Stromal Microenvironment Shapes the Intratumoral Architecture of Pancreatic Cancer.

Single-cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single-cell phenotypes have not been well defined. Combining single-cell RNA and protein analytics in studying the role of stromal cancer-associated fibroblasts (CAFs) in modulating heterogeneity in pancreatic cancer (pancreatic ductal adenocarcinoma [PDAC]) model systems, we have identified significant single-cell population shifts toward invasive epithelial-to-mesenchymal transition (EMT) and proliferative (PRO) phenotypes linked with mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 3 (STAT3) signaling. Using high-content digital imaging of RNA in situ hybridization in 195 PDAC tumors, we quantified these EMT and PRO subpopulations in 319,626 individual cancer cells that can be classified within the context of distinct tumor gland "units." Tumor gland typing provided an additional layer of intratumoral heterogeneity that was associated with differences in stromal abundance and clinical outcomes. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics.

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

Neoadjuvant chemo- or chemo-radiation-therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo-radiation (NCRT) therapy. We employed data-independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment-naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment-naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post-NCT and post-NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment-naïve PDAC. Further analyses on patient survival and protein expression identified treatment-specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment-naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.

Proteome alterations in human autopsy tissues in relation to time after death.

Protein expression is a primary area of interest for routine histological diagnostics and tissue-based research projects, but the limitations of its post-mortem applicability remain largely unclear. On the other hand, tissue specimens obtained during autopsies can provide unique insight into advanced disease states, especially in cancer research. Therefore, we aimed to identify the maximum post-mortem interval (PMI) which is still suitable for characterizing protein expression patterns, to explore organ-specific differences in protein degradation, and to investigate whether certain proteins follow specific degradation kinetics. Therefore, the proteome of human tissue samples obtained during routine autopsies of deceased patients with accurate PMI (6, 12, 18, 24, 48, 72, 96 h) and without specific diseases that significantly affect tissue preservation, from lungs, kidneys and livers, was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). For the kidney and liver, significant protein degradation became apparent at 48 h. For the lung, the proteome composition was rather static for up to 48 h and substantial protein degradation was detected only at 72 h suggesting that degradation kinetics appear to be organ specific. More detailed analyses suggested that proteins with similar post-mortem kinetics are not primarily shared in their biological functions. The overrepresentation of protein families with analogous structural motifs in the kidney indicates that structural features may be a common factor in determining similar postmortem stability. Our study demonstrates that a longer post-mortem period may have a significant impact on proteome composition, but sampling within 24 h may be appropriate, as degradation is within acceptable limits even in organs with faster autolysis.

Discovery of a small protein factor involved in the coordinated degradation of phycobilisomes in cyanobacteria.

Phycobilisomes are the major pigment-protein antenna complexes that perform photosynthetic light harvesting in cyanobacteria, rhodophyte, and glaucophyte algae. Up to 50% of the cellular nitrogen can be stored in their giant structures. Accordingly, upon nitrogen depletion, phycobilisomes are rapidly degraded following an intricate genetic program. Here, we describe the role of NblD, a cysteine-rich, small protein in this process in cyanobacteria. Deletion of the nblD gene in the cyanobacterium Synechocystis sp. PCC 6803 prevented the degradation of phycobilisomes, leading to a nonbleaching (nbl) phenotype, which could be complemented by a plasmid-localized gene copy. Competitive growth experiments between the ΔnblD and the wild-type strain provided direct evidence for the physiological importance of NblD under nitrogen-limited conditions. Ectopic expression of NblD under nitrogen-replete conditions showed no effect, in contrast to the unrelated proteolysis adaptors NblA1 and NblA2, which can trigger phycobilisome degradation. Transcriptome analysis indicated increased nblA1/2 transcript levels in the ΔnblD strain during nitrogen starvation, implying that NblD does not act as a transcriptional (co)regulator. However, immunoprecipitation and far-western experiments identified the chromophorylated (holo form) of the phycocyanin ß-subunit (CpcB) as its target, while apo-CpcB was not bound. The addition of recombinant NblD to isolated phycobilisomes caused a reduction in phycocyanin absorbance and a broadening and shifting of the peak to lower wavelengths, indicating the occurrence of structural changes. These data demonstrate that NblD plays a crucial role in the coordinated dismantling of phycobilisomes and add it as a factor to the genetically programmed response to nitrogen starvation.

