Label-free quantitative proteomic profiling reveals differential plasma protein expression in patients with obesity after treatment with liraglutide.

Introduction: Treatment and management of obesity is clinically challenging. The inclusion of GLP-1 receptor agonists (GLP1RA) in the medical management of obesity has proven to be efficacious. However, mechanisms underlying the molecular changes arising from GLP1RA treatment in patients with obesity remain to be elucidated. Methods: A single-center, prospective study was undertaken to evaluate the changes in the plasma proteins after liraglutide 3 mg therapy in twenty patients (M/F: 7/13) with obesity (mean BMI 40.65 ± 3.7 kg/m2). Anthropometric and laboratory parameters were measured, and blood samples were collected at two time points: baseline, before initiating treatment (pretreatment group, PT), and after three months of receiving the full dose liraglutide 3 mg (posttreatment group, PoT). An untargeted label-free LC MSMS mass spectrometric approach combined with bioinformatics and network pathway analysis was used to determine changes in the proteomic profiles. Results: The mean age of the study participants was 36.0 ± 11.1 years. A statistically significant change was observed in weight, BMI and HbA1c levels between the PT and PoT groups (paired t-test, P < 0.001). A significant dysregulation was noted in the abundances of 151 proteins (31 up and 120 downregulated) between the two groups. The potential biomarkers were evaluated using receiver operating characteristic (ROC) curves. The top ten proteins (area under the curve (AUC) of 0.999 (95% CI)) were identified as potential biomarkers between PT and PoT groups and included Cystatin-B, major vault protein, and plastin-3, which were upregulated, whereas multimerin-2, large ribosomal P2, and proline-rich acidic protein 1 were downregulated in the PoT group compared with the PT group. The top network pathway identified using ingenuity pathway analysis (IPA), centered around dysregulation of MAPK, AKT, and PKc signaling pathways and related to cell-to-cell signaling and interaction, cellular assembly and organization, cellular compromise and a score of 46 with 25 focus proteins. Discussion: Through label-free quantitative proteomic analysis, our study revealed significant dysregulation of plasma proteins after liraglutide 3 mg treatment in patients with obesity. The alterations in the proteomic profile between the PT and PoT groups demonstrated a decrease in levels of proteins involved in inflammation and oxidative stress pathways. On the other hand proteins involved in the glycolytic and lipolytic metabolic pathways as well as those participating in cytoskeletal and endothelial reorganization were observed to be increased. Understanding actions of liraglutide at a molecular and proteomic levels provides a holistic look into how liraglutide impacts metabolism, induces weight loss and improves overall metabolic health.

Assay for characterizing adsorption-properties of surfaces (APS).

Analytes, from sample preparation, until entering an analytical instrument, are prone to adsorb to surfaces, driven by the chemical properties of the surface and the liquids they are dissolved in. This problem can be addressed with internal standards when a single or few known analytes are quantified that are usually not available in omics. However, minimal to no loss of analytes is the aim. Here, we present a novel assay for qualifying and quantifying interactions responsible for adsorption of molecules to surfaces (APS) by using LC-MS/MS-based differential quantitative analysis. To reflect a broad range of chemical interactions with surfaces, a reference mixture of thousands of tryptic peptides, with known compositions was selected, representing a variety of different chemical characteristics. The assay was tested by investigating the adsorption properties of several different vials with different surface chemistries. A significant number of hydrophobic peptides adsorbed to conventional polypropylene vials. In contrast, only few peptides adsorbed to polypropylene vials, assigned as low-protein-binding. The highest number of peptides adsorbed to glass vials driven by electrostatic interactions. In summary, the new assay is suitable to characterize adsorption properties of different surfaces and to approximate the loss of analytes during sample preparation.

Extracellular Proteomic Profiling from the Erythrocytes Infected with Plasmodium Falciparum 3D7 Holds Promise for the Detection of Biomarkers.

