I’m so proud that this is part of the CCLE. It’s a truly special resource. I’ll tell you a little bit about how we looked at protein expression in light of other CCLE data in the paper (2/13).
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I’m thrilled to announce the publication of the quantitive proteomic profiling of the Cancer Cell Line Encyclopedia. The @GygiLab in collaboration with colleagues at Novartis and the Broad we measured the proteomes of 375 cell lines from various tumor lineages (1/13)pic.twitter.com/WXgsODMzFs
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Many biologists are interested in how well RNA and protein expression correlate. We confirmed that they have middling correlation on average (~0.5). But the scope of these data let us ask this on a per-gene level across many tissue lineages. (3/13)pic.twitter.com/pwVkp7qU8Q
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It turns out there is wide diversity, with proteins at and outside the cell membrane showing relatively high correlation between RNA and protein while nuclear proteins and those in notable complexes showed lower average correlation. (4/13)
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Perhaps the biggest surprise was that when looking at tumors derived from solid organs there was a large amount of similarity in protein expression that dominated the first component in PCA. (5/13)
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Deeper investigation revealed that the large amounts of the proteome shows correlated expression across tissues and pathways. We saw correlation between members of many pathways and gene sets like MAPK, Glycolysis, and Mitosis. (6/13pic.twitter.com/TVTGn8nZkq
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This appears to be a broad correlated organization of the proteome that transcends tissue or pathway that’ve never seen before. This is because it doesn’t happen in RNA data. What organizes that? It looks like the mechanisms of transcription. (7/13)
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Turning to cancer, we were interested in how the proteome, might change under extremely high mutation burden. We ended up focusing on a particular form of cancer called microsatellite instability (MSI) and found surprising changes in several protein complexes. (8/13)
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We have a strong interest in protein complexes in the
@GygiLab because of the@HMSBioplex project, which itself just announced an interaction map of the MSI cell line HCT116. So these efforts dovetailed nicely. (9/13)Prikaži ovu nit -
In the CCLE, we found that expected complexes like mismatch repair were downregulated in MSI, but also several unexpected including two ribosome-associated complexes, SKI and RQC, that had no previous association with MSI. (10/13)pic.twitter.com/xuQLhvvNTI
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Finding anything ribosome-associated with hypermutation was a surprise and the role of these complexes here is unknown. (11/13)
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Inspired by this we looked for consistent changes in other protein complexes associated with the sensitivity to different gene knockdowns and found such genes with associated complexes. These complexes hint at biochemical mechanisms underlying genetic sensitivity (12/13)pic.twitter.com/WC6Vpzk4bB
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There’s lots more in the paper, but we’re mostly excited to see how the community is able to use these data to advance our understanding of both cancer and basic cell biology. The data will be available with the paper, https://gygi.med.harvard.edu/publications/ccle …, and https://depmap.org (13/13)
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I probably should have put it in the first tweet, but the manuscript is available at https://www.cell.com/cell/fulltext/S0092-8674(19)31385-6 … !
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