Figures
Abstract
Among the cancer susceptibility genes, TP53 is one of the crucial genes involved in cell cycle regulations and, therefore, it greatly affects breast cancer initiation and progression. In addition, WRAP53—a natural antisense transcript—regulates TP53 transcription and, as a protein, modulates the normal cell cycle, which results in breast cancer susceptibility. In this study, we aimed to analyze a haplotype comprising four SNPs, including rs1042522, rs17878362, rs2287499, and rs2287498, which are located at 5′ regions of the TP53 and WRAP53 genes, in 118 patients and 110 healthy controls of the Iranian-Azeri population. In silico studies were conducted using the SIFT, Polyphen2, Fanthmm, RNAsnp, and SNP&GO online servers. Linkage disequilibrium (LD) and D′ for each combination of the markers were calculated via the Haploview program. Our results showed that the GA1CC haplotype was the most frequent in the studied population. Additionally, no significant LD between any pairwise haplotypes was observed. The GA1CC and CA2GC haplotypes were significantly associated with breast cancer susceptibility. Moreover, the in silico analysis revealed the negative effects of rs2287499 and rs1042522 on WRAP53 and P53, respectively. In conclusion, the CA1GC haplotype was strongly identified as a breast cancer risk factor, and the GA1CC haplotype was assumed to be a protective factor against breast cancer risk. Hence, these markers may potentially be used as molecular prognostic and predictive biomarkers for breast cancer.
Citation: Pouladi N, Abdolahi S, Farajzadeh D, Hosseinpour Feizi MA (2019) Haplotype and linkage disequilibrium of TP53-WRAP53 locus in Iranian-Azeri women with breast cancer. PLoS ONE 14(8): e0220727. https://doi.org/10.1371/journal.pone.0220727
Editor: Klaus Roemer, Universitat des Saarlandes, GERMANY
Received: March 30, 2019; Accepted: July 22, 2019; Published: August 6, 2019
Copyright: © 2019 Pouladi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
According to the International Agency of Research on Cancer (IARC) in 2018, breast cancer is the second cause of death in both genders, and is the leading cause of mortality in women worldwide [1]. Various factors can contribute to breast cancer risk, including body mass index, breastfeeding, age at menarche, first birth, and menopause [2]. In addition, genetic and hereditary factors account for a considerable portion of diagnosed cases [3] such as family history of breast or ovarian cancer and inherited mutations in breast cancer susceptibility genes of which the TP53 gene has a crucial role in breast cancer risk [3,4]. In response to cellular stresses, the p53 protein induces the expression of genes involved in cell cycle, senescence, apoptosis, and DNA repair regarding the context and extent of the stress [5]. As a tumor suppressor and tetrameric protein, any mutations in its coding region may affect its capability of establishing a functional protein [6]. TP53 mutations are found in over 50% of all types of cancers [7]. It is located on chromosome 17p13.1 composed of 11 exons, 10 of which are coding and the first one is a noncoding exon [8]. A complex regulatory mechanism exists to maintain its functionality in which at the protein level, Mdm2 and Mdm4 [9], and at the RNA level, HuR, L26 RPL26, Wig-1 [10], miR125a [11], and WRAP53α [12] are known to be involved. On the opposite strand of and overlapped with TP53, another gene, called WRAP53, encodes three different products as a result of its three alternative exons [13]. WRAP53α, a noncoding transcript, regulates p53 mRNA through binding to its 5′ untranslated region (UTR) and thus stabilizes it. Although the mechanisms involved are still unclear, this interaction presumably leads to masking or exposing the p53 mRNA sequence to destabilizing or stabilizing elements, respectively [14]. WRAP53β (also known as TCAB1), a coding transcript, plays a key role in RNP biogenesis and telomerase trafficking to the Cajal body [13,15] and is also needed for p53-dependent apoptosis upon DNA damages and p53-indepentent double-strand break repair [16,17]. No specific function has been proposed for WRAP53γ up until now.
