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Identification of drug sensitive gene motifs using 'epigenetic profiles' derived from bioinformatics databases.

机译:使用衍生自生物信息学数据库的“表观遗传谱”鉴定药物敏感性基因基序。

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摘要

The use of epigenetic modifying drugs such as DNA methyltransferase inhibitors (DNMTi) and histone deacetylase inhibitors (HDACi) is becoming more common in the treatment of cancer. Currently, there is a profound interest in determining predictive biomarkers for patient response and the efficacy of known and novel drugs. There are likely distinct "epigenetic profiles" defined by the location and abundance of DNA methylation patterns and histone modifications. Here we propose to investigate the response of a selected subset of genes to particular DNMTi and HDACi treatments, in two human cancer cell lines, colorectal carcinoma HCT-116 and liver adenocarcinoma HepG2. In this study we identified unique epigenetic profiles based on microarray and bioinformatics derived epigenetic data that are predictive of the response to epigenetic drug treatment. Microarray studies were used to identify re-activated genes common in two different cancer cell types treated with epigenetic drugs. Bioinformatics data was compiled on these genes and correlated against re-expression to construct the genes' "epigenetic profile". We then verified the response of the select group of genes in HCT-116 and HepG2 upon treatment at varying concentrations of epigenetic drugs and illustrated that selective reactivation of the target gene. Additionally, two novel genes were introduced and one selectively activated over another.;Further research would prove invaluable for the medical and drug development communities, as a more extensive model would certainly be of use to determining patient response to drug treatment based on their individual epigenetic profile and leading to more successful novel drug design.
机译:表观遗传修饰药物,例如DNA甲基转移酶抑制剂(DNMTi)和组蛋白脱乙酰基酶抑制剂(HDACi)的使用在癌症治疗中变得越来越普遍。当前,对于确定用于患者反应以及已知和新药功效的预测性生物标志物引起了极大的兴趣。 DNA甲基化模式和组蛋白修饰的位置和丰度可能定义了不同的“表观遗传学特征”。在这里,我们建议调查在两个人类癌细胞系(结直肠癌HCT-116和肝腺癌HepG2)中特定的DNMTi和HDACi治疗基因的选定子集的反应。在这项研究中,我们基于微阵列和生物信息学派生的表观遗传数据确定了独特的表观遗传概况,这些数据可预测对表观遗传药物治疗的反应。微阵列研究被用于鉴定在用表观遗传药物治疗的两种不同癌细胞类型中常见的重新激活基因。在这些基因上汇编了生物信息学数据,并将其与重新表达相关联以构建基因的“表观遗传概况”。然后,我们在不同浓度的表观遗传药物治疗后验证了HCT-116和HepG2中所选基因组的反应,并说明了靶基因的选择性重新激活。此外,还引入了两个新基因,并选择性地激活了另一个基因。进一步的研究对于医学和药物开发界来说将是无价的,因为更广泛的模型肯定会用于根据患者的个体表观遗传来确定患者对药物治疗的反应简介并导致更成功的新颖药物设计。

著录项

  • 作者

    Nelson, Jonathan M.;

  • 作者单位

    The University of North Carolina at Greensboro.;

  • 授予单位 The University of North Carolina at Greensboro.;
  • 学科 Biology.;Cellular biology.;Bioinformatics.
  • 学位 M.S.
  • 年度 2016
  • 页码 87 p.
  • 总页数 87
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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