Exploring the relationship between HCMV serostatus and outcomes in COVID-19 sepsis.

Background: Sepsis, a life-threatening condition caused by the dysregulated host response to infection, is a major global health concern. Understanding the impact of viral or bacterial pathogens in sepsis is crucial for improving patient outcomes. This study aimed to investigate the human cytomegalovirus (HCMV) seropositivity as a risk factor for development of sepsis in patients with COVID-19. Methods: A multicenter observational study enrolled 95 intensive care patients with COVID-19-induced sepsis and 80 post-surgery individuals as controls. HCMV serostatus was determined using an ELISA test. Comprehensive clinical data, including demographics, comorbidities, and 30-day mortality, were collected. Statistical analyses evaluated the association between HCMV seropositivity and COVID-19 induced sepsis. Results: The prevalence of HCMV seropositivity did not significantly differ between COVID-19-induced sepsis patients (78%) and controls (71%, p = 0.382) in the entire cohort. However, among patients aged ≤60 years, HCMV seropositivity was significantly higher in COVID-19 sepsis patients compared to controls (86% vs 61%, respectively; p = 0.030). Nevertheless, HCMV serostatus did not affect 30-day survival. Discussion: These findings confirm the association between HCMV seropositivity and COVID-19 sepsis in non-geriatric patients. However, the lack of an independent effect on 30-day survival can be explained by the cross-reactivity of HCMV specific CD8+ T-cells towards SARS-CoV-2 peptides, which might confer some protection to HCMV seropositive patients. The inclusion of a post-surgery control group strengthens the generalizability of the findings. Further research is needed to elucidate the underlying mechanisms of this association, explore different patient populations, and identify interventions for optimizing patient management. Conclusion: This study validates the association between HCMV seropositivity and severe COVID-19-induced sepsis in non-geriatric patients, contributing to the growing body of evidence on viral pathogens in sepsis. Although HCMV serostatus did not independently influence 30-day survival, future investigations should focus on unraveling the intricate interplay between HCMV, immune responses, and COVID-19. These insights will aid in risk stratification and the development of targeted interventions for viral sepsis.

Assessing SOFA score trajectories in sepsis using machine learning: A pragmatic approach to improve the accuracy of mortality prediction.

INTRODUCTION: An increasing amount of longitudinal health data is available on critically ill septic patients in the age of digital medicine, including daily sequential organ failure assessment (SOFA) score measurements. Thus, the assessment in sepsis focuses increasingly on the evaluation of the individual disease's trajectory. Machine learning (ML) algorithms may provide a promising approach here to improve the evaluation of daily SOFA score dynamics. We tested whether ML algorithms can outperform the conventional ΔSOFA score regarding the accuracy of 30-day mortality prediction. METHODS: We used the multicentric SepsisDataNet.NRW study cohort that prospectively enrolled 252 sepsis patients between 03/2018 and 09/2019 for training ML algorithms, i.e. support vector machine (SVM) with polynomial kernel and artificial neural network (aNN). We used the Amsterdam UMC database covering 1,790 sepsis patients for external and independent validation. RESULTS: Both SVM (AUC 0.84; 95% CI: 0.71-0.96) and aNN (AUC 0.82; 95% CI: 0.69-0.95) assessing the SOFA scores of the first seven days led to a more accurate prognosis of 30-day mortality compared to the ΔSOFA score between day 1 and 7 (AUC 0.73; 95% CI: 0.65-0.80; p = 0.02 and p = 0.05, respectively). These differences were even more prominent the shorter the time interval considered. Using the SOFA scores of day 1 to 3 SVM (AUC 0.82; 95% CI: 0.68 0.95) and aNN (AUC 0.80; 95% CI: 0.660.93) led to a more accurate prognosis of 30-day mortality compared to the ΔSOFA score (AUC 0.66; 95% CI: 0.58-0.74; p < 0.01 and p < 0.01, respectively). Strikingly, all these findings could be confirmed in the independent external validation cohort. CONCLUSIONS: The ML-based algorithms using daily SOFA scores markedly improved the accuracy of mortality compared to the conventional ΔSOFA score. Therefore, this approach could provide a promising and automated approach to assess the individual disease trajectory in sepsis. These findings reflect the potential of incorporating ML algorithms as robust and generalizable support tools on intensive care units.

IFNα Subtypes in HIV Infection and Immunity.

