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Gene expression profiling in primary lung cancer with oligonucleotide microarray.

使用寡核苷酸微阵列对原发性肺癌进行基因表达谱分析。

基本信息

批准号：
15591467
负责人：
IYODA Akira
金额：
$ 2.11万
依托单位：
Chiba University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15591467/
关键词：
Lung cancer Microarray Prognosis

项目摘要

In this study, we investigate gene-expression profiles of 64 primary lung cancers by using an oligonucleotide microarray containing 10,000 genes and identify new molecular targets associated with clinicopathological factors. From July 2002 through December 2003, 64 pairs of lung cancer tissues and corresponding adjacent non-cancerous tissues were obtained with informed consent from patients who underwent surgical operation at Chiba University Hospital, Japan. Samples were collected using informed consent according to institutional guidelines and the study protocol approved by our institutional Research Ethics Board. We have analyzed gene expression profiles using oligonucleotide microarray, and hierarchical clustering analysis was performed with expression levels of the selected genes and statistical significance was calculated. Eighty-one genes showed differentially expressed in adenocarcinoma, 304 genes in squamous cell carcinoma. Thirty-four genes showed a distinct expression pattern exclusively in cancer tissues with lymph-node metastasis (P<0.01). Based on the expression analysis of 10,000 genes and clustering algorithm successfully distinguished histological types and clinical status such as lymph node metastasis. Isolated genes provide valuable information for eventually identifying predictive markers and novel therapeutic target molecules for lung cancer.

在这项研究中，我们通过使用包含10，000个基因的寡核苷酸芯片来研究64个原发性肺癌的基因表达谱，并确定与临床病理因素相关的新分子靶点。从2002年7月至2003年12月，在日本千叶大学医院接受外科手术的患者知情同意的情况下，获得了64对肺癌组织和相应的邻近非癌组织。根据机构指南和我们的机构研究伦理委员会批准的研究方案，使用知情同意书收集样品。我们使用寡核苷酸芯片分析基因表达谱，并对所选基因的表达水平进行层次聚类分析，并计算统计学显著性。腺癌中差异表达基因81条，鳞癌中差异表达基因304条。34个基因在有淋巴结转移的癌组织中表达差异显著（P<0.01）。基于10，000个基因的表达分析和聚类算法成功区分了组织学类型和临床状态，如淋巴结转移。分离的基因为最终鉴定肺癌的预测标志物和新的治疗靶分子提供了有价值的信息。