Plasmodium falciparum (P. falciparum), which causes the most severe form of malaria, if left untreated, has 24 h window in which it can cause severe illness and even death. The aim of this study was to create the most comprehensive and informative secretory-proteome possible by combining high-accuracy and high-sensitivity protein identification technology. In this study, we used Plasmodium falciparum 3D7 (Pf3D7) as the model parasite to develop a label-free quantification proteomic strategy with the main goal of identifying Pf3D7 proteins that are supposed to be secreted outside the infected erythrocytes in the spent media culture during the in-vitro study. The spent culture media supernatant was subjected to differential and ultra-centrifugation steps followed by total protein extraction, estimation, and in-solution digestion using trypsin, digested peptides were analyzed using Nano-LC coupled with ESI for MS/MS. MS/MS spectra were processed using Maxquant software (v2.1.4.0.). Non-infected erythrocytes incubated spent cultured media supernatant were considered as control. Out of discovered 38 proteins, proteins belonging to P. falciparum spp. were EGF-like protein (C0H544), Endoplasmic reticulum chaperone GRP170 (C0H5H0), Small GTP-binding protein sar1 (Q8I1S0), Erythrocyte membrane protein 1, PfEMP1 (Q8I639), aldehyde reductase (Q8ID61), Conserved Plasmodium proteins (Q8IEH3, Q8ILD1), Antigen 332, DBL-like protein (Q8IHN4), Fe-S cluster assembly protein (Q8II78), identified and chosen for further in-depth investigation. This study highlights the value of secretory Plasmodium proteins play crucial roles in various aspects of the disease progression and host-pathogen interactions which can serve as diagnostic markers for malaria infection.

Efficient and Sensitive Sample Preparation, Separations, and Data Acquisition for Label-Free Single-Cell Proteomics.

We describe a sensitive and efficient workflow for label-free single-cell proteomics that spans sample preparation, liquid chromatography separations, and mass spectrometry data acquisition. The Tecan Uno Single Cell Dispenser provides rapid cell isolation and nanoliter-volume reagent dispensing within 384-well PCR plates. A newly developed sample processing workflow achieves cell lysis, protein denaturation, and digestion in 1 h with a single reagent dispensing step. Low-flow liquid chromatography coupled with wide-window data-dependent acquisition results in the quantification of nearly 3000 proteins per cell using an Orbitrap Exploris 480 mass spectrometer. This approach greatly broadens accessibility to sensitive single-cell proteome profiling for nonspecialist laboratories.

A candidate panel of eight urinary proteins shows potential of early diagnosis and risk assessment for diabetic kidney disease in type 1 diabetes.

Diabetic kidney disease (DKD) poses a significant health challenge for individuals with diabetes. At its initial stages, DKD often presents asymptomatically, and the standard for non-invasive diagnosis, the albumin-creatinine ratio (ACR), employs discrete categorizations (normal, microalbuminuria, macroalbuminuria) with limitations in sensitivity and specificity across diverse population cohorts. Single biomarker reliance further restricts the predictive value in clinical settings. Given the escalating prevalence of diabetes, our study uses proteomic technologies to identify novel urinary proteins as supplementary DKD biomarkers. A total of 158 T1D subjects provided urine samples, with 28 (15 DKD; 13 non-DKD) used in the discovery stage and 131 (45 DKD; 40 pDKD; 46 non-DKD) used in the confirmation. We identified eight proteins (A1BG, AMBP, AZGP1, BTD, RBP4, ORM2, GM2A, and PGCP), all of which demonstrated excellent area-under-the-curve (AUC) values (0.959 to 0.995) in distinguishing DKD from non-DKD. Furthermore, this multi-marker panel successfully segregated the most ambiguous group (microalbuminuria) into three distinct clusters, with 80% of subjects aligning either as DKD or non-DKD. The remaining 20% exhibited continued uncertainty. Overall, the use of these candidate urinary proteins allowed for the better classification of DKD and offered potential for significant improvements in the early identification of DKD in T1D populations.

