Automated image analysis for high-throughput quantitative detection of ER and PR expression levels in large-scale clinical studies: The TEAM Trial Experience
Automated image analysis for high-throughput quantitative detection of ER and PR expression levels in large-scale clinical studies: The TEAM Trial Experience
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DOI：
10.1111/j.1365-2559.2009.03419.x
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发表时间：
2009-11-01
期刊：
影响因子：
6.4
通讯作者：
Bartlett, John M. S.
中科院分区：
文献类型：
--
作者：
Faratian, Dana;Kay, Charlene;Bartlett, John M. S.
目的：常规免疫组织化学被认为是一种半定量的原位蛋白表达评价方法。在大型临床试验中，组织生物标记物的分析是开发新的靶向治疗方法的核心，需要分析数万个数据点，并且经常使用组织微阵列(TMA)的高通量分析。本研究的目的是探讨图像分析在生物标志物准确和重复性定量评估中的潜力。方法和结果：在III期临床试验的397例乳腺癌患者中，TMAS的半自动图像分析与人工评分的雌激素受体(ER)和孕激素受体(PR)水平具有良好的相关性(组间相关系数分别为0.93和0.96)。两个或更多的TMA核心与手动评分有很好的相关性，使用三个以上的核心将可用于分析的病例数量增加到>；92%。结论：半自动图像分析适合于大型临床试验中组织生物标志物的分析。这些数据为在翻译研究中使用TMA和图像分析提供了支持。
Aims:Routine immunohistochemistry is regarded as a semiquantitative method for the evaluation of in situ protein expression. Analysis of tissue biomarkers in large clinical trials is central to the development of novel targeted approaches to therapy, requires the analysis of tens of thousands of data points, and frequently makes use of high-throughput analysis of tissue microarrays (TMAs). The aim of this study was to investigate the potential of image analysis for accurate and reproducible quantitative evaluation of biomarkers.Methods and results:We showed, in 397 cases of breast cancer from the Phase III TEAM clinical trial, excellent correlations between semiautomated image analysis of TMAs and manual scoring of oestrogen receptor (ER) and progesterone receptor (PR) levels (interclass correlation coefficients 0.93 and 0.96 respectively). Two or more TMA cores were excellently correlated with manual scores, and using more than three cores increased the number of cases available for analysis to > 92%. TMAs are confirmed as representative of whole sections for immunohistochemical analysis of the tissue biomarkers ER and PR.Conclusions:Semiautomated image analysis is appropriate for the analysis of tissue biomarkers within large clinical trials. These data provide support for the use of TMAs and image analysis in translational research.