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. Author manuscript; available in PMC: 2024 Sep 1.
Published in final edited form as: Nat Rev Genet. 2023 Nov 8;25(3):196–210. doi: 10.1038/s41576-023-00663-0

Table 1.

Pan-cancer analyses of chromothripsis

Study Methods of detection Algorithms of detection Sources Samples n Cancer types n Estimated frequency Associated oncogene amplifications Associated loss of suppressors
Cortes-Ciriano et al., Nat Genet 2020-Ref.33 WGS ShatterSeq PCAWG 2,658 38 40–60% 20% 2%
Voronina et al., Nat Commun 2020-Ref.35 WGS, WES ShatterSeq NCT/DKTK MASTER 634 28 49% Examples identified, % not reported
Rasnic and Linial, Cancers 2021-Ref.36 CNA ML based on ShatterSeq TCGA 10,728 20 39% Examples identified, % not reported
Steele et al., Nature 2022-Ref.37 WGS, WES, SNP6 profiling NA TCGA PCAWG 9,873 33 NA, 5 signatures of chromothripsis Examples identified, % not reported
Bao et al., Nat Cancer 2022-Ref.38 WGS Starfish PCAWG 2,428 37 53%, 6 CGR signatures Examples identified, % not reported

WGS: whole genome sequencing; WES: whole exome sequencing; CNA: copy number alteration; SNP6: single nucleotide polymorphism (SNP) 6.0 microarrays; ML: machine learning; PCAWG: Pan-Cancer Analysis of Whole Genomes; NCT/DKTK MASTER program: Molecularly Aided Stratification for Tumour Eradication; TCGA: The Cancer Genome Atlas; CGR: Complex genomic rearrangements, NA: not available.