Pervasive chromosomal instability and karyotype order in tumour evolution

Watkins, Thomas B.K.; Lim, Emilia L.; Petković, Marina; Elizalde, Sergi; Birkbak, Nicolai J.; Wilson, Gareth A.; Moore, David A.; Grönroos, Eva; Rowan, Andrew; Dewhurst, Sally M.; Demeulemeester, Jonas; Dentro, Stefan C.; Horswell, Stuart; Au, Lewis; Haase, Kerstin; Escudero, Mickael; Rosenthal, Rachel; Bakir, Maise Al; Xu, Hang; Litchfield, Kevin; Lü, Wei; Mourikis, Thanos P.; Dietzen, Michelle; Spain, Lavinia; Cresswell, George D; Biswas, Dhruva; Lamy, Philippe; Nordentoft, Iver; Harbst, Katja; Castro-Giner, Francesc; Yates, Lucy R.; Caramia, Franco; Jaulin, Fanny; Vicier, Cécile; Tomlinson, Ian; Brastianos, Priscilla K.; Cho, Raymond J.; Bastian, Boris C.; Dyrskjøt, Lars; Jönsson, Göran; Savas, Peter; Loi, Sherene; Campbell, Peter J.; André, Fabrice; Luscombe, Nicholas M.; Steeghs, Neeltje; Tjan‐Heijnen, Vivianne C. G.; Szállási, Zoltán; Turajlic, Samra; Jamal‐Hanjani, Mariam; Loo, Peter Van; Bakhoum, Samuel F.; Schwarz, Roland F.; McGranahan, Nicholas; Swanton, Charles

doi:10.1038/s41586-020-2698-6

Cited by 290 publications

(357 citation statements)

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“…Chromosomal instability (CIN) is a hallmark of human cancer and it is associated with metastasis, immune evasion, and therapeutic resistance (1)(2)(3)(4)(5). In addition to the generation of chromosome copy number heterogeneity, which serves as a substrate for natural selection, CIN also promotes tumor progression by inducing chronic inflammatory signaling leading to increased cancer cell migration and invasion (1,6).…”

Section: Introductionmentioning

confidence: 99%

“…Given the pervasive nature of CIN in human cancer (4), tumor cells must cope with the presence of persistent inflammatory signaling arising from cGAS-sensing of cytosolic dsDNA. The activation of cGAS-STING has cell-autonomous and cell nonautonomous consequences and therefore cancer cells must mitigate the effects of this inflammatory pathway at multiple levels.…”

Section: Introductionmentioning

confidence: 99%

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Metastasis and Immune Evasion from Extracellular cGAMP Hydrolysis

et al. 2020

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Cytosolic DNA is characteristic of chromosomally unstable metastatic cancer cells, resulting in constitutive activation of the cGAS–STING innate immune pathway. How tumors co-opt inflammatory signaling while evading immune surveillance remains unknown. Here, we show that the ectonucleotidase ENPP1 promotes metastasis by selectively degrading extracellular cGAMP, an immune-stimulatory metabolite whose breakdown products include the immune suppressor adenosine. ENPP1 loss suppresses metastasis, restores tumor immune infiltration, and potentiates response to immune checkpoint blockade in a manner dependent on tumor cGAS and host STING. Conversely, overexpression of wild-type ENPP1, but not an enzymatically weakened mutant, promotes migration and metastasis, in part through the generation of extracellular adenosine, and renders otherwise sensitive tumors completely resistant to immunotherapy. In human cancers, ENPP1 expression correlates with reduced immune cell infiltration, increased metastasis, and resistance to anti–PD-1/PD-L1 treatment. Thus, cGAMP hydrolysis by ENPP1 enables chromosomally unstable tumors to transmute cGAS activation into an immune-suppressive pathway. Significance: Chromosomal instability promotes metastasis by generating chronic tumor inflammation. ENPP1 facilitates metastasis and enables tumor cells to tolerate inflammation by hydrolyzing the immunotransmitter cGAMP, preventing its transfer from cancer cells to immune cells. This article is highlighted in the In This Issue feature, p. 995

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Metastasis and Immune Evasion from Extracellular cGAMP Hydrolysis

et al. 2020

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“…6C ). Overall TmS shows a significantly higher correlation with ongoing chromosomal instability 48 (Spearman r = 0.44) than static chromosomal instability (difference in r = 0.20, 95% CI: 0.04, 0.37, Fig. 6D , Methods and SI ).…”

Section: Resultsmentioning

confidence: 91%

Tumor cell total mRNA expression shapes the molecular and clinical phenotype of cancer

