Proteins in Tumor-Derived Plasma Extracellular Vesicles Indicate Tumor Origin.

Cancer-derived extracellular vesicles (EVs) promote tumorigenesis, premetastatic niche formation, and metastasis via their protein cargo. However, the proteins packaged by patient tumors into EVs cannot be determined in vivo because of the presence of EVs derived from other tissues. We therefore developed a cross-species proteomic method to quantify the human tumor-derived proteome of plasma EVs produced by patient-derived xenografts of four cancer types. Proteomic profiling revealed individualized packaging of novel protein cargo, and machine learning accurately classified the type of the underlying tumor.

ProteoSushi: A Software Tool to Biologically Annotate and Quantify Modification-Specific, Peptide-Centric Proteomics Data Sets.

Large-scale proteomic profiling of protein post-translational modifications has provided important insights into the regulation of cell signaling and disease. These modification-specific proteomics workflows nearly universally enrich modified peptides prior to mass spectrometry analysis, but protein-centric proteomic software tools have many limitations evaluating and interpreting these peptide-centric data sets. We, therefore, developed ProteoSushi, a software tool tailored to analysis of each modified site in peptide-centric proteomic data sets that is compatible with any post-translational modification or chemical label. ProteoSushi uses a unique approach to assign identified peptides to shared proteins and genes, minimizing redundancy by prioritizing shared assignments based on UniProt annotation score and optional user-supplied protein/gene lists. ProteoSushi simplifies quantitation by summing or averaging intensities for each modified site, merging overlapping peptide charge states, missed cleavages, spectral matches, and variable modifications into a single value. ProteoSushi also annotates each PTM site with the most up-to-date biological information available from UniProt, such as functional roles or known modifications, the protein domain in which the site resides, the protein's subcellular location and function, and more. ProteoSushi has a graphical user interface for ease of use. ProteoSushi's flexibility and combination of analysis features streamlines peptide-centric data processing and knowledge mining of large modification-specific proteomics data sets.

Automating Assignment, Quantitation, and Biological Annotation of Redox Proteomics Datasets with ProteoSushi.

Redox proteomics plays an increasingly important role characterizing the cellular redox state and redox signaling networks. As these datasets grow larger and identify more redox regulated sites in proteins, they provide a systems-wide characterization of redox regulation across cellular organelles and regulatory networks. However, these large proteomic datasets require substantial data processing and analysis in order to fully interpret and comprehend the biological impact of oxidative posttranslational modifications. We therefore developed ProteoSushi, a software tool to biologically annotate and quantify redox proteomics and other modification-specific proteomics datasets. ProteoSushi can be applied to differentially alkylated samples to assay overall cysteine oxidation, chemically labeled samples such as those used to profile the cysteine sulfenome, or any oxidative posttranslational modification on any residue.Here we demonstrate how to use ProteoSushi to analyze a large, public cysteine redox proteomics dataset. ProteoSushi assigns each modified peptide to shared proteins and genes, sums or averages signal intensities for each modified site of interest, and annotates each modified site with the most up-to-date biological information available from UniProt. These biological annotations include known functional roles or modifications of the site, the protein domain(s) that the site resides in, the protein's subcellular location and function, and more.