Structural mechanism of CRL4-instructed STAT2 degradation via a novel cytomegaloviral DCAF receptor.

Human cytomegalovirus (CMV) is a ubiquitously distributed pathogen whose rodent counterparts such as mouse and rat CMV serve as common infection models. Here, we conducted global proteome profiling of rat CMV-infected cells and uncovered a pronounced loss of the transcription factor STAT2, which is crucial for antiviral interferon signalling. Via deletion mutagenesis, we found that the viral protein E27 is required for CMV-induced STAT2 depletion. Cellular and in vitro analyses showed that E27 exploits host-cell Cullin4-RING ubiquitin ligase (CRL4) complexes to induce poly-ubiquitylation and proteasomal degradation of STAT2. Cryo-electron microscopy revealed how E27 mimics molecular surface properties of cellular CRL4 substrate receptors called DCAFs (DDB1- and Cullin4-associated factors), thereby displacing them from the catalytic core of CRL4. Moreover, structural analyses showed that E27 recruits STAT2 through a bipartite binding interface, which partially overlaps with the IRF9 binding site. Structure-based mutations in M27, the murine CMV homologue of E27, impair the interferon-suppressing capacity and virus replication in mouse models, supporting the conserved importance of DCAF mimicry for CMV immune evasion.

Differential interferon-α subtype induced immune signatures are associated with suppression of SARS-CoV-2 infection.

Type I interferons (IFN-I) exert pleiotropic biological effects during viral infections, balancing virus control versus immune-mediated pathologies, and have been successfully employed for the treatment of viral diseases. Humans express 12 IFN-alpha (α) subtypes, which activate downstream signaling cascades and result in distinct patterns of immune responses and differential antiviral responses. Inborn errors in IFN-I immunity and the presence of anti-IFN autoantibodies account for very severe courses of COVID-19; therefore, early administration of IFN-I may be protective against life-threatening disease. Here we comprehensively analyzed the antiviral activity of all IFNα subtypes against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to identify the underlying immune signatures and explore their therapeutic potential. Prophylaxis of primary human airway epithelial cells (hAEC) with different IFNα subtypes during SARS-CoV-2 infection uncovered distinct functional classes with high, intermediate, and low antiviral IFNs. In particular, IFNα5 showed superior antiviral activity against SARS-CoV-2 infection in vitro and in SARS-CoV-2-infected mice in vivo. Dose dependency studies further displayed additive effects upon coadministration with the broad antiviral drug remdesivir in cell culture. Transcriptomic analysis of IFN-treated hAEC revealed different transcriptional signatures, uncovering distinct, intersecting, and prototypical genes of individual IFNα subtypes. Global proteomic analyses systematically assessed the abundance of specific antiviral key effector molecules which are involved in IFN-I signaling pathways, negative regulation of viral processes, and immune effector processes for the potent antiviral IFNα5. Taken together, our data provide a systemic, multimodular definition of antiviral host responses mediated by defined IFN-I. This knowledge will support the development of novel therapeutic approaches against SARS-CoV-2.

Activation of the MAPK network provides a survival advantage during the course of COVID-19-induced sepsis: a real-world evidence analysis of a multicenter COVID-19 Sepsis Cohort.

PURPOSE: There is evidence that lower activity of the RAF/MEK/ERK network is associated with positive outcomes in mild and moderate courses of COVID-19. The effect of this cascade in COVID-19 sepsis is still undetermined. Therefore, we tested the hypothesis that activity of the RAF/MEK/ERK network in COVID-19-induced sepsis is associated with an impact on 30-day survival. METHODS: We used biomaterial from 81 prospectively recruited patients from the multicentric CovidDataNet.NRW-study cohort (German clinical trial registry: DRKS00026184) with their collected medical history, vital signs, laboratory parameters, microbiological findings and patient outcome. ERK activity was measured by evaluating ERK phosphorylation using a Proximity Ligation Assay. RESULTS: An increased ERK activity at 4 days after diagnosis of COVID-19-induced sepsis was associated with a more than threefold increased chance of survival in an adjusted Cox regression model. ERK activity was independent of other confounders such as Charlson Comorbidity Index or SOFA score (HR 0.28, 95% CI 0.10-0.84, p = 0.02). CONCLUSION: High activity of the RAF/MEK/ERK network during the course of COVID-19 sepsis is a protective factor and may indicate recovery of the immune system. Further studies are needed to confirm these results.

