Biomarker Predictors of Clinical Efficacy of the Anti-IgE Biologic Omalizumab in Severe Asthma in Adults: Results of the SoMOSA Study.

Background: The anti-IgE monoclonal antibody omalizumab is widely used for severe asthma. This study aimed to identify biomarkers that predict clinical improvement during 1 year of omalizumab treatment. Methods: One-year open-label Study of Mechanisms of action of Omalizumab in Severe Asthma (SoMOSA) involving 216 patients with severe (Global Initiative for Asthma step 4/5) uncontrolled atopic asthma (at least two severe exacerbations in the previous year) taking high-dose inhaled corticosteroids and long-acting ß-agonists with or without maintenance oral corticosteroids. It had two phases: 0-16 weeks, to assess early clinical improvement by Global Evaluation of Therapeutic Effectiveness (GETE); and 16-52 weeks, to assess late responses based on ⩾50% reduction in exacerbations or mOCS dose. All participants provided samples (exhaled breath, blood, sputum, urine) before and after 16 weeks of omalizumab treatment. Measurements and Main Results: A total of 191 patients completed phase 1; 63% had early improvement. Of 173 who completed phase 2, 69% had reduced exacerbations by ⩾50% and 57% (37 of 65) taking mOCSs had reduced their dose by ⩾50%. The primary outcomes 2,3-dinor-11-ß-PGF2α, GETE score, and standard clinical biomarkers (blood and sputum eosinophils, exhaled nitric oxide, serum IgE) did not predict either clinical response. Five volatile organic compounds and five plasma lipid biomarkers strongly predicted the ⩾50% reduction in exacerbations (receiver operating characteristic areas under the curve of 0.780 and 0.922, respectively) and early responses (areas under the curve of 0.835 and 0.949, respectively). In an independent cohort, gas chromatography/mass spectrometry biomarkers differentiated between severe and mild asthma. Conclusions: This is the first discovery of omics biomarkers that predict improvement in asthma with biologic agent treatment. Prospective validation and development for clinical use is justified.

Immunopeptidomic analysis of influenza A virus infected human tissues identifies internal proteins as a rich source of HLA ligands.

CD8+ and CD4+ T cells provide cell-mediated cross-protection against multiple influenza strains by recognising epitopes bound as peptides to human leukocyte antigen (HLA) class I and -II molecules respectively. Two challenges in identifying the immunodominant epitopes needed to generate a universal T cell influenza vaccine are: A lack of cell models susceptible to influenza infection which present population-prevalent HLA allotypes, and an absence of a reliable in-vitro method of identifying class II HLA peptides. Here we present a mass spectrometry-based proteomics strategy for identifying viral peptides derived from the A/H3N2/X31 and A/H3N2/Wisconsin/67/2005 strains of influenza. We compared the HLA-I and -II immunopeptidomes presented by ex-vivo influenza challenged human lung tissues. We then compared these with directly infected immortalised macrophage-like cell line (THP1) and primary dendritic cells fed apoptotic influenza-infected respiratory epithelial cells. In each of the three experimental conditions we identified novel influenza class I and II HLA peptides with motifs specific for the host allotype. Ex-vivo infected lung tissues yielded few class-II HLA peptides despite significant numbers of alveolar macrophages, including directly infected ones, present within the tissues. THP1 cells presented HLA-I viral peptides derived predominantly from internal proteins. Primary dendritic cells presented predominantly viral envelope-derived HLA class II peptides following phagocytosis of apoptotic infected cells. The most frequent viral source protein for HLA-I and -II was matrix 1 protein (M1). This work confirms that internal influenza proteins, particularly M1, are a rich source of CD4+ and CD8+ T cell epitopes. Moreover, we demonstrate the utility of two ex-vivo fully human infection models which enable direct HLA-I and -II immunopeptide identification without significant viral tropism limitations. Application of this epitope discovery strategy in a clinical setting will provide more certainty in rational vaccine design against influenza and other emergent viruses.

