2019
DOI: 10.1038/s41586-019-1056-z
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Genomic characterization of metastatic breast cancers

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Cited by 539 publications
(530 citation statements)
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References 57 publications
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“…For instance, metastases have been reported to originate from a single cell or clone in the primary tumor (monoclonal seeding) [1][2][3][4] or multiple clones (polyclonal seeding) [5][6][7] , but the prevalence of these patterns across distinct tumor types is unknown as is the impact of therapy and the timing of metastatic seeding [8][9][10] . While several recent studies have genomically characterized metastatic lesions [11][12][13] in the absence of the matched primary tumor, it is not feasible to disentangle the drivers of metastasis from those that are treatment associated since metastases are often sampled after treatment. However, comparisons of paired primary tumors and metastases have been far more limited due to the challenge in obtaining such samples 5,8,[14][15][16][17][18] .…”
Section: Introductionmentioning
confidence: 99%
“…For instance, metastases have been reported to originate from a single cell or clone in the primary tumor (monoclonal seeding) [1][2][3][4] or multiple clones (polyclonal seeding) [5][6][7] , but the prevalence of these patterns across distinct tumor types is unknown as is the impact of therapy and the timing of metastatic seeding [8][9][10] . While several recent studies have genomically characterized metastatic lesions [11][12][13] in the absence of the matched primary tumor, it is not feasible to disentangle the drivers of metastasis from those that are treatment associated since metastases are often sampled after treatment. However, comparisons of paired primary tumors and metastases have been far more limited due to the challenge in obtaining such samples 5,8,[14][15][16][17][18] .…”
Section: Introductionmentioning
confidence: 99%
“…The involvement of DNA repair might also explain why tumors deficient in the p53 DNA damage checkpoint regulatory pathway accumulate more 5-FU mutations, as shown here for the first time. Interestingly, breast tumors with high contribution of Signature 17 mutations were recently shown to have poor prognosis (Bertucci et al 2019).…”
Section: Discussionmentioning
confidence: 99%
“…The motivation for the present work originates from the work of the Raphael Lab, centred around the Dendrix algorithm [23], and its later improvements including CoMEt [9]. Both algorithms are in widespread use in whole-genome analysis-for instance, in [16,17,4,20]. Building on those foundations, our work extends in the following two directions: First, the two key notions of exclusivity and coverage are abstracted here by the two simplicial complexes K ε and K η or, more precisely, by the filtrations of simplicial complexes K ε 0 ⊂ · · · ⊂ K ε and K η 0 ⊂ · · · ⊂ K η , where we allow the two parameters to vary: ε 0 ≤ ε ≤ ε and η 0 ≤ η ≤ η .…”
Section: Related Workmentioning
confidence: 99%
“…The dimensions β i := dim(H i (K)) are called Betti numbers and provide the formal description of the concept of shape measurements. 4 We move now to the notion of persistent homology and make it a bit more precise. For that, let us reintroduce the persistent parameter ε and let K ε be again an independence complex.…”
Section: A Primer On Persistent Homologymentioning
confidence: 99%
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