Journal Article

DKFZ-2022-01626

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Inferring structural variant cancer cell fraction.

Cmero, M. ; Yuan, K. ; Ong, C. S. ; Schröder, J. ; PCAWG, E. ; Heterogeneity Working, G. ; Corcoran, N. M. ; Papenfuss, T. ; Hovens, C. M. ; Markowetz, F. ; Macintyre, G. ; PCAWGConsortium

2020
Nature Publishing Group UK [London]

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Please use a persistent id in citations: doi:10.1038/s41467-020-14351-8

Abstract: We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines the variant allele frequencies of both SV breakends, then simultaneously estimates the cancer cell fraction and SV copy number. We assess performance using in silico mixtures of real samples, at known proportions, created from two clonal metastases from the same patient. We find that SVclone's performance is comparable to single-nucleotide variant-based methods, despite having an order of magnitude fewer data points. As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we use SVclone to reveal a subset of liver, ovarian and pancreatic cancers with subclonally enriched copy-number neutral rearrangements that show decreased overall survival. SVclone enables improved characterisation of SV intra-tumour heterogeneity.

Keyword(s): Algorithms (MeSH) ; Computational Biology: methods (MeSH) ; Computer Simulation (MeSH) ; DNA Copy Number Variations (MeSH) ; Female (MeSH) ; Gene Frequency (MeSH) ; Genome, Human (MeSH) ; Humans (MeSH) ; Liver Neoplasms: genetics (MeSH) ; Liver Neoplasms: pathology (MeSH) ; Male (MeSH) ; Neoplasms: genetics (MeSH) ; Neoplasms: pathology (MeSH) ; Ovarian Neoplasms: genetics (MeSH) ; Ovarian Neoplasms: pathology (MeSH) ; Pancreatic Neoplasms: genetics (MeSH) ; Pancreatic Neoplasms: pathology (MeSH) ; Prostatic Neoplasms: genetics (MeSH) ; Prostatic Neoplasms: pathology (MeSH) ; Sensitivity and Specificity (MeSH) ; Whole Genome Sequencing (MeSH)

Note: siehe Correction: DKFZ Autoren affiliiert im PCAWG Consortium:https://inrepo02.dkfz.de/record/212436 / https://doi.org/10.1038/s41467-022-32338-5

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Contributing Institute(s):

1. Theoretische Bioinformatik (B080)
2. Bioinformatik und Omics Data Analytics (B240)
3. Epigenomik (B370)
4. Angewandte Bioinformatik (B330)
5. DKTK HD zentral (HD01)
6. B060 Molekulare Genetik (B060)
7. Pädiatrische Gliomforschung (B360)
8. DKTK Koordinierungsstelle Berlin (BE01)
9. B062 Pädiatrische Neuroonkologie (B062)
10. B066 Chromatin-Netzwerke (B066)
11. B063 Krebsgenomforschung (B063)
12. Hochdurchsatz-Sequenzierung (W190)
13. Core Facility Omics IT (W610)
14. B260 Bioinformatik der Genomik und Systemgenetik (B260)

Research Program(s):

1. 312 - Funktionelle und strukturelle Genomforschung (POF4-312) (POF4-312)

Appears in the scientific report 2020

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