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.

DLC1 is a tumor suppressor protein whose full activity depends on its presence at focal adhesions, its Rho-GTPase activating protein (Rho-GAP) function, and its ability to bind several ligands, including tensin and talin. However, the mechanisms that regulate and coordinate these activities remain poorly understood. Here we identify CDK5, a predominantly cytoplasmic serine/threonine kinase, as an important regulator of DLC1 functions. The CDK5 kinase phosphorylates four serines in DLC1 located N-terminal to the Rho-GAP domain. When not phosphorylated, this N-terminal region functions as an autoinhibitory domain that places DLC1 in a closed, inactive conformation by efficiently binding to the Rho-GAP domain. CDK5 phosphorylation reduces this binding and orchestrates the coordinate activation DLC1, including its localization to focal adhesions, its Rho-GAP activity, and its ability to bind tensin and talin. In cancer, these anti-oncogenic effects of CDK5 can provide selective pressure for the down-regulation of DLC1, which occurs frequently in tumors, and can contribute to the pro-oncogenic activity of CDK5 in lung adenocarcinoma.

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

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.

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.

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.

Deciphering the signaling networks that underlie normal and disease processes remains a major challenge. Here, we report the discovery of signaling components involved in the Toll-like receptor (TLR) response of immune dendritic cells (DCs), including a previously unkown pathway shared across mammalian antiviral responses. By combining transcriptional profiling, genetic and small-molecule perturbations, and phosphoproteomics, we uncover 35 signaling regulators, including 16 known regulators, involved in TLR signaling. In particular, we find that Polo-like kinases (Plk) 2 and 4 are essential components of antiviral pathways in vitro and in vivo and activate a signaling branch involving a dozen proteins, among which is Tnfaip2, a gene associated with autoimmune diseases but whose role was unknown. Our study illustrates the power of combining systematic measurements and perturbations to elucidate complex signaling circuits and discover potential therapeutic targets.

Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids. Varying the physicochemical properties of engineered NPs translates to distinct protein corona patterns enabling differential and reproducible interrogation of biological samples, including deep sampling of the plasma proteome. Spike experiments confirm a linear signal response. The median coefficient of variation was 22%. We screened 43 NPs and selected a panel of 5, which detect more than 2,000 proteins from 141 plasma samples using a 96-well automated workflow in a pilot non-small cell lung cancer classification study. Our streamlined workflow combines depth of coverage and throughput with precise quantification based on unique interactions between proteins and NPs engineered for deep and scalable quantitative proteomic studies.

Polycomb repressive epigenetic complexes are recurrently dysregulated in cancer. Unlike polycomb repressive complex 2 (PRC2), the role of PRC1 in oncogenesis and therapy resistance is not well-defined. Here, we demonstrate that highly recurrent mutations of the PRC1 subunits BCOR and BCORL1 in leukemia disrupt assembly of a noncanonical PRC1.1 complex, thereby selectively unlinking the RING-PCGF enzymatic core from the chromatin-targeting auxiliary subcomplex. As a result, BCOR-mutated PRC1.1 is localized to chromatin but lacks repressive activity, leading to epigenetic reprogramming and transcriptional activation at target loci. We define a set of functional targets that drive aberrant oncogenic signaling programs in PRC1.1-mutated cells and primary patient samples. Activation of these PRC1.1 targets in BCOR-mutated cells confers acquired resistance to treatment while sensitizing to targeted kinase inhibition. Our study thus reveals a novel epigenetic mechanism that explains PRC1.1 tumor-suppressive activity and identifies a therapeutic strategy in PRC1.1-mutated cancer.