The cuticle proteome of a planktonic crustacean.

The cuticles of arthropods provide an interface between the organism and its environment. Thus, the cuticle's structure influences how the organism responds to and interacts with its surroundings. Here, we used label-free quantification proteomics to provide a proteome of the moulted cuticle of the aquatic crustacean Daphnia magna, which has long been a prominent subject of studies on ecology, evolution, and developmental biology. We detected a total of 278 high-confidence proteins. Using protein sequence domain and functional enrichment analyses, we identified chitin-binding structural proteins and chitin-modifying enzymes as the most abundant protein groups in the cuticle proteome. Structural cuticular protein families showed a similar distribution to those found in other arthropods and indicated proteins responsible for the soft and flexible structure of the Daphnia cuticle. Finally, cuticle protein genes were also clustered as tandem gene arrays in the D. magna genome. The cuticle proteome presented here will be a valuable resource to the Daphnia research community, informing genome annotations and investigations on diverse topics such as the genetic basis of interactions with predators and parasites.

Dynamic Protein Phosphorylation in Streptococcus pyogenes during Growth, Stationary Phase, and Starvation.

Phosphorylation of proteins at serine, threonine, and tyrosine residues plays an important role in physiological processes of bacteria, such as cell cycle, metabolism, virulence, dormancy, and stationary phase functions. Little is known about the targets and dynamics of protein phosphorylation in Streptococcus pyogenes, which possesses a single known transmembrane serine/threonine kinase belonging to the class of PASTA kinases. A proteomics and phosphoproteomics workflow was performed with S. pyogenes serotype M49 under different growth conditions, stationary phase, and starvation. The quantitative analysis of dynamic phosphorylation, which included a subset of 463 out of 815 identified phosphorylation sites, revealed two main types of phosphorylation events. A small group of phosphorylation events occurred almost exclusively at threonine residues of proteins related to the cell cycle and was enhanced in growing cells. The majority of phosphorylation events occurred during stationary phase or starvation, preferentially at serine residues. PASTA kinase-dependent cell cycle regulation processes found in related bacteria are conserved in S. pyogenes. Increased protein phosphorylation during the stationary phase has also been described for some other bacteria, and could therefore be a general feature in the physiology of bacteria, whose functions and the kinases involved need to be elucidated in further analyses.

Data-Independent Acquisition and Label-Free Quantification for Quantitative Proteomics Analysis of Human Cerebrospinal Fluid.

This article presents a practical guide to mass spectrometry-based data-independent acquisition and label-free quantification for proteomics analysis applied to cerebrospinal fluid, offering a robust and scalable approach to probing the proteomic composition of the central nervous system. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Cerebrospinal fluid sample collection and preparation for mass spectrometry analysis Basic Protocol 2: Mass spectrometry sample analysis with data-independent acquisition Support Protocol: Data-dependent mass spectrometry and spectral library construction Basic Protocol 3: Analysis of mass spectrometry data.

Identification and Targeted Quantification of Endogenous Neuropeptides in the Nematode Caenorhabditis elegans Using Mass Spectrometry.

The nematode Caenorhabditis elegans lends itself as an excellent model organism for peptidomics studies. Its ease of cultivation and quick generation time make it suitable for high-throughput studies. The nervous system, with its 302 neurons, is probably the best-known and studied endocrine tissue. Moreover, its neuropeptidergic signaling pathways display numerous similarities with those observed in other metazoans. Here, we describe two label-free approaches for neuropeptidomics in C. elegans: one for discovery purposes, and another for targeted quantification and comparisons of neuropeptide levels between different samples. Starting from a detailed peptide extraction procedure, we here outline the liquid chromatography tandem mass spectrometry (LC-MS/MS) setup and describe subsequent data analysis approaches.

Label-Free Quantitative Analysis of Pig Liver Proteome after Hepatitis E Virus Infection.

