Gene expression profiling in primary lung cancer with oligonucleotide microarray.

在本研究中，我们利用包含10,000个基因的寡核苷酸芯片研究了原发肺癌的基因表达谱，并寻找了与临床病理因素相关的新的分子靶点。于2002-07/2003-12在知情同意下获得日本千叶大学医院外科手术患者的肺癌组织及相应的癌旁组织。样本是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在知情同意下收集的。我们利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，计算统计意义。有81个基因在腺癌中有差异表达，304个基因在鳞癌中有差异表达。34个基因仅在有淋巴结转移的癌组织中有不同的表达模式(P&lt；0.01)。基于10,000个基因的表达分析和聚类算法，成功地区分了组织学类型和临床状态，如淋巴结转移。分离的基因为最终确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。

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.