Clonal fitness inferred from time-series modelling of single-cell cancer genomes

Salehi, Sohrab; Kabeer, Farhia; Ceglia, Nicholas; Andronescu, Mirela; Williams, Marc; Campbell, Kieran R; Masud, Tehmina; Wang, Beixi; Biele, Justina; Brimhall, Jazmine; Gee, David; Lee, Hakwoo; Ting, Jerome; Zhang, Allen W.; Tran, Hoa; O’Flanagan, Ciara H.; Dorri, Fatemeh; Rusk, Nicole; Algara, Teresa Ruiz de; Lee, So Ra; Cheng, Brian Yu Chieh; Eirew, Peter; Kono, Takako; Pham, Jenifer; Grewal, Diljot; Lai, Daniel; Moore, Richard A.; Mungall, Andrew J.; Marra, Marco A.; McPherson, Andrew; Bouchard‐Côté, Alexandre; Aparicio, Samuel; Shah, Sohrab P.

doi:10.1038/s41586-021-03648-3

Cited by 96 publications

(133 citation statements)

References 53 publications

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“…Moreover, note that such aneuploidy tolerance studies utilized experimental induction of chromosome mis-segregation in cells lacking p53. However, the emergence of aneuploid clones with TP53 loss has been observed in untreated mammary epithelial and RPE-1 cells ( Kok et al, 2020 ; Salehi et al, 2021 ; Soto et al, 2017 ). In addition, multiple cellular processes were deregulated in response to p53 inactivation in transformed murine embryonic fibroblasts, including ploidy control ( Valente et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

TP53 loss initiates chromosomal instability in fallopian tube epithelial cells

Bronder

Tighe

Wangsa

et al. 2021

Disease Models &Amp; Mechanisms

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High-grade serous ovarian cancer (HGSOC) originates in the fallopian tube epithelium and is characterized by ubiquitous TP53 mutation and extensive chromosomal instability (CIN). However, direct causes of CIN, such as mutations in DNA replication and mitosis genes, are rare in HGSOC. We therefore asked whether oncogenic mutations that are common in HGSOC can indirectly drive CIN in non-transformed human fallopian tube epithelial cells. To model homologous recombination deficient HGSOC, we sequentially mutated TP53 and BRCA1 then overexpressed MYC. Loss of p53 function alone was sufficient to drive the emergence of sub-clonal karyotype alterations. TP53 mutation also led to global gene expression changes, influencing modules involved in cell cycle commitment, DNA replication, G2/M checkpoint control, and mitotic spindle function. Both transcriptional deregulation and karyotype diversity were exacerbated by loss of BRCA1 function, with whole-genome doubling events observed in independent p53/BRCA1-deficient lineages. Thus, our observations indicate that loss of the key tumour suppressor TP53 is sufficient to deregulate multiple cell cycle control networks and thereby initiate CIN in pre-malignant fallopian tube epithelial cells.

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Section: Resultsmentioning

confidence: 99%

TP53 loss initiates chromosomal instability in fallopian tube epithelial cells

Bronder

Tighe

Wangsa

et al. 2021

Disease Models &Amp; Mechanisms

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“…Based on the dispensable role for tumour suppression of p53 mediated DNA damage response, the mechanism by which genomic instability is prevented remains elusive. The last decade has seen a massive expansion of cancer genomics studies, including development of predictive model of gene network [ 69 – 75 ] and improvement of experimental model of studies, including effective genetic editing techniques and 3D cell culture models [ 76 – 79 ]. With the support of the expansion of cancer genomics studies [ 70 , 80 – 86 ] and methodological improvements [ 77 , 87 , 88 ], the determination of the p53 mediated gene network can lead not only to a greater understanding of tumour biology but also to design of more accurate anti-cancer therapies.…”

Section: Discussionmentioning

confidence: 99%

Understanding p53 tumour suppressor network

et al. 2021

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The mutation of TP53 gene affects half of all human cancers, resulting in impairment of the regulation of several cellular functions, including cell cycle progression and cell death in response to genotoxic stress. In the recent years additional p53-mediated tumour suppression mechanisms have been described, questioning the contribution of its canonical pathway for tumour suppression. These include regulation of alternative cell death modalities (i.e. ferroptosis), cell metabolism and the emerging role in RNA stability. Here we briefly summarize our knowledge on p53 “canonical DNA damage response” and discuss the most relevant recent findings describing potential mechanistic explanation of p53-mediated tumour suppression.

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“…Phylogenetic tree reconstruction is a principled way to identify subpopulations in a heterogeneous single-cell population. This in turn enables the use of population genetics models that track the abundance of subpopulations over multiple timepoints [5] and to make inferences about the evolutionary forces acting on each clone. Further study with timeseries modelling will provide insight into therapeutic strategies promoting early intervention, drug combinations and evolution-aware approaches to clinical management.…”

Section: Discussionmentioning

confidence: 99%

“…Phylogenetic reconstruction is central to identifying clones in longitudinal xenoengraftment [5,6] as well as patients [7], and has been used to approximate the rate and timing of mutation [8] to determine the origins and clonality of metastasis [9,10]. Single cell cancer phylogenetics is an evolving field.…”

Section: Introductionmentioning

confidence: 99%

Cancer phylogenetic tree inference at scale from 1000s of single cell genomes

Dorri

Salehi²,

Chern³

et al. 2020

Preprint

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A new generation of scalable single cell whole genome sequencing (scWGS) methods [Zahn et al., 2017, Laks et al., 2019, allows unprecedented high resolution measurement of the evolutionary dynamics of cancer cells populations. Phylogenetic reconstruction is central to identifying sub-populations and distinguishing mutational processes. The ability to sequence tens of thousands of single genomes at high resolution per experiment [Laks et al., 2019] is challenging the assumptions and scalability of existing phylogenetic tree building methods and calls for tailored phylogenetic models and scalable inference algorithms. We propose a phylogenetic model and associated Bayesian inference procedure which exploits the specifics of scWGS data. A first highlight of our approach is a novel phylogenetic encoding of copy-number data providing an attractive statistical-computational trade-off by simplifying the site dependencies induced by rearrangements while still forming a sound foundation to phylogenetic inference. A second highlight is an innovative phylogenetic tree exploration move which makes the cost of MCMC iterations bounded by O(|C| + |L|), where |C| is the number of cells and |L| is the number of loci. In contrast, existing off-the-shelf likelihood-based methods incur iteration cost of O(|C| |L|). Moreover, the novel move considers an exponential number of neighbouring trees whereas offthe-shelf moves consider a polynomial size set of neighbours. The third highlight is a novel * Equal contribution 1 mutation calling method that incorporates the copy-number data and the underlying phylogenetic tree to overcome the missing data issue. This framework allows us to realistically consider routine Bayesian phylogenetic inference at the scale of scWGS data.

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Clonal fitness inferred from time-series modelling of single-cell cancer genomes

Cited by 96 publications

References 53 publications

TP53 loss initiates chromosomal instability in fallopian tube epithelial cells

TP53 loss initiates chromosomal instability in fallopian tube epithelial cells

Understanding p53 tumour suppressor network

Cancer phylogenetic tree inference at scale from 1000s of single cell genomes

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