Acute aortic dissection: evidence, uncertainties, and future therapies.

Remarkable progress has become especially apparent in aortic medicine in the last few decades, leading to essential changes in how thoracic aortic dissection is understood and treated. This state-of-the-art review article addresses the mechanisms of acute aortic dissection, explaining the role of its primary entry location, proximal, and distal dissection extension in their clinical presentation and impact on the decision-making process towards the best treatment approach. The latest evidence on novel treatment methods for acute aortic syndromes is presented, and the diverse dissection classification systems that remain uncertain are discussed, which reveals the need for shared terminology and more clarity. Finally, future aspects are discussed in treating acute aortic dissection, such as the endovascular treatment of aortic dissection Type A and biomarkers for acute aortic syndromes.

The serum proteome of VA-ECMO patients changes over time and allows differentiation of survivors and non-survivors: an observational study.

BACKGROUND: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is applied in patients with refractory hemodynamic failure. Exposure of blood components to high shear stress and the large extracorporeal surfaces in the ECMO circuit trigger a complex inflammatory response syndrome and coagulopathy which are believed to worsen the already poor prognosis of these patients. Mass spectrometry-based proteomics allow a detailed characterization of the serum proteome as it provides the identity and concentration of large numbers of individual proteins at the same time. In this study, we aimed to characterize the serum proteome of patients receiving VA-ECMO. METHODS: Serum samples were collected on day 1 and day 3 after initiation of VA-ECMO. Samples underwent immunoaffinity based depletion for the 14 most abundant serum proteins, in-solution digestion and PreOmics clean-up. A spectral library was built with multiple measurements of a master-mix sample using variable mass windows. Individual samples were measured in data independent acquisition (DIA) mode. Raw files were analyzed by DIA-neural network. Unique proteins were log transformed and quantile normalized. Differential expression analysis was conducted with the LIMMA-R package. ROAST was applied to generate gene ontology enrichment analyses. RESULTS: Fourteen VA-ECMO patients and six healthy controls were recruited. Seven patients survived. Three hundred and fifty-one unique proteins were identified. One hundred and thirty-seven proteins were differentially expressed between VA-ECMO patients and controls. One hundred and forty-five proteins were differentially expressed on day 3 compared to day 1. Many of the differentially expressed proteins were involved in coagulation and the inflammatory response. The serum proteomes of survivors and non-survivors on day 3 differed from each other according to partial least-squares discriminant analysis (PLS-DA) and 48 proteins were differentially expressed. Many of these proteins have also been ascribed to processes in coagulation and inflammation (e.g., Factor IX, Protein-C, Kallikrein, SERPINA10, SEMA4B, Complement C3, Complement Factor D and MASP-1). CONCLUSION: The serum proteome of VA-ECMO patients displays major changes compared to controls and changes from day 1 until day 3. Many changes in the serum proteome are related to inflammation and coagulation. Survivors and non-survivors can be differentiated according to their serum proteomes using PLS-DA analysis on day 3. Our results build the basis for future studies using mass-spectrometry based serum proteomics as a tool to identify novel prognostic biomarkers. TRIAL REGISTRATION: DRKS00011106.

The roles of proteases in prostate cancer.