Hepatitis E represents an emerging zoonotic disease caused by the Hepatitis E virus (HEV), for which the main route of transmission is foodborne. In particular, infection in humans has been associated with the consumption of contaminated undercooked meat of pig origin. The aim of this study was to apply comparative proteomics to determine if porcine liver protein profiles could be used to distinguish between pigs seropositive and seronegative for HEV. Preliminarily, an ELISA was used to evaluate the presence of anti-HEV antibodies in the blood serum of 136 animals sent to slaughter. Among the analyzed samples, a seroprevalence of 72.8% was estimated, and it was also possible to identify 10 animals, 5 positive and 5 negative, coming from the same farm. This condition created the basis for the quantitative proteomics comparison between homogeneous animals, in which only the contact with HEV should represent the discriminating factor. The analysis of the proteome in all samples of liver exudate led to the identification of 554 proteins differentially expressed between the two experimental groups, with 293 proteins having greater abundance in positive samples and 261 more represented in negative exudates. The pathway enrichment analysis allowed us to highlight the effect of the interaction between HEV and the host biological system in inducing the potential enrichment of 69 pathways. Among these, carbon metabolism stands out with the involvement of 41 proteins, which were subjected to interactomic analysis. This approach allowed us to focus our attention on three enzymes involved in glycolysis: glucose-6-phosphate isomerase (GPI), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and fructose-bisphosphate aldolase A (ALDOA). It therefore appears that infection with HEV induced a strengthening of the process, which involves the breakdown of glucose to obtain energy and carbon residues useful for the virus's survival. In conclusion, the label-free LC-MS/MS approach showed effectiveness in highlighting the main differences induced on the porcine liver proteome by the interaction with HEV, providing crucial information in identifying a viral signature on the host metabolism.

LFQRatio: A Normalization Method to Decipher Quantitative Proteome Changes in Microbial Coculture Systems.

The value of synthetic microbial communities in biotechnology is gaining traction due to their ability to undertake more complex metabolic tasks than monocultures. However, a thorough understanding of strain interactions, productivity, and stability is often required to optimize growth and scale up cultivation. Quantitative proteomics can provide valuable insights into how microbial strains adapt to changing conditions in biomanufacturing. However, current workflows and methodologies are not suitable for simple artificial coculture systems where strain ratios are dynamic. Here, we established a workflow for coculture proteomics using an exemplar system containing two members, Azotobacter vinelandii and Synechococcus elongatus. Factors affecting the quantitative accuracy of coculture proteomics were investigated, including peptide physicochemical characteristics such as molecular weight, isoelectric point, hydrophobicity, and dynamic range as well as factors relating to protein identification such as varying proteome size and shared peptides between species. Different quantification methods based on spectral counts and intensity were evaluated at the protein and cell level. We propose a new normalization method, named "LFQRatio", to reflect the relative contributions of two distinct cell types emerging from cell ratio changes during cocultivation. LFQRatio can be applied to real coculture proteomics experiments, providing accurate insights into quantitative proteome changes in each strain.

Pilot Evaluation of the Long-Term Reproducibility of Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Top-Down Proteomics of a Complex Proteome Sample.

Mass spectrometry (MS)-based top-down proteomics (TDP) has revolutionized biological research by measuring intact proteoforms in cells, tissues, and biofluids. Capillary zone electrophoresis-tandem MS (CZE-MS/MS) is a valuable technique for TDP, offering a high peak capacity and sensitivity for proteoform separation and detection. However, the long-term reproducibility of CZE-MS/MS in TDP remains unstudied, which is a crucial aspect for large-scale studies. This work investigated the long-term qualitative and quantitative reproducibility of CZE-MS/MS for TDP for the first time, focusing on a yeast cell lysate. Over 1000 proteoforms were identified per run across 62 runs using one linear polyacrylamide (LPA)-coated separation capillary, highlighting the robustness of the CZE-MS/MS technique. However, substantial decreases in proteoform intensity and identification were observed after some initial runs due to proteoform adsorption onto the capillary inner wall. To address this issue, we developed an efficient capillary cleanup procedure using diluted ammonium hydroxide, achieving high qualitative and quantitative reproducibility for the yeast sample across at least 23 runs. The data underscore the capability of CZE-MS/MS for large-scale quantitative TDP of complex samples, signaling its readiness for deployment in broad biological applications. The MS RAW files were deposited in ProteomeXchange Consortium with the data set identifier of PXD046651.

