Aneuploidies, defined as whole-arm or whole-chromosome imbalances, are the most prevalent alteration in cancer genomes. However, the extent to which they are enriched due to selection is unclear, against the alternative hypothesis that they are passenger events that are simply highly prone to occur. We developed a novel method, BrISCUT, that identifies loci under selective advantage or disadvantage due to arm-level copy-number alterations by interrogating length distributions of events that are bounded at either the telomere or centromere. These loci were significantly enriched for known cancer driver genes, including genes not detected through analysis of focal copy-number events, and were often lineage-specific. We also formally quantified the role of selection and mechanistic biases in driving aneuploidy, finding that rates of arm-level SCNAs are most highly correlated with selective pressures. These results provide insight into the causes of aneuploidies and their contributions to tumorigenesis.
Yes there is potential Competing Interest. Galen F. Gao, Ashton C. Berger, Andrew D. Cherniack, and Matthew Meyerson receive or received research support from Bayer AG. Matthew Meyerson and Alison M. Taylor receive research support from Ono Pharmaceutical. Matthew Meyerson is an equity holder, consultant for, and Scientific Advisory Board chair for OrigiMed. Matthew Meyerson additionally receives research support from Novo Nordisk and Janssen Pharmaceuticals, consults for Interline Therapeutics, and is an inventor of a patent for EGFR mutation diagnosis in lung cancer, licensed to Labcorp. Rameen Beroukhim consults for and owns equity in Scorpion Therapeutics and receives research support from Merck & Co. and Novartis.
This is a list of supplementary files associated with this preprint. Click to download.
Extended Data Table 1
Extended Data Table 2
Extended Data Table 3
Extended Data Table 4
Extended Data Table 5
Extended Data Figure 1
Extended Data Figure 2
Extended Data Figure 3
Extended Data Figure 4
Extended Data Figure 5
Extended Data Figure 6
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Posted 26 May, 2021
Posted 26 May, 2021
Aneuploidies, defined as whole-arm or whole-chromosome imbalances, are the most prevalent alteration in cancer genomes. However, the extent to which they are enriched due to selection is unclear, against the alternative hypothesis that they are passenger events that are simply highly prone to occur. We developed a novel method, BrISCUT, that identifies loci under selective advantage or disadvantage due to arm-level copy-number alterations by interrogating length distributions of events that are bounded at either the telomere or centromere. These loci were significantly enriched for known cancer driver genes, including genes not detected through analysis of focal copy-number events, and were often lineage-specific. We also formally quantified the role of selection and mechanistic biases in driving aneuploidy, finding that rates of arm-level SCNAs are most highly correlated with selective pressures. These results provide insight into the causes of aneuploidies and their contributions to tumorigenesis.
Yes there is potential Competing Interest. Galen F. Gao, Ashton C. Berger, Andrew D. Cherniack, and Matthew Meyerson receive or received research support from Bayer AG. Matthew Meyerson and Alison M. Taylor receive research support from Ono Pharmaceutical. Matthew Meyerson is an equity holder, consultant for, and Scientific Advisory Board chair for OrigiMed. Matthew Meyerson additionally receives research support from Novo Nordisk and Janssen Pharmaceuticals, consults for Interline Therapeutics, and is an inventor of a patent for EGFR mutation diagnosis in lung cancer, licensed to Labcorp. Rameen Beroukhim consults for and owns equity in Scorpion Therapeutics and receives research support from Merck & Co. and Novartis.
This is a list of supplementary files associated with this preprint. Click to download.
Extended Data Table 1
Extended Data Table 2
Extended Data Table 3
Extended Data Table 4
Extended Data Table 5
Extended Data Figure 1
Extended Data Figure 2
Extended Data Figure 3
Extended Data Figure 4
Extended Data Figure 5
Extended Data Figure 6
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