Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer
Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer
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DOI：
10.1200/jco.2006.05.6564
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发表时间：
2006-07-01
影响因子：
45.3
通讯作者：
Ross, Douglas T.
中科院分区：
文献类型：
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作者：
Ring, Brian Z.;Seitz, Robert S.;Ross, Douglas T.
乳腺癌患者经历了不同的进展和对治疗的反应，但肿瘤学家的预后和预测工具有限。我们已经使用基因表达数据来指导生产数百种新的抗体试剂，以发现新的诊断工具分层癌patients.Patients和MethodsOne的40种新的和23种商业抗血清，选择他们的能力差异染色肿瘤样本，被用来染色石蜡块从回顾性乳腺癌队列。考克斯比例风险和回归树分析确定了能够预测复发风险的最小试剂组。我们在两个独立的cohols.ResultsIn两个验证队列，Kaplan-Meier估计复发证实，使用五种试剂的考克斯模型（p53、NDRG 1、CEACAM 5、SLC 7A 5和HTF 9 C）和使用六种试剂的回归树模型（ID 53、PR、Ki 67、NAT 1、SLC 7A 5和HTF 9 C）区分具有不良结果的雌激素受体（ER）阳性患者。考克斯模型具有上级优势，可区分结局较差的患者和结局良好或中等的患者，验证队列1的风险比为2.21（P =.0008），队列2的风险比为1.88（P =.004）。在多变量分析中，计算的复发风险与分期、分级和淋巴结状态无关。ER阴性患者提出的模型未能在独立cohols.ConclusionA面板的五种抗体的验证，可以显着提高传统的crysticators在ER阳性乳腺癌患者的预测结果。
PurposePatients with breast cancer experience progression and respond to treatment in diverse ways, but prognostic and predictive tools for the oncologist are limited. We have used gene expression data to guide the production of hundreds of novel antibody reagents to discover novel diagnostic tools for stratifying carcinoma patients.Patients and MethodsOne hundred forty novel and 23 commercial antisera, selected on their ability to differentially stain tumor samples, were used to stain paraffin blocks from a retrospective breast cancer cohort. Cox proportional hazards and regression tree analysis identified minimal panels of reagents able to predict risk of recurrence. We tested the prognostic association of these prospectively defined algorithms in two independent cohorts.ResultsIn both validation cohorts, the Kaplan-Meier estimates of recurrence confirmed that both the Cox model using five reagents (p53, NDRG1, CEACAM5, SLC7A5, and HTF9C) and the regression tree model using six reagents (ID53, PR, Ki67, NAT1, SLC7A5, and HTF9C) distinguished estrogen receptor (ER)-positive patients with poor outcomes. The Cox model was superior and distinguished patients with poor outcomes from patients with good or moderate outcomes with a hazard ratio of 2.21 (P =.0008) in Validation cohort 1 and 1.88 (P =.004) in cohort 2. In multivariable analysis, the calculated risk of recurrence was independent of stage, grade, and lymph node status. A model proposed for ER-negative patients failed validation in the independent cohorts.ConclusionA panel of five antibodies can significantly improve on traditional prognosticators in predicting outcome for ER-positive breast cancer patients.