Literature DB >> 33735891

Combined Genotype Effects of TP53 and PAI-1 Polymorphisms in Breast Cancer Susceptibility: Multifactor Dimensionality Reduction and in silico Analysis.

Nasser Pouladi1, Mojtaba Shavali2, Sepehr Abdolahi2.   

Abstract

INTRODUCTION: Breast cancer is a heterogeneous and multifactorial disease. TP53 and PAI-1 as important tumor suppressor genes are involved in the development, invasion, and metastasis of many cancers. This study's objective was to demonstrate the combined genotype effects of these 2 genes by investigating their single nucleotide polymorphisms.
METHODS: In this case-control study, 200 individuals with breast cancer and 179 healthy individuals were studied. The genotypes were determined using the tetra-ARMS method. For data analysis, MDR, online javstat statistics package, and SPSS v.24 software were used. Also, in silico studies on the estimated effects of each of these polymorphisms were performed.
RESULTS: We showed a novel gene-gene interaction of these 2 genes and demonstrated a strong synergistic interaction for TP53/PAI-1, moderate synergistic interaction for PAI-1/age, and correlation for TP53/age. On the other hand, there was no association between the allelic and genotype frequency alone and in combination, with case-control status, using the parametric method, between TP53 and PAI-1. DISCUSSION/
CONCLUSION: Our findings suggest that the polymorphism of codon 72 of the TP53 gene was significantly associated with tumor stage (p < 0.023). In conclusion, we showed a gene-gene interaction between TP53 and PAI-1, in combination, using the MDR method.
© 2021 S. Karger AG, Basel.

Entities:  

Keywords:  Breast cancer; Multifactor dimensionality reduction; PAI-1 gene; Single nucleotide polymorphisms; Susceptibility; TP53 gene

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Year:  2021        PMID: 33735891     DOI: 10.1159/000514398

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  1 in total

1.  PAI-1 Polymorphisms Have Significant Associations With Cancer Risk, Especially Feminine Cancer.

Authors:  Jiaxi Wang; Yuanyuan Peng; Hejia Guo; Cuiping Li
Journal:  Technol Cancer Res Treat       Date:  2021 Jan-Dec
  1 in total

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