Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling.
Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling.
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DOI：
10.1158/1078-0432.ccr-08-1067
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发表时间：
2009-01-15
期刊：
影响因子：
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通讯作者：
Hammer G
中科院分区：
文献类型：
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作者：
Giordano TJ;Kuick R;Else T;Gauger PG;Vinco M;Bauersfeld J;Sanders D;Thomas DG;Doherty G;Hammer G
我们对肾上腺皮质癌（ACC）的认识已经有了很大的提高，但仍有许多未解之谜。例如，可以识别ACC的分子亚型吗？如果是，其潜在的发病基础是什么，它们是否具有临床意义？我们进行了一个全基因组基因表达研究的一大群肾上腺皮质组织的临床病理资料注释。使用Affyscore Human Genome U133 Plus 2.0寡核苷酸阵列，生成10个正常肾上腺皮质（NC）、22个肾上腺皮质腺瘤（ACA）和33个ACC的转录谱。使用整个数据集的主成分分析（PCA）概括了肾上腺皮质肿瘤的总体分类。NC和ACA队列显示出很小的组内变异，而ACC队列显示出更大的基因表达变异。生成了ACC中与NC和ACA相比的2875个差异表达基因的稳健列表，并将其用于功能富集分析以找到具有生物学意义的途径和属性。ACCs的聚类分析揭示了2个亚型，反映了肿瘤增殖，如有丝分裂计数和细胞周期基因所测量的。这些ACC簇的Kaplan-Meier分析显示存活率的显著差异（p<0.020）。多变量考克斯模型使用ACC样品的分期、有丝分裂率和基因表达数据（如通过第一主成分测量的）显示基因表达数据包含显著的独立预后信息（p<0.017）。本研究为肾上腺皮质肿瘤的分子分类和鉴定奠定了基础，同时也为潜在的诊断和预后标志物提供了丰富的来源。
Our understanding of adrenocortical carcinoma (ACC) has improved considerably, yet many unanswered questions remain. For instance, can molecular subtypes of ACC be identified? If so, what is their underlying pathogenetic basis and do they possess clinical significance? We performed a whole genome gene expression study of a large cohort of adrenocortical tissues annotated with clinicopathologic data. Using Affymetrix Human Genome U133 Plus 2.0 oligonucleotide arrays, transcriptional profiles were generated for 10 normal adrenal cortices (NCs), 22 adrenocortical adenomas (ACAs), and 33 ACCs. The overall classification of adrenocortical tumors was recapitulated using principal component analysis (PCA) of the entire data set. The NC and ACA cohorts showed little intragroup variation, whereas the ACC cohort revealed much greater variation in gene expression. A robust list of 2875 differentially expressed genes in ACC compared to both NC and ACA was generated and used in functional enrichment analysis to find pathways and attributes of biological significance. Cluster analysis of the ACCs revealed 2 subtypes that reflected tumor proliferation, as measured by mitotic counts and cell cycle genes. Kaplan-Meier analysis of these ACC clusters demonstrated a significant difference in survival (p<.020). Multivariate Cox modeling using stage, mitotic rate and gene expression data as measured by the first principal component for ACC samples showed that gene expression data contains significant independent prognostic information (p<.017). This study lays the foundation for the molecular classification and prognostication of adrenocortical tumors and also provides a rich source of potential diagnostic and prognostic markers.