Comparative proteome analysis identified CD44 as a possible serum marker for docetaxel resistance in castration-resistant prostate cancer.

Baseline or acquired resistance to docetaxel (DOC) represents a significant risk for patients with metastatic prostate cancer (PC). In the last years, novel therapy regimens have been approved providing reasonable alternatives for DOC-resistant patients making prediction of DOC resistance of great clinical importance. We aimed to identify serum biomarkers, which are able to select patients who will not benefit from DOC treatment. DOC-resistant PC3-DR and DU145-DR sublines and their sensitive parental cell lines (DU145, PC3) were comparatively analyzed using liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS). Results were filtered using bioinformatics approaches to identify promising serum biomarkers. Serum levels of five proteins were determined in serum samples of 66 DOC-treated metastatic castration-resistant PC patients (mCRPC) using ELISA. Results were correlated with clinicopathological and survival data. CD44 was subjected to further functional cell culture analyses. We found at least 177 two-fold significantly overexpressed proteins in DOC-resistant cell lines. Our bioinformatics method suggested 11/177 proteins to be secreted into the serum. We determined serum levels of five (CD44, MET, GSN, IL13RA2 and LNPEP) proteins in serum samples of DOC-treated patients and found high CD44 serum levels to be independently associated with poor overall survival (p = 0.001). In accordance, silencing of CD44 in DU145-DR cells resulted in re-sensitization to DOC. In conclusion, high serum CD44 levels may help identify DOC-resistant patients and may thereby help optimize clinical decision-making regarding type and timing of therapy for mCRPC patients. In addition, our in vitro results imply the possible functional involvement of CD44 in DOC resistance.

Proteome profiling of enzalutamide-resistant cell lines and serum analysis identified ALCAM as marker of resistance in castration-resistant prostate cancer.

Enzalutamide (ENZA) is a frequently used therapy in metastatic castration-resistant prostate cancer (mCRPC). Baseline or acquired resistance to ENZA have been observed, but the molecular mechanisms of resistance are poorly understood. We aimed to identify proteins involved in ENZA resistance and to find therapy-predictive serum markers. We performed comparative proteome analyses on ENZA-sensitive parental (LAPC4, DuCaP) and -resistant prostate cancer cell lines (LAPC4-ENZA, DuCaP-ENZA) using liquid chromatography tandem mass spectrometry (LC-MS/MS). The top four most promising candidate markers were selected using bioinformatic approaches. Serum concentrations of selected markers (ALCAM, AGR2, NDRG1, IDH1) were measured in pretreatment samples of 72 ENZA-treated mCRPC patients using ELISA. In addition, ALCAM serum levels were measured in 101 Abiraterone (ABI) and 100 Docetaxel (DOC)-treated mCRPC patients' baseline samples. Results were correlated with clinical and follow-up data. The functional role of ALCAM in ENZA resistance was assessed in vitro using siRNA. Our proteome analyses revealed 731 significantly differentially abundant proteins between ENZA-sensitive and -resistant cells and our filtering methods identified four biomarker candidates. Serum analyses of these proteins revealed only ALCAM to be associated with poor patient survival. Furthermore, higher baseline ALCAM levels were associated with poor survival in ABI- but not in DOC-treated patients. In LAPC4-ENZA resistant cells, ALCAM silencing by siRNA knockdown resulted in significantly enhanced ENZA sensitivity. Our analyses revealed that ALCAM serum levels may help to identify ENZA- and ABI-resistant patients and may thereby help to optimize future clinical decision-making. Our functional analyses suggest the possible involvement of ALCAM in ENZA resistance.

The impact of the COVID-19 pandemic on non-COVID induced sepsis survival.

