The mechanisms of the highly metastatic property using human lung cancer sublines with highly metastatic potential established and the expolation of the molecular targets for lung cancer therapy

利用具有高转移潜力的人肺癌亚系建立高转移特性的机制并揭示肺癌治疗的分子靶点

基本信息

  • 批准号:
    13670620
  • 负责人:
  • 金额:
    $ 2.62万
  • 依托单位:
  • 依托单位国家:
    日本
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
  • 财政年份:
    2001
  • 资助国家:
    日本
  • 起止时间:
    2001 至 2002
  • 项目状态:
    已结题

项目摘要

A better understanding of the key factors of metastasis may be useful for designing new molecular targets of cancer therapy. In order to identify these factors, we established two highly metastatic human lung adenocarcinoma cell lines in an experimental metastasis model by repeated inoculation in nude mice and compared the expression profiles of two subpopulations of an adenocarcinoma cell line with high metastatic potential, with the parent cell line, using cDNA arrays; microarray and macroarray. The expression of 5 genes was found to be significantly enhanced or reduced in the highly metastatic subpopulations by microarray. One of the over-expressed genes that was identified encoded the β-galactoside-binding protein Galectin 3. A population (10/30) of the non-small-cell lung cancers examined was found to over-express the Galectin 3 gene at levels 3 times higher than normal epithelial cells. Galectin 3 may represent a novel target molecule in non-small-cell lung cancer therapy. The expression of matrix metalloproteinase-2 (MMP-2), plasminogen activator inhibitor-1 (PAI-1), carcinoembryonic antigen (CEA) and etc. were upregulated or downregulated in the highly metastatic subpopulations. Altered expression of these genes seems topromote the highly metastatic phenotype in these function. To determine whether the change in p16INK4 methylation status and the genomic status of hBUB1, hMAD2, Insulin-like growth factor 2 receptor genes, chromosome 8p and 3p occurs during metastasis of primary lung cancers, we also analyzed the primary and metastatic tumor tissues and normal lung samples from 30 cases of advanced lung cancer with distant metastasis. The results of this study indicate that tumor cells in which the p16INK4 gene has been inactivated by hypermethylation of the promoter region could have an advantage in metastasis in non-small cell lung cancers. We will evaluate the clinical significance of MMP-2, PAI-1, CEA, Galectin 3 and identified unknown clones.
更好地了解转移的关键因素可能有助于设计新的肿瘤治疗分子靶点。为了确定这些因素,我们建立了两个高转移的人肺腺癌细胞系的实验转移模型,通过重复接种在裸鼠和比较的表达谱的两个亚群的腺癌细胞系具有高转移潜力,与亲本细胞系,使用cDNA阵列;微阵列和宏阵列。基因芯片检测发现5个基因在高转移亚群中表达显著增强或降低。其中一个被鉴定的过表达基因编码β-半乳糖苷结合蛋白Galectin 3。在非小细胞肺癌中,有10例(10/30)过表达Galectin 3基因,其水平是正常上皮细胞的3倍。Galectin 3可能是非小细胞肺癌治疗的一个新靶分子。高转移亚群中基质金属蛋白酶-2(MMP-2)、纤溶酶原激活物抑制剂-1(派-1)、癌胚抗原(CEA)等表达上调或下调。这些基因表达的改变似乎促进了这些功能的高转移表型。为探讨原发性肺癌转移过程中p16 INK 4甲基化状态、hBUB 1、hMAD 2、胰岛素样生长因子2受体基因、染色体8 p和3 p的基因组状态是否发生改变,我们还分析了30例晚期肺癌远处转移患者的原发癌组织、转移癌组织和正常肺组织。这项研究的结果表明,肿瘤细胞中的p16 INK 4基因已被失活的启动子区域的超甲基化可能有一个优势,在非小细胞肺癌的转移。我们将评估MMP-2、派-1、CEA、Galectin 3和鉴定的未知克隆的临床意义。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Seike M: "The promoter region of the human BUBR1 gene and its expression analysis in lung cancer."Lung Cancer. 38(3). 229-234 (2002)
Seike M:“人类 BUBR1 基因的启动子区域及其在肺癌中的表达分析。”肺癌。
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    0
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GEMMA Akihiko其他文献

