Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers.
Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers.
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DOI：
10.1186/1479-5876-6-69
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发表时间：
2008-11-07
影响因子：
7.4
通讯作者：
Rohr UP
中科院分区：
文献类型：
--
作者：
Rohrbeck A;Neukirchen J;Rosskopf M;Pardillos GG;Geddert H;Schwalen A;Gabbert HE;von Haeseler A;Pitschke G;Schott M;Kronenwett R;Haas R;Rohr UP
我们检查了 29 名未经治疗的肺癌患者（10 名腺癌 (AC)、10 名鳞状细胞癌 (SCC) 和 9 名小细胞肺癌 (SCLC)）的肿瘤细胞基因表达谱，并与 5 份正常肺组织 (NT) 样本进行比较。遵循欧洲和美国的微阵列实验方法学质量指南，包括规定使用激光捕获显微切割从周围组织中分离和纯化肺癌肿瘤细胞。基于差异表达的基因，可以使用层次聚类将不同的肺癌样本彼此区分并与正常肺组织区分。将 AC、SCC 和 SCLC 与 NT 进行比较，我们分别发现 205、335 和 404 个基因至少有 2 倍差异表达（估计错误发现率：< 2.6%）。不同的肺癌亚型具有不同的分子表型，这也反映了其生物学特征。通过定量实时 PCR 证实了人类肺部肿瘤中可能与各肺癌亚型相关的差异表达基因。进行遗传编程 (GP) 来构建用于区分 AC、SCC、SCLC 和 NT 的分类器。已鉴定出 40 个可用于正确分类肿瘤或 NT 样本的基因。此外，来自 13 个其他肿瘤（AC 或 SCC）的独立测试集的所有样本也被正确分类。这项研究的数据确定了潜在的候选基因，可用作开发诊断工具和肺肿瘤类型特异性靶向治疗的基础。
We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue. Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR. Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified. The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.
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影响因子：
3.4
作者：
Kontogianni, K;Nicholson, AG;Sheppard, MN
通讯作者：
Sheppard, MN
影响因子：
8
作者：
Kikuchi, T;Daigo, Y;Nakamura, Y
通讯作者：
Nakamura, Y
影响因子：
2.5
作者：
Hirabayashi, H;Ohta, M;Matsuda, H
通讯作者：
Matsuda, H
DOI：
10.1073/pnas.0601231103
发表时间：
2006-04-11
影响因子：
11.1
作者：
Ein-Dor, L;Zuk, O;Domany, E
通讯作者：
Domany, E
影响因子：
2
作者：
Bisgaard, Anne-Marie;Kirchhoff, Maria;Skovby, Flemming
通讯作者：
Skovby, Flemming