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

机译:表达谱的潜在用途:预测类风湿关节炎治疗反应的意义

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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:全基因组表达谱或转录组学是一项高通量技术,可能对临床环境以及药物发现和诊断产生重大影响。尤其是,人们对该技术作为预测治疗反应的机制非常感兴趣。基因表达谱分析需要对数千种基因的信使RNA水平进行定量测量,同时具有固有的可能性,即可以识别对特定疗法有反应的生物标志物,也可以通过筛选出有严重不良事件风险的生物标志物来识别。这项技术应为分层医学的时代做出贡献,在这种时代中,患者的特定人群通过临床测试与潜在有益的药物相匹配。实际上,在肿瘤学领域,已经建议进行基因表达测试,以允许合理使用疗法来治疗乳腺癌。但是,围绕各种可用测试平台的使用以及与生成结果的解释相关的统计分析,仍然存在许多问题。这篇综述将讨论这项有前途的技术在预测治疗反应方面的意义,并概述与使用该技术有关的各种优势和陷阱。

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