Proteogenomics connects somatic mutations to signalling in breast cancer

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. We describe quantitative mass spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers of which 77 provided high-quality data. Integrated analyses allowed insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated against the Library of Integrated Network-based Cellular Signatures, thereby connecting CETN3 and SKP1 loss to elevated expression of EGFR, and SKP1 loss also to increased SRC. Global proteomic data confirmed a stromal-enriched group in addition to basal and luminal clusters and pathway analysis of the phosphoproteome identified a G Protein-coupled receptor cluster that was not readily identified at the mRNA level. Besides ERBB2, other amplicon-associated, highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins

Mitochondria are complex organelles that house essential pathways involved in energy metabolism, ion homeostasis, signalling and apoptosis. To understand mitochondrial pathways in health and disease, it is crucial to have an accurate inventory of the organelle's protein components. In 2008, we made substantial progress toward this goal by performing in-depth mass spectrometry of mitochondria from 14 organs, epitope tagging/microscopy and Bayesian integration to assemble MitoCarta (www.broadinstitute.org/pubs/MitoCarta): an inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Using the same strategy we have now reconstructed this inventory separately for human and for mouse based on (i) improved gene transcript models, (ii) updated literature curation, including results from proteomic analyses of mitochondrial sub-compartments, (iii) improved homology mapping and (iv) updated versions of all seven original data sets. The updated human MitoCarta2.0 consists of 1158 human genes, including 918 genes in the original inventory as well as 240 additional genes. The updated mouse MitoCarta2.0 consists of 1158 genes, including 967 genes in the original inventory plus 191 additional genes. The improved MitoCarta 2.0 inventory provides a molecular framework for system-level analysis of mammalian mitochondria.

The matrisome: in silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices

The extracellular matrix (ECM) is a complex meshwork of cross-linked proteins providing both biophysical and biochemical cues that are important regulators of cell proliferation, survival, differentiation, and migration. We present here a proteomic strategy developed to characterize the in vivo ECM composition of normal tissues and tumors using enrichment of protein extracts for ECM components and subsequent analysis by mass spectrometry. In parallel, we have developed a bioinformatic approach to predict the in silico "matrisome" defined as the ensemble of ECM proteins and associated factors. We report the characterization of the extracellular matrices of murine lung and colon, each comprising more than 100 ECM proteins and each presenting a characteristic signature. Moreover, using human tumor xenografts in mice, we show that both tumor cells and stromal cells contribute to the production of the tumor matrix and that tumors of differing metastatic potential differ in both the tumor- and the stroma-derived ECM components. The strategy we describe and illustrate here can be broadly applied and, to facilitate application of these methods by others, we provide resources including laboratory protocols, inventories of ECM domains and proteins, and instructions for bioinformatically deriving the human and mouse matrisome.

Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing MS or MS/MS and database searching

We describe the impact of advances in mass measurement accuracy, +/- 10 ppm (internally calibrated), on protein identification experiments. This capability was brought about by delayed extraction techniques used in conjunction with matrix-assisted laser desorption ionization (MALDI) on a reflectron time-of-flight (TOF) mass spectrometer. This work explores the advantage of using accurate mass measurement (and thus constraint on the possible elemental composition of components in a protein digest) in strategies for searching protein, gene, and EST databases that employ (a) mass values alone, (b) fragment-ion tagging derived from MS/MS spectra, and (c) de novo interpretation of MS/MS spectra. Significant improvement in the discriminating power of database searches has been found using only molecular weight values (i.e., measured mass) of > 10 peptide masses. When MALDI-TOF instruments are able to achieve the +/- 0.5-5 ppm mass accuracy necessary to distinguish peptide elemental compositions, it is possible to match homologous proteins having > 70% sequence identity to the protein being analyzed. The combination of a +/- 10 ppm measured parent mass of a single tryptic peptide and the near-complete amino acid (AA) composition information from immonium ions generated by MS/MS is capable of tagging a peptide in a database because only a few sequence permutations > 11 AA's in length for an AA composition can ever be found in a proteome. De novo interpretation of peptide MS/MS spectra may be accomplished by altering our MS-Tag program to replace an entire database with calculation of only the sequence permutations possible from the accurate parent mass and immonium ion limited AA compositions. A hybrid strategy is employed using de novo MS/MS interpretation followed by text-based sequence similarity searching of a database.

