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Validation of tumor protein marker quantification by two independent automated immunofluorescence image analysis platforms

机译:通过两个独立的自动免疫荧光图像分析平台验证肿瘤蛋白标记物的定量

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摘要

Protein marker levels in formalin-fixed, paraffin-embedded tissue sections traditionally have been assayed by chromogenic immunohistochemistry and evaluated visually by pathologists. Pathologist scoring of chromogen staining intensity is subjective and generates low-resolution ordinal or nominal data rather than continuous data. Emerging digital pathology platforms now allow quantification of chromogen or fluorescence signals by computer-assisted image analysis, providing continuous immunohistochemistry values. Fluorescence immunohistochemistry offers greater dynamic signal range than chromogen immunohistochemistry, and combined with image analysis holds the promise of enhanced sensitivity and analytic resolution, and consequently more robust quantification. However, commercial fluorescence scanners and image analysis software differ in features and capabilities, and claims of objective quantitative immunohistochemistry are difficult to validate as pathologist scoring is subjective and there is no accepted gold standard. Here we provide the first side-by-side validation of two technologically distinct commercial fluorescence immunohistochemistry analysis platforms. We document highly consistent results by (1) concordance analysis of fluorescence immunohistochemistry values and (2) agreement in outcome predictions both for objective, data-driven cutpoint dichotomization with Kaplan–Meier analyses or employment of continuous marker values to compute receiver-operating curves. The two platforms examined rely on distinct fluorescence immunohistochemistry imaging hardware, microscopy vs line scanning, and functionally distinct image analysis software. Fluorescence immunohistochemistry values for nuclear-localized and tyrosine-phosphorylated Stat5a/b computed by each platform on a cohort of 323 breast cancer cases revealed high concordance after linear calibration, a finding confirmed on an independent 382 case cohort, with concordance correlation coefficients >0.98. Data-driven optimal cutpoints for outcome prediction by either platform were reciprocally applicable to the data derived by the alternate platform, identifying patients with low Nuc-pYStat5 at ~3.5-fold increased risk of disease progression. Our analyses identified two highly concordant fluorescence immunohistochemistry platforms that may serve as benchmarks for testing of other platforms, and low interoperator variability supports the implementation of objective tumor marker quantification in pathology laboratories.
机译:传统上,福尔马林固定,石蜡包埋的组织切片中的蛋白质标记物水平已通过生色免疫组织化学法测定,并由病理学家目测评估。病理学家对发色团染色强度的评分是主观的,并且会生成低分辨率的序数或名义数据,而不是连续数据。新兴的数字病理平台现在可以通过计算机辅助图像分析对色原或荧光信号进行定量,从而提供连续的免疫组织化学值。荧光免疫组织化学比色原免疫组织化学提供更大的动态信号范围,并且与图像分析相结合有望提高灵敏度和分析分辨率,从而实现更可靠的定量。但是,商用荧光扫描仪和图像分析软件在功能和特性上有所不同,并且由于病理学家的评分是主观的并且没有公认的金标准,因此客观定量免疫组织化学的说法很难得到验证。在这里,我们提供了两个技术独特的商业荧光免疫组织化学分析平台的首个并行验证。我们通过(1)荧光免疫组织化学值的一致性分析和(2)在结果预测中达成一致的结果来进行客观的预测,无论是客观的,数据驱动的切点二分法(使用Kaplan-Meier分析),还是采用连续的标记值来计算接收器操作曲线。检查的两个平台依赖于独特的荧光免疫组织化学成像硬件,显微镜与线扫描以及功能独特的图像分析软件。每个平台计算的323个乳腺癌病例队列中每个平台计算的核定位和酪氨酸磷酸化Stat5a / b的荧光免疫组织化学值在线性校正后显示出高度一致性,这一发现在独立的382例病例队列中得到证实,一致性相关系数> 0.98。两种平台上用于预测结果的数据驱动的最佳切点都可适用于备用平台得出的数据,从而确定Nuc-pYStat5低至疾病进展风险增加约3.5倍的患者。我们的分析确定了两个高度一致的荧光免疫组织化学平台,可以作为其他平台测试的基准,而互操作性低的变异性则支持病理实验室中客观肿瘤标记物定量的实现。

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