The Association between Single Nucleotide Polymorphisms rs1042522 and rs1642785 in the TP53 gene and Acute Myeloid leukemia in a sample of the Baghdad/ Iraq population
Main Article Content
Abstract
Acute myeloid leukemia (AML) represents the most prevalent type of acute leukemia in adults and is responsible for approximately 80% of all cases. The tumor suppressor gene (TP53) is a gene that has been frequently studied in cancer, and mutations in this gene account for about 50% of human cancers. This study aims to evaluate the correlation between two single nucleotide polymorphisms (SNPs) in the gene: rs1042522 and rs1642785, and a group of Iraqi patients suffering from pre-diagnostic acute myeloid leukemia (AML). Blood samples were collected from sixty patients (26 males and 34 females) and sixty controls (26 males and 34 females); these subjects were matched in gender, age, and ethnicity. Genomic DNA has been extracted from whole frozen blood samples by using the Easy Pure® Blood Genomic Kit, and then the purity and concentration have been measured by using the Nano drop NAS-99 spectrophotometer. Nano Drop readings ranged between 7-55ng/µl for the concentration and between 1.78-1.9 for the purity. High resolution melt (HRM) real-time PCR was used in the detection of these two SNPs. TP53 genotype frequencies have been in accordance with Hardy–Weinberg equilibrium (HWE), with statistically significant differences p≤0.05 between the genotypes of the control and patient groups. The rs1042522 genotype frequency was significantly different between patients and controls p = 0.0001, and participants with the GA genotype were more likely to develop AML OR = 7.8, 95% CI 3.2–18.4, p= 0.0001. In addition, the genotype frequency of rs1642785 was significantly different between patients and controls p = 0.002, and participants with the GA genotype were more likely to develop AML OR = 3.5, 95% CI 1.5–8.12, p = 0.002.
Received 09/12/2022
Revised 07/03/2023
Accepted 09/03/2023
Published Online First 20/08/2023
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
References
Stubbins R.J, Stamenkovic M, Roy C, Rodrigo J, Chung S, Kuchenbauer F.C, et al. Incidence and socioeconomic factors in older adults with acute myeloid leukaemia: Real-world outcomes from apopulation-based cohort. Eur J Haematol. 2022; 108: 437–445. https://doi.org/10.1111/ejh.13752.
Alea FS, Karima.FA, Alaa FA. Evaluation of electrolytes in adult patients with acute leukemia before and after Chemotherapy. Baghdad Sci J. 2013; 10(2): 362-367. https://doi.org/10.21123/bsj.2013.10.2.362-367.
Zjablovskaja P, Florian M. Acute Myeloid Leukemia: Aging and Epigenetics. Cancers. 2019; 12: 103. https://doi.org/10.3390/cancers12010103.
Ghadeer JM. A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset. Baghdad Sci J. 2020; 17(4):1255-1266. https://doi.org/10.21123/bsj.2020.17.4.1255
Hafner A, Bulyk M, Jambhekar A, Lahav G. The multiple mechanisms that regulate p53 activity and cell fate. Nat Rev Mol Cell Biol. 2019; 20(4): 199–210. https://doi.org/10.1038/s41580-019-0110-x.
Stein Y, Rotter V, Aloni-Grinstein R. Gain-of-function mutant p53: all the roads lead to tumorigenesis. Int J Mol Sci. 2019; 20 (24): 6197. https://doi.org/10.3390/ijms20246197.
Zhu H, Gao H, Ji Y. Targeting p53-MDM2 interaction by small-molecule inhibitors: learning from MDM2 inhibitors in clinical trials. J Hematol Oncol. 2022; 15(1): 91. https://doi.org/10.1186/s13045-022-01314-3.
Zhao Y, Wu L, Yue X, Zhang C, Wang J, Li J, et al. A polymorphism in the tumor suppressor p53 affects aging and longevity in mouse models. elife. 2018; 7: e34701. https://doi.org/10.7554/eLife.34701
Francisco G, Menezes RR, Eluf-Neto J, Chammas R. Arg72Pro. TP53 polymorphism and cancer susceptibility: a comprehensive meta-analysis of 302 case–control studies. Int J Cancer. 2011; 129 (4): 920-930. https://doi.org/10.1002/ijc.25710.
Whibley C, Pharoah PD, Hollstein M. P53 polymorphisms: Cancer implications. Nat Rev Cancer. 2009; 9: 95–107. https://doi.org/10.1038/nrc2584.
