Changes in protein fluxes in skeletal muscle during sequential stages of muscle regeneration after acute injury in male mice.

Changes in protein turnover play an important role in dynamic physiological processes, including skeletal muscle regeneration, which occurs as an essential part of tissue repair after injury. The inability of muscle tissue to recapitulate this regenerative process can lead to the manifestation of clinical symptoms in various musculoskeletal diseases, including muscular dystrophies and pathological atrophy. Here, we employed a workflow that couples deuterated water (2H2O) administration with mass spectrometry (MS) to systematically measure in-vivo protein turnover rates across the muscle proteome in 8-week-old male C57BL6/J mice. We compared the turnover kinetics of over 100 proteins in response to cardiotoxin (CTX) induced muscle damage and regeneration at unique sequential stages along the regeneration timeline. This analysis is compared to gene expression data from mRNA-sequencing (mRNA-seq) from the same tissue. The data reveals quantitative protein flux signatures in response to necrotic damage, in addition to sequential differences in cell proliferation, energy metabolism, and contractile gene expression. Interestingly, the mRNA changes correlated poorly with changes in protein synthesis rates, consistent with post-transcriptional control mechanisms. In summary, the experiments described here reveal the signatures and timing of protein flux changes during skeletal muscle regeneration, as well as the inability of mRNA expression measurements to reveal changes in directly measured protein turnover rates. The results of this work described here provide a better understanding of the muscle regeneration process and could help to identify potential biomarkers or therapeutic targets.

Progression of monoclonal gammopathy of undetermined significance to multiple myeloma is associated with enhanced translational quality control and overall loss of surface antigens.

BACKGROUND: Despite significant advancements in treatment strategies, multiple myeloma remains incurable. Additionally, there is a distinct lack of reliable biomarkers that can guide initial treatment decisions and help determine suitable replacement or adjuvant therapies when relapse ensues due to acquired drug resistance. METHODS: To define specific proteins and pathways involved in the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), we have applied super-SILAC quantitative proteomic analysis to CD138 + plasma cells from 9 individuals with MGUS and 37 with MM. RESULTS: Unsupervised hierarchical clustering defined three groups: MGUS, MM, and MM with an MGUS-like proteome profile (ML) that may represent a group that has recently transformed to MM. Statistical analysis identified 866 differentially expressed proteins between MM and MGUS, and 189 between MM and ML, 177 of which were common between MGUS and ML. Progression from MGUS to MM is accompanied by upregulated EIF2 signaling, DNA repair, and proteins involved in translational quality control, whereas integrin- and actin cytoskeletal signaling and cell surface markers are downregulated. CONCLUSION: Compared to the premalignant plasma cells in MGUS, malignant MM cells apparently have mobilized several pathways that collectively contribute to ensure translational fidelity and to avoid proteotoxic stress, especially in the ER. The overall reduced expression of immunoglobulins and surface antigens contribute to this and may additionally mediate evasion from recognition by the immune apparatus. Our analyses identified a range of novel biomarkers with potential prognostic and therapeutic value, which will undergo further evaluation to determine their clinical significance.

Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering.

Technological advances in massively parallel sequencing have led to an exponential growth in the number of known protein sequences. Much of this growth originates from metagenomic projects producing new sequences from environmental and clinical samples. The Unified Human Gastrointestinal Proteome (UHGP) catalogue is one of the most relevant metagenomic datasets with applications ranging from medicine to biology. However, the low levels of sequence annotation may impair its usability. This work aims to produce a family classification of UHGP sequences to facilitate downstream structural and functional annotation. This is achieved through the release of the DPCfam-UHGP50 dataset containing 10,778 putative protein families generated using DPCfam clustering, an unsupervised pipeline grouping sequences into single or multi-domain architectures. DPCfam-UHGP50 considerably improves family coverage at protein and residue levels compared to the manually curated repository Pfam. In the hope that DPCfam-UHGP50 will foster future discoveries in the field of metagenomics of the human gut, we release a FAIR-compliant database of our results that is easily accessible via a searchable web server and Zenodo repository.

Characterization of Aspergillus fumigatus secretome during sublethal infection of Galleria mellonella larvae.

