Functional Impact of Protein-RNA Variation in Clinical Cancer Analyses.

Comprehensive molecular characterization of tumors aims to uncover cancer vulnerabilities, drug resistance mechanisms, and biomarkers. Identification of cancer drivers was suggested as the basis for patient-tailored therapy, and transcriptomic analyses were proposed to reveal the phenotypic outcome of cancer mutations. With the maturation of the proteomic field, studies of protein-RNA discrepancies suggested that RNA analyses are insufficient to predict cellular functions. In this article we discuss the importance of direct mRNA-protein comparisons in clinical cancer studies. We make use of the large amount of data generated by the Clinical Proteomic Tumor Analysis Consortium, which includes protein and mRNA expression analyses from the exact same samples. Analysis of protein-RNA correlations showed marked differences among cancer types, and highlighted the protein-RNA similarities and discrepancies among functional pathways and drug targets. Additionally, unsupervised clustering of the data based on protein or RNA showed substantial differences in tumor classification and the cellular processes that differentiate between clusters. These analyses show the difficulty to predict protein levels from mRNAs, and the critical role of protein analyses for phenotypic tumor characterization.

Deoxyhypusine hydroxylase: A novel therapeutic target differentially expressed in short-term vs long-term survivors of glioblastoma.

Glioblastoma (GB) is the most aggressive neoplasm of the brain. Poor prognosis is mainly attributed to tumor heterogeneity, invasiveness and drug resistance. Only a small fraction of GB patients survives longer than 24 months from the time of diagnosis (ie, long-term survivors [LTS]). In our study, we aimed to identify molecular markers associated with favorable GB prognosis as a basis to develop therapeutic applications to improve patients' outcome. We have recently assembled a proteogenomic dataset of 87 GB clinical samples of varying survival rates. Following RNA-seq and mass spectrometry (MS)-based proteomics analysis, we identified several differentially expressed genes and proteins, including some known cancer-related pathways and some less established that showed higher expression in short-term (<6 months) survivors (STS) compared to LTS. One such target found was deoxyhypusine hydroxylase (DOHH), which is known to be involved in the biosynthesis of hypusine, an unusual amino acid essential for the function of the eukaryotic translation initiation factor 5A (eIF5A), which promotes tumor growth. We consequently validated DOHH overexpression in STS samples by quantitative polymerase chain reaction (qPCR) and immunohistochemistry. We further showed robust inhibition of proliferation, migration and invasion of GB cells following silencing of DOHH with short hairpin RNA (shRNA) or inhibition of its activity with small molecules, ciclopirox and deferiprone. Moreover, DOHH silencing led to significant inhibition of tumor progression and prolonged survival in GB mouse models. Searching for a potential mechanism by which DOHH promotes tumor aggressiveness, we found that it supports the transition of GB cells to a more invasive phenotype via epithelial-mesenchymal transition (EMT)-related pathways.

An Exercise-Induced Metabolic Shield in Distant Organs Blocks Cancer Progression and Metastatic Dissemination.

Exercise prevents cancer incidence and recurrence, yet the underlying mechanism behind this relationship remains mostly unknown. Here we report that exercise induces the metabolic reprogramming of internal organs that increases nutrient demand and protects against metastatic colonization by limiting nutrient availability to the tumor, generating an exercise-induced metabolic shield. Proteomic and ex vivo metabolic capacity analyses of murine internal organs revealed that exercise induces catabolic processes, glucose uptake, mitochondrial activity, and GLUT expression. Proteomic analysis of routinely active human subject plasma demonstrated increased carbohydrate utilization following exercise. Epidemiologic data from a 20-year prospective study of a large human cohort of initially cancer-free participants revealed that exercise prior to cancer initiation had a modest impact on cancer incidence in low metastatic stages but significantly reduced the likelihood of highly metastatic cancer. In three models of melanoma in mice, exercise prior to cancer injection significantly protected against metastases in distant organs. The protective effects of exercise were dependent on mTOR activity, and inhibition of the mTOR pathway with rapamycin treatment ex vivo reversed the exercise-induced metabolic shield. Under limited glucose conditions, active stroma consumed significantly more glucose at the expense of the tumor. Collectively, these data suggest a clash between the metabolic plasticity of cancer and exercise-induced metabolic reprogramming of the stroma, raising an opportunity to block metastasis by challenging the metabolic needs of the tumor. SIGNIFICANCE: Exercise protects against cancer progression and metastasis by inducing a high nutrient demand in internal organs, indicating that reducing nutrient availability to tumor cells represents a potential strategy to prevent metastasis. See related commentary by Zerhouni and Piskounova, p. 4124.

Proteomic analysis of necroptotic extracellular vesicles.