The extracellular matrix: Tools and insights for the "omics" era

The extracellular matrix (ECM) is a fundamental component of multicellular organisms that provides mechanical and chemical cues that orchestrate cellular and tissue organization and functions. Degradation, hyperproduction or alteration of the composition of the ECM cause or accompany numerous pathologies. Thus, a better characterization of ECM composition, metabolism, and biology can lead to the identification of novel prognostic and diagnostic markers and therapeutic opportunities. The development over the last few years of high-throughput ("omics") approaches has considerably accelerated the pace of discovery in life sciences. In this review, we describe new bioinformatic tools and experimental strategies for ECM research, and illustrate how these tools and approaches can be exploited to provide novel insights in our understanding of ECM biology. We also introduce a web platform "the matrisome project" and the database MatrisomeDB that compiles in silico and in vivo data on the matrisome, defined as the ensemble of genes encoding ECM and ECM-associated proteins. Finally, we present a first draft of an ECM atlas built by compiling proteomics data on the ECM composition of 14 different tissues and tumor types.

Dimerization of the extracellular domain of the human growth hormone receptor by a single hormone molecule

Human growth hormone (hGH) forms a 1:2 complex with the extracellular domain of its receptor-binding protein (hGHbp) as studied by crystallization, size exclusion chromatography, calorimetry, and a previously undescribed fluorescence quenching assay. These and other experiments with protein engineered variants of hGH have led to the identification of the binding determinants for two distinct but adjacent sites on hGH for the hGHbp, and the data indicated that there are two overlapping binding sites on the hGHbp for hGH. Furthermore, the binding of hGH to the hGHbp occurred sequentially; a first hGHbp molecule bound to site 1 on hGH and then a second hGHbp bound to site 2. Hormone-induced receptor dimerization is proposed to be relevant to the signal transduction mechanism for the hGH receptor and other related cytokine receptors.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction

Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.

Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.

A breast cancer stem cell niche supported by juxtacrine signalling from monocytes and macrophages

The cell-biological program termed the epithelial-mesenchymal transition (EMT) confers on cancer cells mesenchymal traits and an ability to enter the cancer stem cell (CSC) state. However, the interactions between CSCs and their surrounding microenvironment are poorly understood. Here we show that tumour-associated monocytes and macrophages (TAMs) create a CSC niche through juxtacrine signalling with CSCs. We performed quantitative proteomic profiling and found that the EMT program upregulates the expression of CD90, also known as Thy1, and EphA4, which mediate the physical interactions of CSCs with TAMs by directly binding with their respective counter-receptors on these cells. In response, the EphA4 receptor on the carcinoma cells activates Src and NF-κB. In turn, NF-κB in the CSCs induces the secretion of a variety of cytokines that serve to sustain the stem cell state. Indeed, admixed macrophages enhance the CSC activities of carcinoma cells. These findings underscore the significance of TAMs as important components of the CSC niche.

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

De novo peptide sequencing via tandem mass spectrometry

Peptide sequencing via tandem mass spectrometry (MS/MS) is one of the most powerful tools in proteomics for identifying proteins. Because complete genome sequences are accumulating rapidly, the recent trend in interpretation of MS/MS spectra has been database search. However, de novo MS/MS spectral interpretation remains an open problem typically involving manual interpretation by expert mass spectrometrists. We have developed a new algorithm, SHERENGA, for de novo interpretation that automatically learns fragment ion types and intensity thresholds from a collection of test spectra generated from any type of mass spectrometer. The test data are used to construct optimal path scoring in the graph representations of MS/MS spectra. A ranked list of high scoring paths corresponds to potential peptide sequences. SHERENGA is most useful for interpreting sequences of peptides resulting from unknown proteins and for validating the results of database search algorithms in fully automated, high-throughput peptide sequencing.

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.

A large peptidome dataset improves HLA class I epitope prediction across most of the human population

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Phenotype, specificity and avidity of antitumour CD8+ T cells in melanoma

