2-rs2279744 G/G genotype versus T/T + T/G genotypes showed a tendency toward a higher incidence of lung cancer in the recessive model (P = 0.043). However, there were no significant differences when it was analyzed by the dominant, additive, or multiplicative models. A significantly increased lung cancer risk was observed associated with lower education level, lower body mass index, cancer family history, prior diagnosis of chronic obstructive pulmonary disease and pneumonia, exposure to pesticide or gasoline/diesel, tobacco smoking, and heavy cooking emissions when assessed by multivariate analyses. Moreover, MDM2-rs2279744 was still a significant risk factor even after incorporating environmental and lifestyle factors. However, there was no association between MDM2-rs2279744 and other factors.
Conclusions
The MDM2-rs2279744 G/G genotype was associated with a higher lung cancer risk, even after incorporating other epidemiologic factors.
Keywords: Chinese population, lung cancer risk, mouse double minute-2 homolog, rs2279744 polymorphism, single nucleotide polymorphism
Introduction
Lung cancer is one of the most commonly diagnosed malignancies in the world, accounting for 17.6% (1.18 million people) of worldwide cancer-related deaths annually.1 In China, national death survey and cancer registration data shows that lung cancer is also the leading cause of cancer death in most Chinese cities.2 Lung cancer is indeed a major global public health challenge. However, to date, the precise mechanisms of lung carcinogenesis are still not fully understood. A previous study showed that low-penetrance susceptibility genes in combination with environmental factors were of importance in lung cancer development and contributed to lung cancer risk.3 Therefore, further studies in this field could lead to better understanding of lung cancer risk and susceptibility genes.
Toward this end, our research focuses on murine double minute-2 (MDM2), which is a negative regulator of p53 tumor suppressor. MDM2 protein functions as an E3 ubiquitin ligase that recognizes the N-terminal trans-activation domain of p53 protein, and inhibitor of p53 transcriptional activation. MDM2 protein plays an important role in regulation of p53 pathway activity. A single nucleotide polymorphism (SNP) of MDM2-rs2279744 was identified as a functional SNP with a T-to-G transversion and has been proven to increase the affinity of the transcriptional activator Sp1 and lead to expression of higher MDM2 messenger ribonucleic acid (mRNA) and protein levels, subsequently attenuating p53 pathway activity.4 The elevated levels of MDM2 protein in carriers of the G-allele will inhibit the p53-induced apoptotic responses to DNA-damage, thereby resulting in genetic instability (such as gene mutations in the cells) and eventually leading to tumorigenesis at a young age.5
However, the association between MDM2-rs2279744 SNP and lung cancer risk seems plausible; for example, Hu et al.6 and Pine et al.7 reported that there was no significant association between MDM2 SNP309 variant genotypes and lung cancer risk, whereas studies conducted by Zhang et al.8 and Lind et al.9 showed that the G-allele in the MDM2 promoter was associated with a higher lung cancer risk. Additionally, Chua et al. showed that the T-allele in the MDM2 promoter increased lung cancer risk.10 Other studies have demonstrated that MDM2-rs2279744 SNP is associated with lung cancer risk at an early age.11,12 Thus, this case-control study investigated this functionally important MDM2-rs2279744 SNP in our hospital for association with lung cancer risk, together with other clinicopathological and epidemiologic data from lung cancer patients, as other factors, such as sociodemographic information, medical and family history, and lifestyle data, may also play a role in lung carcinogenesis.13–19
Patients and methods
Study population
The study was approved by the Ethics Committee of the First Hospital of Jilin Medical University, and conducted according to the Declaration of Helsinki Principles. All subjects signed a written informed consent form. This hospital-based case-control study recruited a total of 1000 subjects from Northeastern China between January 2010 and December 2012. Patients who met the following criteria were included in the study: (i) a minimum of 18 years of age; (ii) primary lung cancer confirmed by pathology; (iii) Han descent; (iv) reside in Northeastern China for at least 10 years; and (v) no radiotherapy or chemotherapy performed before blood withdrawal. Patients with any of the following conditions were excluded: (i) secondary (metastatic) lung cancer; (ii) double or multiple primary cancers; and (iii) relapse after operation. Healthy controls had no cancer history within five years of the interview date. These healthy controls were randomly selected individuals who received routine physical examinations in our hospital and were matched to cases by age, gender, and residential area.