Introduction. The fungal pathogen Aspergillus fumigatus can induce prolonged colonization of the lungs of susceptible patients, resulting in conditions such as allergic bronchopulmonary aspergillosis and chronic pulmonary aspergillosis.Hypothesis. Analysis of the A. fumigatus secretome released during sub-lethal infection of G. mellonella larvae may give an insight into products released during prolonged human colonisation.Methodology. Galleria mellonella larvae were infected with A. fumigatus, and the metabolism of host carbohydrate and proteins and production of fungal virulence factors were analysed. Label-free qualitative proteomic analysis was performed to identify fungal proteins in larvae at 96 hours post-infection and also to identify changes in the Galleria proteome as a result of infection.Results. Infected larvae demonstrated increasing concentrations of gliotoxin and siderophore and displayed reduced amounts of haemolymph carbohydrate and protein. Fungal proteins (399) were detected by qualitative proteomic analysis in cell-free haemolymph at 96 hours and could be categorized into seven groups, including virulence (n = 25), stress response (n = 34), DNA repair and replication (n = 39), translation (n = 22), metabolism (n = 42), released intracellular (n = 28) and cellular development and cell cycle (n = 53). Analysis of the Gallerial proteome at 96 hours post-infection revealed changes in the abundance of proteins associated with immune function, metabolism, cellular structure, insect development, transcription/translation and detoxification.Conclusion. Characterizing the impact of the fungal secretome on the host may provide an insight into how A. fumigatus damages tissue and suppresses the immune response during long-term pulmonary colonization.

Urine Proteomic Signatures of Mild Hypothermia Treatment in Cerebral Ischemia-Reperfusion Injury in Rats.

Mild hypothermia (MH) is an effective measure to alleviate cerebral ischemia-reperfusion (I/R) injury. However, the underlying biological mechanisms remain unclear. This study set out to investigate dynamic changes in urinary proteome due to MH in rats with cerebral I/R injury and explore the neuroprotective mechanisms of MH. A Pulsinelli's four-vessel occlusion (4-VO) rat model was used to mimic global cerebral I/R injury. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to profile the urinary proteome of rats with/without MH (32 °C) treatment after I/R injury. Representative differentially expressed proteins (DEPs) associated with MH were validated by western blotting in hippocampus. A total of 597 urinary proteins were identified, among which 119 demonstrated significant changes associated with MH. Gene Ontology (GO) annotation of the DEPs revealed that MH significantly enriched in endopeptidase activity, inflammatory response, aging, response to oxidative stress and reactive oxygen species, blood coagulation, and cell adhesion. Notably, changes in 12 DEPs were significantly reversed by MH treatment. Among them, 8 differential urinary proteins were previously reported to be closely associated with brain disease, including NP, FZD1, B2M, EPCR, ATRN, MB, CA1and VPS4A. Two representative proteins (FZD1, B2M) were further validated by western blotting in the hippocampus and the results were shown to be consistent with urinary proteomic analysis. Overall, this study strengthens the idea that urinary proteome can sensitively reflect pathophysiological changes in the brain, and appears to be the first study to explore the neuroprotective effects of MH by urinary proteomic analysis. FZD1 and B2M may be involved in the most fundamental molecular biological mechanisms of MH neuroprotection.

TSWIFT, a novel method for iterative staining of embedded and mounted human brain sections.

Comprehensive characterization of protein networks in mounted brain tissue represents a major challenge in brain and neurodegenerative disease research. In this study, we develop a simple staining method, called TSWIFT, to iteratively stain pre-mounted formalin fixed, paraffin embedded (FFPE) brain sections, thus enabling high-dimensional sample phenotyping. We show that TSWIFT conserves tissue architecture and allows for relabeling a single mounted FFPE sample more than 10 times, even after prolonged storage at 4 °C. Our results establish TSWIFT as an efficient method to obtain integrated high-dimensional knowledge of cellular proteomes by analyzing mounted FFPE human brain tissue.

Association between plasma proteome and pulmonary heart disease: A two-stage Mendelian randomization analysis.