Interactions between T cell receptors (TCRs) and their cognate tumour antigens are central to antitumour immune responses1-3; however, the relationship between phenotypic characteristics and TCR properties is not well elucidated. Here we show, by linking the antigenic specificity of TCRs and the cellular phenotype of melanoma-infiltrating lymphocytes at single-cell resolution, that tumour specificity shapes the expression state of intratumoural CD8+ T cells. Non-tumour-reactive T cells were enriched for viral specificities and exhibited a non-exhausted memory phenotype, whereas melanoma-reactive lymphocytes predominantly displayed an exhausted state that encompassed diverse levels of differentiation but rarely acquired memory properties. These exhausted phenotypes were observed both among clonotypes specific for public overexpressed melanoma antigens (shared across different tumours) or personal neoantigens (specific for each tumour). The recognition of such tumour antigens was provided by TCRs with avidities inversely related to the abundance of cognate targets in melanoma cells and proportional to the binding affinity of peptide-human leukocyte antigen (HLA) complexes. The persistence of TCR clonotypes in peripheral blood was negatively affected by the level of intratumoural exhaustion, and increased in patients with a poor response to immune checkpoint blockade, consistent with chronic stimulation mediated by residual tumour antigens. By revealing how the quality and quantity of tumour antigens drive the features of T cell responses within the tumour microenvironment, we gain insights into the properties of the anti-melanoma TCR repertoire.

Proteogenomic Characterization of Endometrial Carcinoma

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.

Proteomic analyses of ECM during pancreatic ductal adenocarcinoma progression reveal different contributions by tumor and stromal cells

Pancreatic ductal adenocarcinoma (PDAC) has prominent extracellular matrix (ECM) that compromises treatments yet cannot be nonselectively disrupted without adverse consequences. ECM of PDAC, despite the recognition of its importance, has not been comprehensively studied in patients. In this study, we used quantitative mass spectrometry (MS)-based proteomics to characterize ECM proteins in normal pancreas and pancreatic intraepithelial neoplasia (PanIN)- and PDAC-bearing pancreas from both human patients and mouse genetic models, as well as chronic pancreatitis patient samples. We describe detailed changes in both abundance and complexity of matrisome proteins in the course of PDAC progression. We reveal an early up-regulated group of matrisome proteins in PanIN, which are further up-regulated in PDAC, and we uncover notable similarities in matrix changes between pancreatitis and PDAC. We further assigned cellular origins to matrisome proteins by performing MS on multiple lines of human-to-mouse xenograft tumors. We found that, although stromal cells produce over 90% of the ECM mass, elevated levels of ECM proteins derived from the tumor cells, but not those produced exclusively by stromal cells, tend to correlate with poor patient survival. Furthermore, distinct pathways were implicated in regulating expression of matrisome proteins in cancer cells and stromal cells. We suggest that, rather than global suppression of ECM production, more precise ECM manipulations, such as targeting tumor-promoting ECM proteins and their regulators in cancer cells, could be more effective therapeutically.

Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters

The extracellular matrix (ECM) is a major component of tumors and a significant contributor to cancer progression. In this study, we use proteomics to investigate the ECM of human mammary carcinoma xenografts and show that primary tumors of differing metastatic potential differ in ECM composition. Both tumor cells and stromal cells contribute to the tumor matrix and tumors of differing metastatic ability differ in both tumor- and stroma-derived ECM components. We define ECM signatures of poorly and highly metastatic mammary carcinomas and these signatures reveal up-regulation of signaling pathways including TGFβ and VEGF. We further demonstrate that several proteins characteristic of highly metastatic tumors (LTBP3, SNED1, EGLN1, and S100A2) play causal roles in metastasis, albeit at different steps. Finally we show that high expression of LTBP3 and SNED1 correlates with poor outcome for ER⁻/PR⁻breast cancer patients. This study thus identifies novel biomarkers that may serve as prognostic and diagnostic tools.

DOI:http://dx.doi.org/10.7554/eLife.01308.001

Metastasis is the process whereby tumor cells spread within the body and is the cause of most deaths from cancer. This complex process involves several steps: first the cancer cells invade the tissues that surround the tumor; second, the cancer cells enter the blood stream and travel throughout the body; and third, the cancer cells seed the growth of new tumors in distant organs.

Within tissues, the extracellular matrix forms a complex scaffold of proteins that surrounds cells, to support and organize them: it also provides signals that control how much cells can multiply, how likely cells are to stick together or migrate, and even a cell’s chances of survival. Pathologists have used an accumulation of extracellular matrix proteins in tumors as a sign that the outcome of the disease will likely be unfavorable for a patient, and that treatment will be challenging. However, we still do not have a clear picture of the composition of the tumor extracellular matrix and we do not know all the details of how it affects tumor growth and metastasis.

