Quantitative Multiplexed Analysis of ErbB Family Coexpression for Primary Breast Cancer Prognosis in a Large Retrospective Cohort
Quantitative Multiplexed Analysis of ErbB Family Coexpression for Primary Breast Cancer Prognosis in a Large Retrospective Cohort
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DOI：
10.1002/cncr.24277
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发表时间：
2009-06-01
期刊：
影响因子：
6.2
通讯作者：
Rimm, David L.
中科院分区：
文献类型：
--
作者：
Giltnane, Jennifer M.;Moeder, Christopher B.;Rimm, David L.
背景技术背景：使用单一预后或预测标志物评估结果是靶向治疗的当前基础，但其简单性固有地受到限制。多路复用提供了更好的分类，但仅使用RNA或DNA进行定量。自动定量分析是一种新的技术，可以定量原位评估蛋白质表达。作者假设ErbB受体家族蛋白的多重定量测量可以更好地预测结果。方法：采用正交设计法作者使用乳腺癌组织微阵列定量评估了676例患者4个亚细胞区室中6种蛋白的表达。然后使用考克斯比例风险模型和无监督的层次聚类，他们评估了表达的预后价值。结果：表皮生长因子受体（EGFR）、HER-2和HER-3表达与生存率降低相关。多因素分析显示HER-2和HER-3高表达可作为独立的预后指标。表达数据的分层聚类定义了一个小类，富集HER-2表达，10年生存率为40%，而使用传统方法为55%。聚类分析也显示了一个类似的预后不良的亚组，共表达EGFR和HER-3（但雌激素受体，孕激素受体和HER-2低），10年生存率为42%。结论：这项工作表明，蛋白质表达的联合分析改善了预后分类，并且多重模型上级任何基于单标记的方法来预测10年生存率。这些方法说明了一种基于蛋白质的多重方法，可以更准确地识别患者进行靶向治疗。Cancer 2009;115：2400-9. (C)2009年美国癌症协会。
BACKGROUND: Assessment of outcome using a single prognostic or predictive marker is the current basis of targeted therapy, but is inherently limited by its simplicity. Multiplexing has provided better classification, but has only been done quantitatively using RNA or DNA. Automated quantitative analysis is a new technology that allows quantitative in situ assessment of protein expression. The authors hypothesized that multiplexed quantitative measurement of ErbB receptor family proteins may allow better prediction of outcome. METHODS: The authors quantitatively assessed the expression of 6 proteins in 4 subcellular compartments in 676 patients using breast carcinoma tissue microarrays. Then using Cox proportional hazards modeling and unsupervised hierarchical clustering, they assessed the prognostic value of the expression singly and multiplexed. RESULTS: Epidermal growth factor receptor (EGFR), HER-2, and HER-3 expression were associated with decreased survival. Multivariate analysis showed high HER-2 and HER-3 expression maintained independence as prognostic markers. Hierarchical clustering of expression data defined a small class enriched for HER-2 expression with 40% 10-year survival, compared with 55% using conventional methods. Clustering also revealed a similarly poor-prognostic subgroup coexpressing EGFR and HER-3 (but low for estrogen receptor, progesterone receptor, and HER-2) with a 42% 10-year survival. CONCLUSIONS: This work shows that the combined analysis of protein expression improved prognostic classification, and that multiplexed models were superior to any single-marker-based method for prediction of 10-year survival. These methods illustrate a protein-based, multiplexed approach that could more accurately identify patients for targeted therapies. Cancer 2009;115:2400-9. (C) 2009 American Cancer Society.