Martin K J, Graner E, Li Y, Price L M, Kritzman B M, Fournier M V, Rhei E, Pardee A B
Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
Proc Natl Acad Sci U S A. 2001 Feb 27;98(5):2646-51. doi: 10.1073/pnas.041622398. Epub 2001 Feb 20.
Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P < or = 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 x 10(8) transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.
早期检测是降低癌症死亡率的有效手段。在此,我们描述了一种高灵敏度的高通量筛选方法,该方法能够识别用于早期检测外周血中播散的实体瘤细胞的标志物组合。该方法是差异显示和高灵敏度cDNA阵列的两步组合。在初次筛选中,差异显示鉴定出170个在乳腺肿瘤细胞和正常乳腺上皮细胞之间差异表达的候选标志物基因。在二次筛选中,高灵敏度阵列评估了这些基因在48份血样中的表达水平,其中22份来自健康志愿者,26份来自乳腺癌患者。聚类分析确定了一组在癌症患者血液中表达升高的12个基因。对单个基因的置换分析确定了5个核心基因(P≤0.05,置换检验)。作为一个整体,这12个基因通常能够准确地区分健康志愿者和乳腺癌患者。12个基因的平均表达水平在77%(13例中的10例)未经治疗的浸润性癌症患者中升高,而聚类分析正确地对志愿者和患者进行了分类(P = 0.0022,Fisher精确检验)。定量实时PCR证实了阵列结果,并表明该检测方法的灵敏度(1:2×10^8转录本)足以检测血液中播散的实体瘤细胞。用本文所述筛选方法开发的基于表达的血液检测方法有潜力检测和分类源自身体几乎任何原发部位的实体瘤细胞。