Cao

Wang

et al. 2020

Preprint

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Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, the significance of differences in tumor cell total mRNA content is poorly understood. Studies using single-cell sequencing or model systems have suggested a role for total mRNA content in regulating cellular phenotypes. However, analytical challenges related to technical artifacts and cellular admixture have impeded examination of total mRNA expression at scale across cancers. To address this, we evaluated total mRNA expression using single cell sequencing, and developed a computational method for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data. We systematically estimated TmS in 5,181 patients across 15 cancer types and observed close correlations with clinicopathologic characteristics and molecular features, where high TmS generally accompanies high-risk disease. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Moreover, TmS captures tumor type-specific effects of somatic mutations, chromosomal instability, and hypoxia, as well as aspects of intratumor heterogeneity. Taken together, our results suggest that measuring total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important clinical and biological implications.

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“…For example, an SNV occurring before an amplification may result in cancer cells with different mutation multiplicities: a group of cells without the amplification and with a single copy of the SNV, and another group of cells with the amplification and multiple copies of the SNV. Scenarios such as this are frequent in solid tumors that often have subclonal CNAs 12,27,33,36 . Thus, the CMM assumption is both too restrictive to model many real tumors and also too weak to overcome the issue of non-identifiability.…”

Section: Multiple Computational Methods Have Been Developed In Recentmentioning

confidence: 99%

“…In statistical terms, the CCF is not identifiable from DNA sequencing data ( Figure S1a). Since CNAs and LOH events that amplify or delete large genomic segments, chromosomal arms, and even the whole genome [33][34][35][36] are frequent in cancer -particularly in solid tumors where up to ⇠90% of tumors 37 may contain CNAs -it is imperative to have robust methods to calculate…”

Section: Introductionmentioning

confidence: 99%

DeCiFering the Elusive Cancer Cell Fraction in Tumor Heterogeneity and Evolution

Satas

Zaccaria

El-Kebir

et al. 2021

Preprint

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Most tumors are heterogeneous mixtures of normal cells and cancer cells, with individual cancer cells distinguished by somatic mutations that accumulated during the evolution of the tumor. The fundamental quantity used to measure tumor heterogeneity from somatic single-nucleotide variants (SNVs) is the Cancer Cell Fraction (CCF), or proportion of cancer cells that contain the SNV. However, in tumors containing copy-number aberrations (CNAs) -- e.g., most solid tumors -- the estimation of CCFs from DNA sequencing data is challenging because a CNA may alter the mutation multiplicity, or number of copies of an SNV. Existing methods to estimate CCFs rely on the restrictive Constant Mutation Multiplicity (CMM) assumption that the mutation multiplicity is constant across all tumor cells containing the mutation. However, the CMM assumption is commonly violated in tumors containing CNAs, and thus CCFs computed under the CMM assumption may yield unrealistic conclusions about tumor heterogeneity and evolution. The CCF also has a second limitation for phylogenetic analysis: the CCF measures the presence of a mutation at the present time, but SNVs may be lost during the evolution of a tumor due to deletions of chromosomal segments. Thus, SNVs that co-occur on the same phylogenetic branch may have different CCFs. In this work, we address these limitations of the CCF in two ways. First, we show how to compute the CCF of an SNV under a less restrictive and more realistic assumption called the Single Split Copy Number (SSCN) assumption. Second, we introduce a novel statistic, the descendant cell fraction (DCF), that quantifies both the prevalence of an SNV and the past evolutionary history of SNVs under an evolutionary model that allows for mutation losses. That is, SNVs that co-occur on the same phylogenetic branch will have the same DCF. We implement these ideas in an algorithm named DeCiFer. DeCiFer computes the DCFs of SNVs from read counts and copy-number proportions and also infers clusters of mutations that are suitable for phylogenetic analysis. We show that DeCiFer clusters SNVs more accurately than existing methods on simulated data containing mutation losses. We apply DeCiFer to sequencing data from 49 metastatic prostate cancer samples and show that DeCiFer produces more parsimonious and reasonable reconstructions of tumor evolution compared to previous approaches. Thus, DeCiFer enables more accurate quantification of intra-tumor heterogeneity and improves downstream inference of tumor evolution.

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Pervasive chromosomal instability and karyotype order in tumour evolution

Cited by 290 publications

References 60 publications

Metastasis and Immune Evasion from Extracellular cGAMP Hydrolysis

Metastasis and Immune Evasion from Extracellular cGAMP Hydrolysis

Tumor cell total mRNA expression shapes the molecular and clinical phenotype of cancer

DeCiFering the Elusive Cancer Cell Fraction in Tumor Heterogeneity and Evolution

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