Diagnostic criteria and data collection
Standardized interviews were conducted by well-trained interviewers at either the hospital or at the homes of the studied subjects. Sociodemographic information, medical and family history, lifestyle data, and cancer diagnosis were recorded (Table 1). Risk factors and peripheral blood lymphocytes were collected for the time prior and up to the index date (i.e. the time of diagnosis for cases and the interview date for controls). However, there were no data available on exposure to asbestos for analysis.
Table 1.
Univariate analysis of the risk factors in cases and controls
| Characteristic | Case (n = 500 [%]) | Control (n = 500[%]) | P-value | |
|---|---|---|---|---|
| Gender | Male | 305 (61.0) | 302 (60.4) | 0.846 |
| Female | 195 (39.0) | 198 (39.6) | ||
| Age (years) | <30 | 2 (0.4) | 5 (1.0) | 0.421 |
| 30–39 | 14 (2.8) | 16 (3.2) | ||
| 40–49 | 64 (12.8) | 70 (14.0) | ||
| 50–59 | 176 (35.2) | 196 (39.2) | ||
| 60–69 | 174 (34.8) | 148 (19.7) | ||
| ≥70 | 70 (14.0) | 65 (13.0) | ||
| Education | Junior high school and lower | 318 (63.6) | 130 (26.0) | 0.000 |
| High school | 97 (19.4) | 144 (28.8) | ||
| Greater than high school | 85 (17.0) | 226 (45.2) | ||
| Smoking (pack-years) | 14.25 (0.0–36.0) | 0.00 (0.0–6.9) | 0.000 | |
| Occupational exposure | Absent | 398 (79.6) | 473 (94.6) | 0.000 |
| Pesticide | Present | 102 (20.4) | 27 (5.4) | |
| Exposure Gasoline /diesel | Absent | 487 (97.4) | 496 (99.2) | 0.037 |
| Present | 13 (2.6) | 4 (0.8) | ||
| Exposure to Ink | Absent | 493 (98.6) | 497 (99.4) | 0.217 |
| Present | 7 (1.4) | 3 (0.6) | ||
| Cooking emissions (total dish-years) | Absent | 244 (48.8) | 250 (50.0) | 0.003 |
| ≤50 | 149 (29.8) | 152 (30.4) | ||
| 51–100 | 61 (12.2) | 80 (16.0) | ||
| 101–150 | 46 (9.2) | 18 (3.6) | ||
| Pneumonia history | Absent | 477 (95.4) | 490 (98.0) | 0.025 |
| Present | 23 (4.6) | 10 (2.0) | ||
| COPD history | Absent | 449 (89.8) | 489 (97.8) | 0.000 |
| Present | 51 (10.2) | 11 (2.2) | ||
| Pulmonary tuberculosis history | Absent | 470 (94.0) | 486 (97.2) | 0.016 |
| Present | 30 (6.0) | 14 (2.8) | ||
| Bronchial asthma history | Absent | 488 (97.6) | 495 (99.0) | 0.097 |
| Present | 12 (2.4) | 5 (1.0) | ||
| Cancer family history | Absent | 330 (66.0) | 397 (79.4) | 0.000 |
| Present | 170 (34.0) | 103 (20.6) | ||
| BMI (kg/m2) | <18.5 | 49 (9.8) | 15 (3.0) | 0.000 |
| 18.5–24 | 302 (60.4) | 230 (46.0) | ||
| ≥24 | 149 (29.8) | 255 (51.0) | ||
Including large cell, mixed cell carcinoma, or undifferentiated carcinoma. BMI, body mass index; COPD, chronic obstructive pulmonary disease.
Genotyping and quality control
Genomic DNA was extracted from the peripheral blood lymphocytes of all subjects. MassArray (Sequenom, Inc., San Diego, CA, USA) was used for genotyping all markers by using allele specific matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Primers and multiplex reactions were designed using the RealSNP.com website. All lung cancer patients and healthy controls were genotyped for MDM2-rs2279744 polymorphisms. Concordance among the three genomic control DNA samples presented in duplicate was 100%. Of SNPs with genotyping data, the call rate was >95%.
