University of Southern California Keck School of Medicine, Center for Personalized Medicine, 4650 Sunset Blvd, SRT 1014, Los Angeles, CA 90027, USA.
Expert Rev Anticancer Ther. 2011 Jun;11(6):849-52. doi: 10.1586/era.11.60.
Evaluation of: Smith SC, Baras AS, Dancik G et al. A 20-gene model for molecular nodal staging of bladder cancer: development and prospective assessment. Lancet Oncol. 12, 137-143 (2011). Accurate identification of nodal status in patients with bladder cancer is important in determining their prognosis and administration of perioperative chemotherapy. In this article, we review the study by Smith and colleagues, documenting the identification of a 20-gene model that can predict nodal stage in patients with bladder cancer based on the profiles of their primary tumors. The gene-expression model generated in this study was able to identify node-positive disease based on tumor tissues obtained from patients in a Phase III bladder cancer trial cohort. The model was able to predict nodal status independent of standard clinicopathologic prognostic criteria. This study adds the agnostic profiling dimension to prior investigations that have attempted to define molecular signatures that predict nodal metastasis in bladder cancer patients based on the primary tumors' gene-expression profiles.
Smith SC、Baras AS、Dancik G 等人。用于膀胱癌分子淋巴结分期的 20 基因模型:开发和前瞻性评估。柳叶刀肿瘤学。12,137-143(2011 年)。准确识别膀胱癌患者的淋巴结状态对于确定其预后和围手术期化疗的应用非常重要。在本文中,我们回顾了 Smith 及其同事的研究,该研究记录了一种 20 基因模型的鉴定,该模型可以根据患者的原发肿瘤特征预测膀胱癌的淋巴结分期。该研究中生成的基因表达模型能够基于 III 期膀胱癌试验队列中患者的肿瘤组织识别出阳性淋巴结疾病。该模型能够独立于标准临床病理预后标准预测淋巴结状态。这项研究为先前的研究增加了一个未知的分析维度,这些研究试图根据膀胱癌患者的原发肿瘤基因表达谱来定义预测淋巴结转移的分子特征。