BACKGROUND: The COVID-19 pandemic has taken a toll on health care systems worldwide, which has led to increased mortality of different diseases like myocardial infarction. This is most likely due to three factors. First, an increased workload per nurse ratio, a factor associated with mortality. Second, patients presenting with COVID-19-like symptoms are isolated, which also decreases survival in cases of emergency. And third, patients hesitate to see a doctor or present themselves at a hospital. To assess if this is also true for sepsis patients, we asked whether non-COVID-19 sepsis patients had an increased 30-day mortality during the COVID-19 pandemic. METHODS: This is a post hoc analysis of the SepsisDataNet.NRW study, a multicentric, prospective study that includes septic patients fulfilling the SEPSIS-3 criteria. Within this study, we compared the 30-day mortality and disease severity of patients recruited pre-pandemic (recruited from March 2018 until February 2020) with non-COVID-19 septic patients recruited during the pandemic (recruited from March 2020 till December 2020). RESULTS: Comparing septic patients recruited before the pandemic to those recruited during the pandemic, we found an increased raw 30-day mortality in sepsis-patients recruited during the pandemic (33% vs. 52%, p = 0.004). We also found a significant difference in the severity of disease at recruitment (SOFA score pre-pandemic: 8 (5 - 11) vs. pandemic: 10 (8 - 13); p < 0.001). When adjusted for this, the 30-day mortality rates were not significantly different between the two groups (52% vs. 52% pre-pandemic and pandemic, p = 0.798). CONCLUSIONS: This led us to believe that the higher mortality of non-COVID19 sepsis patients during the pandemic might be attributed to a more severe septic disease at the time of recruitment. We note that patients may experience a delayed admission, as indicated by elevated SOFA scores. This could explain the higher mortality during the pandemic and we found no evidence for a diminished quality of care for critically ill sepsis patients in German intensive care units.

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD).

Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.

Tissue-resident macrophages mediate neutrophil recruitment and kidney injury in shiga toxin-induced hemolytic uremic syndrome.

Enterohaemorrhagic E. coli cause major epidemics worldwide with significant organ damage and very high percentages of death. Due to the ability of enterohaemorrhagic E. coli to produce shiga toxin these bacteria damage the kidney leading to the hemolytic uremic syndrome. A therapy against this serious kidney disease has not been developed yet and the impact and mechanism of leukocyte activation and recruitment are unclear. Tissue-resident macrophages represent the main leukocyte population in the healthy kidney, but the role of this important cell population in shiga toxin-producing E. coli-hemolytic uremic syndrome is incompletely understood. Using state of the art microscopy and mass spectrometry imaging, our preclinical study demonstrated a phenotypic and functional switch of tissue-resident macrophages after disease induction in mice. Kidney macrophages produced the inflammatory molecule TNFα and depletion of tissue-resident macrophages via the CSF1 receptor abolished TNFα levels in the kidney and significantly diminished disease severity. Furthermore, macrophage depletion did not only attenuate endothelial damage and thrombocytopenia, but also activation of thrombocytes and neutrophils. Moreover, we observed that neutrophils infiltrated the kidney cortex and depletion of macrophages significantly reduced the recruitment of neutrophils and expression of the neutrophil-attracting chemokines CXCL1 and CXCL2. Intravital microscopy revealed that inhibition of CXCR2, the receptor for CXCL1 and CXCL2, significantly reduced the infiltration of neutrophils and reduced kidney injury. Thus, our study shows activation of tissue-resident macrophages during shiga toxin-producing E. coli-hemolytic uremic syndrome leading to the production of disease-promoting TNFα and CXCR2-dependent recruitment of neutrophils.

Quantitative analysis of proteome dynamics in a mouse model of asthma.

BACKGROUND: Asthma is an inflammatory disease of the respiratory system, and a major factor of increasing health care costs worldwide. The molecular actors leading to the development of chronic asthma are not fully understood and require further investigation. OBJECTIVE: The aim of this study was to monitor the proteome dynamics during asthma development from early inflammatory to late fibrotic stages. METHODS: A mouse asthma model was used to analyse the lung proteome at four time points during asthma development (0 weeks = control, 5, 8 and 12 weeks of treatment, n = 6 each). The model was analysed using lung function tests, immune cell counting and histology. Furthermore, a multi-fraction mass spectrometry-based proteome analysis was performed to achieve a comprehensive coverage and quantification of the lung proteome. RESULTS: At early stages, the mice showed predominant eosinophilic inflammation of the airways, which disappeared at later stages and was replaced by marked airway hyper-reactivity and fibrosis of the airways. 3325 proteins were quantified with 435 proteins found to be significantly differentially abundant between the experimental groups (ANOVA p-value ≤.05, maximum fold change ≥1.5). We applied hierarchical clustering to identify common protein abundance profiles along the asthma development and analysed these clusters using gene ontology annotation and enrichment analysis. We demonstrate the correlation of protein clusters with the course of asthma development, that is eosinophilic inflammation and fibrotic remodelling of the airways. CONCLUSIONS AND CLINICAL RELEVANCE: Proteome analysis revealed proteins that were previously described to be important during asthma chronification. Moreover, we identified additional proteins previously not described in the context of asthma. We provide a comprehensive data set of a long-term mouse model of asthma that may contribute to a better understanding and allow new insights into the progression and development of chronic asthma. Data are available via ProteomeXchange with identifier PXD011159.

