Deep Coverage of Global Protein Expression and Phosphorylation in Breast Tumor Cell Lines Using TMT 10-plex Isobaric Labeling.

Labeling peptides with isobaric tags is a popular strategy in quantitative bottom-up proteomics. In this study, we labeled six breast tumor cell lysates (1.34 mg proteins per channel) using 10-plex tandem mass tag reagents and analyzed the samples on a Q Exactive HF Quadrupole-Orbitrap mass spectrometer. We identified a total of 8,706 proteins and 28,186 phosphopeptides, including 7,394 proteins and 23,739 phosphosites common to all channels. The majority of technical replicates correlated with a R2 ≥ 0.98, indicating minimum variability was introduced after labeling. Unsupervised hierarchical clustering of phosphopeptide data sets successfully classified the breast tumor samples into Her2 (epidermal growth factor receptor 2) positive and Her2 negative groups, whereas mRNA abundance did not. The tyrosine phosphorylation levels of receptor tyrosine kinases, phosphoinositide-3-kinase, protein kinase C delta, and Src homology 2, among others, were significantly higher in the Her2 positive than the Her2 negative group. Despite ratio compression in MS2-based experiments, we demonstrated the ratios calculated using an MS2 method are highly correlated (R2 > 0.65) with ratios obtained using MS3-based quantitation (using a Thermo Orbitrap Fusion mass spectrometer) with reduced ratio suppression. Given the deep coverage of global and phosphoproteomes, our data show that MS2-based quantitation using TMT can be successfully used for large-scale multiplexed quantitative proteomics.

Inhibition of circulating dipeptidyl peptidase 4 activity in patients with metastatic prostate cancer.

Cancer is responsible for many deaths and is a major source of healthcare expenditures. The identification of new, non-invasive biomarkers might allow improvement of the direct diagnostic or prognostic ability of already available tools. Here, we took the innovative approach of interrogating the activity of exopeptidases in the serum of cancer patients with the aim of establishing a distinction based on enzymatic function, instead of simple protein levels, as a means to biomarker discovery. We first analyzed two well-characterized mouse models of prostate cancer, each with a distinct genetic lesion, and established that broad exopeptidase and targeted aminopeptidase activity tests reveal proteolytic changes associated with tumor development. We also describe new peptide-based freeze-frame reagents uniquely suited to probe the altered balance of selected aminopeptidases, as opposed to the full array of exopeptidases, and/or their modulators in patient serum or plasma. One particular proteolytic activity was impaired in animals with aggressive disease relative to cancer-free littermates. We identified the protease in question as dipeptidyl peptidase 4 (DPP4) by analyzing selected knockout mice and evaluating the effect of specific inhibitors. DPP4 activity was also reduced in the sera of patients with metastatic prostate cancer relative to patients with localized disease or healthy controls. However, no significant differences in DPP4 serum levels were observed, which established the loss of activity as the result of impaired enzymatic function. Biochemical analysis indicated that reduced activity was the result not of post-translational modifications or allosteric changes, but instead of a low-molecular-weight inhibitor. After we adjusted for age and total prostate-specific antigen, reduced DPP4 activity remained a significant predictor of cancer status. The results of this proof-of-principle study suggest that DPP4 activity might be a potential blood-based indicator of the presence of metastatic cancer of prostatic origin, either by itself or, more likely, as a means to improve the sensitivity and specificity of existing markers.

Monitoring peptidase activities in complex proteomes by MALDI-TOF mass spectrometry.

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semiquantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide substrates using robotic extraction and a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometric readout. Relative quantitation of the peptide metabolites is carried out by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be used for diagnostic or predictive purposes and it enables profiling of 96 samples in 30 h. It could be tailored to many diagnostic and pharmaco-dynamic purposes as a readout of catalytic and metabolic activities in body fluids or tissues.

Pathway-based biomarker search by high-throughput proteomics profiling of secretomes.

An efficient means for the identification of prognostic and predictive biomarkers is essential in today's cancer management. A new approach toward biomarker discovery has therefore been proposed, where pathways instead of individual proteins would be monitored and targeted. Recently, the 'secretome', a biological fluid that may be enriched with secreted and/or shed proteins from adjacent disease-relevant cancer cells, has been targeted for biomarker discovery. We describe a novel method for secretome analysis using "stacking gels", label-free relative quantitation, and pathway analysis. The protocol presented here increases the throughput of secretome analysis by approximately 1 order of magnitude compared to earlier methodologies. In the first application, six cancer cell lines from three different tissues were studied. The global secretome data sets obtained were analyzed using pathway analysis software to attempt integrating the experimental findings into a cellular signaling context. This suggested that several secretome proteins might be interconnected with intracellular canonical pathways. This, in turn, may eventually allow the use of secretomes for discovery of pathway-based biomarkers. When this strategy was applied to two breast cancer cell lines, it appeared that the IGF signaling and the plasminogen activating system may be differentially regulated in invasive breast cancer, but this remains speculative until it is verified in a clinical setting. In summary, the methodology proposed optimizes cell culture with sample fractionation and LC-MS to obtain the highest yield from cultured cell secretomes, with a focus on rational biomarker discovery through putative linkage with cancer relevant pathways.