Since the proposition of the pro-invasive activity of proteolytic enzymes over 70 years ago, several roles for proteases in cancer progression have been established. About half of the 473 active human proteases are expressed in the prostate and many of the most well-characterized members of this enzyme family are regulated by androgens, hormones essential for development of prostate cancer. Most notably, several kallikrein-related peptidases, including KLK3 (prostate-specific antigen, PSA), the most well-known prostate cancer marker, and type II transmembrane serine proteases, such as TMPRSS2 and matriptase, have been extensively studied and found to promote prostate cancer progression. Recent findings also suggest a critical role for proteases in the development of advanced and aggressive castration-resistant prostate cancer (CRPC). Perhaps the most intriguing evidence for this role comes from studies showing that the protease-activated transmembrane proteins, Notch and CDCP1, are associated with the development of CRPC. Here, we review the roles of proteases in prostate cancer, with a special focus on their regulation by androgens.

Positional proteomics: is the technology ready to study clinical cohorts?

INTRODUCTION: Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED: We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION: Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.

A Galaxy of informatics resources for MS-based proteomics.

INTRODUCTION: Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software. AREAS COVERED: The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses. EXPERT OPINION: The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.

Changes in calpain-2 expression during glioblastoma progression predisposes tumor cells to temozolomide resistance by minimizing DNA damage and p53-dependent apoptosis.

BACKGROUND: Glioblastoma multiforme (GBM) is characterized by an unfavorable prognosis for patients affected. During standard-of-care chemotherapy using temozolomide (TMZ), tumors acquire resistance thereby causing tumor recurrence. Thus, deciphering essential molecular pathways causing TMZ resistance are of high therapeutic relevance. METHODS: Mass spectrometry based proteomics were used to study the GBM proteome. Immunohistochemistry staining of human GBM tissue for either calpain-1 or -2 was performed to locate expression of proteases. In vitro cell based assays were used to measure cell viability and survival of primary patient-derived GBM cells and established GBM cell lines after TMZ ± calpain inhibitor administration. shRNA expression knockdowns of either calpain-1 or calpain-2 were generated to study TMZ sensitivity of the specific subunits. The Comet assay and É£H2AX signal measurements were performed in order to assess the DNA damage amount and recognition. Finally, quantitative real-time PCR of target proteins was applied to differentiate between transcriptional and post-translational regulation. RESULTS: Calcium-dependent calpain proteases, in particular calpain-2, are more abundant in glioblastoma compared to normal brain and increased in patient-matched initial and recurrent glioblastomas. On the cellular level, pharmacological calpain inhibition increased the sensitivities of primary glioblastoma cells towards TMZ. A genetic knockdown of calpain-2 in U251 cells led to increased caspase-3 cleavage and sensitivity to neocarzinostatin, which rapidly induces DNA strand breakage. We hypothesize that calpain-2 causes desensitization of tumor cells against TMZ by preventing strong DNA damage and subsequent apoptosis via post-translational TP53 inhibition. Indeed, proteomic comparison of U251 control vs. U251 calpain-2 knockdown cells highlights perturbed levels of numerous proteins involved in DNA damage response and downstream pathways affecting TP53 and NF-κB signaling. TP53 showed increased protein abundance, but no transcriptional regulation. CONCLUSION: TMZ-induced cell death in the presence of calpain-2 expression appears to favor DNA repair and promote cell survival. We conclude from our experiments that calpain-2 expression represents a proteomic mode that is associated with higher resistance via "priming" GBM cells to TMZ chemotherapy. Thus, calpain-2 could serve as a prognostic factor for GBM outcome.

Netherton syndrome subtypes share IL-17/IL-36 signature with distinct IFN-α and allergic responses.

