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Abstract
Annotation of structural variations (SVs) and base-level karyotyping in cancer cells remains challenging. Here, we present Integrative Framework for Genome Reconstruction (InfoGenomeR)-a graph-based framework that can reconstruct individual SVs into karyotypes based on whole-genome sequencing data, by integrating SVs, total copy number alterations, allele-specific copy numbers, and haplotype information. Using whole-genome sequencing data sets of patients with breast cancer, glioblastoma multiforme, and ovarian cancer, we demonstrate the analytical potential of InfoGenomeR. We identify recurrent derivative chromosomes derived from chromosomes 11 and 17 in breast cancer samples, with homogeneously staining regions for CCND1 and ERBB2, and double minutes and breakage-fusion-bridge cycles in glioblastoma multiforme and ovarian cancer samples, respectively. Moreover, we show that InfoGenomeR can discriminate private and shared SVs between primary and metastatic cancer sites that could contribute to tumour evolution. These findings indicate that InfoGenomeR can guide targeted therapies by unravelling cancer-specific SVs on a genome-wide scale.
Karyotyping of cancer genomes at the base-level is technically challenging. Here, the authors introduce InfoGenomeR, an algorithm that can infer cancer genome karyotypes from whole-genome sequencing data, and test their model on breast, ovarian and brain cancer samples; and identify private and shared mutations between primary and metastatic cancer samples.
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