Statistical analysis
The Hardy-Weinberg equilibrium was performed to analyze the balance of case and control using a goodness-of-fit chi-square (χ2) test. The univariate χ2 test was used to determine genotype frequencies with observed genotype frequencies in healthy controls versus lung cancer cases and association between MDM2-rs2279744 SNP and clinicopathological data from lung cancer patients. Multivariate logistic regression analysis was used to assess the association between risk factors (SNPs were included) and lung cancer risk. All categorical variables were set as dummy variables. The first category of each environmental variable was selected as the baseline, as well as the low-risk allele of each locus. All analysis was conducted using SPSS v19.0 software (SPSS, Inc., Chicago, IL, USA). A p-value of less than 0.05 was considered statistically significant.
Results
Univariate analysis of MDM2-rs2279744 polymorphism for association with lung cancer risk
A total of 1000 subjects (i.e. 500 incident lung cancer cases and 500 healthy controls) were recruited for genotyping of MDM2-rs2279744. Univariate analysis revealed that lung cancer occurred more frequently in individuals with a family history of cancer, history of chronic obstructive pulmonary disease (COPD), pulmonary tuberculosis, pneumonia, low body mass index (BMI), tobacco smoking, occupational exposure to pesticides, gasoline, or diesel, and exposure to cooking emissions, as well as a low education level (Table 1).
Furthermore, our data also showed that the genotype distribution of MDM2-rs2279744 polymorphism was followed by Hardy-Weinberg equilibrium (P > 0.05). MDM2 G/G genotype occurred in 25.8%, G/T genotype in 48.8%, and T/T genotype in 25.4% of lung cancer cases, with a similar distribution in the healthy control (P > 0.05). Univariate analysis showed that when comparing G/G with T/T + T/G genotypes, the G/G had a tendency toward a higher incidence of lung cancer in the recessive model (P = 0.043; Table 2). However, there were no significant differences in the dominant, additive, or multiplicative models.
Table 2.
Association of MDM2-rs2279744 polymorphism with lung cancer risk analyzed by univariate analysis
| Genotype | Exp (B) | 95% CI | P-value | |
|---|---|---|---|---|
| Additive model | T/T | 1 | Reference | — |
| G/T | 0.932 | (0.691–1.258) | 0.645 | |
| G/G | 1.295 | (0.906–1.849) | 0.156 | |
| Dominant model | T/T | 1 | Reference | — |
| G/G + G/T | 1.032 | (0.777–1.370) | 0.828 | |
| Recessive model | T/T + G/T | 1 | Reference | — |
| G/G | 1.357 | (1.009–1.824) | 0.043 | |
| Multiplicative model | G-allele | 1.131 | (0.947–1.351) | 0.174 |
CI, confidence interval; MDM2, mouse double minute-2.
Multivariate analysis of MDM2-rs2279744 polymorphism for association with lung cancer risk
Multivariate analysis showed a significantly increased lung cancer risk in individuals with a lower education level, lower BMI, cancer family history, prior diagnosis of COPD and pneumonia, exposure to pesticide or gasoline/diesel, tobaccco smoking, heavy cooking smoke, and MDM2-rs2279744 SNP. The latter was still a significant risk factor for lung cancer, even after incorporating environmental and lifestyle factors (Table 3).
Table 3.
Multivariate risk model with adjusted odds ratios and 95% CI
| Risk factors | Exp (B) | 95% CI | P-value |
|---|---|---|---|
| Education level | 0.000 | ||
| Junior high school and lower | 1.00 | Reference | — |
| High school | 0.307 | 0.211–0.446 | 0.000 |
| Greater than high school | 0.195 | 0.134–0.284 | 0.000 |
| Smoking (pack-years) | 1.032 | 1.023–1.041 | 0.000 |
| Occupational exposure to pesticide | |||
| Absent | 1.00 | Reference | — |
| Present | 1.700 | 1.024–2.824 | 0.040 |
| Exposure to gasoline /diesel | |||
| Absent | 1.00 | Reference | — |
| Present | 5.065 | 1.430–17.945 | 0.012 |
| Cooking smoke (total dish-years) | 0.004 | ||
| ≤50 | 1.00 | Reference | — |
| 51–100 | 1.417 | 0.998–2.011 | 0.869 |
| 101–150 | 0.962 | 0.610–1.519 | 0.006 |
| >150 | 2.511 | 1.301–4.846 | 0.026 |
| COPD history | |||
| Absent | 1.00 | Reference | — |
| Present | 4.162 | 1.950–8.883 | 0.000 |
| Pneumonia history | |||
| Present | 1.00 | Reference | — |
| Absent | 0.369 | 0.151–0.902 | 0.029 |
| Cancer family history | |||
| Absent | 1.00 | Reference | — |
| Present | 2.024 | 1.442–2.842 | 0.000 |
| BMI (kg/m2) | 0.000 | ||
| <18.5 | 1.00 | Reference | |
| 18.5–24 | 0.426 | 0.215–0.843 | 0.014 |
| ≥24 | 0.215 | 0.107–0.432 | 0.000 |
| rs2279744 | |||
| T/T + G/T | 1.00 | Reference | — |
| G/G | 1.475 | 1.153–1.887 | 0.002 |
BMI, body mass index; CI, confidence interval; COPD, chronic obstructive pulmonary disease.
