ArticleMolecular genetics and genomics : MGG2026
Identification and functional analysis of exonic SNPs in MMP2 and MMP3 genes as prognostic biomarkers for breast cancer patients.
Article in Molecular genetics and genomics : MGG, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Breast cancer is the most prevalent malignancy among women worldwide, and metastasis remains the leading cause of breast cancer-related deaths. Matrix metallopeptidase genes MMP2 and MMP3 are key regulators of extracellular matrix degradation and tumour invasion, yet the role of their exonic single nucleotide polymorphisms (SNPs) in breast cancer progression remains unexplored. This study aimed to identify exonic SNPs in MMP2 and MMP3 among Malaysian breast cancer patients, to assess their functional effects on mRNA structure and stability, and to evaluate their prognostic value in breast cancer metastasis. In total, 36 SNPs (21 in MMP2 and 15 in MMP3), including 10 novel SNPs and one novel deletion, were identified using high-resolution melting (HRM) analysis and confirmatory DNA sequencing. Logistic regression analysis revealed that two exonic SNPs, c.1842C>G (MMP2) and c.1070-23T>A (MMP3) were significant predictors of metastasis, improving the accuracy and sensitivity of the predictive model compared with clinicopathological factors alone. Bioinformatics analysis further showed that c.1842C>G and several other exonic SNPs altered mRNA secondary structure, potentially reducing metastasis risk by diminishing mRNA stability. In addition, synonymous SNPs (sSNPs) such as c.678G>C (MMP2), c.288T>C (MMP3), and c.626-14A>G (MMP3) exhibited overdominance effects, with heterozygous genotypes modulating mRNA folding and stability and thereby exerting a protective influence against metastasis. These findings highlight exonic SNPs in MMP2 and MMP3 as promising prognostic biomarkers for breast cancer, with the potential to improve metastasis risk assessment and support more personalised approaches to patient management. Validation in larger, ethnically diverse cohorts will be important to confirm their clinical utility and to elucidate the underlying biological mechanisms.
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