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Optimal Tumor Sampling for Immunostaining of Biomarkers in Breast Carcinoma.

机译:乳腺癌中生物标志物免疫染色的最佳肿瘤取样。

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摘要

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 purpose of this study is 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: estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), AKT, extracellular signal-regulated kinase (ERK), ribosomal protein S6 kinase 1 (S6K1), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), cytokeratin, and microtubule-associated protein-Tau (MAP-Tau).;Two collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using Automated Quantitative Analysis (AQUA). Simulated sampling of various numbers of fields (ranging from 1 -- 35) 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 marker, ranging between 3--14 fields. More heterogeneous markers, such as MAP-Tau, required a larger sample of 20X fields to produce representative measurement. The clinical implication of these findings is that small core needle breast biopsies may be inadequate to represent whole tumor biomarker expression for many markers. Also, 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.
机译:生物标志物,例如雌激素受体,可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具有很高的不准确率,例如,对雌激素受体的估计高达20%。已经显示生物标志物在乳腺肿瘤中异质表达,并且这种异质性可能导致免疫染色测定法的不准确性。目前,尚无针对校正生物标志物异质性必须取样的肿瘤数量的循证标准。;本研究的目的是确定估计代表性表达测量所必需的20X视野的最佳数目在整个组织切片中用于选定的生物标记物:雌激素受体(ER),人表皮生长因子受体2(HER2),AKT,细胞外信号调节激酶(ERK),核糖体蛋白S6激酶1(S6K1),3-磷酸甘油醛脱氢酶(GAPDH),细胞角蛋白和微管相关蛋白-Tau(MAP-Tau)。;对乳腺癌的整个组织切片的两个集合进行了免疫染色以检测生物标志物。使用自动定量分析(AQUA)对表达进行定量。对每个标记进行了各种领域的模拟采样(范围从1到35)。通过重采样技术为每个标记选择了最佳数量,并在独立的测试集上将预测误差最小化。20X场的最佳数量因标记而异,范围在3--14个场之间。更多异构的标记(例如MAP-Tau)需要更大的20X场样本才能产生代表性的测量结果。这些发现的临床含义是,小芯针乳房活检可能不足以代表许多标记物的完整肿瘤生物标记物表达。另外,对于新近引入临床的生物标志物,特别是如果治疗反应是由表达水平决定的,组织样品的最佳大小必须在逐个标志物的基础上确定。

著录项

  • 作者

    Tolles, Juliana.;

  • 作者单位

    Yale University.;

  • 授予单位 Yale University.;
  • 学科 Statistics.;Health Sciences Pathology.
  • 学位 M.D.
  • 年度 2011
  • 页码 46 p.
  • 总页数 46
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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