Single Nucleotide Polymorphisms (SNPs) may alter gene regulation and structure and result in aberrant RNA or protein dysfunction. Although cancer-associated SNPs in determinant genes can increase the risk of cancer, as shown already for TP53 and WRAP53 in breast cancer susceptibility [18,19,20], it is necessary to define haplotype blocks to investigate the role of neighboring SNPs in cancer risk and calculate the linkage disequilibrium (LD) [21]. LD is the association between two nearby markers (e.g., SNPs), that result from common inheritance and are influenced by population size and mutation age. Further, a haplotype is a set of co-inherited SNPs that pass down through generations as a single unit [22]. Many studies have investigated different haplotypes’ role in breast cancer susceptibility to elucidate the effects of ancestral SNPs in a given population [22,23,24]. Our goal in this study was to conduct a haplotype-based association analysis at the TP53-WRAP53 locus in breast cancer. To do so, we analyzed the association between four SNPs, including rs1042522, rs17878362, rs2287499, and rs2287498, which refer to R72P substitution in exon 4 of TP53 [25], a 16 bp duplication in intron 3 of TP53 [26], a R68G substitution in the first exon of WRAP53 [27], and a WRAP53 Ex2+19 C>T polymorphism, respectively, in Iranian-Azeri women to validate the question of “whether this haplotype has a potential to be utilized as a prognostic biomarker for breast cancer or not”.
Materials and methods
Subjects
The study population comprised of 118 breast cancer patients and 110 healthy controls with no history of cancer. All subjects were selected from among the Iranian-Azeri population. Full written consents for all subjects were then obtained and approved by the Ethics Committee of Tabriz University of Medical Sciences research center (ethical approval code: 27997N1R2). This study protocol follows the ethical guidelines of the 1975 Declaration of Helsinki.
SNPs selection and genotyping
The selected SNPs for this study consisted of five polymorphisms spanning 7,674–7,689 kb of chromosome 17 at the TP53-WRAP53 locus, three of which (rs17880604, rs1042522, rs17878362) are located at 5′ region of the TP53 gene and two of which (rs2287498, rs2287499) are located at 5′ region of the WRAP53 gene.
In the TP53 gene, rs17880604, rs1042522, and rs17878362 polymorphisms were genotyped by RFLP-PCR, ARMS-PCR, and PCR with silver staining methods, respectively, as previously described [25]. The genotype of rs2287499 polymorphism in the WRAP53 gene was determined using SSCP-PCR as described by Bonab et al. [27]. The WRAP53 rs2287498 polymorphism was genotyped by tetra-ARMS-PCR method. PCR-amplification was carried out in a total volume of 20 μl reaction mixture, including 2 μl PCR buffer (10X), 1.2 μl MgCl2 (50 μM), 1 μl of each external primers (10 μM), 0.3 μl of each internal primers, 0.62 μl dNTPs (10 μM), 13.35 μl sterile distilled H2O, 0.23 μl Taq DNA polymerase (5 unit μl-1) and 1 μl template DNA (20–25 ng), all were purchased from Takapouzist company, Iran. PCR was conducted in a thermal cycler (Sensoquest, GmbH, Germany) with the following cycling setting: an initial denaturation step for 10 minutes at 95°C, followed by 35 cycles of 30 seconds at 95°C for denaturation, 30 seconds at 58°C for primer annealing, 35 seconds at 72°C for extension, and also a final extension was carried out for 10 min at 72°C. The amplified products and a 50-bp DNA ladder, as molecular size marker, were loaded on 2% agarose gel wells, and then electrophoresis was conducted for 30 minutes at 8 V cm-1.
Data and in silico analysis
To verify the Hardy-Weinberg equilibrium, P-value was set at 0.001. The frequency of polymorphisms and combinations of the three SNP markers were evaluated via the Haploview program v4.2 [28] based on P-value less than 0.05 as significant. A permutation test was also performed using this program to check the differences of haplotypes distribution between controls and breast cancer patients. In addition, calculating of Lewontin's standardized pairwise LD coefficient (D′) between each combination of the markers was done to determine the linkage disequilibrium. The in silico analysis was conducted to determine the deleterious and harmful effect of diseases, cancer-associated SNPs and SNP on RNA secondary structure using SIFT, Polyphen2, Fanthmm, RNAsnp, and SNP&GO online servers for three of the mentioned polymorphisms (e.g., rs2287498, rs2287499, and rs1042522).
Results
To verify the Hardy-Weinberg equilibrium, P-value was set at 0.001, which led to the exclusion of rs17880604 from the 5 markers selected. Therefore, four of five SNPs (rs1042522, rs17878362, rs2287499, and rs2287498) were included in the analysis at the TP53-WRAP53 locus as haplotype blocks that were constructed with Haploview v4.2, after which a linkage disequilibrium plot was generated (Fig 1).