The trafficking of specific protein cohorts to correct subcellular locations at correct times is essential for every signaling and regulatory process in biology. Gene perturbation screens could provide a powerful approach to probe the molecular mechanisms of protein trafficking, but only if protein localization or mislocalization can be tied to a simple and robust phenotype for cell selection, such as cell proliferation or fluorescence-activated cell sorting (FACS). To empower the study of protein trafficking processes with gene perturbation, we developed a genetically encoded molecular tool named HiLITR (High-throughput Localization Indicator with Transcriptional Readout). HiLITR converts protein colocalization into proteolytic release of a membrane-anchored transcription factor, which drives the expression of a chosen reporter gene. Using HiLITR in combination with FACS-based CRISPRi screening in human cell lines, we identified genes that influence the trafficking of mitochondrial and ER tail-anchored proteins. We show that loss of the SUMO E1 component SAE1 results in mislocalization and destabilization of many mitochondrial tail-anchored proteins. We also demonstrate a distinct regulatory role for EMC10 in the ER membrane complex, opposing the transmembrane-domain insertion activity of the complex. Through transcriptional integration of complex cellular functions, HiLITR expands the scope of biological processes that can be studied by genetic perturbation screening technologies.

Proximity labeling (PL) with genetically-targeted promiscuous enzymes has emerged as a powerful tool for unbiased proteome discovery. By combining the spatiotemporal specificity of PL with methods for functional protein enrichment, we show that it is possible to map specific protein subclasses within distinct compartments of living cells. In particular, we develop a method to enrich subcompartment-specific RNA binding proteins (RBPs) by combining peroxidase-catalyzed PL with organic-aqueous phase separation of crosslinked protein-RNA complexes ("APEX-PS"). We use APEX-PS to generate datasets of nuclear, nucleolar, and outer mitochondrial membrane (OMM) RBPs, which can be mined for novel functions. For example, we find that the OMM RBP SYNJ2BP retains specific nuclear-encoded mitochondrial mRNAs at the OMM during translation stress, facilitating their local translation and import of protein products into the mitochondrion during stress recovery. Functional PL in general, and APEX-PS in particular, represent versatile approaches for the discovery of proteins with novel function in specific subcellular compartments.

While gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of "connectivity" to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics .

Immunopeptidome profiling of infected cells is a powerful technique for detecting viral peptides that are naturally processed and loaded onto class I human leukocyte antigens (HLAs-I). Here, we provide a protocol for preparing samples for immunopeptidome profiling that can inactivate enveloped viruses while still preserving the integrity of the HLA-I complex. We detail steps for lysate preparation of infected cells followed by HLA-I immunoprecipitation and virus inactivation. We further describe peptide purification for mass spectrometry outside a high-containment facility. For complete details on the use and execution of this protocol, please refer to Weingarten-Gabbay et al. (2021).1.

Targeted protein degradation is a rapidly advancing and expanding therapeutic approach. Drugs that degrade GSPT1 via the CRL4CRBN ubiquitin ligase are a new class of cancer therapy in active clinical development with evidence of activity against acute myeloid leukemia in early-phase trials. However, other than activation of the integrated stress response, the downstream effects of GSPT1 degradation leading to cell death are largely undefined, and no murine models are available to study these agents. We identified the domains of GSPT1 essential for cell survival and show that GSPT1 degradation leads to impaired translation termination, activation of the integrated stress response pathway, and TP53-independent cell death. CRISPR/Cas9 screens implicated decreased translation initiation as protective following GSPT1 degradation, suggesting that cells with higher levels of translation are more susceptible to the effects of GSPT1 degradation. We defined 2 Crbn amino acids that prevent Gspt1 degradation in mice, generated a knockin mouse with alteration of these residues, and demonstrated the efficacy of GSPT1-degrading drugs in vivo with relative sparing of numbers and function of long-term hematopoietic stem cells. Our results provide a mechanistic basis for the use of GSPT1 degraders for the treatment of cancer, including TP53-mutant acute myeloid leukemia.

Stimulator of interferon genes (STING) is an intracellular sensor of cyclic di-nucleotides involved in the innate immune response against pathogen- or self-derived DNA. STING trafficking is tightly linked to its function, and its dysregulation can lead to disease. Here, we systematically characterize genes regulating STING trafficking and examine their impact on STING-mediated responses. Using proximity-ligation proteomics and genetic screens, we demonstrate that an endosomal sorting complex required for transport (ESCRT) complex containing HGS, VPS37A and UBAP1 promotes STING degradation, thereby terminating STING-mediated signaling. Mechanistically, STING oligomerization increases its ubiquitination by UBE2N, forming a platform for ESCRT recruitment at the endosome that terminates STING signaling via sorting in the lysosome. Finally, we show that expression of a UBAP1 mutant identified in patients with hereditary spastic paraplegia and associated with disrupted ESCRT function, increases steady-state STING-dependent type I IFN responses in healthy primary monocyte-derived dendritic cells and fibroblasts. Based on these findings, we propose that STING is subject to a tonic degradative flux and that the ESCRT complex acts as a homeostatic regulator of STING signaling.

