Reproducibility of differential proteomic technologies in CPTAC fractionated xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation

Proteogenomic integration reveals therapeutic targets in breast cancer xenografts

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities

Proteogenomic landscape of breast cancer tumorigenesis and targeted therapy

The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this "proteogenomics" approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy

Navigating Critical Challenges Associated with Immunopeptidomics-Based Detection of Proteasomal Spliced Peptide Candidates.

Within the tumor immunology community, the topic of proteasomal spliced peptides (PSP) has generated a great deal of controversy. In the earliest reports, careful biological validation led to the conclusion that proteasome-catalyzed peptide splicing was a rare event. To date, six PSPs have been validated biologically. However, the advent of algorithms to identify candidate PSPs in mass spectrometry data challenged this notion, with several studies concluding that the frequency of spliced peptides binding to MHC class I was quite high. Since this time, much debate has centered around the methodologies used in these studies. Several reanalyses of data from these studies have led to questions about the validity of the conclusions. Furthermore, the biological and technical validation that should be necessary for verifying PSP assignments was often lacking. It has been suggested therefore that the research community should unite around a common set of standards for validating candidate PSPs. In this review, we propose and highlight the necessary steps for validation of proteasomal splicing at both the mass spectrometry and biological levels. We hope that these guidelines will serve as a foundation for critical assessment of results from proteasomal splicing studies

Methods for quantification of in vivo changes in protein ubiquitination following proteasome and deubiquitinase inhibition

Ubiquitination plays a key role in protein degradation and signal transduction. Ubiquitin is a small protein modifier that is adducted to lysine residues by the combined function of E1, E2, and E3 enzymes and is removed by deubiquitinating enzymes. Characterization of ubiquitination sites is important for understanding the role of this modification in cellular processes and disease. However, until recently, large-scale characterization of endogenous ubiquitination sites has been hampered by the lack of efficient enrichment techniques. The introduction of antibodies that specifically recognize peptides with lysine residues that harbor a di-glycine remnant (K-{epsilon}-GG) following tryptic digestion has dramatically improved the ability to enrich and identify ubiquitination sites from cellular lysates. We used this enrichment technique to study the effects of proteasome inhibition by MG-132 and deubiquitinase inhibition by PR-619 on ubiquitination sites in human Jurkat cells by quantitative high performance mass spectrometry. Minimal fractionation of digested lysates prior to immunoaffinity enrichment increased the yield of K-ε-GG peptides three- to fourfold resulting in detection of up to ~3300 distinct K-GG peptides in SILAC triple encoded experiments starting from 5 mg of protein per label state. In total, we identify 5533 distinct K-{epsilon}-GG peptides of which 4907 were quantified in this study, demonstrating that the strategy presented is a practical approach to perturbational studies in cell systems. We found that proteasome inhibition by MG-132 and deubiquitinase inhibition by P-619 induces significant changes to the ubiquitin landscape, but that not all ubiquitination sites regulated by MG-132 and PR-619 are likely substrates for the ubiquitin-proteasome system. Additionally, we find that the proteasome and deubiquitinase inhibitors studied induced only minor changes in protein expression levels regardless of the extent of regulation induced at the ubiquitin site level. We attribute this finding to the low stoichiometry of the majority ubiquitination sites identified in this study

iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics

Labeling of primary amines on peptides with reagents containing stable isotopes is a commonly used technique in quantitative mass spectrometry. Isobaric labeling techniques such as iTRAQ(TM) or TMT(TM) allow for relative quantification of peptides based on ratios of reporter ions in the low m/z region of spectra produced by precursor ion fragmentation. In contrast, nonisobaric labeling with mTRAQ(TM) yields precursors with different masses that can be directly quantified in MS1 spectra. In this study, we compare iTRAQ- and mTRAQ-based quantification of peptides and phosphopeptides derived from EGF-stimulated HeLa cells. Both labels have identical chemical structures, therefore precursor ion- and fragment ion-based quantification can be directly compared. Our results indicate that iTRAQ labeling has an additive effect on precursor intensities, whereas mTRAQ labeling leads to more redundant MS2 scanning events caused by triggering on the same peptide with different mTRAQ labels. We found that iTRAQ labeling quantified nearly threefold more phosphopeptides (12,129 versus 4,448) and nearly twofold more proteins (2,699 versus 1,597) than mTRAQ labeling. Although most key proteins in the EGFR signaling network were quantified with both techniques, iTRAQ labeling allowed quantification of twice as many kinases. Accuracy of reporter ion quantification by iTRAQ is adversely affected by peptides that are cofragmented in the same precursor isolation window, dampening observed ratios toward unity. However, because of tighter overall iTRAQ ratio distributions, the percentage of statistically significantly regulated phosphopeptides and proteins detected by iTRAQ and mTRAQ was similar. We observed a linear correlation of logarithmic iTRAQ to mTRAQ ratios over two orders of magnitude, indicating a possibility to correct iTRAQ ratios by an average compression factor. Spike-in experiments using peptides of defined ratios in a background of nonregulated peptides show that iTRAQ quantification is less accurate but not as variable as mTRAQ quantification

TMT labeling for the masses: a robust and cost-efficient, in-solution labeling approach

Isobaric stable isotope labeling using, for example, tandem mass tags (TMTs) is increasingly being applied for large-scale proteomic studies. Experiments focusing on proteoform analysis in drug time course or perturbation studies or in large patient cohorts greatly benefit from the reproducible quantification of single peptides across samples. However, such studies often require labeling of hundreds of micrograms of peptides such that the cost for labeling reagents represents a major contribution to the overall cost of an experiment. Here, we describe and evaluate a robust and cost-effective protocol for TMT labeling that reduces the quantity of required labeling reagent by a factor of eight and achieves complete labeling. Under- and over-labeling of peptides derived from complex digests of tissues and cell lines were systematically evaluated using peptide quantities of between 12.5 and 800 μg and TMT-to-peptide ratios (wt/wt) ranging from 8:1 to 1:2 at different TMT and peptide concentrations. When reaction volumes were reduced to maintain TMT and peptide concentrations of at least 10 mM and 2 g/L, respectively, TMT-to-peptide ratios as low as 1:1 (wt/wt) resulted in labeling efficiencies of > 99 % and excellent intra- and inter-laboratory reproducibility. The utility of the optimized protocol was further demonstrated in a deep-scale proteome and phosphoproteome analysis of patient-derived xenograft tumor tissue benchmarked against the labeling procedure recommended by the TMT vendor. Finally, we discuss the impact of labeling reaction parameters for N-hydroxysuccinimide ester-based chemistry and provide guidance on adopting efficient labeling protocols for different peptide quantities

Multiplexed, quantitative workflow for sensitive biomarker discovery in plasma yields novel candidates for early myocardial injury

We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, "planned" myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments

Integrated proteomic analysis of post-translational modifications by serial enrichment

We report a mass spectrometry-based method for the integrated analysis of protein expression, phosphorylation, ubiquitination and acetylation by serial enrichments of different post-translational modifications (SEPTM) from the same biological sample. This technology enabled quantitative analysis of nearly 8,000 proteins and more than 20,000 phosphorylation, 15,000 ubiquitination and 3,000 acetylation sites per experiment, generating a holistic view of cellular signal transduction pathways as exemplified by analysis of bortezomib-treated human leukemia cells