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影响临床应用中基因表达谱一致性的标准。

Standards affecting the consistency of gene expression arrays in clinical applications.

机构信息

Molecular Genomics Laboratory, H. Lee Moffitt Cancer Center and Research Institute, SRB2 12902 Magnolia Drive, Tampa, FL 33612, USA.

出版信息

Cancer Epidemiol Biomarkers Prev. 2010 Apr;19(4):1000-3. doi: 10.1158/1055-9965.EPI-10-0044. Epub 2010 Mar 23.

Abstract

The use of microarray technology to measure gene expression has created optimism for the feasibility of using molecular assessments of tumors routinely in the clinical management of cancer. Gene expression arrays have been pioneers in the development of standards; both for research use and now for clinical application. Some of the existing standards have been driven by the early perception that microarray technology was inconsistent and perhaps unreliable. More recent experimentation has shown that reproducible data can be achieved and clinical standards are beginning to emerge. For the transcriptional assessment of tumors, this means a system that correctly samples a tumor, isolates RNA and processes this for microarray analysis, evaluates the data, and communicates findings in a consistent and timely fashion. The most important standard is to show that a clinically important assessment can be made with microarray data. The standards emerging from work on various parts of the entire process could guide the development of a workable system. However, the final standard for each component of the process depends on the accuracy required when the assay becomes part of the clinical routine: a routine that now includes the molecular evaluation of tumors.

摘要

微阵列技术在测量基因表达方面的应用,为人们提供了乐观的前景,即在癌症的临床管理中常规使用肿瘤的分子评估。基因表达阵列在标准的制定方面处于领先地位;无论是用于研究用途,还是现在用于临床应用。一些现有的标准是基于早期的认识,即微阵列技术不一致,也许不可靠。最近的实验表明,可重复性数据可以实现,临床标准也开始出现。对于肿瘤的转录评估,这意味着一个系统能够正确地对肿瘤进行采样,分离 RNA 并进行微阵列分析,评估数据,并以一致和及时的方式传达发现。最重要的标准是表明可以使用微阵列数据进行临床重要的评估。在整个过程的各个部分的工作中出现的标准,可以为开发可行的系统提供指导。然而,该过程每个组件的最终标准取决于当检测成为临床常规的一部分时所需的准确性:现在包括对肿瘤的分子评估的常规。

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本文引用的文献

1
Robust biomarker identification for cancer diagnosis with ensemble feature selection methods.
Bioinformatics. 2010 Feb 1;26(3):392-8. doi: 10.1093/bioinformatics/btp630. Epub 2009 Nov 25.
2
Comparison of feature selection and classification combinations for cancer classification using microarray data.
Int J Bioinform Res Appl. 2009;5(4):417-31. doi: 10.1504/IJBRA.2009.027515.
3
Intra-platform repeatability and inter-platform comparability of microRNA microarray technology.
PLoS One. 2009;4(5):e5540. doi: 10.1371/journal.pone.0005540. Epub 2009 May 14.
5
Array-based comparative genomic hybridization as a tool for analyzing the leukemia genome.
Methods Mol Biol. 2009;538:151-77. doi: 10.1007/978-1-59745-418-6_8.
7
Quality assessment and data analysis for microRNA expression arrays.
Nucleic Acids Res. 2009 Feb;37(2):e17. doi: 10.1093/nar/gkn932. Epub 2008 Dec 22.
10
Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.
Nat Med. 2008 Aug;14(8):822-7. doi: 10.1038/nm.1790. Epub 2008 Jul 20.

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