Division of Biostatistics, Yale University School of Public Health, New Haven, CT 06511, USA.
Breast Cancer Res. 2011 May 18;13(3):R51. doi: 10.1186/bcr2882.
Biomarkers, such as Estrogen Receptor, are used to determine therapy and prognosis in breast carcinoma. Immunostaining assays of biomarker expression have a high rate of inaccuracy; for example, estimates are as high as 20% for Estrogen Receptor. Biomarkers have been shown to be heterogeneously expressed in breast tumors and this heterogeneity may contribute to the inaccuracy of immunostaining assays. Currently, no evidence-based standards exist for the amount of tumor that must be sampled in order to correct for biomarker heterogeneity. The aim of this study was to determine the optimal number of 20X fields that are necessary to estimate a representative measurement of expression in a whole tissue section for selected biomarkers: ER, HER-2, AKT, ERK, S6K1, GAPDH, Cytokeratin, and MAP-Tau.
Two collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using the Automated Quantitative Analysis (AQUA) method of quantitative immunofluorescence. Simulated sampling of various numbers of fields (ranging from one to thirty five) was performed for each marker. The optimal number was selected for each marker via resampling techniques and minimization of prediction error over an independent test set.
The optimal number of 20X fields varied by biomarker, ranging between three to fourteen fields. More heterogeneous markers, such as MAP-Tau protein, required a larger sample of 20X fields to produce representative measurement.
The optimal number of 20X fields that must be sampled to produce a representative measurement of biomarker expression varies by marker with more heterogeneous markers requiring a larger number. The clinical implication of these findings is that breast biopsies consisting of a small number of fields may be inadequate to represent whole tumor biomarker expression for many markers. Additionally, for biomarkers newly introduced into clinical use, especially if therapeutic response is dictated by level of expression, the optimal size of tissue sample must be determined on a marker-by-marker basis.
生物标志物，如雌激素受体，用于确定乳腺癌的治疗和预后。生物标志物表达的免疫染色测定存在很高的不准确性；例如，雌激素受体的估计值高达 20%。生物标志物在乳腺肿瘤中的表达存在异质性，这种异质性可能导致免疫染色测定的不准确性。目前，尚无关于为纠正生物标志物异质性而必须采样的肿瘤量的循证标准。本研究旨在确定为选定的生物标志物（ER、HER-2、AKT、ERK、S6K1、GAPDH、细胞角蛋白和 MAP-Tau）估计整个组织切片代表性表达所需的最佳 20X 视野数量。
对乳腺癌的两个全组织切片系列进行了生物标志物免疫染色。使用定量免疫荧光的自动定量分析（AQUA）方法对表达进行量化。针对每个标记物模拟了各种数量的视野（从一个到三十五个）的采样。通过重新采样技术和在独立测试集上最小化预测误差为每个标记物选择最佳数量。
最佳 20X 视野数量因标志物而异，范围在三到十四个视野之间。更具异质性的标志物，如 MAP-Tau 蛋白，需要更大的 20X 视野样本才能产生代表性测量。
为了产生生物标志物表达的代表性测量，必须采样的最佳 20X 视野数量因标志物而异，具有更大异质性的标志物需要更多的数量。这些发现的临床意义是，对于许多标志物，由少数几个视野组成的乳腺活检可能不足以代表整个肿瘤的生物标志物表达。此外，对于新引入临床使用的生物标志物，特别是如果治疗反应取决于表达水平，则必须根据标志物逐个确定组织样本的最佳大小。
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