Gene Combination of CD44 rs187116, CD133 rs2240688, NF-κB1 rs28362491 and GSTM1 Deletion as a Potential Biomarker in Risk Prediction of Breast Cancer in Lower Northern Thailand

Document Type: Research Articles

Authors

1 Department of Biochemistry, Faculty of Medical Science, Naresuan University, Phitsanulok, Thailand.

2 Department of Forensic Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.

3 Center of Excellence in Medical Biotechnology, Faculty of Medical Science, Naresuan University, Phitsanulok, Thailand.

Abstract

Background: Biomarkers play an important role in oncology, including risk assessment, treatment prediction, and
monitoring the progression of disease. In breast cancer, many genes are used as biomarkers. Since, several SNP variations
of hallmark – related genes have been reported to be of value in risk prediction in various cancers and populations, some
genetic polymorphism loci were combined and reported as biomarkers for use in the risk assessment of breast cancer
in Thai people. Methods: Twelve cancer gene hallmarks (15 polymorphic loci) were selected and genotyped in 184
breast cancer patients and 176 healthy individuals in Phitsanulok, Thailand. Results: AA genotype of CD44 rs187116
(c.67+4883G>A), the C allele of CD133 rs2240688 (c.*667A>C), the *2 allele (4 bp deletion) of NF-κB1 rs28362491
and the homozygous null allele genotype of GSTM1 were significantly associated with an increased risk of breast cancer
(p<0.05). A combination of these 4 significant loci showed that AA-AA-*1*1-homozygous null allele genotype has the
greatest correlation with increased risk of breast cancer (OR = 21.00; 95% CI: 1.77 to 248.11; p = 0.015), followed by
GA-AA-*2*2- homozygous null allele genotype (p = 0.037) and GG-AC-*1*2- homozygous null allele genotype (p
= 0.028). Conclusion: These findings suggest that the polymorphisms of CD44 rs187116 (c.67+4883G>A), CD133
rs2240688 (c.*667A>C), NF-κB1 rs28362491 and GSTM1 homozygous null allele genotype might be associated with
an increased risk of breast cancer, and this gene combination could possibly be used as biomarkers for risk prediction,
which would be of benefit in planning health surveillance and cancer prevention.

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