Necroptosis is a regulated and inflammatory form of cell death. We, and others, have previously reported that necroptotic cells release extracellular vesicles (EVs). We have found that necroptotic EVs are loaded with proteins, including the phosphorylated form of the key necroptosis-executing factor, mixed lineage kinase domain-like kinase (MLKL). However, neither the exact protein composition, nor the impact, of necroptotic EVs have been delineated. To characterize their content, EVs from necroptotic and untreated U937 cells were isolated and analyzed by mass spectrometry-based proteomics. A total of 3337 proteins were identified, sharing a high degree of similarity with exosome proteome databases, and clearly distinguishing necroptotic and control EVs. A total of 352 proteins were significantly upregulated in the necroptotic EVs. Among these were MLKL and caspase-8, as validated by immunoblot. Components of the ESCRTIII machinery and inflammatory signaling were also upregulated in the necroptotic EVs, as well as currently unreported components of vesicle formation and transport, and necroptotic signaling pathways. Moreover, we found that necroptotic EVs can be phagocytosed by macrophages to modulate cytokine and chemokine secretion. Finally, we uncovered that necroptotic EVs contain tumor neoantigens, and are enriched with components of antigen processing and presentation. In summary, our study reveals a new layer of regulation during the early stage of necroptosis, mediated by the secretion of specific EVs that influences the microenvironment and may instigate innate and adaptive immune responses. This study sheds light on new potential players in necroptotic signaling and its related EVs, and uncovers the functional tasks accomplished by the cargo of these necroptotic EVs.

Proteogenomics of glioblastoma associates molecular patterns with survival.

Glioblastoma (GBM) is the most aggressive form of glioma, with poor prognosis exhibited by most patients, and a median survival time of less than 2 years. We assemble a cohort of 87 GBM patients whose survival ranges from less than 3 months and up to 10 years and perform both high-resolution mass spectrometry proteomics and RNA sequencing (RNA-seq). Integrative analysis of protein expression, RNA expression, and patient clinical information enables us to identify specific immune, metabolic, and developmental processes associated with survival as well as determine whether they are shared between expression layers or are layer specific. Our analyses reveal a stronger association between proteomic profiles and survival and identify unique protein-based classification, distinct from the established RNA-based classification. By integrating published single-cell RNA-seq data, we find a connection between subpopulations of GBM tumors and survival. Overall, our findings establish proteomic heterogeneity in GBM as a gateway to understanding poor survival.

Across the Globe: Proteogenomic Landscapes of Lung Cancer.

In this issue of Cell, articles by Gillette et al., Chen et al., and Xu, et al. collectively provide a deep and comprehensive proteogenomic analysis of lung adenocarcinoma, addressing differences in patient ethnicity and smoking background. They highlight the importance of associating genomics with the functional proteomic outcome.

Proteomics of Melanoma Response to Immunotherapy Reveals Mitochondrial Dependence.

Immunotherapy has revolutionized cancer treatment, yet most patients do not respond. Here, we investigated mechanisms of response by profiling the proteome of clinical samples from advanced stage melanoma patients undergoing either tumor infiltrating lymphocyte (TIL)-based or anti- programmed death 1 (PD1) immunotherapy. Using high-resolution mass spectrometry, we quantified over 10,300 proteins in total and ∼4,500 proteins across most samples in each dataset. Statistical analyses revealed higher oxidative phosphorylation and lipid metabolism in responders than in non-responders in both treatments. To elucidate the effects of the metabolic state on the immune response, we examined melanoma cells upon metabolic perturbations or CRISPR-Cas9 knockouts. These experiments indicated lipid metabolism as a regulatory mechanism that increases melanoma immunogenicity by elevating antigen presentation, thereby increasing sensitivity to T cell mediated killing both in vitro and in vivo. Altogether, our proteomic analyses revealed association between the melanoma metabolic state and the response to immunotherapy, which can be the basis for future improvement of therapeutic response.

Simultaneous Integration of Multi-omics Data Improves the Identification of Cancer Driver Modules.

The identification of molecular pathways driving cancer progression is a fundamental challenge in cancer research. Most approaches to address it are limited in the number of data types they employ and perform data integration in a sequential manner. Here, we describe ModulOmics, a method to de novo identify cancer driver pathways, or modules, by integrating protein-protein interactions, mutual exclusivity of mutations and copy number alterations, transcriptional coregulation, and RNA coexpression into a single probabilistic model. To efficiently search and score the large space of candidate modules, ModulOmics employs a two-step optimization procedure that combines integer linear programming with stochastic search. Applied across several cancer types, ModulOmics identifies highly functionally connected modules enriched with cancer driver genes, outperforming state-of-the-art methods and demonstrating the power of using multiple omics data types simultaneously. On breast cancer subtypes, ModulOmics proposes unexplored connections supported by an independent patient cohort and independent proteomic and phosphoproteomic datasets.

Single-stranded DNA-binding protein recruits DNA polymerase V to primer termini on RecA-coated DNA.

Translesion DNA synthesis (TLS) by DNA polymerase V (polV) in Escherichia coli involves accessory proteins, including RecA and single-stranded DNA-binding protein (SSB). To elucidate the role of SSB in TLS we used an in vitro exonuclease protection assay and found that SSB increases the accessibility of 3' primer termini located at abasic sites in RecA-coated gapped DNA. The mutant SSB-113 protein, which is defective in protein-protein interactions, but not in DNA binding, was as effective as wild-type SSB in increasing primer termini accessibility, but deficient in supporting polV-catalyzed TLS. Consistently, the heterologous SSB proteins gp32, encoded by phage T4, and ICP8, encoded by herpes simplex virus 1, could replace E. coli SSB in the TLS reaction, albeit with lower efficiency. Immunoprecipitation experiments indicated that polV directly interacts with SSB and that this interaction is disrupted by the SSB-113 mutation. Taken together our results suggest that SSB functions to recruit polV to primer termini on RecA-coated DNA, operating by two mechanisms: 1) increasing the accessibility of 3' primer termini caused by binding of SSB to DNA and 2) a direct SSB-polV interaction mediated by the C terminus of SSB.