Impact of 5' Near Gene Variants of Mannose Binding Lectin (MBL2) on Breast Cancer Risk.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Shreya Singh Kashyap, Surmeet Kaur, Rajiv Kumar Devgan, Sumitoj Singh, Jatinder Singh, Manpreet Kaur
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引用次数: 0

Abstract

The immune system plays a bifaceted role in tumour development through modulation of inflammation. MBL binds to damage-associated molecular patterns and induces inflammation through the activation of complement pathway. Dysregulated inflammation plays a major role in breast cancer pathogenesis, thereby suggesting its contribution towards breast cancer risk. Literature asserts single-nucleotide polymorphisms (SNPs) modulating serum MBL levels. Therefore, studying MBL2 SNPs in breast cancer might provide valuable insight in the disease pathogenesis. The present case-control association study aimed to elucidate the association between MBL2 5' near gene SNPs and breast cancer risk. Breast cancer patients were recruited from Government Medical College, G.N.D. Hospital, Amritsar. The age- and gender-matched genetically unrelated healthy individuals, from adjoining regions, with no history of malignancy up to three generations were recruited as controls. The SNPs of MBL2 from the 5' near gene region with putative functional significance were selected based upon the in silico analysis and literature review. The genotypic, allelic and haplotype frequencies for the studied variants were assessed and compared in the study participants by ARMS-PCR and PCR-RFLP. No difference in allelic, genotypic and haplotype frequencies was reported for rs7096206, rs7084554 and rs11003125 in both the participant groups. rs7084554 (CC) was found to confer risk towards hormone receptor-positive breast cancer. An intermediate LD was observed between rs7084554 and rs11003125. The study reports association between MBL2 variant (rs7084554) and hormone receptor-positive breast cancer risk. Further research in this direction might validate the findings.

Abstract Image

甘露糖结合凝集素 (MBL2) 5' 附近基因变异对乳腺癌风险的影响。
免疫系统通过调节炎症在肿瘤发生发展过程中扮演着双重角色。MBL 与损伤相关分子模式结合,并通过激活补体途径诱发炎症。失调的炎症在乳腺癌发病机制中起着重要作用,因此表明它对乳腺癌风险有影响。文献证实单核苷酸多态性(SNPs)可调节血清 MBL 水平。因此,研究乳腺癌中的 MBL2 SNPs 可能会对该疾病的发病机制提供有价值的见解。本病例对照关联研究旨在阐明 MBL2 5' 附近基因 SNPs 与乳腺癌风险之间的关联。乳腺癌患者来自阿姆利则的政府医学院、G.N.D. 医院。从邻近地区招募三代以内无恶性肿瘤病史、年龄和性别匹配的遗传无关的健康人作为对照。根据硅学分析和文献综述,从 MBL2 的 5'近基因区域筛选出具有推定功能意义的 SNPs。研究人员通过 ARMS-PCR 和 PCR-RFLP 评估和比较了所研究变异的基因型、等位基因和单倍型频率。结果显示,rs7096206、rs7084554 和 rs11003125 的等位基因、基因型和单倍型频率在两组参与者中均无差异。在 rs7084554 和 rs11003125 之间观察到了中间 LD。该研究报告了 MBL2 变异(rs7084554)与激素受体阳性乳腺癌风险之间的关联。这方面的进一步研究可能会验证这些发现。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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