Biomarker Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Mol Oncol. 2017 Oct;11(10):1399-1412. doi: 10.1002/1878-0261.12107. Epub 2017 Aug 22.
None of the clinically relevant gene expression signatures available for breast cancer were specifically developed to capture the influence of the microenvironment on tumor cells. Here, we attempted to build subtype-specific signatures derived from an in vitro model reproducing tumor cell modifications after interaction with activated or normal stromal cells. Gene expression signatures derived from HER2+, luminal, and basal breast cancer cell lines (treated by normal fibroblasts or cancer-associated fibroblasts conditioned media) were evaluated in clinical tumors by in silico analysis on published gene expression profiles (GEPs). Patients were classified as microenvironment-positive (μENV+ve), that is, with tumors showing molecular profiles suggesting activation by the stroma, or microenvironment-negative (μENV-ve) based on correlation of their tumors' GEP with the respective subtype-specific signature. Patients with estrogen receptor alpha (ER)+/HER2-/μENV+ve tumors were characterized by 2.5-fold higher risk of developing distant metastases (HR = 2.546; 95% CI: 1.751-3.701, P = 9.84E-07), while μENV status did not affect, or only suggested the risk of distant metastases, in women with HER2+ (HR = 1.541; 95% CI: 0.788-3.012, P = 0.206) or ER-/HER2- tumors (HR = 1.894; 95% CI: 0.938-3.824; P = 0.0747), respectively. In ER+/HER2- tumors, the μENV status remained significantly associated with metastatic progression (HR = 2.098; CI: 1.214-3.624; P = 0.00791) in multivariable analysis including size, age, and Genomic Grade Index. Validity of our in vitro model was also supported by in vitro biological endpoints such as cell growth (MTT assay) and migration/invasion (Transwell assay). In vitro-derived gene signatures tracing the bidirectional interaction with cancer activated fibroblasts are subtype-specific and add independent prognostic information to classical prognostic variables in women with ER+/HER2- tumors.
目前用于乳腺癌的临床相关基因表达特征都没有专门用于捕捉肿瘤细胞微环境的影响。在这里，我们试图构建源自体外模型的特定于亚型的特征，该模型再现了肿瘤细胞在与激活的或正常基质细胞相互作用后的改变。通过对发表的基因表达谱（GEP）进行计算机分析，评估了从 HER2+、管腔和基底乳腺癌细胞系中获得的基因表达特征（用正常成纤维细胞或癌症相关成纤维细胞条件培养基处理）在临床肿瘤中的应用。根据其肿瘤的 GEP 与各自的特定于亚型的特征的相关性，将患者分类为微环境阳性（μENV+ve），即肿瘤表现出分子特征提示受基质激活，或微环境阴性（μENV-ve）。具有雌激素受体α（ER）+/HER2-/μENV+ve 肿瘤的患者发生远处转移的风险高出 2.5 倍（HR=2.546；95%CI：1.751-3.701，P=9.84E-07），而 μENV 状态对 HER2+（HR=1.541；95%CI：0.788-3.012，P=0.206）或 ER-/HER2- 肿瘤（HR=1.894；95%CI：0.938-3.824；P=0.0747）的远处转移风险没有影响，或者仅提示风险。在 ER+/HER2- 肿瘤中，在包括大小、年龄和基因组分级指数在内的多变量分析中，μENV 状态仍然与转移进展显著相关（HR=2.098；CI：1.214-3.624；P=0.00791）。我们的体外模型的有效性还得到了体外生物学终点的支持，如细胞生长（MTT 测定）和迁移/侵袭（Transwell 测定）。源自体外的基因特征追踪与癌症激活成纤维细胞的双向相互作用是特定于亚型的，并为 ER+/HER2- 肿瘤患者的经典预后变量提供了独立的预后信息。
