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Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.This Review examines recent developments in proteogenomics, key findings from the proteogenomic analyses of a wide range of cancers and emerging applications of proteogenomics to translational studies and immuno-oncology, as well as discussing future prospects regarding integration into clinical trials and patient care.

Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets. New tumor epitopes are discovered by ribosome profiling and immunopeptidome 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.

Pancreatic ductal adenocarcinoma (PDAC) has a collagen-rich dense extracellular matrix (ECM) that promotes malignancy of cancer cells and presents a barrier for drug delivery. Data analysis of our published mass spectrometry (MS)-based studies on enriched ECM from samples of progressive PDAC stages reveal that the C-terminal prodomains of fibrillar collagens are partially uncleaved in PDAC ECM, suggesting reduced procollagen C-proteinase activity. We further show that the enzyme responsible for procollagen C-proteinase activity, bone morphogenetic protein1 (BMP1), selectively suppresses tumor growth and metastasis in cells expressing high levels of COL1A1. Although BMP1, as a secreted proteinase, promotes fibrillar collagen deposition from both cancer cells and stromal cells, only cancer-cell-derived procollagen cleavage and deposition suppresses tumor malignancy. These studies reveal a role for cancer-cell-derived fibrillar collagen in selectively restraining tumor growth and suggest stratification of patients based on their tumor epithelial collagen I expression when considering treatments related to perturbation of fibrillar collagens. Pancreatic ductal adenocarcinoma has a collagen-rich dense extracellular matrix that promotes malignancy of cancer cells. Here, the authors show that fibrillar collagen that is cancer-cell-derived, but not stroma-derived, selectively restrains tumor growth under control of their pC-proteinase, BMP1.

Small ubiquitin-like modifier (SUMO) modification regulates numerous cellular processes. Unlike ubiquitin, detection of endogenous SUMOylated proteins is limited by the lack of naturally occurring protease sites in the C-terminal tail of SUMO proteins. Proteome-wide detection of SUMOylation sites on target proteins typically requires ectopic expression of mutant SUMOs with introduced tryptic sites. Here, we report a method for proteome-wide, site-level detection of endogenous SUMOylation that uses α-lytic protease, WaLP. WaLP digestion of SUMOylated proteins generates peptides containing SUMO-remnant diglycyl-lysine (KGG) at the site of SUMO modification. Using previously developed immuno-affinity isolation of KGG-containing peptides followed by mass spectrometry, we identified 1209 unique endogenous SUMO modification sites. We also demonstrate the impact of proteasome inhibition on ubiquitin and SUMO-modified proteomes using parallel quantitation of ubiquitylated and SUMOylated peptides. This methodological advancement enables determination of endogenous SUMOylated proteins under completely native conditions. SUMOylation is post-translational modification implicated in several biological pathways. Here the authors describe an approach for the global profiling of SUMO attachment sites under native conditions that also allows the parallel determination of SUMO and Ub attachments.

A mass spectrometry–based method using serial enrichments of different post-translational modifications (SEPTM) enables high-coverage proteomic analysis of multiple PTMs from a single biological sample. 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.

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. 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.

The angiogenic switch, the time at which a tumor becomes vascularized, is a critical step in tumor progression. Indeed, without blood supply, tumors will fail to grow beyond 1 mm 3 and are unlikely to disseminate. The extracellular matrix (ECM), a major component of the tumor microenvironment, is known to undergo significant changes during angiogenesis and tumor progression. However the extent of these changes remains unknown. In this study, we used quantitative proteomics to profile the composition of the ECM of pancreatic islets in a mouse model of insulinoma characterized by a precisely timed angiogenic switch. Out of the 120 ECM proteins quantified, 35 were detected in significantly different abundance as pancreatic islets progressed from being hyperplastic to angiogenic to insulinomas. Among these, the core ECM proteins, EFEMP1, fibrillin 1, and periostin were found in higher abundance, and decorin, Dmbt1, hemicentin, and Vwa5 in lower abundance. The angiogenic switch being a common feature of solid tumors, we propose that some of the proteins identified represent potential novel anti-angiogenic targets. In addition, we report the characterization of the ECM composition of normal pancreatic islets and propose that this could be of interest for the design of tissue-engineering strategies for treatment of diabetes.

Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample. We demonstrate that the depth of coverage and quantitative precision of each ‘ome is not compromised by serialization, and the addition of HLA immunopeptidomics enables the identification of peptides derived from cancer/testis antigens and patient specific neoantigens. We evaluate the technical feasibility of the MONTE workflow using a small cohort of patient lung adenocarcinoma tumors. Patient samples are often available in limited amounts, restricting the number of possible omics analyses. Here the authors present MONTE, a workflow that enables serial HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome data collection from patient samples.

Animal cells initiate cytokinesis in parallel with anaphase onset, when an actomyosin ring assembles and constricts through localized activation of the small GTPase RhoA, giving rise to a cleavage furrow. Furrow formation relies on positional cues provided by anaphase spindle microtubules (MTs), but how such cues are generated remains unclear. Using chemical genetics to achieve both temporal and spatial control, we show that the self-organized delivery of Polo-like kinase 1 (Plk1) to the midzone and its local phosphorylation of a MT-bound substrate are critical for generating this furrow-inducing signal. When Plk1 was active but unable to target itself to this equatorial landmark, both cortical RhoA recruitment and furrow induction failed to occur, thus recapitulating the effects of anaphase-specific Plk1 inhibition. Using tandem mass spectrometry and phosphospecific antibodies, we found that Plk1 binds and directly phosphorylates the HsCYK-4 subunit of centralspindlin (also known as MgcRacGAP) at the midzone. At serine 157, this modification creates a major docking site for the tandem BRCT repeats of the Rho GTP exchange factor Ect2. Cells expressing only a nonphosphorylatable form of HsCYK-4 failed to localize Ect2 at the midzone and were severely impaired in cleavage furrow formation, implying that HsCYK-4 is Plk1's rate-limiting target upstream of RhoA. Conversely, tethering an inhibitor-resistant allele of Plk1 to HsCYK-4 allowed furrows to form despite global inhibition of all other Plk1 molecules in the cell. Our findings illuminate two key mechanisms governing the initiation of cytokinesis in human cells and illustrate the power of chemical genetics to probe such regulation both in time and space.