A sequence-specific exopeptidase activity test (SSEAT) for "functional" biomarker discovery.

One form of functional proteomics entails profiling of genuine activities, as opposed to surrogates of activity or active "states," in a complex biological matrix: for example, tracking enzyme-catalyzed changes, in real time, ranging from simple modifications to complex anabolic or catabolic reactions. Here we present a test to compare defined exoprotease activities within individual proteomes of two or more groups of biological samples. It tracks degradation of artificial substrates, under strictly controlled conditions, using semiautomated MALDI-TOF mass spectrometric analysis of the resulting patterns. Each fragment is quantitated by comparison with double labeled, non-degradable internal standards (all-d-amino acid peptides) spiked into the samples at the same time as the substrates to reflect adsorptive and processing-related losses. The full array of metabolites is then quantitated (coefficients of variation of 6.3-14.3% over five replicates) and subjected to multivariate statistical analysis. Using this approach, we tested serum samples of 48 metastatic thyroid cancer patients and 48 healthy controls, with selected peptide substrates taken from earlier standard peptidomics screens (i.e. the "discovery" phase), and obtained class predictions with 94% sensitivity and 90% specificity without prior feature selection (24 features). The test all but eliminates reproducibility problems related to sample collection, storage, and handling as well as to possible variability in endogenous peptide precursor levels because of hemostatic alterations in cancer patients.

PU.1 and a TTTAAA element in the myeloid defensin-1 promoter create an operational TATA box that can impose cell specificity onto TFIID function.

Defensins are major components of a peptide-based, antimicrobial system in human neutrophils. While packed with peptide, circulating cells contain no defensin-1 (def1) transcripts, except in some leukemia patients and in derivative promyelocytic leukemia cell lines. Expression is modulated by serum factors, mediators of inflammation, and kinase activators and inhibitors, but the underlying mechanisms are not fully understood. A minimal def1 promoter drives transcription in HL-60 cells under control of PU.1 and a def1-binding protein ("D1BP"), acting through, respectively, proximal (-22/-19) and distal (-62/-59) GGAA elements. In this study, we identify D1BP, biochemically and functionally, as GA-binding protein (GABP)alpha/GABPbeta. Whereas GABP operates as an essential upstream activator, PU.1 assists the flanking "TTTAAA" element (-32/-27), a "weak" but essential TATA box, to bring TBP/TFIID to the transcription start site. PU.1 thus imparts a degree of cell specificity to the minimal promoter and provides a potential link between a number of signaling pathways and TFIID. However, a "strong" TATA box ("TATAAA") eliminates the need for the PU.1 binding site and for PU.1, but not for GABP. As GABP is widely expressed, a strong TATA box thus alleviates promyelocytic cell specificity of the def1 promoter. These findings suggest how the myeloid def1 promoter may have evolutionarily acquired its current properties.

The RNA processing exosome is linked to elongating RNA polymerase II in Drosophila.

The RNA polymerase II elongation complex contains several factors that facilitate transcription elongation and catalyse the processing of precursor messenger RNAs (pre-mRNAs). The conserved elongation factor Spt6 is recruited rapidly and robustly to sites of active transcription. Here we show that Drosophila Spt6 (dSpt6) co-purifies with the exosome, a complex of 3' to 5' exoribonucleases that is implicated in the processing of structural RNA and in the degradation of improperly processed pre-mRNA. Immunoprecipitation assays of Drosophila nuclear extracts show that the exosome also associates with the elongation factor dSpt5 and RNA polymerase II. In vivo, exosome subunits colocalize with dSpt6 at transcriptionally active loci on polytene chromosomes during normal development and are strongly recruited to heat-shock loci on gene induction. At higher resolution, chromatin immunoprecipitation analysis shows that the exosome is recruited to transcriptionally active units of heat-shock genes. These data provide a physical basis for the hypothesis that exosome-mediated pre-mRNA surveillance accompanies transcription elongation.