Lapointe Jacques, Li Chunde, Higgins John P, van de Rijn Matt, Bair Eric, Montgomery Kelli, Ferrari Michelle, Egevad Lars, Rayford Walter, Bergerheim Ulf, Ekman Peter, DeMarzo Angelo M, Tibshirani Robert, Botstein David, Brown Patrick O, Brooks James D, Pollack Jonathan R
Department of Pathology, Stanford University, Stanford, CA 94305, USA.
Proc Natl Acad Sci U S A. 2004 Jan 20;101(3):811-6. doi: 10.1073/pnas.0304146101. Epub 2004 Jan 7.
Prostate cancer, a leading cause of cancer death, displays a broad range of clinical behavior from relatively indolent to aggressive metastatic disease. To explore potential molecular variation underlying this clinical heterogeneity, we profiled gene expression in 62 primary prostate tumors, as well as 41 normal prostate specimens and nine lymph node metastases, using cDNA microarrays containing approximately 26,000 genes. Unsupervised hierarchical clustering readily distinguished tumors from normal samples, and further identified three subclasses of prostate tumors based on distinct patterns of gene expression. High-grade and advanced stage tumors, as well as tumors associated with recurrence, were disproportionately represented among two of the three subtypes, one of which also included most lymph node metastases. To further characterize the clinical relevance of tumor subtypes, we evaluated as surrogate markers two genes differentially expressed among tumor subgroups by using immunohistochemistry on tissue microarrays representing an independent set of 225 prostate tumors. Positive staining for MUC1, a gene highly expressed in the subgroups with "aggressive" clinicopathological features, was associated with an elevated risk of recurrence (P = 0.003), whereas strong staining for AZGP1, a gene highly expressed in the other subgroup, was associated with a decreased risk of recurrence (P = 0.0008). In multivariate analysis, MUC1 and AZGP1 staining were strong predictors of tumor recurrence independent of tumor grade, stage, and preoperative prostate-specific antigen levels. Our results suggest that prostate tumors can be usefully classified according to their gene expression patterns, and these tumor subtypes may provide a basis for improved prognostication and treatment stratification.
前列腺癌是癌症死亡的主要原因之一,其临床行为范围广泛,从相对惰性到侵袭性转移性疾病。为了探索这种临床异质性背后的潜在分子变异,我们使用包含约26000个基因的cDNA微阵列,对62例原发性前列腺肿瘤、41例正常前列腺标本和9例淋巴结转移灶进行了基因表达谱分析。无监督层次聚类很容易区分肿瘤和正常样本,并根据不同的基因表达模式进一步确定了前列腺肿瘤的三个亚类。在这三个亚型中的两个亚型中,高级别和晚期肿瘤以及与复发相关的肿瘤比例过高,其中一个亚型还包括大多数淋巴结转移灶。为了进一步表征肿瘤亚型的临床相关性,我们通过对代表一组独立的225例前列腺肿瘤的组织微阵列进行免疫组织化学分析,评估了在肿瘤亚组中差异表达的两个基因作为替代标志物。MUC1在具有“侵袭性”临床病理特征的亚组中高度表达,其阳性染色与复发风险升高相关(P = 0.003),而AZGP1在另一个亚组中高度表达,其强染色与复发风险降低相关(P = 0.0008)。在多变量分析中,MUC1和AZGP1染色是肿瘤复发的强预测指标,独立于肿瘤分级、分期和术前前列腺特异性抗原水平。我们的结果表明,前列腺肿瘤可以根据其基因表达模式进行有效分类,这些肿瘤亚型可能为改善预后和治疗分层提供基础。