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The potential use of expression profiling: implications for predicting treatment response in rheumatoid arthritis

机译:表达分析的潜在用途:对预测类风湿性关节炎治疗反应的影响

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摘要

Whole genome expression profiling, or transcriptomics, is a high throughput technology with the potential for major impacts in both clinical settings and drug discovery and diagnostics. In particular, there is much interest in this technique as a mechanism for predicting treatment response. Gene expression profiling entails the quantitative measurement of messenger RNA levels for thousands of genes simultaneously with the inherent possibility of identifying biomarkers of response to a particular therapy or by singling out those at risk of serious adverse events. This technology should contribute to the era of stratified medicine, in which patient specific populations are matched to potentially beneficial drugs via clinical tests. Indeed, in the oncology field, gene expression testing is already recommended to allow rational use of therapies to treat breast cancer. However, there are still many issues surrounding the use of the various testing platforms available and the statistical analysis associated with the interpretation of results generated. This review will discuss the implications this promising technology has in predicting treatment response and outline the various advantages and pitfalls associated with its use.
机译:全基因组表达分析或转录组织,是一种高通量技术,具有临床环境和药物发现和诊断中的主要影响。特别地,对该技术有很多兴趣作为预测治疗响应的机制。基因表达分析需要同时鉴定对特定治疗的响应的生物标志物的固有可能性,或者通过单打严重不良事件的风险的固定剂来定量测量数千个基因的定量测量。该技术应该有助于分层医学的时代,其中患者特异性群体通过临床试验与潜在的有益药物匹配。实际上,在肿瘤学领域,已经建议已经建议基因表达测试以允许合理使用治疗治疗乳腺癌。然而,仍然存在许多问题,使用各种测试平台的使用以及与产生的结果的解释相关的统计分析。本综述将讨论这一有希望技术在预测治疗响应和概述与其使用相关的各种优势和陷阱的影响。

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