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非小细胞肺癌的基因表达谱分析

Gene expression profiling of non-small-cell lung cancer.

作者信息

Lacroix Ludovic, Commo Frédéric, Soria Jean-Charles

机构信息

Institut de Cancérologie Gustave Roussy, Translational Research Laboratory, 39 rue Camille Desmoulins, 94805 Villejuif Cedex, France.

出版信息

Expert Rev Mol Diagn. 2008 Mar;8(2):167-78. doi: 10.1586/14737159.8.2.167.

Abstract

Lung cancer is the leading cause of cancer worldwide. Despite recent advances in the management of resected lung cancer tumors (i.e., the use of adjuvant therapy) and more effective treatments in the metastatic setting (i.e., molecular targeted agents), the cure rate of lung cancer remains low. Successful molecular testing of lung cancer requires the identification and understanding of events that take place during the multistep tumorigenic process of lung cancer. As with other solid tumors, lung cancer is the result of the accumulation of genetic and epigenetic alterations over a long course of exposure to a carcinogen, such as tobacco smoke. Discovering new prognostic or predictive biomarkers or developing new detection tools for lung cancer is one of the major areas of translational cancer research. However, given our current understanding of the multifactorial process of lung carcinogenesis and the heterogeneous nature of the disease, monitoring of one or a few genes is limited. A pangenomic analysis seems more efficient for deciphering the complexity of lung cancer. The prospect of identifying specific events in lung carcinogenesis is significantly brightened by the recent development of high-throughput gene expression analysis. Since 2000, several studies have reported on the molecular classification of human lung carcinomas on the basis of gene expression and have described numerous putative biological markers of cancer. At this time, improving the biological significance of microarray data appears to be an important challenge. The most recent studies propose refining molecular classification of non-small-cell lung cancer on the basis of mRNA expression profiles. Other studies described new prognostic biomarkers that will be useful for the therapeutic management of patient's bearing lung cancer (non-small-cell lung cancer). The present review summarizes the main recent advances associated with gene expression analysis in the field of lung cancer and, notably, non-small-cell lung tumors.

摘要

肺癌是全球癌症的主要病因。尽管在切除的肺癌肿瘤管理方面(即辅助治疗的应用)以及转移性肺癌的治疗(即分子靶向药物)取得了最新进展,但肺癌的治愈率仍然很低。肺癌的成功分子检测需要识别和理解肺癌多步骤致癌过程中发生的事件。与其他实体瘤一样,肺癌是长期暴露于致癌物(如烟草烟雾)后基因和表观遗传改变积累的结果。发现新的预后或预测生物标志物或开发新的肺癌检测工具是转化癌症研究的主要领域之一。然而,鉴于我们目前对肺癌发生多因素过程的理解以及该疾病的异质性,监测一个或几个基因是有限的。全基因组分析似乎更有效地解读肺癌的复杂性。高通量基因表达分析的最新进展显著提高了识别肺癌发生中特定事件的前景。自2000年以来,多项研究报告了基于基因表达的人类肺癌分子分类,并描述了众多假定的癌症生物标志物。目前,提高微阵列数据的生物学意义似乎是一项重要挑战。最新研究建议根据mRNA表达谱完善非小细胞肺癌的分子分类。其他研究描述了新的预后生物标志物,这些标志物将有助于肺癌(非小细胞肺癌)患者的治疗管理。本综述总结了肺癌领域,尤其是非小细胞肺癌肿瘤中与基因表达分析相关的主要最新进展。

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