Kazantseva M, Mehta S, Eiholzer RA, Gimenez G, Bowie S, Campbell H, et al. The δ133p53β isoform promotes an immunosuppressive environment leadingto aggressive prostate cancer. Cell Death Dis. 2019; 1: 631. https://doi.org/10.1038/s41419-019-1861-1
Anoushirvani A, Aghabozorgi R, Ahmadi A, Arjomandzadegan M, Sahraei M, Khalili S, et al. Association of rs1042522 SNP with clinic pathologic factors of breast cancer patients in the markazi province of Iran Open Access Maced. J Med Sci. 2018; 6(12): 2277–2282. https://doi.org/10.3889/oamjms.486.
Bulgakova O, Kussainova A, Bersimbaev R. The cell cycle regulatory gene polymorphisms TP53 (rs1042522) and MDM2 (rs2279744) in lung cancer: a meta-analysis. Vavilovskii Zhurnal Genet Selektsii. 2020; 24(7): 777–784. https://doi.org/10.18699/VJ20.673
Matteo F, Giovanna P, Paolo C, Maria LI, Maristella I, Maria RD, et al. Impact on breast cancer susceptibility and clinicopathological traits of common genetic polymorphisms in TP53, MDM2 and ATM genes in Sardinian women. Oncol. Lett. 2022; 24: 331. https://doi.org/10.1111/1759-7714.13467
Wigginton JE, Cutler DJ, Abecasis GR. A note on exact tests of Hardy-Weinberg equilibrium. Am J Hum Genet. 2005; 76: 887–893. https://doi.org/10.1086/429864
Mohammed RK, Ibrahim AA. Distribution of dfrA1 and cat1 antibiotic resistance genes in uropathogenic Escherichia coli isolated from teens pregnant women in Iraq. Iraqi J Sci. 2022; 63(8): 3340–3353. https://doi.org/10.24996/ijs.2022.63.8.9.
Chatzidimopoulos M, Ganopoulos I, Madesis P, Vellios E, Tsaftaris A, and Pappas AC. High-resolution melting (HRM) analysis for rapid detection and characterization of Botrytis cinerea phenotypes resistant to fenhexamid and boscalid. Plant Pathol. 2014a; 63: 1336–1343. https://doi.org/10.1111/ppa.12210.
Bezerra M.F, Coelho-Silva JL, Nascimento JC , Benicio MT, Rocha CR, Machado CG, et al. Association between the TP53 Arg72Pro polymorphism and clinical outcomes in acute myeloid leukemia. Haematologica. 2017; 102:43–46. https://doi.org/10.3324/haematol.2016.155069.
Gu J, Spitz MR, Zhao H, Lin J, Grossman HB, Dinney CP, et al. Roles of tumor suppressor and telomere maintenance genes in cancer and aging - an epidemiological study. Carcinogenesis. 2005; 26: 1741–1747.
Bonafé M, Ceccarelli C, Farabegoli F, Santini D, Taffurelli M, Barbi C, et al. Retention of the p53 codon 72 arginine allele is associated with a reduction of disease-free and overall survival in arginine/proline heterozygous breast cancer patients. Clin Cancer Res. 2003; 9: 4860–4864.
Dumont P, Leu J-J, Della Pietra AC, George DL, and Murphy M. The codon 72 polymorphic variants of p53 have markedly different apoptotic potential. Nat Genet. 2003a; 33: 357–65. https://doi.org/10.1038/ng1093.
Tian X, Dai S, Sun J, Jiang S, Jiang Y. Association between TP53 Arg72Pro polymorphism and leukemia risk: A meta-analysis of 14 case-control studies. Sci Rep. 2016; 6: 24097. https://doi.org/10.1038/srep24097.
Hamadou WS, Besbes S, Bourdon V, Youssef YB, Laatiri MA, Noguchi T, et al. Mutational analysis of TP53 gene in Tunisian familial hematological malignancies and sporadic acute leukemia cases. Fam Cancer. 2017; 16(1): 153–157. https://doi.org/10.1007/s10689-016-9931-3.
Perriaud L, Marcel V, Sagne C, Favaudon V, Guédin A, De Rache A, et al. Impact of G-quadruplex structures and intronic polymorphisms rs17878362 and rs1642785 on basal and ionizing radiation-induced expression of alternative p53 transcripts. Carcinogenesis. 2014; 35: 2706–2715. https://doi.org/10.1093/carcin/bgu206.
Sadia A, Rabbia M, Aisha S, Muhammad A M. Frequencies of TP53 germline variations and identification of two novel 3’UTR variants in a series of head and neck cancer cases view. medRxiv. 2021. https://doi.org/10.1101/2021.09.09.21263314.
Sailaja K, Rao V, Yadav S, Reddy R, Surekha D, Rao N, et al. Intronic SNPs of TP53 gene in chronic myeloid leukemia: Impact on drug response. J Nat Sci Biol Med. 2012; 3(2): 182–185. https://doi.org/10.4103/0976-9668.101910.