Association of MDM2-rs2279744 SNP with clinicopathological patient data
We also evaluated MDM2-rs2279744 SNP for association with the clinicopathological data from lung cancer patients. We did not find any statistically significant associations (Table 4).
Table 4.
Association of MDM2-rs2279744 SNP with the clinicopathological data from lung cancer patients
| Characteristic | G/G (n = 231) | T/T + G/T (n = 769) | P-value | |
|---|---|---|---|---|
| Gender | Male | 141 | 466 | 0.965 |
| Female | 90 | 303 | ||
| Age (years) | <30 | 3 | 4 | 0.530 |
| 30–39 | 5 | 25 | ||
| 40–49 | 36 | 98 | ||
| 50–59 | 85 | 287 | ||
| 60–69 | 75 | 247 | ||
| ≥70 | 27 | 108 | ||
| BMI (kg/m2) | <18.5 | 8 | 56 | 0.101 |
| 18.5–24 | 130 | 402 | ||
| ≥24 | 93 | 311 | ||
| Histology types | Squamous cell | 35 | 106 | 0.946 |
| Adenocarcinoma | 48 | 128 | ||
| Small cell | 31 | 95 | ||
| Other carcinomas* | 15 | 42 | ||
*Including large cell, mixed cell carcinoma, or undifferentiated carcinoma. BMI, Body mass index; MDM2, mouse double minute-2; SNP, single nucleotide polymorphism.
Discussion
Several study models have been developed to predict the individual risk for lung cancer using patient characteristics, epidemiologic, social, and clinical risk factors.13–19 Our current study genotyped MDM2-rs2279744 SNP in a Northeastern Chinese population to associate lung cancer risk, together with other clinicopathological and epidemiologic factors. We found that there were several factors associated with lung cancer risk, including family history of cancer, COPD, pneumonia, occupational exposure to pesticide or gasoline/diesel, duration of tobacco smoking, and heavy cooking smoke, as well as lower education level or BMI. Our current data are consistent with the findings of previous studies.13–19 Furthermore, our current study also showed that the MDM2-rs2279744 G/G genotype was associated with lung cancer risk in recessive model analysis and was still associated with lung cancer risk after incorporating environmental and lifestyle factors. Thus, this study has demonstrated that the MDM2-rs2279744 G/G genotype is associated with lung cancer risk. Molecularly, MDM2-rs2279744 is a functional SNP and is able to regulate MDM2 protein expression, that is, the MDM2-rs2279744 G-allele results in higher levels of MDM2 mRNA and protein, which, in turn, attenuate the p53 stress response pathway through directly blocking p53 transcriptional activity and mediating p53 protein degradation.4,20 The attenuation of p53 pathway activity will lead to lung carcinogenesis, which has been confirmed in an animal experiments, that is, suppression of the p53 pathway increased the lung tumor multiplicity in p53-mutated mice after they were exposed to tobacco smoke.21,22 A predisposition to cancer has been presented in MDM2 overexpressed mice.23
Furthermore, MDM2-rs2279744 SNP was not associated with any clinicopathological data from lung cancer patients. This was a surprising result, but mechanistically it may be rationalized that p53 expression is a result of p53 mutations in most lung cancers. In this case, the p53 gene pathway was already altered and the increased MDM2 expression as a result of MDM2-rs2279744 G/G SNP did not contribute to tumor progression. Indeed, in previous studies, the p53 rs1042522 C-allele SNP was associated with reduced apoptotic potential in lung cancer patients compared to the p53 G-allele, and might modulate lung cancer risk, cancer progression, and/or response to treatment,24–26 indicating that p53 plays an important role in the suppression of lung carcinogenesis.
