TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data
Open Access
- 24 July 2014
- journal article
- Published by Cold Spring Harbor Laboratory in Genome Research
- Vol. 24 (11), 1881-1893
- https://doi.org/10.1101/gr.180281.114
Abstract
The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN.This publication has 37 references indexed in Scilit:
- Diverse Mechanisms of Somatic Structural Variations in Human Cancer GenomesCell, 2013
- The Life History of 21 Breast CancersCell, 2012
- Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion SequencingThe New England Journal of Medicine, 2012
- Clonal evolution in cancerNature, 2012
- Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencingNature, 2012
- Copy number variation detection in whole-genome sequencing data using the Bayesian information criterionProceedings of the National Academy of Sciences of the United States of America, 2011
- Integrated genomic analyses of ovarian carcinomaNature, 2011
- Allele-specific copy number analysis of tumorsProceedings of the National Academy of Sciences of the United States of America, 2010
- International network of cancer genome projectsNature, 2010
- Driver mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovaryThe Journal of Pathology, 2010