Type I interferons (IFN), immediately triggered following most viral infections, play a pivotal role in direct antiviral immunity and act as a bridge between innate and adaptive immune responses. However, numerous viruses have evolved evasion strategies against IFN responses, prompting the exploration of therapeutic alternatives for viral infections. Within the type I IFN family, 12 IFNα subtypes exist, all binding to the same receptor but displaying significant variations in their biological activities. Currently, clinical treatments for chronic virus infections predominantly rely on a single IFNα subtype (IFNα2a/b). However, the efficacy of this therapeutic treatment is relatively limited, particularly in the context of Human Immunodeficiency Virus (HIV) infection. Recent investigations have delved into alternative IFNα subtypes, identifying certain subtypes as highly potent, and their antiviral and immunomodulatory properties have been extensively characterized. This review consolidates recent findings on the roles of individual IFNα subtypes during HIV and Simian Immunodeficiency Virus (SIV) infections. It encompasses their induction in the context of HIV/SIV infection, their antiretroviral activity, and the diverse regulation of the immune response against HIV by distinct IFNα subtypes. These insights may pave the way for innovative strategies in HIV cure or functional cure studies.

Pancreatic cancer acquires resistance to MAPK pathway inhibition by clonal expansion and adaptive DNA hypermethylation.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis. It is marked by extraordinary resistance to conventional therapies including chemotherapy and radiation, as well as to essentially all targeted therapies evaluated so far. More than 90% of PDAC cases harbor an activating KRAS mutation. As the most common KRAS variants in PDAC remain undruggable so far, it seemed promising to inhibit a downstream target in the MAPK pathway such as MEK1/2, but up to now preclinical and clinical evaluation of MEK inhibitors (MEKi) failed due to inherent and acquired resistance mechanisms. To gain insights into molecular changes during the formation of resistance to oncogenic MAPK pathway inhibition, we utilized short-term passaged primary tumor cells from ten PDACs of genetically engineered mice. We followed gain and loss of resistance upon MEKi exposure and withdrawal by longitudinal integrative analysis of whole genome sequencing, whole genome bisulfite sequencing, RNA-sequencing and mass spectrometry data. RESULTS: We found that resistant cell populations under increasing MEKi treatment evolved by the expansion of a single clone but were not a direct consequence of known resistance-conferring mutations. Rather, resistant cells showed adaptive DNA hypermethylation of 209 and hypomethylation of 8 genomic sites, most of which overlap with regulatory elements known to be active in murine PDAC cells. Both DNA methylation changes and MEKi resistance were transient and reversible upon drug withdrawal. Furthermore, MEKi resistance could be reversed by DNA methyltransferase inhibition with remarkable sensitivity exclusively in the resistant cells. CONCLUSION: Overall, the concept of acquired therapy resistance as a result of the expansion of a single cell clone with epigenetic plasticity sheds light on genetic, epigenetic and phenotypic patterns during evolvement of treatment resistance in a tumor with high adaptive capabilities and provides potential for reversion through epigenetic targeting.

AQP3 and AQP9-Contrary Players in Sepsis?

Sepsis involves an immunological systemic response to a microbial pathogenic insult, leading to a cascade of interconnected biochemical, cellular, and organ-organ interaction networks. Potential drug targets can depict aquaporins, as they are involved in immunological processes. In immune cells, AQP3 and AQP9 are of special interest. In this study, we tested the hypothesis that these aquaporins are expressed in the blood cells of septic patients and impact sepsis survival. Clinical data, routine laboratory parameters, and blood samples from septic patients were analyzed on day 1 and day 8 after sepsis diagnosis. AQP expression and cytokine serum concentrations were measured. AQP3 mRNA expression increased over the duration of sepsis and was correlated with lymphocyte count. High AQP3 expression was associated with increased survival. In contrast, AQP9 expression was not altered during sepsis and was correlated with neutrophil count, and low levels of AQP9 were associated with increased survival. Furthermore, AQP9 expression was an independent risk factor for sepsis lethality. In conclusion, AQP3 and AQP9 may play contrary roles in the pathophysiology of sepsis, and these results suggest that AQP9 may be a novel drug target in sepsis and, concurrently, a valuable biomarker of the disease.

Comparative transcriptomic and proteomic signature of lung alveolar macrophages reveals the integrin CD11b as a regulatory hub during pneumococcal pneumonia infection.

