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Gupta, Aditya; Michael Place; Steven Goldstein; Deepayan Sarkar; Shiguo Zhou; Konstantinos Potamousis; Jaehyup Kim; Claire Flanagan; Yang Li; Michael A. Newton; Natalie S. Callander; Peiman Hematti; Emery H. Bresnick; Jian Ma; Fotis Asimakopoulos; David C. Schwartz
Proceedings of the National Academy of Sciences - PNAS, 06/2015, Letnik: 112, Številka: 25Journal Article
Multiple myeloma (MM), a malignancy of plasma cells, is characterized by widespread genomic heterogeneity and, consequently, differences in disease progression and drug response. Although recent large-scale sequencing studies have greatly improved our understanding of MM genomes, our knowledge about genomic structural variation in MM is attenuated due to the limitations of commonly used sequencing approaches. In this study, we present the application of optical mapping, a single-molecule, whole-genome analysis system, to discover new structural variants in a primary MM genome. Through our analysis, we have identified and characterized widespread structural variation in this tumor genome. Additionally, we describe our efforts toward comprehensive characterization of genome structure and variation by integrating our findings from optical mapping with those from DNA sequencing-based genomic analysis. Finally, by studying this MM genome at two time points during tumor progression, we have demonstrated an increase in mutational burden with tumor progression at all length scales of variation. Significance In the last several years, we have seen significant progress toward personalized cancer genomics and therapy. Although we routinely discern and understand genomic variation at single base pair and chromosomal levels, comprehensive analysis of genome variation, particularly structural variation, remains a challenge. We present an integrated approach using optical mappingâa single-molecule, whole-genome analysis systemâand DNA sequencing to comprehensively identify genomic structural variation in sequential samples from a multiple myeloma patient. Through our analysis, we have identified widespread structural variation and an increase in mutational burden with tumor progression. Our findings highlight the need to routinely incorporate structural variation analysis at many length scales to understand cancer genomes more comprehensively.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Vir: Osebne bibliografije
in: SICRIS
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