Rapid proteomic analysis for solid tumors reveals LSD1 as a drug target in an end-stage cancer patient.

Recent advances in mass spectrometry (MS)-based technologies are now set to transform translational cancer proteomics from an idea to a practice. Here, we present a robust proteomic workflow for the analysis of clinically relevant human cancer tissues that allows quantitation of thousands of tumor proteins in several hours of measuring time and a total turnaround of a few days. We applied it to a chemorefractory metastatic case of the extremely rare urachal carcinoma. Quantitative comparison of lung metastases and surrounding tissue revealed several significantly upregulated proteins, among them lysine-specific histone demethylase 1 (LSD1/KDM1A). LSD1 is an epigenetic regulator and the target of active development efforts in oncology. Thus, clinical cancer proteomics can rapidly and efficiently identify actionable therapeutic options. While currently described for a single case study, we envision that it can be applied broadly to other patients in a similar condition.

Arginine-rhamnosylation as new strategy to activate translation elongation factor P.

Ribosome stalling at polyproline stretches is common and fundamental. In bacteria, translation elongation factor P (EF-P) rescues such stalled ribosomes, but only when it is post-translationally activated. In Escherichia coli, activation of EF-P is achieved by (R)-ß-lysinylation and hydroxylation of a conserved lysine. Here we have unveiled a markedly different modification strategy in which a conserved arginine of EF-P is rhamnosylated by a glycosyltransferase (EarP) using dTDP-L-rhamnose as a substrate. This is to our knowledge the first report of N-linked protein glycosylation on arginine in bacteria and the first example in which a glycosylated side chain of a translation elongation factor is essential for function. Arginine-rhamnosylation of EF-P also occurs in clinically relevant bacteria such as Pseudomonas aeruginosa. We demonstrate that the modification is needed to develop pathogenicity, making EarP and dTDP-L-rhamnose-biosynthesizing enzymes ideal targets for antibiotic development.

Quantitative proteomic assessment of very early cellular signaling events.

Technical limitations have prevented proteomic analyses of events occurring less than 30 s after signal initiation. We developed an automated, continuous quench-flow system allowing quantitative proteomic assessment of very early cellular signaling events (qPACE) with a time resolution of 1 s. Using this technique, we determined that autophosphorylation of the epidermal growth factor receptor occurs within 1 s after ligand stimulation and is followed rapidly by phosphorylation of the downstream signaling intermediates Src homologous and collagen-like protein and phospholipase C gamma 1.

Mass spectrometric-based approaches in quantitative proteomics.

Classically, experiments aimed at studying changes in protein expression have always followed a small set of proteins. This focused approach was necessary since tools to efficiently analyze large numbers of proteins were simply not available. Large-scale quantitative proteomics promises to produce reams of data that previously would have taken decades to measure with classical methods. Mass spectrometry is already a well-established protein identification tool and recent methodological developments indicate that it can also be successfully applied to extract quantitative data of protein abundance. From the first reports 4 years ago, numerous schemes to take advantage of stable isotope nuclei incorporation in proteins and peptides have been developed. Here we review the benefits and pitfalls of some of the most commonly used protocols, focusing on a procedure now being used extensively in our laboratory, stable isotope labeling with amino acids in cell culture (SILAC). The basic theory, application, and data analysis of a SILAC experiment are discussed. The emerging nature of these techniques and the rapid pace of technological development make forecasting the directions of the field difficult but we speculate that SILAC will soon be a key tool of quantitative proteomics.