001     153601
005     20240320151820.0
024 7 _ |a 10.1038/s41586-019-1907-7
|2 doi
024 7 _ |a pmid:32025013
|2 pmid
024 7 _ |a 0028-0836
|2 ISSN
024 7 _ |a 1476-4687
|2 ISSN
024 7 _ |a altmetric:75075728
|2 altmetric
037 _ _ |a DKFZ-2020-00345
041 _ _ |a eng
082 _ _ |a 500
100 1 _ |a Gerstung, Moritz
|b 0
245 _ _ |a The evolutionary history of 2,658 cancers.
260 _ _ |a London [u.a.]
|c 2020
|b Nature Publ. Group52462
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1710944072_4145
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a siehe Correction: DKFZ Autoren affiliiert im PCAWG Consortium: https://inrepo02.dkfz.de/record/212474 / https://doi.org/10.1038/s41586-022-05601-4
520 _ _ |a Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.
536 _ _ |a 312 - Functional and structural genomics (POF3-312)
|0 G:(DE-HGF)POF3-312
|c POF3-312
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed,
700 1 _ |a Jolly, Clemency
|b 1
700 1 _ |a Leshchiner, Ignaty
|b 2
700 1 _ |a Dentro, Stefan
|b 3
700 1 _ |a Gonzalez, Santiago
|b 4
700 1 _ |a Rosebrock, Daniel
|b 5
700 1 _ |a Mitchell, Thomas J
|b 6
700 1 _ |a Rubanova, Yulia
|b 7
700 1 _ |a Anur, Pavana
|b 8
700 1 _ |a Yu, Kaixian
|b 9
700 1 _ |a Tarabichi, Maxime
|b 10
700 1 _ |a Deshwar, Amit
|b 11
700 1 _ |a Wintersinger, Jeff
|b 12
700 1 _ |a Kleinheinz, Kortine
|0 P:(DE-He78)e053817bc90becc8a8dd8250e677e773
|b 13
700 1 _ |a Vázquez-García, Ignacio
|b 14
700 1 _ |a Haase, Kerstin
|b 15
700 1 _ |a Jerman, Lara
|b 16
700 1 _ |a Sengupta, Subhajit
|b 17
700 1 _ |a Macintyre, Geoff
|b 18
700 1 _ |a Malikic, Salem
|b 19
700 1 _ |a Donmez, Nilgun
|b 20
700 1 _ |a Livitz, Dimitri G
|b 21
700 1 _ |a Cmero, Marek
|b 22
700 1 _ |a Demeulemeester, Jonas
|b 23
700 1 _ |a Schumacher, Steven
|b 24
700 1 _ |a Fan, Yu
|b 25
700 1 _ |a Yao, Xiaotong
|b 26
700 1 _ |a Lee, Juhee
|b 27
700 1 _ |a Schlesner, Matthias
|0 P:(DE-He78)f2a782242acf94a3114d75c45dc75b37
|b 28
700 1 _ |a Boutros, Paul C
|b 29
700 1 _ |a Bowtell, David D
|b 30
700 1 _ |a Zhu, Hongtu
|b 31
700 1 _ |a Getz, Gad
|b 32
700 1 _ |a Imielinski, Marcin
|b 33
700 1 _ |a Beroukhim, Rameen
|b 34
700 1 _ |a Sahinalp, S Cenk
|b 35
700 1 _ |a Ji, Yuan
|b 36
700 1 _ |a Peifer, Martin
|b 37
700 1 _ |a Markowetz, Florian
|b 38
700 1 _ |a Mustonen, Ville
|b 39
700 1 _ |a Yuan, Ke
|b 40
700 1 _ |a Wang, Wenyi
|b 41
700 1 _ |a Morris, Quaid D
|b 42
700 1 _ |a PCAWGEvolution&HeterogeneityWorkingGroup
|0 P:(DE-HGF)0
|b 43
700 1 _ |a Spellman, Paul T
|b 44
700 1 _ |a Wedge, David C
|b 45
700 1 _ |a Van Loo, Peter
|b 46
700 1 _ |a PCAWGConsortium
|0 P:(DE-HGF)0
|b 47
773 _ _ |a 10.1038/s41586-019-1907-7
|g Vol. 578, no. 7793, p. 122 - 128
