Synapse - Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig

Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig Journal Article

Authors:	Rubanova, Y.; Shi, R.; Harrigan, C. F.; Li, R.; Wintersinger, J.; Sahin, N.; Deshwar, A.; PCAWG Evolution and Heterogeneity Working Group; Morris, Q.; & PCAWG Consortium
Contributors:	Vázquez-García, I.; Abeshouse, A.; Al-Ahmadie, H.; Armenia, J.; Chen, H. W.; Davidson, N. R.; Gao, J.; Ghossein, R.; Giri, D. D.; Gundem, G.; Heins, Z.; Huse, J.; Iacobuzio-Donahue, C. A.; Kahles, A.; King, T. A.; Kundra, R.; Lehmann, K. V.; Levine, D. A.; Liu, E. M.; Ochoa, A.; Pastore, A.; Rätsch, G.; Reis-Filho, J.; Reuter, V.; Roehrl, M. H. A.; Sanchez-Vega, F.; Sander, C.; Schultz, N.; Senbabaoglu, Y.; Singer, S.; Socci, N. D.; Stark, S. G.; Yellapantula, V. D.; Zhang, H.
Article Title:	Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig
Abstract:	The type and genomic context of cancer mutations depend on their causes. These causes have been characterized using signatures that represent mutation types that co-occur in the same tumours. However, it remains unclear how mutation processes change during cancer evolution due to the lack of reliable methods to reconstruct evolutionary trajectories of mutational signature activity. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we present TrackSig, a new method that reconstructs these trajectories using optimal, joint segmentation and deconvolution of mutation type and allele frequencies from a single tumour sample. In simulations, we find TrackSig has a 3–5% activity reconstruction error, and 12% false detection rate. It outperforms an aggressive baseline in situations with branching evolution, CNA gain, and neutral mutations. Applied to data from 2658 tumours and 38 cancer types, TrackSig permits pan-cancer insight into evolutionary changes in mutational processes. © 2020, The Author(s).
Keywords:	mutation; genomics; reconstruction; trajectory; cancer
Journal Title:	Nature Communications
Volume:	11
ISSN:	2041-1723
Publisher:	Nature Publishing Group
Date Published:	2020-02-05
Start Page:	731
Language:	English
DOI:	10.1038/s41467-020-14352-7
PUBMED:	32024834
PROVIDER:	scopus
PMCID:	PMC7002414
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079071600&doi=10.1038%2fs41467-020-14352-7&partnerID=40&md5=6c0f1b2948d12983c08651dc3b3f5354
Notes:	Article -- Erratum issued, see DOI: 10.1038/s41467-022-32336-7 -- Export Date: 2 March 2020 -- Source: Scopus