Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gene expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying this method to 16,172 patient-derived tumor samples, we replicated many loci with aberrant copy numbers and identified recurrently disrupted genes in genomically unstable cancers.
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We thank J.L. Senior for editing the manuscript. This work was financially supported by grants from the Netherlands Organization for Scientific Research (NWO-VENI grant 916-10135 to L.F., NWO VIDI grant 916-76062 to M.A.T.M.v.V. and NWO VIDI grant 917-14374 to L.F.), a Horizon Breakthrough grant from the Netherlands Genomics Initiative (grant 92519031 to L.F.), a grant from the Van der Meer–Boerema Foundation to M.K. and grants from the Dutch Cancer Society (RUG 2011-5093 to M.A.T.M.v.V. and RUG 2013-5960 to R.S.N.F.). In addition, this study was financed in part by the SIA-raakPRO subsidy for project BioCOMP. The research leading to these results has received funding from the European Community's Health Seventh Framework Programme (FP7/2007–2013) under grant agreement 259867. This publication was made possible through the support of a grant from the John Templeton Foundation. Additional support for E.A.S. was provided by the Leiden Centre for Data Sciences.
Predicted frequencies of increased signals. For each individual gene, the percentage of samples with a significantly increased signal was quantified across 41 tumor types.
Predicted frequencies of decreased signals. For each individual gene, the percentage of samples with a significantly decreased signal was quantified across 41 tumor types.
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The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome
Molecular Aspects of Medicine (2019)