首页> 外文学位 >Investigating the metabolism of tumours with an in silico chemical genetics approach.
【24h】

Investigating the metabolism of tumours with an in silico chemical genetics approach.

机译:使用计算机化学遗传学方法研究肿瘤的代谢。

获取原文
获取原文并翻译 | 示例

摘要

Tumours are well known to adopt a physiologic state known as aerobic glycolysis---they use glycolysis rather than mitochondrial respiration even when oxygen is abundant. We hypothesize that the predominant pathway by which a cell line generates its energy is indicative of the degree to which the cell line is transformed. Specifically, we postulate that a cell line that is more dependent on oxidative phosphorylation and mitochondrial respiration is less transformed, and a cell line that is more dependent on glycolysis is more transformed. Using pre-existing, publicly available datasets and information from the literature, I examined in silico both the basal level expression of genes in a panel of cancer cell lines, including those genes relevant to glycolysis and oxidative phosphorylation/mitochondrial respiration, as well as the growth responses of these cell lines to small molecules that target elements of the two energy pathways. To facilitate my investigations, I constructed a relational database to which I deposited the data. Using this database, I performed a global, non-supervised hierarchical clustering of cell lines vs. small-molecule inhibitors; this process revealed two major subsets of the cell lines (referred to here as subsets A and B). By visual inspection of a computed heatmap, I was able to hypothesize that ATP synthase inhibitors are the most effective classifiers of the two subsets. I next computed the rank of the genes whose expression levels in the untreated state of the cell lines best correlated with the two (sensitivity-derived) subsets of the cell lines. This marker selection enabled me to identify the genes that are the most effective classifiers of the two subsets. Most strikingly, an enrichment of the genes encoding elements of the mitochondrial respiration pathway was revealed, which supports our original hypothesis. In order to enable the database to be used to address a broader set of questions, I created a user interface that links the database to software platforms available from previous research efforts at the Broad Institute. Finally, I used my database as an analysis environment to extract knowledge not previously gained from the individual studies that yield the data. This exercise yielded three primary new hypotheses, namely: (1) the loss of a pyruvate dehydrogenase complex subunit contributes to the switch from dependency on ATP synthase to glycolysis; (2) in more transformed (i.e., more resistant to ATP synthase inhibitors) tumour cells, an isozyme of fructose-1,6-bisphosphatase that is capable of carrying out gluconeogenesis even though glycolysis is occurring is up-regulated, apparently providing tumour cells a selective advantage of survival; and (3) the expression of a major histocompatibility complex Class Ib molecule, HLA-F, also correlates increased transformation (resistance to ATP synthase inhibitors). I speculate that this part of the strategy a tumour utilizes in vivo to evade the immune system. These hypotheses now await future exploration.
机译:众所周知,肿瘤采用一种生理状态,称为有氧糖酵解-即使氧气充足,它们也使用糖酵解而不是线粒体呼吸。我们假设细胞系产生能量的主要途径指示细胞系转化的程度。具体来说,我们假设一个更依赖于氧化磷酸化和线粒体呼吸的细胞系的转化较少,而一个更依赖糖酵解的细胞系的转化则更多。利用已有的公开可用的数据集和文献资料,我在计算机上研究了一组癌细胞系中基因的基础水平表达,包括与糖酵解和氧化磷酸化/线粒体呼吸有关的那些基因,以及这些细胞系对靶向两种能量途径元素的小分子的生长反应。为了便于调查,我建立了一个关系数据库,将数据存放到该数据库中。使用这个数据库,我对细胞系与小分子抑制剂进行了全局,无监督的分层聚类。该过程揭示了细胞系的两个主要子集(此处称为子集A和B)。通过目测检查计算的热图,我可以假设ATP合酶抑制剂是这两个子集中最有效的分类器。接下来,我计算了在未经处理的细胞系中其表达水平与细胞系的两个(敏感度衍生)子集最相关的基因的排名。通过选择标记,我可以识别出这两个子集中最有效的分类基因。最引人注目的是,揭示了编码线粒体呼吸途径元素的基因的富集,这支持了我们最初的假设。为了使该数据库能够用于解决更广泛的问题,我创建了一个用户界面,将该数据库链接到Broad Institute先前研究工作中可用的软件平台。最后,我将数据库用作分析环境,以提取以前无法从产生数据的单个研究中获得的知识。这项工作产生了三个主要的新假设,即:(1)丙酮酸脱氢酶复合物亚基的丧失导致了从对ATP合酶的依赖性转变为糖酵解; (2)在更多转化的(即,对ATP合酶抑制剂更具抵抗力的)肿瘤细胞中,即使发生糖酵解也能够进行糖异生的果糖-1,6-双磷酸酶的同工酶被上调,显然提供了肿瘤细胞生存的选择性优势; (3)主要的组织相容性复杂的Ib类分子HLA-F的表达也与转化率的提高(对ATP合酶抑制剂的抗性)相关。我推测肿瘤的这一策略部分是在体内利用其逃避免疫系统的。这些假设现在等待着将来的探索。

著录项

  • 作者

    Ow, Yong-Ling Patricia.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Immunology.;Bioinformatics.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 155 p.
  • 总页数 155
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号