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DNA Repair Genes Polymorphisms: Impact on Acute Myeloid Leukemia Patients Outcome

Salah Aref1, Nadia El Menshawy1, Tarek Abou Zeid2

  • 1Hematology Unit, Clinical Pathology Department, Faculty of Medicine, Mansoura University, Egypt.

Asian Pacific Journal of Cancer Prevention : APJCP
|October 29, 2022
PubMed
Abstract

Insights

Specific gene variants in ATM, XRCC6, and LIG4 are linked to lower gene expression in Acute Myeloid Leukemia (AML) patients. This reduced expression impacts patient survival, suggesting a role in therapy optimization.

Area of Science:

  • Genetics
  • Molecular Biology
  • Oncology

Background:

  • ATM, XRCC6, and LIG4 genes are crucial for DNA double-strand break repair and genome stability.
  • Single nucleotide polymorphisms (SNPs) in these genes can alter their expression and function.
  • Understanding SNP effects is vital for assessing their impact on disease outcomes.

Purpose of the Study:

  • To investigate the effect of specific SNPs in DNA repair genes (ATM, XRCC6, LIG4) on gene expression.
  • To determine the association between these gene expression changes and patient outcomes in Acute Myeloid Leukemia (AML).

Main Methods:

  • Cross-sectional study of 95 newly diagnosed AML patients.
  • Evaluation of SNPs (ATM rs189037, XRCC6 rs2267437, LIG4 rs1805388) using Restriction Fragment Length Polymorphism (RFLP).
  • Quantification of gene expression using real-time PCR.

Main Results:

  • Specific SNPs (ATM AA, XRCC6 GG, LIG4 TT) were associated with significant downregulation of corresponding genes (P<0.001).
  • Lower expression of ATM and LIG4 correlated with shorter Overall Survival (OS) and Disease-Free Survival (DFS).
  • Multivariate analysis indicated lower ATM expression as a predictor for OS (HR: 2.02, P=0.020).

Conclusions:

  • Identified SNPs in ATM, XRCC6, and LIG4 are linked to reduced gene expression.
  • Lower ATM and XRCC6 expression predict poorer OS, while lower ATM expression predicts poorer DFS.
  • These findings suggest potential for using these genetic markers in optimizing AML therapy.
Keywords:
AMLATMLIG4XRCC6

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