Multispecies Benchmark Analysis for LC-MS/MS Validation and Performance Evaluation in Bottom-Up Proteomics.

We present an instrument-independent benchmark procedure and software (LFQ_bout) for the validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. The procedure enables a back-to-back comparison of common and emerging workflows, e.g., diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary and inadequately documented settings or black-box data processing algorithms. It enhances the overall performance and quantification accuracy by recognizing and reporting common quantification errors.

Precision Sequence-Defined Polymers: From Sequencing to Biological Functions.

Precise sequence-defined polymers (SDPs) with uniform chain-to-chain structure including chain length, unit sequence, and end functionalities represent the pinnacle of sophistication in the realm of polymer science. For example, the absolute control over the unit sequence of SDPs allows for the bottom-up design of polymers with hierarchical microstructures and functions. Accompanied with the development of synthetic techniques towards precision SDPs, the decoding of SDP sequences and construction of advanced functions irreplaceable by other synthetic materials is of central importance. In this Minireview, we focus on recent advances in SDP sequencing techniques including tandem mass spectrometry (MS), chemically assisted primary MS, as well as other non-destructive sequencing methods such as nuclear magnetic resonance (NMR) spectroscopy, circular dichroism (CD), and nanopore sequencing. Additionally, we delve into the promising prospects of SDP functions in the area of cutting-edge biological research. Topics of exploration include gene delivery systems, the development of hybrid materials combining SDPs and nucleic acids, protein recognition and regulation, as well as the interplay between chirality and biological functions. A brief outlook towards the future directions of SDPs is also presented.

Label-free quantification of host cell protein impurity in recombinant hemoglobin materials.

Quantitative analysis relies on pure-substance primary calibrators with known mass fractions of impurity. Here, label-free quantification (LFQ) is being evaluated as a readily available, reliable method for determining the mass fraction of host cell proteins (HCPs) in bioengineered proteins which are intended for use as protein calibration standards. In this study a purified hemoglobin-A2 (HbA2) protein, obtained through its overexpression in E. coli, was used. Two different materials were produced: natural and U15N-labeled HbA2. For the quantification of impurities, precursor ion (MS1-) intensities were integrated over all E. coli proteins identified and divided by the intensities obtained for HbA2. This ratio was calibrated against the corresponding results for an E. coli cell lysate, which had been spiked at known mass ratios to pure HbA2. To demonstrate the universal applicability of LFQ, further proteomes (yeast and human K562) were then alternatively used for calibration and found to produce comparable results. Valid results were also obtained when the complexity of the calibrator was reduced to a mix of just nine proteins, and a minimum of five proteins was estimated to be sufficient to keep the sampling error below 15%. For the studied materials, HbA2 mass fractions (or purities) of 923 and 928 mg(HbA2)/g(total protein) were found with expanded uncertainties (U) of 2.8 and 1.3%, resp. Value assignment by LFQ thus contributes up to about 3% of the overall uncertainty of HbA2 quantification when these materials are used as calibrators. Further purification of the natural HbA2 yielded a mass fraction of 999.1 mg/g, with a negligible uncertainty (U = 0.02%), though at a significant loss of material. If an overall uncertainty of 5% is acceptable for protein quantification, working with the original materials would therefore definitely be viable, circumventing the need of further purification.

All-in-one stability indicating polysorbate 20 degradation root-cause analytics via UPLC-QDa.