CalibraCurve: A Tool for Calibration of Targeted MS-Based Measurements.

Targeted proteomics techniques allow accurate quantitative measurements of analytes in complex matrices with dynamic linear ranges that span up to 4-5 orders of magnitude. Hence, targeted methods are promising for the development of robust protein assays in several sensitive areas, for example, in health care. However, exploiting the full method potential requires reliable determination of the dynamic range along with related quantification limits for each analyte. Here, a software named CalibraCurve that enables an automated batch-mode determination of dynamic linear ranges and quantification limits for both targeted proteomics and similar assays is presented. The software uses a variety of measures to assess the accuracy of the calibration, namely precision and trueness. Two different kinds of customizable graphs are created (calibration curves and response factor plots). The accuracy measures and the graphs offer an intuitive, detailed, and reliable opportunity to assess the quality of the model fit. Thus, CalibraCurve is deemed a highly useful and flexible tool to facilitate the development and control of reliable SRM/MRM-MS-based proteomics assays.

Systematic Comparison of Label-Free, SILAC, and TMT Techniques to Study Early Adaption toward Inhibition of EGFR Signaling in the Colorectal Cancer Cell Line DiFi.

We evaluated the quantification strategies label-free (LF), stable isotope labeling by amino acids in cell culture (SILAC), and tandem mass tags (TMT) and their performance in quantification of proteins and phosphosites (p-sites) to identify the most powerful approach for monitoring cellular signaling. We analyzed the epidermal growth factor receptor (EGFR) signaling network, which plays an essential role in colorectal cancer, and studied its dynamics within 24 h upon treatment with the EGFR-blocking antibody cetuximab, representing the first cellular adaption toward therapy. LF achieved superior coverage but was outperformed by label-based approaches regarding technical variability, especially for quantification of p-sites. TMT showed the lowest coverage and most missing values. We found that its performance considerably decreases when experimental replicates are distributed over several TMT plexes. SILAC showed the highest precision and outstanding performance for quantification of p-sites, rendering it the method of choice for analyzing cellular signaling in cell culture models. On the protein level, we observed only little regulation upon cetuximab treatment, whereas a great fraction of p-sites was significantly regulated. These dynamics represented an initial downregulation of the MAPK pathway, which was partially rescued as early as 24 h after treatment. We identified upregulation and signaling via ERBB3 as well as calcium and cAMP signaling as possible mechanisms bypassing the blockage of EGFR.

C19orf66 is an interferon-induced inhibitor of HCV replication that restricts formation of the viral replication organelle.

BACKGROUND & AIMS: HCV is a positive-strand RNA virus that primarily infects human hepatocytes. Recent studies have reported that C19orf66 is expressed as an interferon (IFN)-stimulated gene; however, the intrinsic regulation of this gene within the liver as well as its antiviral effects against HCV remain elusive. METHODS: Expression of C19orf66 was quantified in both liver biopsies and primary human hepatocytes, with or without HCV infection. Mechanistic studies of the potent anti-HCV phenotype mediated by C19orf66 were conducted using state-of-the-art virological, biochemical and genetic approaches, as well as correlative light and electron microscopy and transcriptome and proteome analysis. RESULTS: Upregulation of C19orf66 mRNA was observed in both primary human hepatocytes upon HCV infection and in the livers of patients with chronic hepatitis C (CHC). In addition, pegIFNα/ribavirin therapy induced C19orf66 expression in patients with CHC. Transcriptomic profiling and whole cell proteomics of hepatoma cells ectopically expressing C19orf66 revealed no induction of other antiviral genes. Expression of C19orf66 restricted HCV infection, whereas CRIPSPR/Cas9 mediated knockout of C19orf66 attenuated IFN-mediated suppression of HCV replication. Co-immunoprecipitation followed by mass spectrometry identified a stress granule protein-dominated interactome of C19orf66. Studies with subgenomic HCV replicons and an expression system revealed that C19orf66 expression impairs HCV-induced elevation of phosphatidylinositol-4-phosphate, alters the morphology of the viral replication organelle (termed the membranous web) and thereby targets viral RNA replication. CONCLUSION: C19orf66 is an IFN-stimulated gene, which is upregulated in hepatocytes within the first hours post IFN treatment or HCV infection in vivo. The encoded protein possesses specific antiviral activity against HCV and targets the formation of the membranous web. Our study identifies C19orf66 as an IFN-inducible restriction factor with a novel antiviral mechanism that specifically targets HCV replication. LAY SUMMARY: Interferon-stimulated genes are thought to be important to for antiviral immune responses to HCV. Herein, we analysed C19orf66, an interferon-stimulated gene, which appears to inhibit HCV replication. It prevents the HCV-induced elevation of phosphatidylinositol-4-phosphate and alters the morphology of HCV's replication organelle.