Now, Naba et al. have explored these questions by injecting different types of human breast tumor cells into mice. Some of the cells were capable of spreading throughout the body and were said to have a high ‘metastatic potential’; others were less capable of spreading and were said to have a low metastatic potential. Naba et al. then analyzed the proteins that made up the extracellular matrix of the tumors that grew in the mice. Some proteins were found in both types of tumor; whereas some proteins were only found in the tumors with low metastatic potential and some were only found in the highly metastatic tumors. Naba et al. also demonstrated that both cancer cells and non-cancer cells—which are also found within the tumors—contributed to the production of the extracellular matrix in the tumor. Moreover, and somewhat surprisingly, the contributions from the non-cancer cells in the two types of tumors were also different.

Computational analysis predicted that the production of several extracellular matrix proteins in the highly metastatic tumors was under the control of signaling pathways that are involved in cancer progression. Furthermore, Naba et al. also demonstrated that several of the extracellular matrix proteins specific to highly metastatic tumors were required for the cancer to spread. These proteins are involved in different stages of the metastatic process, and some of them are commonly over-produced in tumors from patients with some of the worst chances of recovery.

If similar results are consistently observed in clinical samples from humans, the work of Naba et al. could help doctors to discriminate between tumors that will spread and those that will not, which should lead to improved patient care. The proteins and pathways associated with the highly metastatic tumors could be also investigated as potential drug targets.

DOI:http://dx.doi.org/10.7554/eLife.01308.002

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 overlabeling 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 interlaboratory 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.

A proteogenomic portrait of lung squamous cell carcinoma

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Use of mass spectrometry to identify protein biomarkers of disease severity in the synovial fluid and serum of patients with rheumatoid arthritis

OBJECTIVE

To identify a panel of candidate protein biomarkers of rheumatoid arthritis (RA) that can predict which patients will develop erosive, disabling disease.

METHODS

A 2-step proteomic approach was used for biomarker discovery and verification. In the first step, 2-dimensional liquid chromatography-coupled tandem mass spectrometry was used to generate protein profiles of synovial fluid (SF) from patients with either erosive RA (n = 5) or nonerosive RA (n = 5). In the second step, the selected candidate markers were verified using quantitative multiple reaction monitoring mass spectrometry in sera of patients with erosive RA (n = 15) or nonerosive RA (n = 15) and of healthy controls (n = 15).

RESULTS

Through differential profiling of proteins in the <40-kd portion of the SF proteome, we selected 33 prospective candidate biomarkers from a total of 418 identified proteins. Among the proteins that were elevated in the SF of patients with erosive RA were C-reactive protein (CRP) and 6 members of the S100 protein family of calcium-binding proteins. Significantly, levels of CRP, S100A8 (calgranulin A), S100A9 (calgranulin B), and S100A12 (calgranulin C) proteins were also elevated in the serum of patients with erosive disease compared with patients with nonerosive RA or healthy individuals.

CONCLUSION

Several potential protein marker candidates have been identified for prognosis of the erosive form of RA. This study demonstrates the facility of using protein mass spectrometry in SF and serum for global discovery and verification of clinically relevant sets of disease biomarkers.

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.

Proteomic screen defines the Polo-box domain interactome and identifies Rock2 as a Plk1 substrate

Polo-like kinase-1 (Plk1) phosphorylates a number of mitotic substrates, but the diversity of Plk1-dependent processes suggests the existence of additional targets. Plk1 contains a specialized phosphoserine-threonine binding domain, the Polo-box domain (PBD), postulated to target the kinase to its substrates. Using the specialized PBD of Plk1 as an affinity capture agent, we performed a screen to define the mitotic Plk1-PBD interactome by mass spectrometry. We identified 622 proteins that showed phosphorylation-dependent mitosis-specific interactions, including proteins involved in well-established Plk1-regulated processes, and in processes not previously linked to Plk1 such as translational control, RNA processing, and vesicle transport. Many proteins identified in our screen play important roles in cytokinesis, where, in mammalian cells, the detailed mechanistic role of Plk1 remains poorly defined. We go on to characterize the mitosis-specific interaction of the Plk1-PBD with the cytokinesis effector kinase Rho-associated coiled-coil domain-containing protein kinase 2 (Rock2), demonstrate that Rock2 is a Plk1 substrate, and show that Rock2 colocalizes with Plk1 during cytokinesis. Finally, we show that Plk1 and RhoA function together to maximally enhance Rock2 kinase activity in vitro and within cells, and implicate Plk1 as a central regulator of multiple pathways that synergistically converge to regulate actomyosin ring contraction during cleavage furrow ingression.