Molecular Stratification of Clear Cell Renal Cell Carcinoma by Consensus Clustering Reveals Distinct Subtypes and Survival Patterns.
Molecular Stratification of Clear Cell Renal Cell Carcinoma by Consensus Clustering Reveals Distinct Subtypes and Survival Patterns.
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DOI：
10.1177/1947601909359929
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发表时间：
2010-02-01
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影响因子：
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通讯作者：
Rathmell WK
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作者：
Brannon AR;Reddy A;Seiler M;Arreola A;Moore DT;Pruthi RS;Wallen EM;Nielsen ME;Liu H;Nathanson KL;Ljungberg B;Zhao H;Brooks JD;Ganesan S;Bhanot G;Rathmell WK
透明细胞肾细胞癌（ccRCC）是主要的RCC亚型，但即使在这种分类中，自然史也是异质的，难以预测。对潜在肿瘤异质性最具鉴别力的分子特征的复杂理解应该基于可识别的和具有生物学意义的基因表达模式。使用实现迭代无监督一致聚类算法的软件分析基因表达微阵列数据，以鉴定最佳分子亚类，而无需临床或其他分类信息。聚类分析在训练集中鉴定了两种不同的ccRCC亚型，指定为透明细胞A型（ccA）和B型（ccB）。基于每个亚型中的核心肿瘤或大多数定义明确的阵列，数据的逻辑分析（LAD）定义了一个小的，高度预测的基因集，然后可以用于单独分类其他肿瘤。在177个肿瘤的验证数据集中证实了这些亚类，并分析了临床结果。基于个体肿瘤分配，与ccB相比，命名为ccA的肿瘤具有显著改善的疾病特异性生存期（中位生存期为8.6 vs 2.0年，P = 0.002）。通过单变量和多变量分析，分类方案与生存率独立相关。使用基于定义的基因集的基因表达模式，基于最终对应于临床结果的显著差异的固有分子特征，将ccRCC分为两个稳健的亚类。因此，该分类方案提供了适用于个体肿瘤的分子分层，其具有影响治疗决策、定义涉及ccRCC肿瘤进展的生物学机制和指导未来药物发现的意义。
Clear cell renal cell carcinoma (ccRCC) is the predominant RCC subtype, but even within this classification, the natural history is heterogeneous and difficult to predict. A sophisticated understanding of the molecular features most discriminatory for the underlying tumor heterogeneity should be predicated on identifiable and biologically meaningful patterns of gene expression. Gene expression microarray data were analyzed using software that implements iterative unsupervised consensus clustering algorithms to identify the optimal molecular subclasses, without clinical or other classifying information. ConsensusCluster analysis identified two distinct subtypes of ccRCC within the training set, designated clear cell type A (ccA) and B (ccB). Based on the core tumors, or most well-defined arrays, in each subtype, logical analysis of data (LAD) defined a small, highly predictive gene set that could then be used to classify additional tumors individually. The subclasses were corroborated in a validation data set of 177 tumors and analyzed for clinical outcome. Based on individual tumor assignment, tumors designated ccA have markedly improved disease-specific survival compared to ccB (median survival of 8.6 vs 2.0 years, P = 0.002). Analyzed by both univariate and multivariate analysis, the classification schema was independently associated with survival. Using patterns of gene expression based on a defined gene set, ccRCC was classified into two robust subclasses based on inherent molecular features that ultimately correspond to marked differences in clinical outcome. This classification schema thus provides a molecular stratification applicable to individual tumors that has implications to influence treatment decisions, define biological mechanisms involved in ccRCC tumor progression, and direct future drug discovery.