O-GlcNAc transferase (OGT) modifies serine and threonine residues on nuclear and cytosolic proteins with O-linked N-acetylglucosamine (GlcNAc). OGT is essential for mammalian cell viability, but the underlying mechanisms are still enigmatic. We performed a genome-wide CRISPR-Cas9 screen in mouse embryonic stem cells (mESCs) to identify candidates whose depletion rescued the block in cell proliferation induced by OGT deficiency. We show that the block in cell proliferation in OGT-deficient cells stems from mitochondrial dysfunction secondary to mTOR (mechanistic target of rapamycin) hyperactivation. In normal cells, OGT maintains low mTOR activity and mitochondrial fitness through suppression of proteasome activity; in the absence of OGT, increased proteasome activity results in increased steady-state amino acid levels, which in turn promote mTOR lysosomal translocation and activation, and increased oxidative phosphorylation. mTOR activation in OGT-deficient mESCs was confirmed by an independent phospho-proteomic screen. Our study highlights a unique series of events whereby OGT regulates the proteasome/ mTOR/ mitochondrial axis in a manner that maintains homeostasis of intracellular amino acid levels, mitochondrial fitness, and cell viability. A similar mechanism operates in CD8+ T cells, indicating its generality across mammalian cell types. Manipulating OGT activity may have therapeutic potential in diseases in which this signaling pathway is impaired.

Immunotherapies have emerged to treat diseases by selectively modulating a patient's immune response. Although the roles of T and B cells in adaptive immunity have been well studied, it remains difficult to select targets for immunotherapeutic strategies. Because human leukocyte antigen class II (HLA-II) peptides activate CD4+ T cells and regulate B cell activation, proliferation, and differentiation, these peptide antigens represent a class of potential immunotherapy targets and biomarkers. To better understand the molecular basis of how HLA-II antigen presentation is involved in disease progression and treatment, systematic HLA-II peptidomics combined with multiomic analyses of diverse cell types in healthy and diseased states is required. For this reason, MS-based innovations that facilitate investigations into the interplay between disease pathologies and the presentation of HLA-II peptides to CD4+ T cells will aid in the development of patient-focused immunotherapies.

MS is the most effective method to directly identify peptides presented on human leukocyte antigen (HLA) molecules. However, current standard approaches often use 500 million or more cells as input to achieve high coverage of the immunopeptidome, and therefore, these methods are not compatible with the often limited amounts of tissue available from clinical tumor samples. Here, we evaluated microscaled basic reversed-phase fractionation to separate HLA peptide samples offline followed by ion mobility coupled to LC-MS/MS for analysis. The combination of these two separation methods enabled identification of 20% to 50% more peptides compared with samples analyzed without either prior fractionation or use of ion mobility alone. We demonstrate coverage of HLA immunopeptidomes with up to 8107 distinct peptides starting with as few as 100 million cells. The increased sensitivity obtained using our methods can provide data useful to improve HLA-binding prediction algorithms as well as to enable detection of clinically relevant epitopes such as neoantigens.

Proteogenomics involves the integrative analysis of genomic, transcriptomic, proteomic and post-translational modification data produced by next-generation sequencing and mass spectrometry-based proteomics. Several publications by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and others have highlighted the impact of proteogenomics in enabling deeper insight into the biology of cancer and identification of potential drug targets. In order to encapsulate the complex data processing required for proteogenomics, and provide a simple interface to deploy a range of algorithms developed for data analysis, we have developed PANOPLY—a cloud-based platform for automated and reproducible proteogenomic data analysis. A wide array of algorithms have been implemented, and we highlight the application of PANOPLY to the analysis of cancer proteogenomic data.