Pulmonary heart disease (PHD) involves altered structure and function of the right ventricle caused by an abnormal respiratory system that causes pulmonary hypertension. However, the association between changes in plasma proteomics and PHD remains unclear. Hence, we aimed to identify causal associations between genetically predicted plasma protein levels and PHD. Mendelian randomization was performed to test the target proteins associated with PHD. Summary statistics for the human plasma proteome and pulmonary heart disease were acquired from the UK Biobank (6038 cases and 426 977 controls) and the FinnGen study (6753 cases and 302 401 controls). Publicly available pQTLs datasets for human plasma proteins were obtained from a largescale genome-wide association study in the INTERVAL study. The results were validated using a case-control cohort. We first enrolled 3622 plasma proteins with conditionally independent genetic variants; three proteins (histo-blood group ABO system transferase, activating signal cointegration 1 complex subunit 1, and calcium/calmodulin-dependent protein kinase I [CAMK1]) were significantly associated with the risk of pulmonary heart disease in the UK Biobank cohort. Only CAMK1 was successfully replicated (odds ratio: 1.1056, 95% confidence interval: 1.019-1.095, p = 0.0029) in the FinnGen population. In addition, the level of CAMK1 in 40 patients with PHD was significantly higher (p = 0.023) than that in the control group. This work proposes that CAMK1 is associated with PHD, underscoring the importance of the calcium signaling pathway in the pathophysiology to improve therapies for PHD.

Determining the ERK-regulated phosphoproteome driving KRAS-mutant cancer.

To delineate the mechanisms by which the ERK1 and ERK2 mitogen-activated protein kinases support mutant KRAS-driven cancer growth, we determined the ERK-dependent phosphoproteome in KRAS-mutant pancreatic cancer. We determined that ERK1 and ERK2 share near-identical signaling and transforming outputs and that the KRAS-regulated phosphoproteome is driven nearly completely by ERK. We identified 4666 ERK-dependent phosphosites on 2123 proteins, of which 79 and 66%, respectively, were not previously associated with ERK, substantially expanding the depth and breadth of ERK-dependent phosphorylation events and revealing a considerably more complex function for ERK in cancer. We established that ERK controls a highly dynamic and complex phosphoproteome that converges on cyclin-dependent kinase regulation and RAS homolog guanosine triphosphatase function (RHO GTPase). Our findings establish the most comprehensive molecular portrait and mechanisms by which ERK drives KRAS-dependent pancreatic cancer growth.

A reanalysis and integration of transcriptomics and proteomics datasets unveil novel drug targets for Mekong schistosomiasis.

Schistosomiasis, caused by Schistosoma trematodes, is a significant global health concern, particularly affecting millions in Africa and Southeast Asia. Despite efforts to combat it, the rise of praziquantel (PZQ) resistance underscores the need for new treatment options. Protein kinases (PKs) are vital in cellular signaling and offer potential as drug targets. This study focused on focal adhesion kinase (FAK) as a candidate for anti-schistosomal therapy. Transcriptomic and proteomic analyses of adult S. mekongi worms identified FAK as a promising target due to its upregulation and essential role in cellular processes. Molecular docking simulations assessed the binding energy of FAK inhibitors to Schistosoma FAK versus human FAK. FAK inhibitor 14 and PF-03814735 exhibited strong binding to Schistosoma FAK with minimal binding for human FAK. In vitro assays confirmed significant anti-parasitic activity against S. mekongi, S. mansoni, and S. japonicum, comparable to PZQ, with low toxicity in human cells, indicating potential safety. These findings highlight FAK as a promising target for novel anti-schistosomal therapies. However, further research, including in vivo studies, is necessary to validate efficacy and safety before clinical use. This study offers a hopeful strategy to combat schistosomiasis and reduce its global impact.

What's the situation with ocular inflammation? A cross-seasonal investigation of proteomic changes in ocular allergy sufferers' tears in Victoria, Australia.