There were a number of limitations in our study. Firstly, the MDM2-TP53 interaction played a pivotal role in regulation of the cell-cycle checkpoint, DNA repair, and apoptotic cell death. A common SNP at p53 rs1042522 has also been found to be of functional significance, with the C-allele having reduced the apoptotic potential compared to the G-allele, which may modulate the lung cancer risk, progression, and/or response to treatment.24–26 Our current data would be much stronger in the prediction of lung cancer risk if we would combine this p53 SNP with MDM2-rs2279744 G/G SNP. Secondly, our current data may not be generalizable to other populations because this is a hospital-based case-control study, and, thus, needs external validation in other populations. Thirdly, our current analyses did not include all epidemiological factors, such as exposure to asbestos. Finally, this was a retrospectively designed study, and the sample size is relatively small; therefore, the results need to be validated by a large-scale and prospective design study.
Conclusion
In conclusion, MDM2-rs2279744 is associated with lung cancer risk in Northeastern Chinese population.
Disclosure
No authors report any conflict of interest.
Acknowledgments
We thank all of the individuals who participated in this study. We also thank Li Deng for excellent assistance in sample collection and preparation and Hua He for assistance with data and statistical analysis. This study was supported in part by grants from the Key Clinical Project of the Ministry of Health of the People's Republic of China (#2001133) and the Jilin Provincial Science and Technology Department (#201201023).
References
- Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55:74–108. doi: 10.3322/canjclin.55.2.74. [DOI] [PubMed] [Google Scholar]
- Chen WQ. Estimation of cancer incidence and mortality in China in 2004-2005. Zhonghua Zhong Liu Za Zhi. 2009;31:664–668. (In Chinese.) [PubMed] [Google Scholar]
- Toh CK, Gao F, Lim WT, et al. Never-smokers with lung cancer: epidemiologic evidence of a distinct disease entity. J Clin Oncol. 2006;24:2245–2251. doi: 10.1200/JCO.2005.04.8033. [DOI] [PubMed] [Google Scholar]
- Bond GL, Hu W, Bond EE, et al. A single nucleotide polymorphism in the MDM2 promoter attenuates the p53 tumor suppressor pathway and accelerates tumor formation in humans. Cell. 2004;119:591–602. doi: 10.1016/j.cell.2004.11.022. [DOI] [PubMed] [Google Scholar]
- Bond GL, Hu W, Levine A. A single nucleotide polymorphism in the MDM2 gene: from a molecular and cellular explanation to clinical effect. Cancer Res. 2005;65:5481–5484. doi: 10.1158/0008-5472.CAN-05-0825. [DOI] [PubMed] [Google Scholar]
- Hu Z, Ma H, Lu D, et al. Genetic variants in the MDM2 promoter and lung cancer risk in a Chinese population. Int J Cancer. 2006;118:1275–1278. doi: 10.1002/ijc.21463. [DOI] [PubMed] [Google Scholar]
- Pine SR, Mechanic LE, Bowman ED, et al. MDM2 SNP309 and SNP354 are not associated with lung cancer risk. Cancer Epidemiol Biomarkers Prev. 2006;15:1559–1561. doi: 10.1158/1055-9965.EPI-06-0217. [DOI] [PubMed] [Google Scholar]
- Zhang X, Miao X, Guo Y, et al. Genetic polymorphisms in cell cycle regulatory genes MDM2 and TP53 are associated with susceptibility to lung cancer. Hum Mutat. 2006;27:110–117. doi: 10.1002/humu.20277. [DOI] [PubMed] [Google Scholar]
- Lind H, Zienolddiny S, Ekstrøm PO, Skaug V, Haugen A. Association of a functional polymorphism in the promoter of the MDM2 gene with risk of non-small cell lung cancer. Int J Cancer. 2006;119:718–721. doi: 10.1002/ijc.21872. [DOI] [PubMed] [Google Scholar]
