Research Department of Pathology, Cancer Institute, University College London, London, UK.
Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA.
Nature. 2022 Jun;606(7916):984-991. doi: 10.1038/s41586-022-04738-6. Epub 2022 Jun 15.
Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage-fusion-bridge cycles, among others, which may lead to chromosomal instability and aneuploidy. These copy number alterations contribute to cancer initiation, progression and therapeutic resistance. Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2. In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations.
DNA 的增益和缺失在癌症中很常见,是复制应激、有丝分裂错误、纺锤体多极和断裂-融合-桥循环等相互关联的过程的结果,这些过程可能导致染色体不稳定和非整倍体。这些拷贝数改变有助于癌症的发生、发展和治疗耐药。在这里,我们提出了一个概念框架来检查人类癌症中拷贝数改变的模式,该框架广泛适用于多种数据类型,包括全基因组测序、全外显子组测序、简化代表性亚硫酸氢盐测序、单细胞 DNA 测序和 SNP6 微阵列数据。将该框架应用于代表 33 个人类癌症类型的 9873 种癌症,揭示了一组 21 个拷贝数特征,可解释 97%样本的拷贝数模式。17 个拷贝数特征归因于全基因组加倍、非整倍体、杂合性丢失、同源重组缺陷、染色体重排和单倍体化等生物学现象。四个拷贝数特征的病因仍未得到解释。一些癌症类型具有与染色体外 DNA、疾病特异性生存和原癌基因增益(如 MDM2)相关的扩增特征。与碱基尺度突变特征相反,没有拷贝数特征与许多已知的外源性癌症风险因素相关。我们的结果通过揭示导致这些改变的多种突变过程,综合了人类癌症中拷贝数改变的全球格局。