NM_00546 and NM_018081 are the mRNA reference sequence numbers of the TP53 and WRAP53 genes, respectively. The 5−UTR is the 5− untranslated region of the TP53 gene. Solid squares indicate exons. The SNPs were represented in haplotype block sequentially from rs1042522, rs17878362, rs2287499, and rs2287498 (left to right).
As shown in this figure, there was no significant LD between any pairwise haplotypes. The highest LD was 54 and manifested between rs1042522 (C allele) of the TP53 gene and rs2287499 (G) of the WRAP53 gene, indicating a moderate linkage disequilibrium. The results showed that GA1CC was the most frequent haplotype with 0.297% and the rarest haplotypes were GA2CT with 0.014% frequency in both case and control samples. The GA1CC and CA1GC haplotypes were significantly associated with breast cancer susceptibility (P <0.05). The CA1GC haplotype was strongly identified as a breast cancer risk factor, and the GA1CC haplotype was assumed to be a protective factor against breast cancer risk. Subsequently, the permutation tests on the formed TP53-WRAP53 haplotypes confirmed the hypothesized role of the above-mentioned haplotypes in breast cancer susceptibility (Table 1).
Additionally, an analysis of haplotypes formed by the three markers (all combinations of the three markers formed by excluding one at a time) was performed. P-values were consistent with the aforementioned statistically significant P-values resulting from the haplotypes analysis with four markers (Table 2), suggesting that these markers in haplotype blocks formed by three or four markers are closely related to breast cancer susceptibility.
Three of five SNPs (rs2287499, rs1042522, and rs2287498) were used for in silico analysis, but the other two (e.g., rs17880604 and rs17878362) were excluded due to their intronic positions. The in silico analysis results are shown in Table 3 such that RNAsnp analysis showed a significant alteration in secondary RNA structure of WRAP53 due to rs2287499 polymorphism.
Also, Fathmm website predicted damaging statues for rs1042522 polymorphism in p53 protein. Secondary RNA structure alterations of TP53 and WRAP53 were observed due to the mentioned three SNPs as shown in Fig 2.
Local regions for a1) R72P substitution in TP53, a2) R68G substitution in WRAP53, a3) F150F substitution in WRAP53. a4) black lines demonstrate insignificant alteration (P >0.02) and other colors are demonstration of significant changes. Secondary RNA structure of R72P substitution in b1) mutation and b2) wild-type. Secondary RNA structure of R68G substitution in c1) mutation and c2) wild-type. Secondary RNA structure of F150F substitution in d1) mutation and d2) wild-type.
Discussion
Polymorphisms and haplotypes in the TP53 and WRAP53 genes may affect their products, thereby causing cancer vulnerability, tumor invasiveness and prognosis, or cancer therapy response [20,29,30]. Our results demonstrated an increased risk of breast cancer in one out of 12 possible combinations of polymorphisms (the CA1GC haplotype block)(). Additionally, one of the haplotypes (GA1CC) was assumed to be a protective risk factor. These imply the essential roles of the haplotypes at the TP53-WRAP53 locus, possibly due to the crucial role of p53 in various cell functions and due to WRAP53 being a regulator of p53 or a vital RNP biogenesis mediator.