Introduction: Streptococcus pneumoniae is one of the main causes of community-acquired infections in the lung alveoli in children and the elderly. Alveolar macrophages (AM) patrol alveoli in homeostasis and under infectious conditions. However, the molecular adaptations of AM upon infections with Streptococcus pneumoniae are incompletely resolved. Methods: We used a comparative transcriptomic and proteomic approach to provide novel insights into the cellular mechanism that changes the molecular signature of AM during lung infections. Using a tandem mass spectrometry approach to murine cell-sorted AM, we revealed significant proteomic changes upon lung infection with Streptococcus pneumoniae. Results: AM showed a strong neutrophil-associated proteomic signature, such as expression of CD11b, MPO, neutrophil gelatinases, and elastases, which was associated with phagocytosis of recruited neutrophils. Transcriptomic analysis indicated intrinsic expression of CD11b by AM. Moreover, comparative transcriptomic and proteomic profiling identified CD11b as the central molecular hub in AM, which influenced neutrophil recruitment, activation, and migration. Discussion: In conclusion, our study provides novel insights into the intrinsic molecular adaptations of AM upon lung infection with Streptococcus pneumoniae and reveals profound alterations critical for effective antimicrobial immunity.

Comparative proteome and serum analysis identified FSCN1 as a marker of abiraterone resistance in castration-resistant prostate cancer.

BACKGROUND: Abiraterone (Abi) is an androgen receptor signaling inhibitor that significantly improves patients' life expectancy in metastatic prostate cancer (PCa). Despite its beneficial effects, many patients have baseline or acquired resistance against Abi. The aim of this study was to identify predictive serum biomarkers for Abi treatment. METHODS: We performed a comparative proteome analysis on three Abi sensitive (LNCaPabl, LAPC4, DuCaP) and resistant (LNCaPabl-Abi, LAPC4-Abi, DuCaP-Abi) PCa cell lines using liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Two bioinformatic selection workflows were applied to select the most promising candidate serum markers. Serum levels of selected proteins were assessed in samples of 100 Abi-treated patients with metastatic castration-resistant disease (mCRPC) using ELISA. Moreover, FSCN1 serum concentrations were measured in samples of 69 Docetaxel (Doc) treated mCRPC patients. RESULTS: Our proteome analysis identified 68 significantly, at least two-fold upregulated proteins in Abi resistant cells. Using two filtering workflows four proteins (AMACR, KLK2, FSCN1 and CTAG1A) were selected for ELISA analyses. We found high baseline FSCN1 serum levels to be significantly associated with poor survival in Abi-treated mCRPC patients. Moreover, the multivariable analysis revealed that higher ECOG status (>1) and high baseline FSCN1 serum levels (>10.22 ng/ml by ROC cut-off) were independently associated with worse survival in Abi-treated patients (p < 0.001 and p = 0.021, respectively). In contrast, no association was found between serum FSCN1 concentrations and overall survival in Doc-treated patients. CONCLUSIONS: Our analysis identified baseline FSCN1 serum levels to be independently associated with poor survival of Abi-treated, but not Doc-treated mCRPC patients, suggesting a therapy specific prognostic value for FSCN1.

Fc N-glycosylation of autoreactive Aß antibodies as a blood-based biomarker for Alzheimer's disease.

INTRODUCTION: Naturally occurring autoantibodies (nAbs) against the pathologic isoform of amyloid beta (Aß42 ) were found in body fluids and indicate a systemic B cell response that may prevent Alzheimer's disease (AD) onset. N-glycans attached to immunoglobulin G-Fab/Fc fragments are features that influence their mechanism of action. The aim was to study the role of N-glycans in nAbs-Aß42 . METHODS: nAbs-Aß42 were isolated from AD patients and age-/sex-matched controls (n = 40) and immunoglobulin preparations. Glycosylated/deglycosylated nAbs-Aß42 were analyzed for their effect on Aß42 's aggregation, toxicity, and phagocytosis. Glycan structure was analyzed using matrix assisted laser desorption ionization time of flight mass spectrometry. RESULTS: Deglycosylation of nAbs-Aß42 had a major impact on Aß42 's aggregation/toxicity/phagocytosis. The glycan structure showed considerable differences between AD and controls. We were able to predict disease status with a sensitivity/specificity of 95% (confidence interval [CI]: 76.4-99.7%)/100% (CI: 83.9-100%). DISCUSSION: N-glycosylation has been identified as a critical attribute maintaining the beneficial effects of autoreactive Aß antibodies. These data have consequences for the development of monocloncal Aß antibodies and may open new avenues for diagnostics.

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.

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.

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.

An increase in surface hydrophobicity mediates chaperone activity in N-chlorinated RidA.