A high throughput immuno-affinity mass spectrometry method for detection and quantitation of SARS-CoV-2 nucleoprotein in human saliva and its comparison with RT-PCR, RT-LAMP, and lateral flow rapid antigen test.

OBJECTIVES: Many reverse transcription polymerase chain reaction (RT-PCR) methods exist that can detect SARS-CoV-2 RNA in different matrices. RT-PCR is highly sensitive, although viral RNA may be detected long after active infection has taken place. SARS-CoV-2 proteins have shorter detection windows hence their detection might be more meaningful. Given salivary droplets represent a main source of transmission, we explored the detection of viral RNA and protein using four different detection platforms including SISCAPA peptide immunoaffinity liquid chromatography-mass spectrometry (SISCAPA-LC-MS) using polyclonal capture antibodies. METHODS: The SISCAPA-LC MS method was compared to RT-PCR, RT-loop-mediated isothermal amplification (RT-LAMP), and a lateral flow rapid antigen test (RAT) for the detection of virus material in the drool saliva of 102 patients hospitalised after infection with SARS-CoV-2. Cycle thresholds (Ct) of RT-PCR (E gene) were compared to RT-LAMP time-to-positive (TTP) (NE and Orf1a genes), RAT optical densitometry measurements (test line/control line ratio) and to SISCAPA-LC-MS for measurements of viral protein. RESULTS: SISCAPA-LC-MS showed low sensitivity (37.7 %) but high specificity (89.8 %). RAT showed lower sensitivity (24.5 %) and high specificity (100 %). RT-LAMP had high sensitivity (83.0 %) and specificity (100.0 %). At high initial viral RNA loads (<20 Ct), results obtained using SISCAPA-LC-MS correlated with RT-PCR (R2 0.57, p-value 0.002). CONCLUSIONS: Detection of SARS-CoV-2 nucleoprotein in saliva was less frequent than the detection of viral RNA. The SISCAPA-LC-MS method allowed processing of multiple samples in <150 min and was scalable, enabling high throughput.

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

BACKGROUND: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. OBJECTIVE: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. METHODS: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. RESULTS: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. CONCLUSION: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

Identification of neoantigens in oesophageal adenocarcinoma.

Oesophageal adenocarcinoma (OAC) has a relatively poor long-term survival and limited treatment options. Promising targets for immunotherapy are short peptide neoantigens containing tumour mutations, presented to cytotoxic T-cells by human leucocyte antigen (HLA) molecules. Despite an association between putative neoantigen abundance and therapeutic response across cancers, immunogenic neoantigens are challenging to identify. Here we characterized the mutational and immunopeptidomic landscapes of tumours from a cohort of seven patients with OAC. We directly identified one HLA-I presented neoantigen from one patient, and report functional T-cell responses from a predicted HLA-II neoantigen in a second patient. The predicted class II neoantigen contains both HLA I and II binding motifs. Our exploratory observations are consistent with previous neoantigen studies in finding that neoantigens are rarely directly observed, and an identification success rate following prediction in the order of 10%. However, our identified putative neoantigen is capable of eliciting strong T-cell responses, emphasizing the need for improved strategies for neoantigen identification.

