Goodman Cancer Research Centre, McGill University, Montreal, Quebec, Canada.
Department of Biochemistry, McGill University, Montreal, Quebec, Canada.
Cancer Res. 2017 Sep 1;77(17):4673-4683. doi: 10.1158/0008-5472.CAN-16-3427. Epub 2017 Jun 26.
Triple-negative breast cancer (TNBC) is a molecularly heterogeneous cancer that is difficult to treat. Despite the role it may play in tumor progression and response to therapy, microenvironmental (stromal) heterogeneity in TNBC has not been well characterized. To address this challenge, we investigated the transcriptome of tumor-associated stroma isolated from TNBC ( = 57). We identified four stromal axes enriched for T cells (T), B cells (B), epithelial markers (E), or desmoplasia (D). Our analysis method (STROMA4) assigns a score along each stromal axis for each patient and then combined the axis scores to subtype patients. Analysis of these subtypes revealed that prognostic capacity of the B, T, and E scores was governed by the D score. When compared with a previously published TNBC subtyping scheme, the STROMA4 method better captured tumor heterogeneity and predicted patient benefit from therapy with increased sensitivity. This approach produces a simple ontology that captures TNBC heterogeneity and informs how tumor-associated properties interact to affect prognosis. .
三阴性乳腺癌（TNBC）是一种分子异质性癌症，难以治疗。尽管它可能在肿瘤进展和对治疗的反应中发挥作用，但 TNBC 的微环境（基质）异质性尚未得到很好的描述。为了应对这一挑战，我们研究了从 TNBC 中分离的肿瘤相关基质的转录组（= 57）。我们鉴定了四个富含 T 细胞（T）、B 细胞（B）、上皮标志物（E）或间充质（D）的基质轴。我们的分析方法（STROMA4）为每个患者沿每个基质轴分配一个分数，然后组合轴分数对患者进行亚型分类。对这些亚型的分析表明，B、T 和 E 评分的预后能力受 D 评分的控制。与之前发表的 TNBC 亚型分类方案相比，STROMA4 方法更好地捕获了肿瘤异质性，并通过提高敏感性预测了患者从治疗中获益的情况。这种方法产生了一个简单的本体，捕获了 TNBC 的异质性，并说明了肿瘤相关特性如何相互作用影响预后。