Under physiological conditions, Escherichia coli RidA is an enamine/imine deaminase, which promotes the release of ammonia from reactive enamine/imine intermediates. However, when modified by hypochlorous acid (HOCl), it turns into a potent chaperone-like holdase that can effectively protect E. coli's proteome during oxidative stress. However, it is unknown, which residues need to be chlorinated for activation. Here, we employ a combination of LC-MS/MS analysis, a chemo-proteomic approach, and a mutagenesis study to identify residues responsible for RidA's chaperone-like function. Through LC-MS/MS of digested RidAHOCl, we obtained direct evidence of the chlorination of one arginine residue. To overcome the instability of the N-chloramine modification, we established a chemoproteomic approach using 5-(dimethylamino) naphthalene-1-sulfinic acid (DANSO2H) as a probe to label N-chlorinated lysines. Using this probe, we were able to detect the N-chlorination of six additional lysine residues. Moreover, using a mutagenesis study to genetically probe the role of single arginine and lysine residues, we found that the removal of arginines R105 and/or R128 led to a substantial reduction of RidAHOCl's chaperone activity. These results, together with structural analysis, confirm that the chaperone activity of RidA is concomitant with the loss of positive charges on the protein surface, leading to an increased overall protein hydrophobicity. Molecular modelling of RidAHOCl and the rational design of a RidA variant that shows chaperone activity even in the absence of HOCl further supports our hypothesis. Our data provide a molecular mechanism for HOCl-mediated chaperone activity found in RidA and a growing number of other HOCl-activated chaperones.

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.

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.

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.

NTRK1/TrkA Signaling in Neuroblastoma Cells Induces Nuclear Reorganization and Intra-Nuclear Aggregation of Lamin A/C.

(1) Background: Neuroblastomas (NBs) are the most common extracranial solid tumors of children. The amplification of the Myc-N proto-oncogene (MYCN) is a major driver of NB aggressiveness, while high expression of the neurotrophin receptor NTRK1/TrkA is associated with mild disease courses. The molecular effects of NTRK1 signaling in MYCN-amplified NB, however, are still poorly understood and require elucidation. (2) Methods: Inducible NTRK1 expression was realized in four NB cell lines with (IMR5, NGP) or without MYCN amplification (SKNAS, SH-SY5Y). Proteome and phosphoproteome dynamics upon NTRK1 activation by its ligand, NGF, were analyzed in a time-dependent manner in IMR5 cells. Target validation by immunofluorescence staining and automated image processing was performed using the three other NB cell lines. (3) Results: In total, 230 proteins and 134 single phosphorylated class I phosphosites were found to be significantly regulated upon NTRK1 activation. Among known NTRK1 targets, Stathmin and the neurosecretory protein VGF were recovered. Additionally, we observed the upregulation and phosphorylation of Lamin A/C (LMNA) that accumulated inside nuclear foci. (4) Conclusions: We provide a comprehensive picture of NTRK1-induced proteome and phosphoproteome dynamics. The phosphorylation of LMNA within nucleic aggregates was identified as a prominent feature of NTRK1 signaling independent of the MYCN status of NB cells.

Proteome Analysis with Classical 2D-PAGE.

Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) is based on the combination of two orthogonal separation techniques. In the first dimension, proteins are separated by their isoelectric point, a technique known as isoelectric focusing (IEF). There are two important variants of IEF, which are carrier-ampholine (CA)-based IEF and immobilized pH-gradient (IPG)-based IEF. In the second dimension, proteins are further separated by their electrophoretic mobility using SDS-PAGE. Finally, proteins can be visualized and quantified by different staining procedures such as Coomassie, silver staining, or fluorescence labeling. This article gives detailed protocols for 2D-PAGE, using both CA- and IPG-based separation in the first dimension.

Differential Proteome Analysis Using 2D-DIGE.

Classical 2D-PAGE allows comparison and quantitation of proteomes by visualization of protein patterns using gel stains and comparative image analysis. The introduction of fluorescent reagents for protein labeling (difference in-gel electrophoresis or DIGE) has brought substantial improvement in this field. It provides multiplexing of up to three samples in one gel, higher sensitivity compared to normal protein staining methods, and a higher linear range for quantitation. This article gives detailed protocols for 2D-DIGE, including both minimal and saturation labeling.

Application of Label-Free Proteomics for Quantitative Analysis of Urothelial Carcinoma and Cystitis Tissue.

A label-free approach based on a highly reproducible and stable workflow allows for quantitative proteome analysis . Due to advantages compared to labeling methods, the label-free approach has the potential to measure unlimited samples from clinical specimen monitoring and comparing thousands of proteins. The presented label-free workflow includes a new sample preparation technique depending on automatic annotation and tissue isolation via FTIR-guided laser microdissection, in-solution digestion, LC-MS/MS analyses, data evaluation by means of Proteome Discoverer and Progenesis software, and verification of differential proteins. We successfully applied this workflow in a proteomics study analyzing human cystitis and high-grade urothelial carcinoma tissue regarding the identification of a diagnostic tissue biomarker. The differential analysis of only 1 mm2 of isolated tissue cells led to 74 significantly differentially abundant proteins.