Polysorbates (PS) are the most frequently used surfactants to stabilize biologicals. Ironically, these excellent stabilizing non-ionic surfactants have inherent structural properties, which lead to instabilities of their own. Such PS degradation can be triggered by multiple root-causes, like chemical and enzymatic hydrolysis or oxidative degradation. This can on the one hand reduce the concentration of surface-active PS and on the other hand lead to the formation of unfavorable degradants, like poorly soluble free fatty acids (FFA), which may phase separate and form visible FFA particles. Due to the potential criticality of PS degradation in biopharmaceutical formulations, various analytics have been established in recent years not only to monitor the PS content but also to evaluate specific PS markers and crucial degradants. However, in most cases sample preparations and several analytical assays have to be conducted to obtain a comprehensive picture of potential PS degradation root-causes. Here we show a novel approach for PS degradation UPLC-QDa based root-cause analytics, which utilizes previously established analytics for (i) most relevant polysorbate 20 (PS20) esters, (ii) PS20 free fatty acids and (iii) a newly developed method for the evaluation of PS20 specific oxidation markers. Thereby, this triad of analytical methods uses the same sample preparation and detector, which reduces the overall necessary effort, time investment and sample volume. Furthermore, the innovative PS20 oxidation marker method allows to quantify specific concentrations of the determined markers by external calibration and possible perception of oxidative degradation processes prior to relevant losses of PS20 esters, which could serve as an early indication during formulation development. The applicability of this method set was verified using several PS20 containing stress samples, which cover the most relevant root-causes, including acidic and alkaline hydrolysis, enzyme mediated hydrolysis, oxidative AAPH stress and Fe2+/H2O2 mediated degradation as well as autoxidation via long-term storage at elevated temperatures. Overall, this analytical setup has shown to deliver in-depth data about PS20 degradation, which can be used to narrow down the causative stress without the necessity of fundamentally different methods. Therefore, it can be seen as all-in-one solution during sometimes troublesome development of biopharmaceutical formulations, that supports the elucidation of the PS degradation mechanism(s) and thus establish mitigation strategies.

On-Tissue Spatial Proteomics Integrating MALDI-MS Imaging with Shotgun Proteomics Reveals Soy Consumption-Induced Protein Changes in a Fragile X Syndrome Mouse Model.

Fragile X syndrome (FXS), the leading cause of inherited intellectual disability and autism, is caused by the transcriptional silencing of the FMR1 gene, which encodes the fragile X messenger ribonucleoprotein (FMRP). FMRP interacts with numerous brain mRNAs that are involved in synaptic plasticity and implicated in autism spectrum disorders. Our published studies indicate that single-source, soy-based diets are associated with increased seizures and autism. Thus, there is an acute need for an unbiased protein marker identification in FXS in response to soy consumption. Herein, we present a spatial proteomics approach integrating mass spectrometry imaging with label-free proteomics in the FXS mouse model to map the spatial distribution and quantify levels of proteins in the hippocampus and hypothalamus brain regions. In total, 1250 unique peptides were spatially resolved, demonstrating the diverse array of peptidomes present in the tissue slices and the broad coverage of the strategy. A group of proteins that are known to be involved in glycolysis, synaptic transmission, and coexpression network analysis suggest a significant association between soy proteins and metabolic and synaptic processes in the Fmr1KO brain. Ultimately, this spatial proteomics work represents a crucial step toward identifying potential candidate protein markers and novel therapeutic targets for FXS.

Antibacterial Activity of Rainbow Trout Plasma: In Vitro Assays and Proteomic Analysis.

