PDF(Pubmed)
Abstract：
Genome variation is the direct cause of cancer and driver of its clonal evolution. While the impact of many point mutations can be evaluated through their modification of individual genomic elements, even a single copy number aberration (CNA) may encompass hundreds of genes and therefore pose challenges to untangle potentially complex functional effects. However, consistent, recurring and disease-specific patterns in the genome-wide CNA landscape imply that particular CNA may promote cancer-type-specific characteristics. Discerning essential cancer-promoting alterations from the inherent co-dependency in CNA would improve the understanding of mechanisms of CNA and provide new insights into cancer biology and potential therapeutic targets. Here we implement a model using segmental breakpoints to discover non-random gene coverage by copy number deletion (CND). With a diverse set of cancer types from multiple resources, this model identified common and cancer-type-specific oncogenes and tumor suppressor genes as well as cancer-promoting functional pathways. Confirmed by differential expression analysis of data from corresponding cancer types, the results show that for most cancer types, despite dissimilarity of their CND landscapes, similar canonical pathways are affected. In 25 analyses of 17 cancer types, we have identified 19 to 169 significant genes by copy deletion, including RB1, PTEN and CDKN2A as the most significantly deleted genes among all cancer types. We have also shown a shared dependence on core pathways for cancer progression in different cancers as well as cancer type separation by genome-wide significance scores. While this work provides a reference for gene specific significance in many cancers, it chiefly contributes a general framework to derive genome-wide significance and molecular insights in CND profiles with a potential for the analysis of rare cancer types as well as non-coding regions.
摘要：
基因组变异是癌症的直接原因，也是其克隆进化的驱动因素。虽然许多点突变的影响可以通过它们对单个基因组元件的修饰来评估，即使是单个拷贝数畸变(CNA)也可能包含数百个基因,因此对解开潜在复杂的功能效应构成挑战.然而,一致,全基因组CNA格局中的复发和疾病特异性模式意味着特定的CNA可能促进癌症类型特异性特征.从CNA中固有的共同依赖性中识别出必要的促进癌症的改变将提高对CNA机制的理解，并提供对癌症生物学和潜在治疗靶标的新见解。在这里，我们使用分段断点来通过拷贝数缺失（CND）发现非随机基因覆盖的模型。来自多种资源的多种癌症类型，该模型确定了常见和癌症类型特异性癌基因和抑癌基因以及促进癌症的功能途径.通过对相应癌症类型数据的差异表达分析证实，结果显示，对于大多数癌症类型，尽管他们的CND景观不同，类似的规范途径受到影响。在对17种癌症类型的25种分析中，我们通过拷贝缺失鉴定了19到169个重要基因，包括RB1，PTEN和CDKN2A作为所有癌症类型中最显著缺失的基因。我们还显示了对不同癌症中癌症进展的核心途径以及通过全基因组显著性评分的癌症类型分离的共同依赖性。虽然这项工作为许多癌症中的基因特异性意义提供了参考，它主要为在CND谱中获得全基因组意义和分子见解提供了一个通用框架，具有分析罕见癌症类型以及非编码区域的潜力。
