Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability.
Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability.
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DOI：
10.1371/journal.pgen.1007669
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发表时间：
2018-09
期刊：
影响因子：
4.5
通讯作者：
Ciriello G
中科院分区：
文献类型：
--
作者：
Raynaud F;Mina M;Tavernari D;Ciriello G
基因组不稳定性是肿瘤内异质性的主要驱动因素。然而，不稳定的基因组往往表现出不同的分子和临床表型，这与不同的突变过程。在这里，我们通过算法推断了来自32种肿瘤类型的约6，000种人类肿瘤的克隆同源性，以探索肿瘤内异质性如何取决于基因组不稳定性的不同实现。我们发现，与DNA修复缺陷或高染色体不稳定性相关的极不稳定肿瘤本质上并不是最异质的。相反，肿瘤内异质性在表现出相对高数量的突变和拷贝数改变的肿瘤中最大，这是在与外源诱变剂相关的癌症中经常观察到的特征。独立于不稳定性的类型，具有高克隆数的肿瘤总是通过分支的不稳定性进化，其可以基于克隆（早期）和亚克隆（晚期）不稳定性的程度进行分层。有趣的是，具有大量亚克隆突变的肿瘤经常表现出染色体不稳定性、TP 53突变和APOBEC相关突变特征。反之亦然，染色质重塑基因的突变往往具有很少的亚克隆突变，但多克隆突变的肿瘤。了解肿瘤内异质性如何依赖于基因组不稳定性对于识别预测肿瘤复杂性的标志物和设想能够利用这种关联的治疗策略至关重要。癌症的特征在于细胞积累促进特定表型特征的分子改变，例如不受控制的增殖和存活。癌细胞有时会表现出大量的这种改变，通常是由DNA修复途径的缺陷或外部诱变剂（如吸烟或紫外线辐射）驱动的。高度改变的细胞被称为基因组不稳定。基因组不稳定性的一个主要后果是单个肿瘤通常由积累了不同改变的细胞组成。这种多样性被称为肿瘤内异质性，代表了一个关键的临床挑战。在这项研究中，我们研究了不同形式的基因组不稳定性如何与肿瘤内异质性相关。我们在约6000例人类肿瘤中推断了肿瘤内异质性，并发现具有极端突变或染色体不稳定性的肿瘤不是具有最高克隆数的肿瘤。相反，携带突变和染色体改变的肿瘤是最多样化的。此外，我们确定了与早期和/或晚期基因组不稳定性相关的特定遗传指纹。这些结果表明，癌症基因组的不稳定性并不一定会导致高的肿瘤内异质性，重要的是，它们提供了识别这种异质性的标记。
Genomic instability is a major driver of intra-tumor heterogeneity. However, unstable genomes often exhibit different molecular and clinical phenotypes, which are associated with distinct mutational processes. Here, we algorithmically inferred the clonal phylogenies of ~6,000 human tumors from 32 tumor types to explore how intra-tumor heterogeneity depends on different implementations of genomic instability. We found that extremely unstable tumors associated with DNA repair deficiencies or high chromosomal instability are not the most intrinsically heterogeneous. Conversely, intra-tumor heterogeneity is greatest in tumors exhibiting relatively high numbers of both mutations and copy number alterations, a feature often observed in cancers associated with exogenous mutagens. Independently of the type of instability, tumors with high number of clones invariably evolved through branching phylogenies that could be stratified based on the extent of clonal (early) and subclonal (late) instability. Interestingly, tumors with high number of subclonal mutations frequently exhibited chromosomal instability, TP53 mutations, and APOBEC-related mutational signatures. Vice versa, mutations of chromatin remodeling genes often characterized tumors with few subclonal but multiple clonal mutations. Understanding how intra-tumor heterogeneity depends on genomic instability is critical to identify markers predictive of the tumor complexity and envision therapeutic strategies able to exploit this association. Cancer is characterized by cells accumulating molecular alterations promoting specific phenotypic features, such as uncontrolled proliferation and survival. Cancer cells sometimes exhibit a high number of such alterations, often driven by defects of the DNA repair pathway or by external mutagens, such as tobacco smoking or UV-radiation. Highly altered cells are termed genomically unstable. A major consequence of genomic instability is that a single tumor is often composed by cells that have accumulated distinct alterations. This diversity is termed intra-tumor heterogeneity and represents a critical clinical challenge. In this study, we examined how different forms of genomic instability are associated with intra-tumor heterogeneity. We inferred intra-tumor heterogeneity in ~6000 human tumors and found that tumors with extreme mutational or chromosomal instability were not the tumors with the highest number of clones. Instead, tumors harboring both mutational and chromosomal alterations were the most diverse. Furthermore, we identified specific genetic fingerprints that are associated with early and/or late genomic instability. These results show that cancer genomic instability does not necessarily lead to high intra-tumor heterogeneity and, importantly, they provide markers to recognize when it does.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
17.1
作者：
McGranahan N;Favero F;de Bruin EC;Birkbak NJ;Szallasi Z;Swanton C
通讯作者：
Swanton C
影响因子：
11.2
作者：
Birkbak NJ;Eklund AC;Li Q;McClelland SE;Endesfelder D;Tan P;Tan IB;Richardson AL;Szallasi Z;Swanton C
通讯作者：
Swanton C
DOI：
10.1126/science.1253462
发表时间：
2014-10-10
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
de Bruin EC;McGranahan N;Mitter R;Salm M;Wedge DC;Yates L;Jamal-Hanjani M;Shafi S;Murugaesu N;Rowan AJ;Grönroos E;Muhammad MA;Horswell S;Gerlinger M;Varela I;Jones D;Marshall J;Voet T;Van Loo P;Rassl DM;Rintoul RC;Janes SM;Lee SM;Forster M;Ahmad T;Lawrence D;Falzon M;Capitanio A;Harkins TT;Lee CC;Tom W;Teefe E;Chen SC;Begum S;Rabinowitz A;Phillimore B;Spencer-Dene B;Stamp G;Szallasi Z;Matthews N;Stewart A;Campbell P;Swanton C
通讯作者：
Swanton C
影响因子：
82.9
作者：
Andor N;Graham TA;Jansen M;Xia LC;Aktipis CA;Petritsch C;Ji HP;Maley CC
通讯作者：
Maley CC