Abstract
SummaryProtein complexes are responsible for the bulk of activities within the cell, but how their behavior and abundance varies across tumors remains poorly understood. By combining proteomic profiles of breast tumors with a large-scale protein-protein interaction network, we have identified a set of 285 high-confidence protein complexes whose subunits have highly correlated protein abundance across tumor samples. We used this set to identify complexes that are reproducibly under- or overexpressed in specific breast cancer subtypes. We found that mutation or deletion of one subunit of a co-regulated complex was often associated with a collateral reduction in protein expression of additional complex members. This collateral loss phenomenon was typically evident from proteomic, but not transcriptomic, profiles, suggesting post-transcriptional control. Mutation of the tumor suppressor E-cadherin (CDH1) was associated with a collateral loss of members of the adherens junction complex, an effect we validated using an engineered model of E-cadherin loss.
Highlights
Multi-subunit protein complexes are responsible for the bulk of the functionality of the cell (Alberts, 1998; Hartwell et al, 1999)
Using the CORUM manually curated set of human protein complexes (Ruepp et al, 2010) and 77 protein expression profiles from the Cancer Genome Atlas (TCGA) breast cancer proteomics project (Mertins et al, 2016), we assessed the relationship between the similarity of protein expression profiles and the likelihood of two proteins belonging to the same protein complex (Figure S1A)
In comparison with the correlation observed using mRNA expression profiles, protein expression profiles were more predictive of co-complex membership (Figure S1A)
Summary
Multi-subunit protein complexes are responsible for the bulk of the functionality of the cell (Alberts, 1998; Hartwell et al, 1999). Transcriptomic measurements are often used as a proxy measurement for protein expression, but most genes display only a moderate correlation between their mRNA and protein expression levels (Liu et al, 2016; Vogel and Marcotte, 2012) This correlation varies considerably between genes, with members of large protein complexes such as the ribosome and spliceosome reported to have significantly lower mRNA-protein correlation than average (Mertins et al, 2016; Zhang et al, 2016). Advances in mass spectrometry have enabled the quantification of thousands of proteins across large numbers of samples (Mertins et al, 2016; Pozniak et al, 2016; Tyanova et al, 2016) These datasets permit, for the first time, large-scale assessment of the behavior of protein complexes across different tumor samples and between different tumor types. We develop an approach to identify co-regulated protein complexes from tumor proteomic profiles and characterize the expression of these protein complexes across 77 breast tumor proteomes (Mertins et al, 2016)
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