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基于人工神经网络对叶酸和外源性物质代谢途径中基因-营养相互作用的探索,这些代谢途径调节乳腺癌易感性。

Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

作者信息

Naushad Shaik Mohammad, Janaki Ramaiah M, Pavithrakumari Manickam, Jayapriya Jaganathan, Hussain Tajamul, Alrokayan Salman A, Gottumukkala Suryanarayana Raju, Digumarti Raghunadharao, Kutala Vijay Kumar

机构信息

School of Chemical & Biotechnology, SASTRA University, Tirumalaisamudram, Thanjavur 613401, India.

School of Chemical & Biotechnology, SASTRA University, Tirumalaisamudram, Thanjavur 613401, India.

出版信息

Gene. 2016 Apr 15;580(2):159-168. doi: 10.1016/j.gene.2016.01.023. Epub 2016 Jan 16.

DOI:10.1016/j.gene.2016.01.023
PMID:26784656
Abstract

In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 μg/day) and B12 (6 μg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1.

摘要

在当前研究中,基于叶酸和外源性物质代谢途径基因多态性数据以及营养和人口统计学变量,开发了一种基于人工神经网络(ANN)的乳腺癌预测模型,以研究微量营养素如何调节乳腺癌易感性。所开发的ANN模型解释了乳腺癌预测中94.2%的变异性。叶酸(400μg/天)和维生素B12(6μg/天)的固定效应模型分别显示风险降低33.3%和11.3%。多因素降维分析显示叶酸反应者存在以下相互作用:RFC1 G80A×MTHFR C677T(主要)、COMT H108L×CYP1A1 m2(次要)、MTR A2756G(第三)。维生素B12反应者之间的相互作用为RFC1G80A×cSHMT C1420T和CYP1A1 m2×CYP1A1 m4。ANN模拟显示,叶酸增加可能恢复雌激素受体(ER)和孕激素受体(PR)表达,并减少细胞外超氧化物歧化酶和乳腺癌1号基因(BRCA1)启动子CpG岛甲基化。叶酸的膳食摄入似乎通过其对ER和PR表达以及细胞外超氧化物歧化酶(EC-SOD)和BRCA1甲基化的调节作用,对乳腺癌起到保护作用。

相似文献

1
Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.基于人工神经网络对叶酸和外源性物质代谢途径中基因-营养相互作用的探索,这些代谢途径调节乳腺癌易感性。
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Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches.通过白盒、灰盒和黑盒建模方法鉴定代谢途径中的通量控制点。
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