Background: Ocular allergy (OA) is a localized subset of allergy characterized by ocular surface itchiness, redness and inflammation. Inflammation and eye-rubbing, due to allergy-associated itch, are common in OA sufferers and may trigger changes to the ocular surface biochemistry. The primary aim of this study is to assess the differences in the human tear proteome between OA sufferers and Healthy Controls (HCs) across peak allergy season and off-peak season in Victoria, Australia. Methods: 19 participants (14 OA sufferers, 5 HCs) aged 18-45 were recruited for this study. Participants were grouped based on allergy symptom assessment questionnaire scoring. Proteins were extracted from human tear samples and were run on an Orbitrap Mass Spectrometer. Peaks were matched to a DIA library. Data was analyzed using the software MaxQuant, Perseus and IBM SPSS. Results: 1267 proteins were identified in tear samples of OA sufferers and HCs. 23 proteins were differentially expressed between peak allergy season OA suffers vs HCs, and 21 were differentially expressed in off-peak season. Decreased proteins in OA sufferers related to cell structure regulation, inflammatory regulation and antimicrobial regulation. In both seasons, OA sufferers were shown to have increased expression of proteins relating to inflammation, immune responses and cellular development. Conclusion: Tear protein identification showed dysregulation of proteins involved in inflammation, immunity and cellular structures. Proteins relating to cellular structure may suggest a possible link between OA-associated itch and the subsequent ocular surface damage via eye-rubbing, while inflammatory and immune protein changes highlight potential diagnostic and therapeutic biomarkers of OA.

High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response.

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

Hide-&-Go-PhiP-Seq: Finding an elusive predictive MS biomarker.

Whole-proteome autoantibody profiling reveals an immunological signature that predates the clinical onset of multiple sclerosis.

Folding the human proteome using BioNeMo: A fused dataset of structural models for machine learning purposes.

Human proteins are crucial players in both health and disease. Understanding their molecular landscape is a central topic in biological research. Here, we present an extensive dataset of predicted protein structures for 42,042 distinct human proteins, including splicing variants, derived from the UniProt reference proteome UP000005640. To ensure high quality and comparability, the dataset was generated by combining state-of-the-art modeling-tools AlphaFold 2, OpenFold, and ESMFold, provided within NVIDIA's BioNeMo platform, as well as homology modeling using Innophore's CavitomiX platform. Our dataset is offered in both unedited and edited formats for diverse research requirements. The unedited version contains structures as generated by the different prediction methods, whereas the edited version contains refinements, including a dataset of structures without low prediction-confidence regions and structures in complex with predicted ligands based on homologs in the PDB. We are confident that this dataset represents the most comprehensive collection of human protein structures available today, facilitating diverse applications such as structure-based drug design and the prediction of protein function and interactions.

Comprehensive analysis of silk proteins and gland compartments in Limnephilus lunatus, a case-making trichopteran.

Caddisfly larvae produce silk containing heavy and light fibroins, similar to the silk of Lepidoptera, for the construction of underwater structures. We analyzed the silk of Limnephilus lunatus belonging to the case-forming suborder Integripalpia. We analyzed the transcriptome, mapped the transcripts to a reference genome and identified over 80 proteins using proteomic methods, and checked the specificity of their expression. For comparison, we also analyzed the transcriptome and silk proteome of Limnephilus flavicornis. Our results show that fibroins and adhesives are produced together in the middle and posterior parts of the silk glands, while the anterior part produces enzymes and an unknown protein AT24. The number of silk proteins of L. lunatus far exceeds that of the web-spinning Plectrocnemia conspersa, a previously described species from the suborder Annulipalpia. Our results support the idea of increasing the structural complexity of silk in rigid case builders compared to trap web builders.

Proteomic Analysis of Prehypertensive and Hypertensive Patients: Exploring the Role of the Actin Cytoskeleton.

Hypertension is a pervasive and widespread health condition that poses a significant risk factor for cardiovascular disease, which includes conditions such as heart attack, stroke, and heart failure. Despite its widespread occurrence, the exact cause of hypertension remains unknown, and the mechanisms underlying the progression from prehypertension to hypertension require further investigation. Recent proteomic studies have shown promising results in uncovering potential biomarkers related to disease development. In this study, serum proteomic data collected from Qatar Biobank were analyzed to identify altered protein expression between individuals with normal blood pressure, prehypertension, and hypertension and to elucidate the biological pathways contributing to this disease. The results revealed a cluster of proteins, including the SRC family, CAMK2B, CAMK2D, TEC, GSK3, VAV, and RAC, which were markedly upregulated in patients with hypertension compared to those with prehypertension (fold change ≥ 1.6 or ≤-1.6, area under the curve ≥ 0.8, and q-value < 0.05). Pathway analysis showed that the majority of these proteins play a role in actin cytoskeleton remodeling. Actin cytoskeleton reorganization affects various biological processes that contribute to the maintenance of blood pressure, including vascular tone, endothelial function, cellular signaling, inflammation, fibrosis, and mechanosensing. Therefore, the findings of this study suggest a potential novel role of actin cytoskeleton-related proteins in the progression from prehypertension to hypertension. The present study sheds light on the underlying pathological mechanisms involved in hypertension and could pave the way for new diagnostic and therapeutic approaches for the treatment of this disease.

Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference.

Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step makes it challenging to identify optimal workflows that maximize the identification of differentially expressed proteins. To identify optimal workflows and their common properties, we conduct an extensive study involving 34,576 combinatoric experiments on 24 gold standard spike-in datasets. Applying frequent pattern mining techniques to top-ranked workflows, we uncover high-performing rules that demonstrate optimality has conserved properties. Via machine learning, we confirm optimal workflows are indeed predictable, with average cross-validation F1 scores and Matthew's correlation coefficients surpassing 0.84. We introduce an ensemble inference to integrate results from individual top-performing workflows for expanding differential proteome coverage and resolve inconsistencies. Ensemble inference provides gains in pAUC (up to 4.61%) and G-mean (up to 11.14%) and facilitates effective aggregation of information across varied quantification approaches such as topN, directLFQ, MaxLFQ intensities, and spectral counts. However, further development and evaluation are needed to establish acceptable frameworks for conducting ensemble inference on multiple proteomics workflows.

Super-resolution proximity labeling with enhanced direct identification of biotinylation sites.

Promiscuous labeling enzymes, such as APEX2 or TurboID, are commonly used in in situ biotinylation studies of subcellular proteomes or protein-protein interactions. Although the conventional approach of enriching biotinylated proteins is widely implemented, in-depth identification of specific biotinylation sites remains challenging, and current approaches are technically demanding with low yields. A novel method to systematically identify specific biotinylation sites for LC-MS analysis followed by proximity labeling showed excellent performance compared with that of related approaches in terms of identification depth with high enrichment power. The systematic identification of biotinylation sites enabled a simpler and more efficient experimental design to identify subcellular localized proteins within membranous organelles. Applying this method to the processing body (PB), a non-membranous organelle, successfully allowed unbiased identification of PB core proteins, including novel candidates. We anticipate that our newly developed method will replace the conventional method for identifying biotinylated proteins labeled by promiscuous labeling enzymes.

Integrated ribosome and proteome analyses reveal insights into sevoflurane-induced long-term social behavior and cognitive dysfunctions through ADNP inhibition in neonatal mice.

A growing number of studies have demonstrated that repeated exposure to sevoflurane during development results in persistent social abnormalities and cognitive impairment. Davunetide, an active fragment of the activity-dependent neuroprotective protein (ADNP), has been implicated in social and cognitive protection. However, the potential of davunetide to attenuate social deficits following sevoflurane exposure and the underlying developmental mechanisms remain poorly understood. In this study, ribosome and proteome profiles were analyzed to investigate the molecular basis of sevoflurane-induced social deficits in neonatal mice. The neuropathological basis was also explored using Golgi staining, morphological analysis, western blotting, electrophysiological analysis, and behavioral analysis. Results indicated that ADNP was significantly down-regulated following developmental exposure to sevoflurane. In adulthood, anterior cingulate cortex (ACC) neurons exposed to sevoflurane exhibited a decrease in dendrite number, total dendrite length, and spine density. Furthermore, the expression levels of Homer, PSD95, synaptophysin, and vglut2 were significantly reduced in the sevoflurane group. Patch-clamp recordings indicated reductions in both the frequency and amplitude of miniature excitatory postsynaptic currents (mEPSCs). Notably, davunetide significantly ameliorated the synaptic defects, social behavior deficits, and cognitive impairments induced by sevoflurane. Mechanistic analysis revealed that loss of ADNP led to dysregulation of Ca 2+ activity via the Wnt/ß-catenin signaling, resulting in decreased expression of synaptic proteins. Suppression of Wnt signaling was restored in the davunetide-treated group. Thus, ADNP was identified as a promising therapeutic target for the prevention and treatment of neurodevelopmental toxicity caused by general anesthetics. This study provides important insights into the mechanisms underlying social and cognitive disturbances caused by sevoflurane exposure in neonatal mice and elucidates the regulatory pathways involved.

