Huang Qingyao, Baudis Michael
Department of Molecular Life Science, University of Zurich, Zurich, Switzerland.
Swiss Institute of Bioinformatics, Zurich, Switzerland.
Front Genet. 2023 Jan 16;13:1017657. doi: 10.3389/fgene.2022.1017657. eCollection 2022.
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.
基因组变异是癌症的直接原因及其克隆进化的驱动因素。虽然许多点突变的影响可以通过其对单个基因组元件的修饰来评估,但即使是单个拷贝数畸变(CNA)也可能包含数百个基因,因此在梳理潜在复杂的功能效应方面面临挑战。然而,全基因组CNA格局中一致、反复出现且疾病特异性的模式意味着特定的CNA可能促进癌症类型特异性特征。从CNA中固有的共依赖性中辨别出促进癌症的关键改变,将增进对CNA机制的理解,并为癌症生物学和潜在治疗靶点提供新的见解。在这里,我们使用片段断点实现了一个模型,以发现拷贝数缺失(CND)导致的非随机基因覆盖情况。利用来自多种资源的多种癌症类型,该模型识别出了常见的和癌症类型特异性的癌基因、肿瘤抑制基因以及促进癌症的功能通路。通过对相应癌症类型数据的差异表达分析得到证实,结果表明,对于大多数癌症类型,尽管它们的CND格局不同,但相似的经典通路受到影响。在对17种癌症类型的25次分析中,我们通过拷贝缺失鉴定出了19至169个显著基因,其中RB1、PTEN和CDKN2A是所有癌症类型中缺失最显著的基因。我们还展示了不同癌症在癌症进展方面对核心通路的共同依赖性,以及通过全基因组显著性分数进行癌症类型分离。虽然这项工作为许多癌症中基因的特异性意义提供了参考,但它主要贡献了一个通用框架,以推导全基因组的显著性以及CND图谱中的分子见解,具有分析罕见癌症类型以及非编码区域的潜力。