What a great idea for a study, and what interesting results!
We're almost always going after the plasma and serum -- and we all know how much that sucks. 11 orders of magnitude dynamic range? And just about everything is glycosylated? Blech. Some recent studies have shown that there is lots to learn in the cellular blood components -- even in boring old RBCs.
This group goes after another somewhat neglected cell type in our blood stream -- the platelets -- and they study them in people with/without cancer and post tumor removal (!!)
The proteome still appears pretty complex in these cells because they use 1D-gels to simplify the proteins before digesting and running the samples on a NanoESI-Q Exactive. The data is processed in MaxQuant.
A curious decision was made at this point in the data processing. I'm not being critical at all -- the downstream stats and bioinformatics look top notch to me -- but instead of using the XIC extraction and normalization capabilities that are present in MaxQuant and Perseus the group appears to work with spectral counting.
It obviously works for these authors! The downstream pipeline is rock solid and the output heatmaps and pathway representation is as nice as anything I've ever seen.
The platelet proteome is demonstrated to be really complex -- and patients with early stage cancer (n=11!) have some really profound differences in their platelet proteins compared to healthy controls. This looks like an absolute gold mine for potential early cancer detection markers!!
All of the RAW data has been deposited to PRIDE/ProteomeXchange via PXD005921. It hasn't been made activated for download, but I just pinged them to see if it could be. Slackers...the paper officially publishes...April 15th...2018....
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