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Genome Res. 2014 Nov;24(11):1881-93. doi: 10.1101/gr.180281.114. Epub 2014 Jul 24.

TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.

Author information

1
Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Bioinformatics Training Program, University of British Columbia, Vancouver, BC V5Z 4S6, Canada; sshah@bccrc.ca.
2
Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Bioinformatics Training Program, University of British Columbia, Vancouver, BC V5Z 4S6, Canada;
3
Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada;
4
Centre for Translational and Applied Genomics, Vancouver, BC V5Z 4E6, Canada;
5
Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Department of Computer Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada;
6
Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada;
7
Genetic Pathology Evaluation Centre, Vancouver General Hospital, Vancouver, BC V6H 3Z6, Canada;
8
Centre for Translational and Applied Genomics, Vancouver, BC V5Z 4E6, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 2B5, Canada;
9
Department of Gynecology and Obstetrics, University of British Columbia, Vancouver, BC V5Z 1M9, Canada.
10
Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 2B5, Canada;
11
Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Department of Computer Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 2B5, Canada; sshah@bccrc.ca.

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.

PMID:
25060187
PMCID:
PMC4216928
DOI:
10.1101/gr.180281.114
[Indexed for MEDLINE]
Free PMC Article
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