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AmpliconReconstructor integrates NGS and optical mapping to resolve the complex structures of focal amplifications

Oncogene amplification, a major driver of cancer pathogenicity, is often mediated through focal amplification of genomic segments. Recent results implicate extrachromosomal DNA (ecDNA) as the primary driver of focal copy number amplification (fCNA) - enabling gene amplification, rapid tumor evolutio...

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Detalles Bibliográficos
Autores principales: Luebeck, Jens, Coruh, Ceyda, Dehkordi, Siavash R., Lange, Joshua T., Turner, Kristen M., Deshpande, Viraj, Pai, Dave A., Zhang, Chao, Rajkumar, Utkrisht, Law, Julie A., Mischel, Paul S., Bafna, Vineet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7463033/
https://www.ncbi.nlm.nih.gov/pubmed/32873787
http://dx.doi.org/10.1038/s41467-020-18099-z
Descripción
Sumario:Oncogene amplification, a major driver of cancer pathogenicity, is often mediated through focal amplification of genomic segments. Recent results implicate extrachromosomal DNA (ecDNA) as the primary driver of focal copy number amplification (fCNA) - enabling gene amplification, rapid tumor evolution, and the rewiring of regulatory circuitry. Resolving an fCNA’s structure is a first step in deciphering the mechanisms of its genesis and the fCNA’s subsequent biological consequences. We introduce a computational method, AmpliconReconstructor (AR), for integrating optical mapping (OM) of long DNA fragments (>150 kb) with next-generation sequencing (NGS) to resolve fCNAs at single-nucleotide resolution. AR uses an NGS-derived breakpoint graph alongside OM scaffolds to produce high-fidelity reconstructions. After validating its performance through multiple simulation strategies, AR reconstructed fCNAs in seven cancer cell lines to reveal the complex architecture of ecDNA, a breakage-fusion-bridge and other complex rearrangements. By reconstructing the rearrangement signatures associated with an fCNA’s generative mechanism, AR enables a more thorough understanding of the origins of fCNAs.