Differentiation Score and Intrinsic Subtype Predict Breast Cancer Organ of Relapse

The ability to predict metastatic potential is of clinical and biological importance. Numerous metastasis/relapse predictors exist for breast cancer patients; however, what is less well established is whether predicting metastasis to specific organs sites is feasible. In this study we sought to determine: 1) the degree to which gene signatures vary across tumors and their metastases, 2) if genomic intrinsic subtypes associate with particular organs of relapse, and 3) if other genomic signatures can predict spread to specific organs. Using a gene expression microarray data set of >1000 breast tumors and metastases, we observed that >90% of 298 gene signatures were similarly expressed between matched pairs of breast tumors and metastases; those most altered were reflective of cell types including fibroblasts and immune cells. Significant associations were identified between tumor subtypes and organ of first relapse. Among these, HER2-enriched tumors were significantly associated with liver, and Basal-like and Claudin-low tumors with brain and lung. Correspondingly, previously published brain and lung metastasis signatures, along with embryonic stem cell and tumor initiating cell signatures, were also associated with Basal-like and Claudin-low subtypes. These signatures strongly correlated with low Differentiation Scores (DS) and, to a lesser extent, high proliferation. Interestingly, within Basal-like and Claudin-low tumors, low DS further predicted for brain and lung metastases. In total, intrinsic subtype and DS provide clinically useful information that identifies the distant organ sites that should be most closely monitored for signs of disease recurrence. 414 samples profiled on Agilent microarrays.

预测肿瘤转移潜能的能力具有重要的临床与生物学意义。目前已有多款针对乳腺癌患者的转移/复发预测模型，但针对肿瘤向特定器官部位转移的预测可行性尚未得到充分证实。本研究旨在明确三个核心问题：1）基因特征(gene signatures)在原发肿瘤及其转移灶中的差异程度；2）基因组固有亚型(genomic intrinsic subtypes)是否与特定复发器官存在关联；3）其他基因组特征能否预测肿瘤向特定器官的播散。
本研究使用包含逾1000例乳腺癌原发肿瘤与转移灶的基因表达微阵列数据集，分析发现，298个基因特征中超过90%在匹配的原发-转移瘤对中表达模式高度相似；表达差异最显著的特征多对应成纤维细胞与免疫细胞等细胞类群。
研究同时发现肿瘤亚型与首次复发器官间存在显著关联：其中HER2富集型(HER2-enriched)肿瘤与肝脏转移显著相关，而基底样(Basal-like)与Claudin-low(Claudin-low)型肿瘤则与脑、肺转移相关。
相应地，已发表的脑、肺转移特征，以及胚胎干细胞与肿瘤起始细胞(tumor initiating cell)特征，同样与基底样与Claudin-low亚型相关。上述特征与低分化评分(Differentiation Scores, DS)呈强相关，同时在一定程度上与高增殖状态相关。
值得注意的是，在基底样与Claudin-low型肿瘤中，低分化评分可进一步预测脑与肺转移的发生风险。
综上，固有亚型与分化评分可提供具备临床实用价值的信息，帮助识别需要重点监测疾病复发迹象的远处器官位点。
本数据集包含414例经安捷伦(Agilent)微阵列平台检测的样本。