Topological data analysis identifies molecular phenotypes of idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a debilitating, progressive disease with a median survival time of 3-5 years. Diagnosis remains challenging and disease progression varies greatly, suggesting the possibility of distinct subphenotypes. METHODS AND RESULTS: We analysed publicly available peripheral blood mononuclear cell expression datasets for 219 IPF, 411 asthma, 362 tuberculosis, 151 healthy, 92 HIV and 83 other disease samples, totalling 1318 patients. We integrated the datasets and split them into train (n=871) and test (n=477) cohorts to investigate the utility of a machine learning model (support vector machine) for predicting IPF. A panel of 44 genes predicted IPF in a background of healthy, tuberculosis, HIV and asthma with an area under the curve of 0.9464, corresponding to a sensitivity of 0.865 and a specificity of 0.89. We then applied topological data analysis to investigate the possibility of subphenotypes within IPF. We identified five molecular subphenotypes of IPF, one of which corresponded to a phenotype enriched for death/transplant. The subphenotypes were molecularly characterised using bioinformatic and pathway analysis tools identifying distinct subphenotype features including one which suggests an extrapulmonary or systemic fibrotic disease. CONCLUSIONS: Integration of multiple datasets, from the same tissue, enabled the development of a model to accurately predict IPF using a panel of 44 genes. Furthermore, topological data analysis identified distinct subphenotypes of patients with IPF which were defined by differences in molecular pathobiology and clinical characteristics.

The differentiation state of the Schwann cell progenitor drives phenotypic variation between two contagious cancers.

Contagious cancers are a rare pathogenic phenomenon in which cancer cells gain the ability to spread between genetically distinct hosts. Nine examples have been identified across marine bivalves, dogs and Tasmanian devils, but the Tasmanian devil is the only mammalian species known to have given rise to two distinct lineages of contagious cancer, termed Devil Facial Tumour 1 (DFT1) and 2 (DFT2). Remarkably, DFT1 and DFT2 arose independently from the same cell type, a Schwann cell, and while their ultra-structural features are highly similar they exhibit variation in their mutational signatures and infection dynamics. As such, DFT1 and DFT2 provide a unique framework for investigating how a common progenitor cell can give rise to distinct contagious cancers. Using a proteomics approach, we show that DFT1 and DFT2 are derived from Schwann cells in different differentiation states, with DFT2 carrying a molecular signature of a less well differentiated Schwann cell. Under inflammatory signals DFT1 and DFT2 have different gene expression profiles, most notably involving Schwann cell markers of differentiation, reflecting the influence of their distinct origins. Further, DFT2 cells express immune cell markers typically expressed during nerve repair, consistent with an ability to manipulate their extracellular environment, facilitating the cell's ability to transmit between individuals. The emergence of two contagious cancers in the Tasmanian devil suggests that the inherent plasticity of Schwann cells confers a vulnerability to the formation of contagious cancers.

The role of inflammation in anxiety and depression in the European U-BIOPRED asthma cohorts.

BACKGROUND: Growing evidence indicates high comorbid anxiety and depression in patients with asthma. However, the mechanisms underlying this comorbid condition remain unclear. The aim of this study was to investigate the role of inflammation in comorbid anxiety and depression in three asthma patient cohorts of the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project. METHODS: U-BIOPRED was conducted by a European Union consortium of 16 academic institutions in 11 European countries. A subset dataset from subjects with valid anxiety and depression measures and a large blood biomarker dataset were analysed, including 198 non-smoking patients with severe asthma (SAn), 65 smoking patients with severe asthma (SAs), 61 non-smoking patients with mild-to-moderate asthma (MMA), and 20 healthy non-smokers (HC). The Hospital Anxiety and Depression Scale was used to measure anxiety and depression and a series of inflammatory markers were analysed by the SomaScan v3 platform (SomaLogic, Boulder, Colo). ANOVA and the Kruskal-Wallis test were used for multiple-group comparisons as appropriate. RESULTS: There were significant group effects on anxiety and depression among the four cohort groups (p < 0.05). Anxiety and depression of SAn and SAs groups were significantly higher than that of MMA and HC groups (p < 0.05. There were significant differences in serum IL6, MCP1, CCL18, CCL17, IL8, and Eotaxin among the four groups (p < 0.05). Depression was significantly associated with IL6, MCP1, CCL18 level, and CCL17; whereas anxiety was associated with CCL17 only (p < 0.05). CONCLUSIONS: The current study suggests that severe asthma patients are associated with higher levels of anxiety and depression, and inflammatory responses may underlie this comorbid condition.