BACKGROUND: Netherton syndrome (NS) is a rare recessive skin disorder caused by loss-of-function mutations in SPINK5 encoding the protease inhibitor LEKTI (lymphoepithelial Kazal-type-related inhibitor). NS patients experience severe skin barrier defects, display inflammatory skin lesions, and have superficial scaling with atopic manifestations. They present with typical ichthyosis linearis circumflexa (NS-ILC) or scaly erythroderma (NS-SE). OBJECTIVE: We used a combination of several molecular profiling methods to comprehensively characterize the skin, immune cells, and allergic phenotypes of NS-ILC and NS-SE patients. METHODS: We studied a cohort of 13 patients comprising 9 NS-ILC and 4 NS-SE. RESULTS: Integrated multiomics revealed abnormal epidermal proliferation and differentiation and IL-17/IL-36 signatures in lesion skin and in blood in both NS endotypes. Although the molecular profiles of NS-ILC and NS-SE lesion skin were very similar, nonlesion skin of each disease subtype displayed distinctive molecular features. Nonlesion and lesion NS-SE epidermis showed activation of the type I IFN signaling pathway, while lesion NS-ILC skin differed from nonlesion NS-ILC skin by increased complement activation and neutrophil infiltration. Serum cytokine profiling and immunophenotyping of circulating lymphocytes showed a TH2-driven allergic response in NS-ILC, whereas NS-SE patients displayed mainly a TH9 axis with increased CCL22/MDC and CCL17/TARC serum levels. CONCLUSIONS: This study confirms IL-17/IL-36 as the predominant signaling axes in both NS endotypes and unveils molecular features distinguishing NS-ILC and NS-SE. These results identify new therapeutic targets and could pave the way for precision medicine of NS.

MaxQuant and MSstats in Galaxy Enable Reproducible Cloud-Based Analysis of Quantitative Proteomics Experiments for Everyone.

Quantitative mass spectrometry-based proteomics has become a high-throughput technology for the identification and quantification of thousands of proteins in complex biological samples. Two frequently used tools, MaxQuant and MSstats, allow for the analysis of raw data and finding proteins with differential abundance between conditions of interest. To enable accessible and reproducible quantitative proteomics analyses in a cloud environment, we have integrated MaxQuant (including TMTpro 16/18plex), Proteomics Quality Control (PTXQC), MSstats, and MSstatsTMT into the open-source Galaxy framework. This enables the web-based analysis of label-free and isobaric labeling proteomics experiments via Galaxy's graphical user interface on public clouds. MaxQuant and MSstats in Galaxy can be applied in conjunction with thousands of existing Galaxy tools and integrated into standardized, sharable workflows. Galaxy tracks all metadata and intermediate results in analysis histories, which can be shared privately for collaborations or publicly, allowing full reproducibility and transparency of published analysis. To further increase accessibility, we provide detailed hands-on training materials. The integration of MaxQuant and MSstats into the Galaxy framework enables their usage in a reproducible way on accessible large computational infrastructures, hence realizing the foundation for high-throughput proteomics data science for everyone.

Krüppel-like factor 7 influences translation and pathways involved in ribosomal biogenesis in breast cancer.

BACKGROUND: Ribosomal biogenesis and ribosomal proteins have attracted attention in the context of tumor biology in recent years. Instead of being mere translational machineries, ribosomes might play an active role in tumor initiation and progression. Despite its importance, regulation of ribosomal biogenesis is still not completely understood. METHODS: Using Gene Set Enrichment Analysis of RNA sequencing and proteomical mass spectrometry data in breast cancer cells expressing Krüppel-like factor 7 (KLF7), we identified processes altered by this transcription factor. In silico analyses of a cohort of breast cancer patients in The Cancer Genome Atlas confirmed our finding. We further verified the role of KLF7 the identified ribosomal processes in in vitro assays of mammary carcinoma cell lines and analyses of breast cancer patients' tissue slices. RESULTS: We identified the transcription factor Krüppel-like factor 7 (KLF7) as a regulator of ribosomal biogenesis and translation in breast cancer cells and tissue. Highly significant overlapping processes related to ribosomal biogenesis were identified in proteomics and transcriptomics data and confirmed in patients' breast cancer RNA Seq data. Further, nucleoli, the sites of ribosomal biogenesis, were morphologically altered and quantitatively increased in KLF7-expressing cells. Pre-rRNA processing was identified as one potential process affected by KLF7. In addition, an increase in global translation independent from proliferation and transcription was observed upon exogenous KLF7 expression in vitro. Importantly, in a cohort of breast cancer patients, KLF7-expression levels correlated with aggressiveness of the intrinsic breast cancer subtype and tumor grading. Moreover, KLF7 correlated with nucleolar characteristics in human breast tumor tissue, indicating a role for KLF7 in ribosomal biogenesis. CONCLUSION: In mammary carcinoma, KLF7 is involved in ribosomal biogenesis. Alterations of ribosomal biogenesis has far reaching quantitative and qualitative implications for the proteome of the cancer cells. This might influence the aggressiveness of cancer cells.

