首页> 外文学位 >Comparing gene expression profiles of cell culture models with profiles of tumor xenografts and patient tumors: Implications for lung and breast cancers.
【24h】

Comparing gene expression profiles of cell culture models with profiles of tumor xenografts and patient tumors: Implications for lung and breast cancers.

机译:将细胞培养模型的基因表达谱与异种移植瘤和患者肿瘤谱进行比较:对肺癌和乳腺癌的影响。

获取原文
获取原文并翻译 | 示例

摘要

Tumor cell lines are relied upon extensively for cancer investigations, yet cultured cells in an in vitro environment differ considerably in behavior as compared to those of the same cancer cells that proliferate in vivo and form tumors in vivo. At the same time, despite the many differences between the in vitro and in vivo systems, cell cultures are a powerful model for understanding the molecular biology of cancers. In the first part of this thesis, I present an analysis of mRNA profile data obtained from tumors grown from lung cancer cells implanted in immunodeficient mice, in order to characterize the influence of the in vivo microenvironment on cancer gene expression, as well as the transcriptomic programs associated with tumor formation. In the second part of this thesis, I present a series of examples where I integrate mRNA profile data from in vitro cell line experiments with public datasets of human tumor gene expression, in order both to show the pathological relevance of the in vitro models and to aid in the selection of genes from the in vitro data for follow-up studies. These case studies center primarily on the transcriptional programs of estrogen-mediated growth and of estrogen-independent growth in breast cancer.
机译:肿瘤细胞系广泛地用于癌症研究,但是与在体内增殖并在体内形成肿瘤的相同癌细胞相比,在体外环境中培养的细胞的行为差异很大。同时,尽管体外和体内系统之间存在许多差异,但是细胞培养是理解癌症分子生物学的强大模型。在本文的第一部分中,我对从植入免疫缺陷小鼠的肺癌细胞生长的肿瘤中获得的mRNA谱数据进行了分析,以表征体内微环境对癌症基因表达以及转录组学的影响。与肿瘤形成有关的程序。在本文的第二部分中,我提供了一系列示例,其中我将来自体外细胞系实验的mRNA谱图数据与人类肿瘤基因表达的公共数据集进行了整合,以显示体外模型的病理相关性并有助于从体外数据中选择基因以进行后续研究。这些案例研究主要集中于乳腺癌中雌激素介导的生长和雌激素非依赖性生长的转录程序。

著录项

  • 作者

    Creighton, Chad J.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Biology Molecular.; Biology Biostatistics.; Biology Bioinformatics.; Health Sciences Oncology.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 244 p.
  • 总页数 244
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 分子遗传学;生物数学方法;肿瘤学;
  • 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