Operation Moonshot: rapid translation of a SARS-CoV-2 targeted peptide immunoaffinity liquid chromatography-tandem mass spectrometry test from research into routine clinical use.

OBJECTIVES: During 2020, the UK's Department of Health and Social Care (DHSC) established the Moonshot programme to fund various diagnostic approaches for the detection of SARS-CoV-2, the pathogen behind the COVID-19 pandemic. Mass spectrometry was one of the technologies proposed to increase testing capacity. METHODS: Moonshot funded a multi-phase development programme, bringing together experts from academia, industry and the NHS to develop a state-of-the-art targeted protein assay utilising enrichment and liquid chromatography tandem mass spectrometry (LC-MS/MS) to capture and detect low levels of tryptic peptides derived from SARS-CoV-2 virus. The assay relies on detection of target peptides, ADETQALPQRK (ADE) and AYNVTQAFGR (AYN), derived from the nucleocapsid protein of SARS-CoV-2, measurement of which allowed the specific, sensitive, and robust detection of the virus from nasopharyngeal (NP) swabs. The diagnostic sensitivity and specificity of LC-MS/MS was compared with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) via a prospective study. RESULTS: Analysis of NP swabs (n=361) with a median RT-qPCR quantification cycle (Cq) of 27 (range 16.7-39.1) demonstrated diagnostic sensitivity of 92.4% (87.4-95.5), specificity of 97.4% (94.0-98.9) and near total concordance with RT-qPCR (Cohen's Kappa 0.90). Excluding Cq>32 samples, sensitivity was 97.9% (94.1-99.3), specificity 97.4% (94.0-98.9) and Cohen's Kappa 0.95. CONCLUSIONS: This unique collaboration between academia, industry and the NHS enabled development, translation, and validation of a SARS-CoV-2 method in NP swabs to be achieved in 5 months. This pilot provides a model and pipeline for future accelerated development and implementation of LC-MS/MS protein/peptide assays into the routine clinical laboratory.

Bidirectional epithelial-mesenchymal crosstalk provides self-sustaining profibrotic signals in pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is the prototypic progressive fibrotic lung disease with a median survival of 2 to 4 years. Injury to and/or dysfunction of the alveolar epithelium is strongly implicated in IPF disease initiation, but the factors that determine whether fibrosis progresses rather than normal tissue repair occurs remain poorly understood. We previously demonstrated that zinc finger E-box-binding homeobox 1-mediated epithelial-mesenchymal transition in human alveolar epithelial type II (ATII) cells augments transforming growth factor-ß-induced profibrogenic responses in underlying lung fibroblasts via paracrine signaling. Here, we investigated bidirectional epithelial-mesenchymal crosstalk and its potential to drive fibrosis progression. RNA-Seq of lung fibroblasts exposed to conditioned media from ATII cells undergoing RAS-induced epithelial-mesenchymal transition identified many differentially expressed genes including those involved in cell migration and extracellular matrix regulation. We confirmed that paracrine signaling between RAS-activated ATII cells and fibroblasts augmented fibroblast recruitment and demonstrated that this involved a zinc finger E-box-binding homeobox 1-tissue plasminogen activator axis. In a reciprocal fashion, paracrine signaling from transforming growth factor-ß-activated lung fibroblasts or IPF fibroblasts induced RAS activation in ATII cells, at least partially through the secreted protein acidic and rich in cysteine, which may signal via the epithelial growth factor receptor via epithelial growth factor-like repeats. Together, these data identify that aberrant bidirectional epithelial-mesenchymal crosstalk in IPF drives a chronic feedback loop that maintains a wound-healing phenotype and provides self-sustaining profibrotic signals.

Modulation of hepatic stellate cells by Mutaflor® probiotic in non-alcoholic fatty liver disease management.