Integrated Fourier Transform Infrared Imaging and Proteomics for Identification of a Candidate Histochemical Biomarker in Bladder Cancer.

Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections. Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography-tandem mass spectrometry-based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.

Quantitative Analysis of Proteome Modulations in Alveolar Epithelial Type II Cells in Response to Pulmonary Aspergillus fumigatus Infection.

The ubiquitous mold Aspergillus fumigatus threatens immunosuppressed patients as inducer of lethal invasive aspergillosis. A. fumigatus conidia are airborne and reach the alveoli, where they encounter alveolar epithelial cells (AEC). Previous studies reported the importance of the surfactant-producing AEC II during A. fumigatus infection via in vitro experiments using cell lines. We established a negative isolation protocol yielding untouched primary murine AEC II with a purity >90%, allowing ex vivo analyses of the cells, which encountered the mold in vivo By label-free proteome analysis of AEC II isolated from mice 24h after A. fumigatus or mock infection we quantified 2256 proteins and found 154 proteins to be significantly differentially abundant between both groups (ANOVA p value ≤ 0.01, ratio of means ≥1.5 or ≤0.67, quantified with ≥2 peptides). Most of these proteins were higher abundant in the infected condition and reflected a comprehensive activation of AEC II on interaction with A. fumigatus This was especially represented by proteins related to oxidative phosphorylation, hence energy production. However, the most strongly induced protein was the l-amino acid oxidase (LAAO) Interleukin 4 induced 1 (IL4I1) with a 42.9 fold higher abundance (ANOVA p value 2.91-10). IL4I1 has previously been found in B cells, macrophages, dendritic cells and rare neurons. Increased IL4I1 abundance in AEC II was confirmed by qPCR, Western blot and immunohistology. Furthermore, A. fumigatus infected lungs showed high levels of IL4I1 metabolic products. Importantly, higher IL4I1 abundance was also confirmed in lung tissue from human aspergilloma. Because LAAO are key enzymes for bactericidal product generation, AEC II might actively participate in pathogen defense. We provide insights into proteome changes of primary AEC II thereby opening new avenues to analyze the molecular changes of this central lung cell on infectious threats. Data are available via ProteomeXchange with identifier PXD005834.

Immunohistochemical Markers Distinguishing Cholangiocellular Carcinoma (CCC) from Pancreatic Ductal Adenocarcinoma (PDAC) Discovered by Proteomic Analysis of Microdissected Cells.

Cholangiocellular carcinoma (CCC) and pancreatic ductal adenocarcinoma (PDAC) are two highly aggressive cancer types that arise from epithelial cells of the pancreatobiliary system. Owing to their histological and morphological similarity, differential diagnosis between CCC and metastasis of PDAC located in the liver frequently proves an unsolvable issue for pathologists. The detection of biomarkers with high specificity and sensitivity for the differentiation of these tumor types would therefore be a valuable tool. Here, we address this problem by comparing microdissected CCC and PDAC tumor cells from nine and eleven cancer patients, respectively, in a label-free proteomics approach. The novel biomarker candidates were subsequently verified by immunohistochemical staining of 73 CCC, 78 primary, and 18 metastatic PDAC tissue sections. In the proteome analysis, we found 180 proteins with a significantly differential expression between CCC and PDAC cells (p value < 0.05, absolute fold change > 2). Nine candidate proteins were chosen for an immunohistochemical verification out of which three showed very promising results. These were the annexins ANXA1, ANXA10, and ANXA13. For the correct classification of PDAC, ANXA1 showed a sensitivity of 84% and a specificity of 85% and ANXA10 a sensitivity of 90% at a specificity of 66%. ANXA13 was higher abundant in CCC. It presented a sensitivity of 84% at a specificity of 55%. In metastatic PDAC tissue ANXA1 and ANXA10 showed similar staining behavior as in the primary PDAC tumors (13/18 and 17/18 positive, respectively). ANXA13, however, presented positive staining in eight out of eighteen secondary PDAC tumors and was therefore not suitable for the differentiation of these from CCC. We conclude that ANXA1 and ANXA10 are promising biomarker candidates with high diagnostic values for the differential diagnosis of intrahepatic CCC and metastatic liver tumors deriving from PDAC.

