小柯机器人

美国加州大学Laura J. van 't Veer，Christina Yau和Denise M. Wolf共同合作近期取得重要工作进展。他们研究发现了重新定义乳腺癌亚型以指导治疗优先级和最大限度的反应：10种癌症治疗的预测性生物标志物。该项研究成果2022年5月26日在线出版于《癌细胞》杂志。

使用来自I-SPY2新辅助平台试验 (NCT01042379) 的治疗前基因表达、蛋白质/磷蛋白和临床数据，研究人员创建了替代乳腺癌亚型，结合了临床激素受体（HR）和人表皮生长因子受体-2 (HER2)之外的肿瘤生物学状态以更好地预测药物反应。他们评估了用10种针对不同生物学的方案治疗的990名患者的作用机制生物标志物的预测性能。研究人员探索超过11种亚型模式并确定治疗亚型对，以最大限度地提高整个人群的病理完全缓解 (pCR) 率。表现最好的模式包含免疫、DNA修复和HER2/Luminal表型。

随后的治疗分配使用基于HR/HER2的治疗选择将总体 pCR 率从51%提高到63%。在HR⁺亚组中，重新分类和改进患者选择带来的pCR收益最高（>15%）。随着新疗法的引入，分型模式决定了显示疗效所需的最小响应。该数据平台提供了前所未有的资源，并支持使用基于响应的亚型来指导未来的治疗优先级。

附：英文原文

Title: Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies

Author: Denise M. Wolf, Christina Yau, Julia Wulfkuhle, Lamorna Brown-Swigart, Isela R. Gallagher, Pei Rong Evelyn Lee, Zelos Zhu, Mark J. Magbanua, Rosalyn Sayaman, Nicholas O’Grady, Amrita Basu, Amy Delson, Jean Philippe Coppé, Ruixiao Lu, Jerome Braun, Smita M. Asare, Laura Sit, Jeffrey B. Matthews, Jane Perlmutter, Nola Hylton, Minetta C. Liu, Paula Pohlmann, W. Fraser Symmans, Hope S. Rugo, Claudine Isaacs, Angela M. DeMichele, Douglas Yee, Donald A. Berry, Lajos Pusztai, Emanuel F. Petricoin, Gillian L. Hirst, Laura J. Esserman, Laura J. van t Veer

Issue&Volume: 2022-05-26

Abstract: Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ～990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR+ subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization.

DOI: 10.1016/j.ccell.2022.05.005

Source: https://www.cell.com/cancer-cell/fulltext/S1535-6108(22)00216-1

Cancer Cell：《癌细胞》，创刊于2002年。隶属于细胞出版社，最新IF：38.585
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