BACKGROUND: NAFLD and NASH are emerging as primary causes of chronic liver disease, indicating a need for an effective treatment. Mutaflor® probiotic, a microbial treatment of interest, was effective in sustaining remission in ulcerative colitis patients. OBJECTIVE: To construct a genetic-epigenetic network linked to HSC signaling as a modulator of NAFLD/NASH pathogenesis, then assess the effects of Mutaflor® on this network. METHODS: First, in silico analysis was used to construct a genetic-epigenetic network linked to HSC signaling. Second, an investigation using rats, including HFHSD induced NASH and Mutaflor® treated animals, was designed. Experimental procedures included biochemical and histopathologic analysis of rat blood and liver samples. At the molecular level, the expression of genetic (FOXA2, TEAD2, and LATS2 mRNAs) and epigenetic (miR-650, RPARP AS-1 LncRNA) network was measured by real-time PCR. PCR results were validated with immunohistochemistry (α-SMA and LATS2). Target effector proteins, IL-6 and TGF-ß, were estimated by ELISA. RESULTS: Mutaflor® administration minimized biochemical and histopathologic alterations caused by NAFLD/NASH. HSC activation and expression of profibrogenic IL-6 and TGF-ß effector proteins were reduced via inhibition of hedgehog and hippo pathways. Pathways may have been inhibited through upregulation of RPARP AS-1 LncRNA which in turn downregulated the expression of miR-650, FOXA2 mRNA and TEAD2 mRNA and upregulated LATS2 mRNA expression. CONCLUSION: Mutaflor® may slow the progression of NAFLD/NASH by modulating a genetic-epigenetic network linked to HSC signaling. The probiotic may be a useful modality for the prevention and treatment of NAFLD/NASH.

The immunopeptidomes of two transmissible cancers and their host have a common, dominant peptide motif.

Transmissible cancers are malignant cells that can spread between individuals of a population, akin to both a parasite and a mobile graft. The survival of the Tasmanian devil, the largest remaining marsupial carnivore, is threatened by the remarkable emergence of two independent lineages of transmissible cancer, devil facial tumour (DFT) 1 and devil facial tumour 2 (DFT2). To aid the development of a vaccine and to interrogate how histocompatibility barriers can be overcome, we analysed the peptides bound to major histocompatibility complex class I (MHC-I) molecules from Tasmanian devil cells and representative cell lines of each transmissible cancer. Here, we show that DFT1 + IFN-γ and DFT2 cell lines express a restricted repertoire of MHC-I allotypes compared with fibroblast cells, potentially reducing the breadth of peptide presentation. Comparison of the peptidomes from DFT1 + IFNγ, DFT2 and host fibroblast cells demonstrates a dominant motif, despite differences in MHC-I allotypes between the cell lines, with preference for a hydrophobic leucine residue at position 3 and position Ω of peptides. DFT1 and DFT2 both present peptides derived from neural proteins, which reflects a shared cellular origin that could be exploited for vaccine design. These results suggest that polymorphisms in MHC-I molecules between tumours and host can be 'hidden' by a common peptide motif, providing the potential for permissive passage of infectious cells and demonstrating complexity in mammalian histocompatibility barriers.

IL-17-high asthma with features of a psoriasis immunophenotype.

