Association of Interactions between Metabolic ‘Caretaker’ Genes, p53, MDM2, and Tobacco Use with the Risk of Oral Cancer: A Multifactor Dimensionality Reduction Approach

Singh, Ragini D; Patel, Kinjal A; Patel, Jayendra B; Patel, Prabhudas S

doi:10.31557/APJCP.2023.24.4.1231

Association of Interactions between Metabolic ‘Caretaker’ Genes, p53, MDM2, and Tobacco Use with the Risk of Oral Cancer: A Multifactor Dimensionality Reduction Approach

Document Type : Research Articles

Authors

¹ Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Rajkot, Gujarat, India.

² Molecular Oncology Laboratory, Cancer Biology Department, The Gujarat Cancer and Research Institute, Asarwa, Ahmedabad, Gujarat, India.

10.31557/APJCP.2023.24.4.1231

Abstract

Background: The present study investigated the association of interactions between gene polymorphisms in metabolic ‘caretaker’ genes (Phase I: CYP1A1, CYP2E1; Phase II: GSTM1, GSTT1), the cell cycle regulatory gene, p53, along with its negative controller, MDM-2, and the environment variable (tobacco). A nonparametric model, multifactor dimensionality reduction (MDR), was applied to analyse these interactions. Materials and Methods: This case-control study was carried out on 242 subjects. Genomic DNA was extracted from peripheral blood lymphocytes.11 gene variants with an exposure variable (tobacco use) were analysed using MDR to identify the best locus model for gene-gene and gene-environment interactions. Statistical significance was evaluated using a 1000-fold permutation test using MDR permutation testing software (version 1.0 beta 2). The value of p<0.05 was considered statistically significant. Results: The best three-locus model for gene-gene interaction included two of the p53 gene polymorphisms; rs17878362 (intron 3) and rs1042522 (exon 4) and rs6413432 in the Phase I gene, CYP2E1(DraI). The three-locus model to evaluate the gene-environment interaction included two intronic polymorphisms of the p53 gene, that is, rs17878362 (intron 3) and rs1625895 (intron 6), and rs4646903 in the Phase I gene CYP1A1*2C. The interaction graphs revealed independent main effects of the tobacco and p53 polymorphism, rs1042522 (exon 4), and a significant additive interaction effect between rs17878362 (intron 3) and rs1042522 (exon 4). Conclusions: The nonparametric approach highlighted the potential role of tobacco use and variations in the p53 gene as significant contributors to oral cancer risk. The findings of the present study will help implement preventive strategies in both tobacco use and screening using a molecular pathology approach.

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