Landemaine Thomas, Jackson Amanda, Bellahcène Akeila, Rucci Nadia, Sin Soraya, Abad Berta Martin, Sierra Angels, Boudinet Alain, Guinebretière Jean-Marc, Ricevuto Enrico, Noguès Catherine, Briffod Marianne, Bièche Ivan, Cherel Pascal, Garcia Teresa, Castronovo Vincent, Teti Anna, Lidereau Rosette, Driouch Keltouma
Centre René Huguenin, Fédération Nationale des Centres de Lutte Contre le Cancer and Institut National de la Sante et de la Recherche Medicale, U735, Saint-Cloud, France.
Cancer Res. 2008 Aug 1;68(15):6092-9. doi: 10.1158/0008-5472.CAN-08-0436.
The lungs are a frequent target of metastatic breast cancer cells, but the underlying molecular mechanisms are unclear. All existing data were obtained either using statistical association between gene expression measurements found in primary tumors and clinical outcome, or using experimentally derived signatures from mouse tumor models. Here, we describe a distinct approach that consists of using tissue surgically resected from lung metastatic lesions and comparing their gene expression profiles with those from nonpulmonary sites, all coming from breast cancer patients. We show that the gene expression profiles of organ-specific metastatic lesions can be used to predict lung metastasis in breast cancer. We identified a set of 21 lung metastasis-associated genes. Using a cohort of 72 lymph node-negative breast cancer patients, we developed a 6-gene prognostic classifier that discriminated breast primary cancers with a significantly higher risk of lung metastasis. We then validated the predictive ability of the 6-gene signature in 3 independent cohorts of breast cancers consisting of a total of 721 patients. Finally, we show that the signature improves risk stratification independently of known standard clinical variables and a previously established lung metastasis signature based on an experimental breast cancer metastasis model.
肺是转移性乳腺癌细胞常见的转移靶器官,但其潜在分子机制尚不清楚。所有现有数据要么是通过原发性肿瘤中基因表达测量值与临床结果之间的统计关联获得的,要么是使用来自小鼠肿瘤模型的实验性特征获得的。在此,我们描述了一种独特的方法,该方法包括使用从肺转移病灶手术切除的组织,并将其基因表达谱与来自非肺部部位的组织(均来自乳腺癌患者)的基因表达谱进行比较。我们表明,器官特异性转移病灶的基因表达谱可用于预测乳腺癌的肺转移。我们鉴定出一组21个与肺转移相关的基因。利用72例淋巴结阴性乳腺癌患者组成的队列,我们开发了一种6基因预后分类器,该分类器可区分具有显著更高肺转移风险的乳腺癌原发癌。然后,我们在由总共721例患者组成的3个独立乳腺癌队列中验证了6基因特征的预测能力。最后,我们表明,该特征独立于已知的标准临床变量和基于实验性乳腺癌转移模型先前建立的肺转移特征,改善了风险分层。