BACKGROUND: The role of IL-17 immunity is well established in patients with inflammatory diseases, such as psoriasis and inflammatory bowel disease, but not in asthmatic patients, in whom further study is required. OBJECTIVE: We sought to undertake a deep phenotyping study of asthmatic patients with upregulated IL-17 immunity. METHODS: Whole-genome transcriptomic analysis was performed by using epithelial brushings, bronchial biopsy specimens (91 asthmatic patients and 46 healthy control subjects), and whole blood samples (n = 498) from the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort. Gene signatures induced in vitro by IL-17 and IL-13 in bronchial epithelial cells were used to identify patients with IL-17-high and IL-13-high asthma phenotypes. RESULTS: Twenty-two of 91 patients were identified with IL-17, and 9 patients were identified with IL-13 gene signatures. The patients with IL-17-high asthma were characterized by risk of frequent exacerbations, airway (sputum and mucosal) neutrophilia, decreased lung microbiota diversity, and urinary biomarker evidence of activation of the thromboxane B2 pathway. In pathway analysis the differentially expressed genes in patients with IL-17-high asthma were shared with those reported as altered in psoriasis lesions and included genes regulating epithelial barrier function and defense mechanisms, such as IL1B, IL6, IL8, and ß-defensin. CONCLUSION: The IL-17-high asthma phenotype, characterized by bronchial epithelial dysfunction and upregulated antimicrobial and inflammatory response, resembles the immunophenotype of psoriasis, including activation of the thromboxane B2 pathway, which should be considered a biomarker for this phenotype in further studies, including clinical trials targeting IL-17.

Stratification of asthma phenotypes by airway proteomic signatures.

BACKGROUND: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. OBJECTIVE: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. METHODS: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. RESULTS: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. CONCLUSION: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.

Proteomic Profiling of Archived Tissue of Primary Melanoma Identifies Proteins Associated with Metastasis.

Formalin-fixed paraffin embedded (FFPE) clinical tissues represent an abundant and unique resource for translational proteomic studies. In the US, melanoma is the 5th and 6th most common cancer in men and women, respectively, affecting over 230,000 people annually and metastasising in 5-15% of cases. Median survival time for distant metastatic melanoma is 6-9 months with a 5-year-survival of < 15%. In this study, 24 primary FFPE tumours which have metastasised (P-M) and 24 primary FFPE tumours which did not metastasise (P-NM) were subjected to proteomic profiling. In total, 2750 proteins were identified, of which 16 were significantly differentially expressed. Analysis of TCGA data demonstrated that expression of the genes encoding for 6 of these 16 proteins had a significant effect on survival in cutaneous melanoma. Pathway analysis of the proteomics data revealed mechanisms likely involved in the process of melanoma metastasis, including cytoskeleton rearrangement, extracellular changes and immune system alterations. A machine learning prediction model scoring an AUC of 0.922, based on these 16 differentially expressed proteins was able to accurately classify samples into P-M and P-NM. This study has identified potential biomarkers and key processes relating to melanoma metastasis using archived clinical samples, providing a basis for future studies in larger cohorts.

Proteomic Analysis of Azacitidine-Induced Degradation Profiles Identifies Multiple Chromatin and Epigenetic Regulators Including Uhrf1 and Dnmt1 as Sensitive to Azacitidine.

DNA methylation is a critical epigenetic modification that is established and maintained across the genome by DNA methyltransferase enzymes (Dnmts). Altered patterns of DNA methylation are a frequent occurrence in many tumor genomes, and inhibitors of Dnmts have become important epigenetic drugs. Azacitidine is a cytidine analog that is incorporated into DNA and induces the specific inhibition and proteasomal-mediated degradation of Dnmts. The downstream effects of azacitidine on CpG methylation and on gene transcription have been widely studied in many systems, but how azacitidine impacts the proteome is not well-understood. In addition, with its specific ability to induce the rapid degradation of Dnmts (in particular, the primary maintenance DNA methyltransferase, Dnmt1), it may be employed as a specific chemical knockdown for investigating the Dnmt1-associated functional or physical interactome. In this study, we use quantitative proteomics to analyze the degradation profile of proteins in the nuclear proteome of cells treated with azacitidine. We identify specific proteins as well as multiple pathways and processes that are impacted by azacitidine. The Dnmt1 interaction partner, Uhrf1, exhibits significant azacitidine-induced degradation, and this azacitidine-induced degradation is independent of the levels of Dnmt1 protein. We identify multiple other chromatin- and epigenetic-associated factors, including the bromodomain-containing transcriptional regulator, Brd2. We show that azacitidine induces highly specific perturbations of the Dnmt1-associated proteome, and while interaction partners such as Uhrf1 are sensitive to azacitidine, others such as the Dnmt1 interaction partner and stability regulator, Usp7, are not. In summary, we have conducted the first comprehensive proteomic analysis of the azacitidine-sensitive nuclear proteome, and we show how 5-azacitidine can be used as a specific probe to explore Dnmt- and chromatin-related protein networks.

