Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing

Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing

2008 June ; 40(6): 722–729. doi:10.1038/ng.128. | Peter J Campbell, Philip J Stephens, Erin D Pleasance, Sarah O'Meara, Heng Li, Thomas Santarius, Lucy A Stebbings, Catherine Leroy, Sarah Edkins, Claire Hardy, Jon W Teague, Andrew Menzies, Ian Goodhead, Daniel J Turner, Christopher M Clee, Michael A Quail, Antony Cox, Clive Brown, Richard Durbin, Matthew E Hurles, Paul A W Edwards, Graham R Bignell, Michael R Stratton, P Andrew Futreal
This study demonstrates the feasibility of using massively parallel sequencing to identify and characterize somatic genomic rearrangements in cancer genomes. By analyzing paired-end sequencing data from two lung cancer cell lines, the authors identified 306 germline and 103 somatic rearrangements at the base-pair level. The patterns of germline and somatic rearrangements were distinct, with many somatic rearrangements occurring within or outside amplicons. The study also identified fusion transcripts and previously unreported patterns of somatic rearrangement, such as tandem duplications. The high-resolution data provided insights into the genomic architecture of complex amplicons and the evolution of cancer genomes. The results highlight the potential of this approach to uncover novel genes and mechanisms involved in cancer development.This study demonstrates the feasibility of using massively parallel sequencing to identify and characterize somatic genomic rearrangements in cancer genomes. By analyzing paired-end sequencing data from two lung cancer cell lines, the authors identified 306 germline and 103 somatic rearrangements at the base-pair level. The patterns of germline and somatic rearrangements were distinct, with many somatic rearrangements occurring within or outside amplicons. The study also identified fusion transcripts and previously unreported patterns of somatic rearrangement, such as tandem duplications. The high-resolution data provided insights into the genomic architecture of complex amplicons and the evolution of cancer genomes. The results highlight the potential of this approach to uncover novel genes and mechanisms involved in cancer development.
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