Next-generation sequencing and bioinformatics analysis in breast cancer research: Insights from Western Kazakhstan

Abstract

Breast cancer (BC) is one of the most prevalent malignancies among women worldwide and a leading cause of cancer-related mortality. Studying gene mutations associated with BC risk in Kazakh women can help identify hereditary predispositions and facilitate early prevention. Next-generation sequencing (NGS) technology was used to sequence 113 candidate genes, followed by bioinformatics analysis, on BC patients from Western Kazakhstan. NGS sequencing revealed 28 polymorphisms from the genome-wide association studies catalog, seven of which were identified as statistically significant risk polymorphisms for BC: RARG (Rs2229774), FGFR2 (Rs2981582), ATM (Rs1800057), MAP3K1 (Rs889312), BRCA2 (Rs11571833), FGFR2 (Rs7895676), and FGFR2 (Rs1219648). Inheritance model analysis showed that the polymorphism in the Rs2981582 of the FGFR2 gene increased the likelihood of developing BC across four inheritance models. The Rs2229774 polymorphism of the RARG gene elevated BC risk in three models, whereas the Rs889312 polymorphism of the MAP3K1 gene did so in two models. The Rs137852985 polymorphism of the BRIP1 gene raised BC risk in four models, and Rs137852576 of the AR gene increased the risk in the codominant model. In a one-factor risk prediction, 32 significant factors were identified, with risks ranging from 69.7% to 90.6%. The combination of polymorphisms “Rs2229774 (AG),” “Rs889312 (AA, CC),” and “Age <54 years” yielded a high-risk assessment (95.8%), with a predictive quality score of 0.88. Overall, NGS sequencing identified six statistically significant gene polymorphisms (ATM Rs1800057, RARG Rs2229774, BRCA2 Rs11571833, MAP3K1 Rs889312, FGFR2 Rs2981582, and BRIP1 Rs137852985) associated with a high risk of BC in Kazakh women.

Keywords

Next-generation sequencing / Breast cancer / Genome-wide association study / Single-nucleotide polymorphism / Bioinformatics analysis

Funding

This research was funded by the Ministry of Education and Science of the Republic of Kazakhstan as part of the project “New Molecular-Genetic Methods for Pre-Symptomatic Diagnosis and Treatment of Several Significant Diseases” (State Registration Number 0117RK00036; Project Leader: Ramazanova B.A., Asfendiyarov Kazakh National Medical University), 2019.

Conflict of interest

The authors declare that they have no competing interests.

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