- Chua HW, Ng D, Choo S, et al. Effect of MDM2 SNP309 and p53 codon 72 polymorphisms on lung cancer risk and survival among non-smoking Chinese women in Singapore. BMC Cancer. 2010;10:88. doi: 10.1186/1471-2407-10-88. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Yu H, Huang YJ, Liu Z, et al. Effects of MDM2 promoter polymorphisms and p53 codon 72 polymorphism on risk and age at onset of squamous cell carcinoma of the head and neck. Mol Carcinog. 2011;50:697–706. doi: 10.1002/mc.20806. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lum SS, Chua HW, Li H, et al. MDM2 SNP309 G allele increases risk but the T allele is associated with earlier onset age of sporadic breast cancers in the Chinese population. Carcinogenesis. 2008;29:754–761. doi: 10.1093/carcin/bgn024. [DOI] [PubMed] [Google Scholar]
- Bach PB, Kattan MW, Thornquist MD, et al. Variations in lung cancer risk among smokers. J Natl Cancer Inst. 2003;95:470–478. doi: 10.1093/jnci/95.6.470. [DOI] [PubMed] [Google Scholar]
- Tammemagi CM, Pinsky PF, Caporaso NE, et al. Lung cancer risk prediction: prostate, lung, colorectal and ovarian cancer screening trial models and validation. J Natl Cancer Inst. 2011;103:1058–1068. doi: 10.1093/jnci/djr173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cassidy A, Myles JP, van Tongeren M, et al. The LLP risk model: an individual risk prediction model for lung cancer. Br J Cancer. 2008;98:270–276. doi: 10.1038/sj.bjc.6604158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Young RP, Hopkins RJ, Hay BA, et al. Lung cancer susceptibility model based on age, family history and genetic variants. PLoS One. 2009;4:e5302. doi: 10.1371/journal.pone.0005302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chiu YL, Wang XR, Qiu H, Yu IT. Risk factors for lung cancer: a case-control study in Hong Kong women. Cancer Causes Control. 2010;21:777–785. doi: 10.1007/s10552-010-9506-9. [DOI] [PubMed] [Google Scholar]
- Villeneuve PJ, Parent MÉ, Sahni V, Johnson KC Canadian Cancer Registries Epidemiology Research Group. Occupational exposure to diesel and gasoline emissions and lung cancer in Canadian men. Environ Res. 2011;111:727–735. doi: 10.1016/j.envres.2011.04.003. [DOI] [PubMed] [Google Scholar]
- Andreotti G, Hou L, Beane Freeman LE, et al. Body mass index, agricultural pesticide use, and cancer incidence in the agricultural health study cohort. Cancer Causes Control. 2010;21:1759–1775. doi: 10.1007/s10552-010-9603-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Arva NC, Gopen TR, Talbott KE, et al. A chromatin-associated and transcriptionally inactive p53-Mdm2 complex occurs in mdm2 SNP309 homozygous cells. J Biol Chem. 2005;280:26776–26787. doi: 10.1074/jbc.M505203200. [DOI] [PubMed] [Google Scholar]
- Wang Y, Zhang Z, Lubet R, You M. Tobacco smoke-induced lung tumorigenesis in mutant A/J mice with alterations in K-ras, p53, or Ink4a/Arf. Oncogene. 2005;24:3042–3049. doi: 10.1038/sj.onc.1208390. [DOI] [PubMed] [Google Scholar]
- De Flora S, Balansky RM, D'Agostini F, et al. Molecular alterations and lung tumors in p53 mutant mice exposed to cigarette smoke. Cancer Res. 2003;63:793–800. [PubMed] [Google Scholar]
- Jones SN, Hancock AR, Vogel H, Donehower LA, Bradley A. Overexpression of Mdm2 in mice reveals a p53-independent role for Mdm2 in tumorigenesis. Proc Natl Acad Sci U S A. 1998;95:15608–15612. doi: 10.1073/pnas.95.26.15608. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sreeja L, Syamala V, Raveendran PB, Santhi S, Madhavan J, Ankathil R. P53 Arg72Pro polymorphism predicts survival outcome in lung cancer patients in Indian population. Cancer Invest. 2008;26:41–46. doi: 10.1080/07357900701638459. [DOI] [PubMed] [Google Scholar]
- Yan L, Zhang D, Chen C, et al. TP53 Arg72Pro polymorphism and lung cancer risk: a meta-analysis. Int J Cancer. 2009;125:2903–2911. doi: 10.1002/ijc.24603. [DOI] [PubMed] [Google Scholar]
- Sullivan A, Syed N, Gasco M, et al. Polymorphism in wild-type p53 modulates response to chemotherapy in vitro and in vivo. Oncogene. 2004;23:3328–3337. doi: 10.1038/sj.onc.1207428. [DOI] [PubMed] [Google Scholar]