Quantitative Secretome Analysis of Activated Jurkat Cells Using Click Chemistry-Based Enrichment of Secreted Glycoproteins.

Quantitative secretome analyses are a high-performance tool for the discovery of physiological and pathophysiological changes in cellular processes. However, serum supplements in cell culture media limit secretome analyses, but serum depletion often leads to cell starvation and consequently biased results. To overcome these limiting factors, we investigated a model of T cell activation (Jurkat cells) and performed an approach for the selective enrichment of secreted proteins from conditioned medium utilizing metabolic marking of newly synthesized glycoproteins. Marked glycoproteins were labeled via bioorthogonal click chemistry and isolated by affinity purification. We assessed two labeling compounds conjugated with either biotin or desthiobiotin and the respective secretome fractions. 356 proteins were quantified using the biotin probe and 463 using desthiobiotin. 59 proteins were found differentially abundant (adjusted p-value ≤0.05, absolute fold change ≥1.5) between inactive and activated T cells using the biotin method and 86 using the desthiobiotin approach, with 31 mutual proteins cross-verified by independent experiments. Moreover, we analyzed the cellular proteome of the same model to demonstrate the benefit of secretome analyses and provide comprehensive data sets of both. 336 proteins (61.3%) were quantified exclusively in the secretome. Data are available via ProteomeXchange with identifier PXD004280.

Quantitative proteome analysis reveals the correlation between endocytosis-associated proteins and hepatocellular carcinoma dedifferentiation.

The majority of poorly differentiated hepatocellular carcinomas (HCCs) develop from well-differentiated tumors. Endocytosis is a cellular function which is likely to take part in this development due to its important role in regulating the abundances of vital signaling receptors. Here, we aimed to investigate the abundance of endocytosis-associated proteins in HCCs with various differentiation grades. Therefore, we analyzed 36 tissue specimens from HCC patients via LC-MS/MS-based label-free quantitative proteomics including 19 HCC tissue samples with different degrees of histological grades and corresponding non-tumorous tissue controls. As a result, 277 proteins were differentially regulated between well-differentiated tumors and controls. In moderately and poorly differentiated tumors, 278 and 1181 proteins, respectively, were significantly differentially regulated compared to non-tumorous tissue. We explored the regulated proteins based on their functions and identified thirty endocytosis-associated proteins, mostly overexpressed in poorly differentiated tumors. These included proteins that have been shown to be up-regulated in HCC like clathrin heavy chain-1 (CLTC) as well as unknown proteins, such as secretory carrier-associated membrane protein 3 (SCAMP3). The abundances of SCAMP3 and CLTC were immunohistochemically examined in tissue sections of 84 HCC patients. We demonstrate the novel association of several endocytosis-associated proteins, in particular, SCAMP3 with HCC progression.

Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

CONTEXT AND OBJECTIVE: Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. METHODS AND RESULTS: Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. CONCLUSION: RAB1A was verified to be a potent biomarker candidate for HCC.

Quantitative Tissue Proteomics Analysis Reveals Versican as Potential Biomarker for Early-Stage Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most aggressive tumors, and the treatment outcome of this disease is improved when the cancer is diagnosed at an early stage. This requires biomarkers allowing an accurate and early tumor diagnosis. To identify potential markers for such applications, we analyzed a patient cohort consisting of 50 patients (50 HCC and 50 adjacent nontumorous tissue samples as controls) using two independent proteomics approaches. We performed label-free discovery analysis on 19 HCC and corresponding tissue samples. The data were analyzed considering events known to take place in early events of HCC development, such as abnormal regulation of Wnt/b-catenin and activation of receptor tyrosine kinases (RTKs). 31 proteins were selected for verification experiments. For this analysis, the second set of the patient cohort (31 HCC and corresponding tissue samples) was analyzed using selected (multiple) reaction monitoring (SRM/MRM). We present the overexpression of ATP-dependent RNA helicase (DDX39), Fibulin-5 (FBLN5), myristoylated alanine-rich C-kinase substrate (MARCKS), and Serpin H1 (SERPINH1) in HCC for the first time. We demonstrate Versican core protein (VCAN) to be significantly associated with well differentiated and low-stage HCC. We revealed for the first time the evidence of VCAN as a potential biomarker for early-HCC diagnosis.

A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics.