The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.

A decade after the discovery of electrospray and matrix-assisted laser desorption ionization (MALDI), methods that finally allowed gentle ionization of large biomolecules, mass spectrometry has become a powerful tool in protein analysis and the key technology in the emerging field of proteomics. The success of mass spectrometry is driven both by innovative instrumentation designs, especially those operating on the time-of-flight or ion-trapping principles, and by large-scale biochemical strategies, which use mass spectrometry to detect the isolated proteins. Any human protein can now be identified directly from genome databases on the basis of minimal data derived by mass spectrometry. As has already happened in genomics, increased automation of sample handling, analysis, and the interpretation of results will generate an avalanche of qualitative and quantitative proteomic data. Protein-protein interactions can be analyzed directly by precipitation of a tagged bait followed by mass spectrometric identification of its binding partners. By these and similar strategies, entire protein complexes, signaling pathways, and whole organelles are being characterized. Posttranslational modifications remain difficult to analyze but are starting to yield to generic strategies.

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

The efficacy of chimeric antigen receptor (CAR) T cell therapy against poorly responding tumors can be enhanced by administering the cells in combination with immune checkpoint blockade inhibitors. Alternatively, the CAR construct has been engineered to coexpress factors that boost CAR-T cell function in the tumor microenvironment. We modified CAR-T cells to secrete PD-1-blocking single-chain variable fragments (scFv). These scFv-secreting CAR-T cells acted in both a paracrine and autocrine manner to improve the anti-tumor activity of CAR-T cells and bystander tumor-specific T cells in clinically relevant syngeneic and xenogeneic mouse models of PD-L1 hematologic and solid tumors. The efficacy was similar to or better than that achieved by combination therapy with CAR-T cells and a checkpoint inhibitor. This approach may improve safety, as the secreted scFvs remained localized to the tumor, protecting CAR-T cells from PD-1 inhibition, which could potentially avoid toxicities associated with systemic checkpoint inhibition.

Chimeric antigen receptors (CARs) are synthetic antigen receptors that reprogram T cell specificity, function and persistence1. Patient-derived CAR T cells have demonstrated remarkable efficacy against a range of B-cell malignancies1–3, and the results of early clinical trials suggest activity in multiple myeloma4. Despite high complete response rates, relapses occur in a large fraction of patients; some of these are antigen-negative and others are antigen-low1,2,4–9. Unlike the mechanisms that result in complete and permanent antigen loss6,8,9, those that lead to escape of antigen-low tumours remain unclear. Here, using mouse models of leukaemia, we show that CARs provoke reversible antigen loss through trogocytosis, an active process in which the target antigen is transferred to T cells, thereby decreasing target density on tumour cells and abating T cell activity by promoting fratricide T cell killing and T cell exhaustion. These mechanisms affect both CD28- and 4-1BB-based CARs, albeit differentially, depending on antigen density. These dynamic features can be offset by cooperative killing and combinatorial targeting to augment tumour responses to immunotherapy.

SummaryT lymphocytes recognize antigens consisting ofpeptides presented by class I and II major histocompatibility complex (MHC) molecules. The peptides identified so far have been predictable from the amino acid sequences of proteins. We have identified the natural peptide target of a CTL clone that recognizes the tyrosinase gene product on melanoma cells. The peptide results from posttranslational conversion ofasparagine to aspartic acid. This change is of central importance for peptide recognition by melanoma-specific T cells, but has no impact on peptide binding to the MHC molecule. This posttranslational modification has not been previously described for any MHC-associated peptide and represents the first demonstration of posttranslational modification of a naturally processed class I-associated peptide. This observation is relevant to the identification and prediction of potential peptide antigens. The most likely mechanism for production of this peptide leads to the suggestion that antigenic peptides can be derived from proteins that are translated into the endoplasmic reticulum.C lass I molecules of MHC bind to peptides derived from intracellular pathogens or from proteins expressed in tumor cells, and present them on the cell surface to the host immune system (1-3). Identification of the specific peptides that constitute T cell epitopes has been difficult without prior knowledge of the source protein. However, peptides recognized by human melanoma--specific T cells have recently been identified from five proteins using two alternative strategies. One approach has been to generate genomic or cDNA libraries from tumor cells followed by transfection of progressively smaller subsets of these molecular clones into cells that express the appropriate MHC molecule, but not the tumor-specific epitope (4--14). Molecular clones that encode T cell epitopes are identified by their ability to reconstitute tumor-specific T cell recognition of the transfected cells. The exact T cell epitope is then identified by a combination of molecular subcloningThe contributions of the first two authors were equivalent and their order should be considered arbitrary. and the use of synthetic peptides based on the predicted amino acid sequence. This approach led to the identification of antigens encoded by genes whose expression is specific for tumors, such as MAGE and of other antigens related to melanocyte differentiation such as tyrosinase (4, 13). In the second approach, naturally occurring peptides associated with MHC molecules on the tumor cells are directly extracted, fractionated by HPLC, and used to reconstitute recognition by melanoma-specific CTL of a nonmelanoma cell expressing appropriate MHC molecules (15). The peptide epitope within a reconstituting peptide fraction is identified and sequenced by tandem mass spectrometry (16,17). Using this approach, a peptide, YLEPG-PVTA, from the protein Pmel-17/gp100, was identified as an epitope for HLA-A2.1-restricted, melanoma-specific CTL from multiple individuals (18).

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Activating mutations in PIK3CA, the gene encoding phosphoinositide-(3)-kinase α (PI3Kα), are frequently found in estrogen receptor (ER)–positive breast cancer. PI3Kα inhibitors, now in late-stage clinical development, elicit a robust compensatory increase in ER-dependent transcription that limits therapeutic efficacy. We investigated the chromatin-based mechanisms leading to the activation of ER upon PI3Kα inhibition. We found that PI3Kα inhibition mediates an open chromatin state at the ER target loci in breast cancer models and clinical samples. KMT2D, a histone H3 lysine 4 methyltransferase, is required for FOXA1, PBX1, and ER recruitment and activation. AKT binds and phosphorylates KMT2D, attenuating methyltransferase activity and ER function, whereas PI3Kα inhibition enhances KMT2D activity. These findings uncover a mechanism that controls the activation of ER by the posttranslational modification of epigenetic regulators, providing a rationale for epigenetic therapy in ER-positive breast cancer.