Sex similarities and differences in the reverse and anti-remodeling effect of pressure unloading therapy in a rat model of aortic banding and debanding.

Investigating the effect of sex on pressure unloading therapy in a clinical scenario is limited by several nonstandardized factors. Hence, we sought to study sex-related similarities and differences under laboratory conditions. Pressure overload was induced in male and female rats by aortic banding (AB) for 6 and 12 wk. Age-matched sham-operated animals served as controls. Pressure unloading was performed by aortic debanding at week 6. Different aspects of myocardial remodeling were characterized by echocardiography, pressure-volume analysis, histology, qRT-PCR, and explorative proteomics. Hypertrophy, increased fetal gene expression, interstitial fibrosis, and prolonged active relaxation were noted in the AB groups at week 6 in both sexes. However, decompensation of systolic function and further deterioration of diastolic function only occurred in male AB rats at week 12. AB induced similar proteomic alterations in both sexes at week 6, whereas characteristic differences were found at week 12. After debanding, regression of hypertrophy and recovery of diastolic function took place to a similar extent in both sexes. Nevertheless, fibrosis, transcription of ß-myosin-to-α-myosin heavy chain ratio, and myocardial proteomic alterations were reduced to a greater degree in females than in males. Debanding exposed anti-remodeling properties in both sexes and prevented the functional decline in males. Female sex is associated with greater reversibility of fibrosis, fetal gene expression, and proteomic alterations. Nevertheless, pressure unloading exposes a more pronounced anti-remodeling effect on the functional level in males, which is attributed to the more progressive functional deterioration in AB animals.NEW & NOTEWORTHY The present study is the first to assess the role of sex on pressure unloading-induced reverse and anti-remodeling in a rat model of aortic banding and debanding. Our data indicate that female sex is associated with a greater reversibility of fibrosis, fetal gene expression, and proteomic alterations compared with males. Nevertheless, pressure unloading exposes more anti-remodeling effect on the functional level in males, which is attributed to the more rapid functional deterioration in aortic-banded animals.

Serum proteome alterations during conventional and extracorporeal resuscitation in pigs.

BACKGROUND: Only a small number of patients survive an out-of-hospital cardiac arrest (CA) and can be discharged from hospital alive with a large percentage of these patients retaining neurological impairments. In recent years, extracorporeal cardiopulmonary resuscitation (ECPR) has emerged as a beneficial strategy to optimize cardiac arrest treatment. However, ECPR is still associated with various complications. To reduce these problems, a profound understanding of the underlying mechanisms is required. This study aims to investigate the effects of CA, conventional cardiopulmonary resuscitation (CPR) and ECPR using a whole-body reperfusion protocol (controlled and automated reperfusion of the whole body-CARL) on the serum proteome profiles in a pig model of refractory CA. METHODS: N = 7 pigs underwent 5 min of untreated CA followed by 30 min CPR and 120 min perfusion with CARL. Blood samples for proteomic analysis were drawn at baseline, after CPR and at the end of the CARL period. Following albumin-depletion, proteomic analysis was performed using liquid chromatography-tandem mass spectrometry. RESULTS: N = 21 serum samples were measured resulting in the identification and quantification of 308-360 proteins per sample and 388 unique proteins in total. The three serum proteome profiles at the investigated time points clustered individually and segregated almost completely when considering a 90% confidence interval. Differential expression analysis showed significant abundance changes in 27 proteins between baseline and after CPR and in 9 proteins after CARL compared to CPR. Significant findings were further validated through a co-abundance cluster analysis corroborating the observed abundance changes. CONCLUSIONS: The presented data highlight the impact of systemic ischemia and reperfusion on the entire serum proteome during resuscitation with a special focus on changes regarding haemolysis, coagulation, inflammation, and cell-death processes. Generally, the observed changes contribute to post-ischemic complications. Better understanding of the underlying mechanisms during CA and resuscitation may help to limit these complications and improve therapeutic options.

Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework.

BACKGROUND: Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of a urothelial carcinoma dataset. METHODS: Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle infiltrating urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. RESULTS: Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle infiltrating urothelial tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: stromal tissue was characterized by collagen peptides and tumor tissue by histone peptides. Immunohistochemistry confirmed an increased histone H2A abundance in the tumor compared to the stroma tissues. The muscle-infiltration status was distinguished via MSI by peptides from intermediate filaments such as cytokeratin 7 in non-muscle infiltrating carcinomas and vimentin in muscle-infiltrating urothelial carcinomas, which was confirmed by immunohistochemistry. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links . CONCLUSION: Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.

The yeast ER-intramembrane protease Ypf1 refines nutrient sensing by regulating transporter abundance.

Proteolysis by aspartyl intramembrane proteases such as presenilin and signal peptide peptidase (SPP) underlies many cellular processes in health and disease. Saccharomyces cerevisiae encodes a homolog that we named yeast presenilin fold 1 (Ypf1), which we verify to be an SPP-type protease that localizes to the endoplasmic reticulum (ER). Our work shows that Ypf1 functionally interacts with the ER-associated degradation (ERAD) factors Dfm1 and Doa10 to regulate the abundance of nutrient transporters by degradation. We demonstrate how this noncanonical branch of the ERAD pathway, which we termed "ERAD regulatory" (ERAD-R), responds to ligand-mediated sensing as a trigger. More generally, we show that Ypf1-mediated posttranslational regulation of plasma membrane transporters is indispensible for early sensing and adaptation to nutrient depletion. The combination of systematic analysis alongside mechanistic details uncovers a broad role of intramembrane proteolysis in regulating secretome dynamics.

The secreted inhibitor of invasive cell growth CREG1 is negatively regulated by cathepsin proteases.

Previous clinical and experimental evidence strongly supports a breast cancer-promoting function of the lysosomal protease cathepsin B. However, the cathepsin B-dependent molecular pathways are not completely understood. Here, we studied the cathepsin-mediated secretome changes in the context of the MMTV-PyMT breast cancer mouse model. Employing the cell-conditioned media from tumor-macrophage co-cultures, as well as tumor interstitial fluid obtained by a novel strategy from PyMT mice with differential cathepsin B expression, we identified an important proteolytic and lysosomal signature, highlighting the importance of this organelle and these enzymes in the tumor micro-environment. The Cellular Repressor of E1A Stimulated Genes 1 (CREG1), a secreted endolysosomal glycoprotein, displayed reduced abundance upon over-expression of cathepsin B as well as increased abundance upon cathepsin B deletion or inhibition. Moreover, it was cleaved by cathepsin B in vitro. CREG1 reportedly could act as tumor suppressor. We show that treatment of PyMT tumor cells with recombinant CREG1 reduced proliferation, migration, and invasion; whereas, the opposite was observed with reduced CREG1 expression. This was further validated in vivo by orthotopic transplantation. Our study highlights CREG1 as a key player in tumor-stroma interaction and suggests that cathepsin B sustains malignant cell behavior by reducing the levels of the growth suppressor CREG1 in the tumor microenvironment.