Also, with moderate D′ values between rs1042522 and rs2287499 SNPs (Fig 1), it is obvious that there is only a small chance that these markers will be inherited together from the same ancestor, suggesting heterogeneity in our studied SNPs in an Iranian-Azeri population. A number of researchers have investigated the haplotype linkage disequilibrium in the TP53-WRAP53 locus region. Naccarati et al. analyzed the TP53 gene haplotype consisting of four SNPs, including rs17878362, rs1042522, rs12947788, and rs17884306 in a Czech Republic population. They showed a haplotype association (A1CCG) with cancer risk [31]; nonetheless, they proved that the A2GCG haplotype is associated with a significan decrease in the risk of breast cancer (P = 0.0001) [32]. Xingqun et al. investigated eight SNPs in the TP53-WRAP53 locus as a haplotype in Toronto and Portuguese populations for schizophrenia susceptibility. They showed a significant linkage disequilibrium between rs17878362 and rs2287499 and between rs2287499 and rs2287498 polymorphisms with a D′ value of 100 in both Toronto and Portuguese populations, respectively [33]. Our results are in contrast to the results of this study because we did not obtain a significant LD between haplotypes formed by the four investigated SNPs. The pairwise haplotype analysis between TP53 Arg72Pro and WRAP53 rs2287499 in HapMap Caucasians did not show a strong LD (D′ = 48) [34], which was in agreement with our results (D′ = 54). Besides, our previous pairwise analysis on rs2287499 and rs1042522 did not show a strong LD (D′ = 32), but we found a significant association between the GC haplotype with breast cancer risk (P = 0.024) [35]. Our data were consistent with a study by Buyru et al., who analyzed three SNPs (rs17878362, rs1042522, and rs17880604) in two polymorphism combinations (+16 bp GG and –16 bp GG) since this haplotype showed an association with an increase in the risk of breast cancer in a Turkish population [36]. TP53 haplotype comprising of rs17878362, rs1042522 and rs186837503 for the incidence risk of post-angioplasty restenosis was evaluated by Y. L. Zee et al. They demonstrated two polymorphism combinations (–16 bp CG and +16 bp CA) as a protective haplotype [37] which was in accordance with the Hao et al. [38] studies relating to breast cancer risk (investigating rs17878362 and rs1042522), but our study did not confirm it. These conflicting results may be explained by allele frequency differences between ethnic groups or be due to different sample sizes.
We also conducted an in silico analysis which revealed the impact of rs2287499 and rs1042522 polymorphisms on WRAP53 secondary RNA structure by a probable destabilizing effect and on cancer risk presumably by affecting the p53 protein function, respectively.
Conclusion
In conclusion, we found that the CA1GC and GA1CC haplotypes confer an increased risk of breast cancer and a protective role in breast cancer susceptibility, respectively. Therefore, they may be useful as molecular prognostic markers for breast cancer, suggesting that genetic background based on certain haplotypes in TP53-WRAP53 genes may play an important role in breast cancer susceptibility. In addition, LD analysis between four studied polymorphisms indicates heterogeneity of our studied population and provides a presumption that these markers are not linked together. Furthermore, in silico analysis predicted the alterations in TP53 and WRAP53 products in presence of rs1042522 and rs2287499, respectively.
The important functions of WRAP53 and the different polymorphisms within it for regulating p53 are emerging. To the best of our knowledge this is the first study to describe the haplotypes of the TP53-WRAP53 locus. However, more studies are needed to investigate more haplotype blocks within this locus in order to elucidate the complex regulating pathways and to discover cancer-associated markers with possible prognostic utility.
Supporting information
S1 Data. Clinicopathologic data of all the studied cases.
https://doi.org/10.1371/journal.pone.0220727.s001
(XLSX)
S2 Data. Genotypes for all the five SNPs in the studied population related to Tables 1 and 2.
https://doi.org/10.1371/journal.pone.0220727.s002
(XLSX)
Acknowledgments
We would like to thank all participants in this study, including patients, healthy individuals, and all those who helped us in sampling and data collection, Nour-E-Nejat and Imam Reza hospitals staffs.
