Sanchez-Carbayo Marta, Socci Nicholas D, Lozano Juan Jose, Li Wentian, Charytonowicz Elizabeth, Belbin Thomas J, Prystowsky Michael B, Ortiz Angel R, Childs Geoffrey, Cordon-Cardo Carlos
Division of Molecular Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.
Am J Pathol. 2003 Aug;163(2):505-16. doi: 10.1016/S0002-9440(10)63679-6.
To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression.
为了确定膀胱癌进展过程中的基因表达变化,我们使用包含17,842个已知基因和表达序列标签的cDNA微阵列,比较了早期和晚期膀胱肿瘤的表达谱。将自展技术应用于层次聚类,可将早期和浸润性移行细胞癌分为两个主要簇。多维分析证实了这些簇,更重要的是,它将原位癌与乳头状浅表病变以及早期和浸润性肿瘤中显示不同总生存期的亚组区分开来。此外,它识别出了基因谱与浸润性疾病相似的早期肿瘤。应用了包括标准t检验、单基因逻辑回归和支持向量机算法在内的不同技术,以识别参与膀胱癌进展的相关基因。细胞角蛋白20、神经纤毛蛋白-2、p21和p33ING1在差异表达的顶级分子靶点中被选中,并使用组织微阵列(n = 173)通过免疫组织化学进行了验证。它们的表达模式与病理分期、肿瘤分级以及视网膜母细胞瘤(RB)表达改变显著相关。此外,p33ING1表达水平与总生存期显著相关。对最显著基因的注释分析揭示了膀胱癌进展过程中关键基因和途径的相关性,包括浅表肿瘤中致癌基因如DEK的过表达或浸润性疾病中免疫反应基因如Cd86抗原的过表达。基因谱分析成功地根据膀胱癌的进展和临床结果对其进行了分类。本研究确定了具有潜在临床意义的分子生物标志物以及与膀胱癌进展相关的关键分子靶点。