Unscrambling cancer genomes via integrated analysis of structural variation and copy number
Charles Shale,
Daniel L. Cameron,
Jonathan Baber,
Marie Wong,
Mark J. Cowley,
Anthony T. Papenfuss,
Edwin Cuppen,
Peter Priestley
Affiliations
Charles Shale
Hartwig Medical Foundation Australia, Sydney, NSW, Australia; Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands
Daniel L. Cameron
Hartwig Medical Foundation Australia, Sydney, NSW, Australia; Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia
Jonathan Baber
Hartwig Medical Foundation Australia, Sydney, NSW, Australia; Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands
Marie Wong
Children’s Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia; School of Women’s and Children’s Health, UNSW Sydney, Kensington, NSW, Australia
Mark J. Cowley
Children’s Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia; School of Women’s and Children’s Health, UNSW Sydney, Kensington, NSW, Australia
Anthony T. Papenfuss
Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia; Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia; Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
Edwin Cuppen
Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands; Center for Molecular Medicine and Oncode Institute, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, the Netherlands
Peter Priestley
Hartwig Medical Foundation Australia, Sydney, NSW, Australia; Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands; Corresponding author
Summary: Complex somatic genomic rearrangements and copy number alterations are hallmarks of nearly all cancers. We have developed an algorithm, LINX, to aid interpretation of structural variant and copy number data derived from short-read, whole-genome sequencing. LINX classifies raw structural variant calls into distinct events and predicts their effect on the local structure of the derivative chromosome and the functional impact on affected genes. Visualizations facilitate further investigation of complex rearrangements. LINX allows insights into a diverse range of structural variation events and can reliably detect pathogenic rearrangements, including gene fusions, immunoglobulin enhancer rearrangements, intragenic deletions, and duplications. Uniquely, LINX also predicts chained fusions that we demonstrate account for 13% of clinically relevant oncogenic fusions. LINX also reports a class of inactivation events that we term homozygous disruptions that may be a driver mutation in up to 9% of tumors and may frequently affect PTEN, TP53, and RB1.