|0 PERI:(DE-600)1413423-8
|n 7793
|p 122 - 128
|t Nature
|v 578
|y 2020
|x 1476-4687
909 C O |p VDB
|o oai:inrepo02.dkfz.de:153601
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 13
|6 P:(DE-He78)e053817bc90becc8a8dd8250e677e773
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 28
|6 P:(DE-He78)f2a782242acf94a3114d75c45dc75b37
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF3-310
|0 G:(DE-HGF)POF3-312
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-300
|4 G:(DE-HGF)POF
|v Functional and structural genomics
|x 0
914 1 _ |y 2020
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b NATURE : 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1040
|2 StatID
|b Zoological Record
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a IF >= 40
|0 StatID:(DE-HGF)9940
|2 StatID
|b NATURE : 2017
920 1 _ |0 I:(DE-He78)B080-20160331
|k B080
|l Theoretische Bioinformatik
|x 0
920 1 _ |0 I:(DE-He78)B240-20160331
|k B240
|l Bioinformatik und Omics Data Analytics
|x 1
920 1 _ |0 I:(DE-He78)B370-20160331
|k B370
|l Epigenomik
|x 2
920 1 _ |0 I:(DE-He78)B330-20160331
|k B330
|l Angewandte Bioinformatik
|x 3
920 1 _ |0 I:(DE-He78)HD01-20160331
|k HD01
|l DKTK HD zentral
|x 4
920 1 _ |0 I:(DE-He78)B060-20160331
|k B060
|l B060 Molekulare Genetik
|x 5
920 1 _ |0 I:(DE-He78)B360-20160331
|k B360
|l Pädiatrische Gliomforschung
|x 6
920 1 _ |0 I:(DE-He78)BE01-20160331
|k BE01
|l DKTK Koordinierungsstelle Berlin
|x 7
920 1 _ |0 I:(DE-He78)B062-20160331
|k B062
|l B062 Pädiatrische Neuroonkologie
|x 8
920 1 _ |0 I:(DE-He78)B066-20160331
|k B066
|l B066 Chromatin-Netzwerke
|x 9
920 1 _ |0 I:(DE-He78)B063-20160331
|k B063
|l B063 Krebsgenomforschung
|x 10
920 1 _ |0 I:(DE-He78)W190-20160331
|k W190
|l Hochdurchsatz-Sequenzierung
|x 11
920 1 _ |0 I:(DE-He78)B260-20160331
|k B260
|l B260 Bioinformatik der Genomik und Systemgenetik
|x 12
920 1 _ |0 I:(DE-He78)W610-20160331
|k W610
|l Core Facility Omics IT
|x 13
920 1 _ |0 I:(DE-He78)B087-20160331
|k B087
|l B087 Neuroblastom Genomik
|x 14
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)B080-20160331
980 _ _ |a I:(DE-He78)B240-20160331
980 _ _ |a I:(DE-He78)B370-20160331
980 _ _ |a I:(DE-He78)B330-20160331
980 _ _ |a I:(DE-He78)HD01-20160331
980 _ _ |a I:(DE-He78)B060-20160331
980 _ _ |a I:(DE-He78)B360-20160331
980 _ _ |a I:(DE-He78)BE01-20160331
980 _ _ |a I:(DE-He78)B062-20160331
980 _ _ |a I:(DE-He78)B066-20160331
980 _ _ |a I:(DE-He78)B063-20160331
980 _ _ |a I:(DE-He78)W190-20160331
980 _ _ |a I:(DE-He78)B260-20160331
980 _ _ |a I:(DE-He78)W610-20160331
980 _ _ |a I:(DE-He78)B087-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21