References
- 1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jmel A, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6): 394–424. pmid:30207593
- 2. Sung H, Ren J, Li J, Pfeiffer RM, Wang Y, Guida JL, et al. Breast cancer risk factors and mammographic density among high-risk women in urban China. NPJ breast cancer. 2018;4(1): 3. pmid:29423438
- 3. Kim G, Ouzounova M, Quraishi AA, Davis A, Tawakkol N, Clouthier SG, et al. SOCS3-mediated regulation of inflammatory cytokines in PTEN and p53 inactivated triple negative breast cancer model. Oncogene. 2014;34(6): 671–680. pmid:24531711
- 4. Nikkhoo A, Rostami N, Hojjat‐Farsangi M, Azizi G, Yousefi B, Ghalamfarsa G, et al. Smac as novel promising mimetics modulators of apoptosis in the treatment of breast cancer. J Cell Biochem. 2019;120(6): 9300–9314. pmid:30506843
- 5. Uehara I, Tanaka N. Role of p53 in the Regulation of the Inflammatory Tumor Microenvironment and Tumor Suppression. Cancers (Basel). 2018;10: 219. pmid:29954119
- 6. Bellazzo A, Sicari D, Valentino E, Del Sal G, Collavin L. Complexes formed by mutant p53 and their roles in breast cancer. Breast Cancer. 2018;10: 101–112. pmid:29950894
- 7. Leroy B, Ballinger ML, Baran-Marszak F, Bond GL, Braithwaite A, Concin N, et al. Recommended guidelines for validation, quality control, and reporting of TP53 variants in clinical practice. Cancer Res. 2017;77: 1250–1260. pmid:28254861
- 8. Joruiz SM, Bourdon J-C. p53 isoforms: key regulators of the cell fate decision. Cold Spring Harb perspect med. 2016;6(8): a026039. pmid:26801896
- 9. Toledo F, Wahl GMJNRC. Regulating the p53 pathway: in vitro hypotheses, in vivo veritas. Nat Rev Cancer. 2006;6(12): 909. pmid:17128209
- 10. Farnebo M, Bykov VJ, Wiman KG. The p53 tumor suppressor: a master regulator of diverse cellular processes and therapeutic target in cancer. Biochem Biophys Res Commun. 2010;396(1): 85–89. pmid:20494116
- 11. Zhang Y, Gao J-S, Tang X, Tucker LD, Quesenberry P, Rigoutsos I, et al. MicroRNA 125a and its regulation of the p53 tumor suppressor gene. FEBS Lett. 2009;583(22): 3725–3730. pmid:19818772
- 12. Farnebo M. Wrap53, a novel regulator of p53. Cell Cycle. 2009;8(15): 2343–2346. pmid:19571673
- 13. Henriksson S, Farnebo M. On the road with WRAP53β: guardian of Cajal bodies and genome integrity. Front Genet. 2015;6: 91. pmid:25852739
- 14. Pouladi N, Kouhsari SM, Feizi MH, Gavgani RR, Azarfam P. Overlapping region of p53/wrap53 transcripts: mutational analysis and sequence similarity with microRNA-4732-5p. Asian Pac J Cancer Prev. 2013;14(6): 3503–3507. pmid:23886136
- 15. Enwerem II, Velma V, Broome HJ, Kuna M, Begum RA, Hebert MD, et al. Coilin association with Box C/D scaRNA suggests a direct role for the Cajal body marker protein in scaRNP biogenesis. Biol Open. 2014;3(4): 240–249. pmid:24659245
- 16. Rassoolzadeh H, Böhm S, Hedström E, Gad H, Helleday T, Henriksson S, et al. Overexpression of the scaffold WD40 protein WRAP53β enhances the repair of and cell survival from DNA double-strand breaks. Cell death dis. 2016;7: e2267. pmid:27310875
- 17. Yuan JM, Li XD, Liu ZY, Hou GQ, Kang JH, Huang DY, et al. Cisplatin induces apoptosis via upregulating Wrap53 in U-2OS osteosarcoma cells. Asian Pac Cancer Prev. 2011;12(12): 3465–3469. pmid:22471498
- 18. Stracquadanio G, Wang X, Wallace MD, Grawenda AM, Zhang P, Hewitt J, et al. The importance of p53 pathway genetics in inherited and somatic cancer genomes. Nat Rev Cancer. 2016;16(4): 251–265. pmid:27009395
- 19. Cao H, Wang S, Zhang Z, Lou J. Association between the WRAP53 gene rs2287499 C> G polymorphism and cancer risk: A meta-analysis. Genet Mol Res. 2016;15(3). pmid:27525856
- 20. Devi KR, Chenkual S, Majumdar G, Ahmed J, Kaur T, Zonunmawia JC, et al. TLR2Δ 22 (-196-174) significantly increases the risk of breast cancer in females carrying proline allele at codon 72 of TP53 gene: a case–control study from four ethnic groups of North Eastern region of India. Tomur Biol. 2015;36(12): 9995–10002. pmid:26188904
- 21. Wall JD, Pritchard JK. Haplotype blocks and linkage disequilibrium in the human genome. Nat Rev Genet. 2003;4(8): 587–597. pmid:12897771
- 22. Edvardsen H, Kulle B, Tsalenko A, Grenaker Alnaes GI, Ekeberg Johansen F, Enerly E, et al. Haplotypes associated to gene expression in breast cancer: can they lead us to the susceptibility markers?. BioRxiv. 2018.