Multiproteomic and Transcriptomic Analysis of Oncogenic ß-Catenin Molecular Networks.

The dysregulation of Wnt signaling is a frequent occurrence in many different cancers. Oncogenic mutations of CTNNB1/ß-catenin, the key nuclear effector of canonical Wnt signaling, lead to the accumulation and stabilization of ß-catenin protein with diverse effects in cancer cells. Although the transcriptional response to Wnt/ß-catenin signaling activation has been widely studied, an integrated understanding of the effects of oncogenic ß-catenin on molecular networks is lacking. We used affinity-purification mass spectrometry (AP-MS), label-free liquid chromatography-tandem mass spectrometry, and RNA-Seq to compare protein-protein interactions, protein expression, and gene expression in colorectal cancer cells expressing mutant (oncogenic) or wild-type ß-catenin. We generate an integrated molecular network and use it to identify novel protein modules that are associated with mutant or wild-type ß-catenin. We identify a DNA methyltransferase I associated subnetwork that is enriched in cells with mutant ß-catenin and a subnetwork enriched in wild-type cells associated with the CDKN2A tumor suppressor, linking these processes to the transformation of colorectal cancer cells through oncogenic ß-catenin signaling. In summary, multiomics analysis of a defined colorectal cancer cell model provides a significantly more comprehensive identification of functional molecular networks associated with oncogenic ß-catenin signaling.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome.

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Direct evidence for conformational dynamics in major histocompatibility complex class I molecules.

Major histocompatibility complex class I molecules (MHC I) help protect jawed vertebrates by binding and presenting immunogenic peptides to cytotoxic T lymphocytes. Peptides are selected from a large diversity present in the endoplasmic reticulum. However, only a limited number of peptides complement the polymorphic MHC specificity determining pockets in a way that leads to high-affinity peptide binding and efficient antigen presentation. MHC I molecules possess an intrinsic ability to discriminate between peptides, which varies in efficiency between allotypes, but the mechanism of selection is unknown. Elucidation of the selection mechanism is likely to benefit future immune-modulatory therapies. Evidence suggests peptide selection involves transient adoption of alternative, presumably higher energy conformations than native peptide-MHC complexes. However, the instability of peptide-receptive MHC molecules has hindered characterization of such conformational plasticity. To investigate the dynamic nature of MHC, we refolded MHC proteins with peptides that can be hydrolyzed by UV light and thus released. We compared the resultant peptide-receptive MHC molecules with non-hydrolyzed peptide-loaded MHC complexes by monitoring the exchange of hydrogen for deuterium in solution. We found differences in hydrogen-deuterium exchange between peptide-loaded and peptide-receptive molecules that were negated by the addition of peptide to peptide-receptive MHC molecules. Peptide hydrolysis caused significant increases in hydrogen-deuterium exchange in sub-regions of the peptide-binding domain and smaller increases elsewhere, including in the α3 domain and the non-covalently associated ß2-microglobulin molecule, demonstrating long-range dynamic communication. Comparing two MHC allotypes revealed allotype-specific differences in hydrogen-deuterium exchange, consistent with the notion that MHC I plasticity underpins peptide selection.

A Severe Asthma Disease Signature from Gene Expression Profiling of Peripheral Blood from U-BIOPRED Cohorts.

RATIONALE: Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy. OBJECTIVES: To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences. METHODS: Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis. MEASUREMENTS AND MAIN RESULTS: A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids. CONCLUSIONS: Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).