Expression profiling of non-small cell lung carcinoma identifies metastatic genotypes based on lymph node tumor burden
Expression profiling of non-small cell lung carcinoma identifies metastatic genotypes based on lymph node tumor burden
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DOI：
10.1016/j.jtcvs.2003.11.060
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发表时间：
2004-05-01
影响因子：
6
通讯作者：
Maddaus, MA
中科院分区：
文献类型：
--
作者：
Hoang, CD;D'Cunha, J;Maddaus, MA
目的：本研究假设，非小细胞肺癌细胞从原发性肿瘤分离激光捕获显微切割将表现出基因表达谱与分级淋巴结转移细胞burden.Methods：非小细胞肺癌肿瘤（n = 15）进行了分类的基础上，淋巴结转移细胞负荷2种方法，获得3组：无转移，微转移，和明显转移。然后，我们进行了微阵列分析的显微切割的原发性肿瘤细胞，并确定了基因表达谱与分级淋巴结肿瘤负荷使用相关性为基础的选择算法加上交叉验证分析。系统聚类显示肿瘤标本的重新分组;分类推断采用Fisher精确检验进行评估。我们验证了某些基因的数据，通过使用另一个独立的assay.Results：15例标本聚类成3组：集群A占主导地位的标本与明显的淋巴结转移;集群B有更多的标本与淋巴结微转移;和集群C只包括标本没有淋巴结转移。聚类分配是基于一个验证的75个基因的歧视子集。值得注意的是，基因没有以前与阳性非小细胞肺癌淋巴结状态遇到的profilinganalysis.Conclusions：显微切割，结合微阵列分析，是一个潜在的强大的方法来表征肿瘤细胞的分子概况。代表簇A和B的75个基因表达谱可以定义倾向于转移的基因型。总体而言，3组肿瘤标本分别聚类，表明该方法可识别分级转移倾向。此外，在聚类中挑选出的基因可能会深入了解潜在的转移机制，并可能代表新的治疗靶点。
Objective: This study hypothesized that non-small cell lung carcinoma cells from primary tumors isolated by laser capture microdissection would exhibit gene expression profiles associated with graded lymph node metastatic cell burden.Methods: Non-small cell lung carcinoma tumors (n = 15) were classified on the basis of nodal metastatic cell burden by 2 methods, obtaining 3 groups: no metastasis, micrometastasis, and overt metastasis. We then performed microarray analysis on microdissected primary tumor cells and identified gene expression profiles associated with graded nodal tumor burden using a correlation-based selection algorithm coupled with cross-validation analysis. Hierarchical clustering showed the regrouping of tumor specimens; the classification inference was assessed with Fisher's exact test. We verified data for certain genes by using another independent assay.Results: The 15 specimens clustered into 3 groups: cluster A predominated in specimens with overt nodal metastasis; cluster B had more specimens with nodal micrometastases; and cluster C included only specimens without nodal metastases. Cluster assignment was based on a validated 75-gene discriminatory subset. Notably, genes not previously associated with positive non-small cell lung carcinoma lymph node status were encountered in the profiling analysis.Conclusions: Microdissection, combined with microarray analysis, is a potentially powerful method to characterize the molecular profile of tumor cells. The 75-gene expression profiles representative of clusters A and B may define genotypes prone to metastasize. Overall, the 3 groups of tumor specimens clustered separately, suggesting that this approach may identify graded metastatic propensity. Further, genes singled out in clustering may yield insights into underlying metastatic mechanisms and may represent new therapeutic targets.