GEMMA Akihiko的其他文献

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{{ truncateString('GEMMA Akihiko', 18)}}的其他基金

Development of molecular predictive model for molecular targeted therapy in lung cancer using pathway analysis
利用通路分析开发肺癌分子靶向治疗的分子预测模型
  • 批准号:
    21591006
  • 财政年份:
    2009
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
The mechanisms of highly metastetic capasity in highly metastatic subpopulations of lung adenocarcinoma cell line and these clinical applications
肺腺癌细胞系高转移亚群的高转移能力机制及临床应用
  • 批准号:
    15590831
  • 财政年份:
    2003
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Study of mechanisms of the highly metastatic feature using human lung cancer sublines with highly metastatic property established
利用具有高转移特性的人肺癌亚系研究高转移特性的机制
  • 批准号:
    11670598
  • 财政年份:
    1999
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)

相似国自然基金

Missing in Metastasis基因在子宫内膜癌转移中的机制
  • 批准号:
    81060175
  • 批准年份:
    2010
  • 资助金额:
    30.0 万元
  • 项目类别:
    地区科学基金项目

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Gene regulation in metastasis and new methods to analyze its microarray profiles
转移中的基因调控及其微阵列谱分析的新方法
  • 批准号:
    8207416
  • 财政年份:
    2010
  • 资助金额:
    $ 2.62万
  • 项目类别:
Gene regulation in metastasis and new methods to analyze its microarray profiles
转移中的基因调控及其微阵列谱分析的新方法
  • 批准号:
    8324663
  • 财政年份:
    2010
  • 资助金额:
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New Biomarkers for Lymph Node Metastasis in Patients with EndometrialCancer using Exon-expression Microarray
使用外显子表达微阵列检测子宫内膜癌患者淋巴结转移的新生物标志物
  • 批准号:
    22591843
  • 财政年份:
    2010
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Gene regulation in metastasis and new methods to analyze its microarray profiles
转移中的基因调控及其微阵列谱分析的新方法
  • 批准号:
    8215717
  • 财政年份:
    2010
  • 资助金额:
    $ 2.62万
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Gene regulation in metastasis and new methods to analyze its microarray profiles
转移中的基因调控及其微阵列谱分析的新方法
  • 批准号:
    7908458
  • 财政年份:
    2009
  • 资助金额:
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Microarray analysis to detect genes predicting organotropism of lung cancer metastasis.
微阵列分析检测预测肺癌转移器官倾向的基因。
  • 批准号:
    21390395
  • 财政年份:
    2009
  • 资助金额:
    $ 2.62万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Gene regulation in metastasis and new methods to analyze its microarray profiles
转移中的基因调控及其微阵列谱分析的新方法
  • 批准号:
    7500801
  • 财政年份:
    2007
  • 资助金额:
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Gene regulation in metastasis and new methods to analyze its microarray profiles
转移中的基因调控及其微阵列谱分析的新方法
  • 批准号:
    7356763
  • 财政年份:
    2007
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Development of the diagnostic method to evaluate the risks for carcinogenesis, micro-metastasis, and malignant grade of oral cancer using in-house cDNA microarray
开发使用内部cDNA微阵列评估口腔癌的致癌、微转移和恶性程度风险的诊断方法
  • 批准号:
    13470427
  • 财政年份:
    2001
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    $ 2.62万
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    Grant-in-Aid for Scientific Research (B)
The establishment of liver metastasis model in colonic cancer and its gene exression using microarray analyses
结肠癌肝转移模型的建立及其基因表达的微阵列分析
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  • 财政年份:
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