The objective of this study was to investigate the bactericidal activity of blood plasma from cultured rainbow trout obtained from two different fish farms. Plasma from trout naturally infected with the bacterial pathogen Flavobacterium psychrophilum was found to inhibit the growth of Aeromonas hydrophila in vitro. Incubation of A. hydrophila in bacteriostatic trout plasma resulted in agglutination and growth retardation, without causing massive damage to the cell membrane. The proteome of the plasma with high antimicrobial activity revealed an abundance of high-density apolipoproteins, some isoforms of immunoglobulins, complement components C1q and C4, coagulation factors, lectins, periostin, and hemoglobin. Analysis of trout proteins retained on A. hydrophila cells revealed the presence of fish immunoglobulins, lectins, and complement components on bacteria whose growth was inhibited, although the native membrane attack complex of immunised trout plasma did not assemble effectively, resulting in a weak bactericidal effect. Furthermore, this study examined the bacterial response to trout plasma and suggested that the protein synthesis pathway was the target of antimicrobial proteins from fish blood. Taken together, these findings illustrate the advantages of the affinity approach for understanding the role of plasma proteins in host defence against pathogens.

Evaluation of the effect of dimethyl fumarate on human bone marrow-derived mesenchymal stem cells using bottom-up proteomics.

Mesenchymal stem cells (MSCs) have potential as a viable treatment option in the field of regenerative medicine, but MSC-based therapy needs to be more efficient. Preconditioning is a method to improve MSC-based therapy, and dimethyl fumarate (DMF) - an agent that can enhance the antioxidative capacity of cells - can be considered for preconditioning of MSCs. In this study, we treated bone marrow-derived MSCs with DMF and evaluated their proteome using bottom-up proteomics. The MSCs were exposed to 10 µM DMF for 24 h, followed by lysis with an SDS solution, digestion with trypsin using an s-trap column, and analysis using nanoLC-MS/MS, which identified 2262 proteins with confidence. Bioinformatic analysis of the identified proteins revealed 47 upregulated proteins and 81 downregulated proteins upon DMF treatment. Pathway enrichment analysis suggested a possible decrease in autophagy and a decrease in the activity of the TCA cycle, while indicating a potential increase in proliferation and antioxidant activity in DMF-treated MSCs compared to untreated MSCs. Our findings suggest that DMF can enhance the proliferation of MSCs and increase their stability, and that preconditioning could improve the therapeutic efficacy of MSCs for the treatment of regenerative diseases.

Proteomic analysis of chromophobe renal cell carcinoma and benign renal oncocytoma biopsies reveals shared metabolic dysregulation.

BACKGROUND: This study investigates the proteomic landscapes of chromophobe renal cell carcinoma (chRCC) and renal oncocytomas (RO), two subtypes of renal cell carcinoma that together account for approximately 10% of all renal tumors. Despite their histological similarities and shared origins, chRCC is a malignant tumor necessitating aggressive intervention, while RO, a benign growth, is often subject to overtreatment due to difficulties in accurate differentiation. METHODS: We conducted a label-free quantitative proteomic analysis on solid biopsies of chRCC (n = 5), RO (n = 5), and normal adjacent tissue (NAT, n = 5). The quantitative analysis was carried out by comparing protein abundances between tumor and NAT specimens. Our analysis identified a total of 1610 proteins across all samples, with 1379 (85.7%) of these proteins quantified in at least seven out of ten LC‒MS/MS runs for one renal tissue type (chRCC, RO, or NAT). RESULTS: Our findings revealed significant similarities in the dysregulation of key metabolic pathways, including carbohydrate, lipid, and amino acid metabolism, in both chRCC and RO. Compared to NAT, both chRCC and RO showed a marked downregulation in gluconeogenesis proteins, but a significant upregulation of proteins integral to the citrate cycle. Interestingly, we observed a distinct divergence in the oxidative phosphorylation pathway, with RO showing a significant increase in the number and degree of alterations in proteins, surpassing that observed in chRCC. CONCLUSIONS: This study underscores the value of integrating high-resolution mass spectrometry protein quantification to effectively characterize and differentiate the proteomic landscapes of solid tumor biopsies diagnosed as chRCC and RO. The insights gained from this research offer valuable information for enhancing our understanding of these conditions and may aid in the development of improved diagnostic and therapeutic strategies.