- 23. Vitiello GAF, Guembarovski RL, Hirata BKB, Amarante MK, de Oliveira CEC, Oliveira KB, et al. Transforming growth factor beta 1 (TGFβ1) polymorphisms and haplotype structures have dual roles in breast cancer pathogenesis. J Cancer Res Clin Oncol. 2018;144(4): 645–655. pmid:29362917
- 24. Surowy H, Varga D, Burwinkel B, Marmé F, Sohn C, Luedeke M, et al. A low‐frequency haplotype spanning SLX4/FANCP constitutes a new risk locus for early‐onset breast cancer (< 60 years) and is associated with reduced DNA repair capacity. Int J Cancer. 2018;142(5): 757–768. pmid:29044504
- 25. Dehghan R, Hosseinpour Feizi MA, Pouladi N, Babaei E, Montazeri V, Fakhrjoo A, et al. Association of P53 (− 16ins-Pro) Haplotype with the Decreased Risk of Differentiated Thyroid Carcinoma in Iranian-Azeri Patients. Pathol Oncol Res. 2015;21(2): 449–454. pmid:25410025
- 26. Dehghan R, Hosseinpour Feizi MA, Pouladi N, Adampourezare M, Farajzadeh D. The TP53 intron 6 G13964C Polymorphism and Risk of Thyroid and Breast Cancer Development in the Iranian Azeri Population. Asian Pac J Cancer Prev. 2015;16(7): 3073–3077. pmid:25854408
- 27. Bonab AS, Pouladi N, Hosseinpourfeizi MA, Gavgani RR, Dehghan R, Azarfam P, et al. Single-strand conformational polymorphism analysis of a common single nucleotide variation in WRAP53 gene, rs2287499, and evaluating its association in relation to breast cancer risk and prognosis among Iranian-Azeri population. Med Oncol. 2014;31(9): 168. pmid:25134915
- 28. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2): 263–265. pmid:15297300
- 29. Medrek K, Magnowski P, Masojc B, Chudecka-Glaz A, Torbe B, Menkiszak J, et al. Association of common WRAP 53 variant with ovarian cancer risk in the Polish population. Mol Biol Rep. 2013;40(3): 2145–2147. pmid:23192612
- 30. Lin HY, Yang MC, Huang CH, Wu WJ, Yu T-, Lung FW. Polymorphisms of TP53 are markers of bladder cancer vulnerability and prognosis. Urol Oncol. 2013;31(7):1231–1241. pmid:22178231
- 31. Naccarati A, Pardini B, Polakova V, Smerhovsky Z, Vodickova L, Sousek P, et al. Genotype and haplotype analysis of TP53 gene and the risk of pancreatic cancer: an association study in the Czech Republic. Carcinogenesis. 2010;31(4): 666–670. pmid:20110284
- 32. Vymetalkova V, Soucek P, Kunicka T, Jiraskova K, Brynychova V, Pardini B, et al. Genotype and Haplotype Analyses of TP53 Gene in Breast Cancer Patients: Association with Risk and Clinical Outcomes. PLoS One. 2015;10(7): e0134463. pmid:26226484
- 33. Ni X, Trakalo J, Valente J, Azevedo MH, Pato MT, Pato CN, et al. Human p53 tumor suppressor gene (TP53) and schizophrenia: case–control and family studies. Neurosci Lett. 2005;388(3): 173–178. pmid:16039051
- 34. Alonso S, Izagirre N, López S, Smith-Zubiaga I, Hervella M, Boyano MD, et al. The diversity profile of TP53 is influenced by positive selection on the immediately upstream locus WDR79. Hum hered. 2010;69(1): 34–44. pmid:19797907
- 35. Pouladi N, Abdolahi S, Farajzadeh D, Hosseinpour Feizi MA. Association of the 17p13.1 region gene variants rs1042522 and rs2287499 with risk of breast cancer in Iranian-Azeri population. Meta Gene. 2019;19: 117–122.
- 36. Buyru N, Altinisik J, Demokan S, Dalay N. p53 genotypes and haplotypes associated with risk of breast cancer. Cancer Detect Prev. 2007;31(3): 207–213. pmid:17574348
- 37. Zee RYL, Cook NR, Kim C-A, Fernandez-Cruz A, Lindpaintner K. TP53 haplotype-based analysis and incidence of post-angioplasty restenosis. Hum Genet. 2004;114(4): 386–390. pmid:14740296
- 38. Hao W, Xu X, Shi H, Zhang C, Chen X. No association of TP53 codon 72 and intron 3 16-bp duplication polymorphisms with breast cancer risk in Chinese Han women: new evidence from a population-based case-control investigation. Eur J Med Res. 2018;23(1): 47. pmid:30309383