High-Definition Reconstruction of Clonal Composition in Cancer

• Published in: Cell reports (Cambridge) 2014-06, Vol.7 (5), p.1740-1752
• Main Authors: Fischer, Andrej, Vázquez-García, Ignacio, Illingworth, Christopher J.R., Mustonen, Ville
• Format: Article
• Language: English
• Subjects: Algorithms; Breast Neoplasms - genetics; Clonal Evolution; Humans; Leukemia, Lymphoid - genetics; Models, Genetic; Mutation; Resource
• ISSN: 2211-1247; 2211-1247
• DOI: 10.1016/j.celrep.2014.04.055

The extensive genetic heterogeneity of cancers can greatly affect therapy success due to the existence of subclonal mutations conferring resistance. However, the characterization of subclones in mixed-cell populations is computationally challenging due to the short length of sequence reads that are generated by current sequencing technologies. Here, we report cloneHD, a probabilistic algorithm for the performance of subclone reconstruction from data generated by high-throughput DNA sequencing: read depth, B-allele counts at germline heterozygous loci, and somatic mutation counts. The algorithm can exploit the added information present in correlated longitudinal or multiregion samples and takes into account correlations along genomes caused by events such as copy-number changes. We apply cloneHD to two case studies: a breast cancer sample and time-resolved samples of chronic lymphocytic leukemia, where we demonstrate that monitoring the response of a patient to therapy regimens is feasible. Our work provides new opportunities for tracking cancer development. [Display omitted] •Consistent reconstruction of tumor heterogeneity across samples and data types•Subclone and locus-specific estimates of copy number and mutation genotype•Efficient analysis of subclones in multiple tumor samples at moderate coverage•Demonstration of the potential for high-resolution monitoring of subclonal evolution When tumors are genetically diverse, their analysis and therapy can become very challenging. In this study, Fischer et al. present cloneHD, a computational resource for reconstructing the inner composition of a tumor. Different layers of short-read sequencing data are combined to give a coherent and high-definition view of subclonal heterogeneity in cancer. Reanalyzing a chronic lymphocytic leukemia data set, the authors demonstrate the potential of cloneHD to track tumor progression in response to therapy.