Abstract
Along the transformation process, cells accumulate DNA aberrations, including mutations, translocations, amplifications, and deletions. Despite numerous studies, the overall effects of amplifications and deletions on the end point of gene expression—the level of proteins—is generally unknown. Here we use large-scale and high-resolution proteomics combined with gene copy number analysis to investigate in a global manner to what extent these genomic changes have a proteomic output and therefore the ability to affect cellular transformation. We accurately measure expression levels of 6,735 proteins and directly compare them to the gene copy number. We find that the average effect of these alterations on the protein expression is only a few percent. Nevertheless, by using a novel algorithm, we find the combined impact that many of these regional chromosomal aberrations have at the protein level. We show that proteins encoded by amplified oncogenes are often overexpressed, while adjacent amplified genes, which presumably do not promote growth and survival, are attenuated. Furthermore, regulation of biological processes and molecular complexes is independent of general copy number changes. By connecting the primary genome alteration to their proteomic consequences, this approach helps to interpret the data from large-scale cancer genomics efforts.
Highlights
Chromosomal aberrations are a hallmark of cancer cells
We conclude that with high coverage of the proteome and high quantification accuracy, multiple chromosomal aberrations can be predicted directly from the proteomic data
Proteomics can determine which genes in an amplified region are expressed at all and which are changing at the endpoint of the gene expression cascade – the level of the proteins
Summary
Chromosomal aberrations are a hallmark of cancer cells. During transformation cells lose cell-cycle control and fidelity of DNA replication causing multiple changes in DNA copy numbers [1,2]. Technological developments in recent years have allowed high resolution genomic analysis using SNP arrays, and large scale projects have mapped the gene copy number changes in thousands of tumor samples [5,6] Another major step necessary for the interpretation of the biological significance of such studies that is missing so far is the analysis of the consequences of these alterations: to what extent they affect protein expression. Recent advances in SILAC-based proteomics using high resolution mass spectrometry [16,17] enabled accurate proteome coverage of the complete yeast proteome [18] and large proportions of the mammalian proteome [19] Based on these developments, we could compare cancer cell lines containing multiple chromosomal alterations and normal diploid epithelial
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