Potential therapeutic targets for membranous nephropathy: proteome-wide Mendelian randomization and colocalization analysis.

Background: The currently available medications for treating membranous nephropathy (MN) still have unsatisfactory efficacy in inhibiting disease recurrence, slowing down its progression, and even halting the development of end-stage renal disease. There is still a need to develop novel drugs targeting MN. Methods: We utilized summary statistics of MN from the Kiryluk Lab and obtained plasma protein data from Zheng et al. We performed a Bidirectional Mendelian randomization analysis, HEIDI test, mediation analysis, Bayesian colocalization, phenotype scanning, drug bank analysis, and protein-protein interaction network. Results: The Mendelian randomization analysis uncovered 8 distinct proteins associated with MN after multiple false discovery rate corrections. Proteins related to an increased risk of MN in plasma include ABO [(Histo-Blood Group Abo System Transferase) (WR OR = 1.12, 95%CI:1.05-1.19, FDR=0.09, PPH4 = 0.79)], VWF [(Von Willebrand Factor) (WR OR = 1.41, 95%CI:1.16-1.72, FDR=0.02, PPH4 = 0.81)] and CD209 [(Cd209 Antigen) (WR OR = 1.19, 95%CI:1.07-1.31, FDR=0.09, PPH4 = 0.78)], and proteins that have a protective effect on MN: HRG [(Histidine-Rich Glycoprotein) (WR OR = 0.84, 95%CI:0.76-0.93, FDR=0.02, PPH4 = 0.80)], CD27 [(Cd27 Antigen) (WR OR = 0.78, 95%CI:0.68-0.90, FDR=0.02, PPH4 = 0.80)], LRPPRC [(Leucine-Rich Ppr Motif-Containing Protein, Mitochondrial) (WR OR = 0.79, 95%CI:0.69-0.91, FDR=0.09, PPH4 = 0.80)], TIMP4 [(Metalloproteinase Inhibitor 4) (WR OR = 0.67, 95%CI:0.53-0.84, FDR=0.09, PPH4 = 0.79)] and MAP2K4 [(Dual Specificity Mitogen-Activated Protein Kinase Kinase 4) (WR OR = 0.82, 95%CI:0.72-0.92, FDR=0.09, PPH4 = 0.80)]. ABO, HRG, and TIMP4 successfully passed the HEIDI test. None of these proteins exhibited a reverse causal relationship. Bayesian colocalization analysis provided evidence that all of them share variants with MN. We identified type 1 diabetes, trunk fat, and asthma as having intermediate effects in these pathways. Conclusions: Our comprehensive analysis indicates a causal effect of ABO, CD27, VWF, HRG, CD209, LRPPRC, MAP2K4, and TIMP4 at the genetically determined circulating levels on the risk of MN. These proteins can potentially be a promising therapeutic target for the treatment of MN.

Identification of urine biomarkers of endometriosis-Protein mass spectrometry.

INTRODUCTION: Endometriosis is a chronic inflammatory disease that leads to a series of pathological reactions. The basis is a changed proinflammatory activated immune system, which results in more pronounced oxidative stress, disturbed function of proteolysis and cell apoptosis. These processes are crucial in the development of the disease because their dysfunctional activities cause the progression of the disease. It is believed that the proteins excreted in the urine interact with each other and promote pathological processes in endometriosis. METHODS: We analyzed the urine proteome of patients and aimed to detect a potential protein biomarker for endometriosis in the urine proteome. We collected urine samples from 16 patients with endometriosis and 16 patients in the control group with functional ovarian cysts. The diagnosis for all patients was confirmed through pathohistological analysis. After the preanalytical preparation of the urine, chromatography and mass spectrometry (LC-MS/MS) used the technology of urine proteome analysis. RESULTS: The main finding was a significantly different concentration of 14 proteins in the urine samples. We recorded a considerably higher concentration of proteins that have a significant role in activating the immune system (SELL), iron metabolism (HAMP) and cell apoptosis (CHGA) in endometriosis compared to controls. Proteins having an antioxidant function (SOD1) and a role in proteolysis of the extracellular matrix (MMP-9) were significantly reduced in endometriosis compared to controls. CONCLUSION: Consistent with the known pathogenesis of endometriosis, the study results complement the pathological responses that occur with disease progression.