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In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy -
Multiplex Targeted Proteomic Analysis of Cytokine Ratios for ICU Mortality in Severe COVID-19 -
Uncovering Enzyme-Specific Post-Translational Modifications: An Overview of Current Methods -
Proteomic Analysis of Sputum from Patients with Active Tuberculosis -
Reduced Serum Protease Activity Is a Measure for Poor Sample Quality
Journal Description
Proteomes
Proteomes
is an international, peer-reviewed, open access journal on all aspects of proteomics published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), PubMed, PMC, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Biochemistry and Molecular Biology) / CiteScore - Q1 (Structural Biology)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 28.2 days after submission; acceptance to publication is undertaken in 4.8 days (median values for papers published in this journal in the first half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.6 (2024);
5-Year Impact Factor:
3.9 (2024)
Latest Articles
Insights into Missense SNPs on Amyloidogenic Proteins
Proteomes 2025, 13(4), 64; https://doi.org/10.3390/proteomes13040064 (registering DOI) - 2 Dec 2025
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Background: Amyloidogenic proteins, a heterogenous group of proteins characterized by their ability to form amyloid fibrils, lead to pathological conditions when they undergo abnormal folding and self-assembly. Missense single-nucleotide polymorphisms (msSNPs) may occur in their sequence, disrupting the normal structure and function of
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Background: Amyloidogenic proteins, a heterogenous group of proteins characterized by their ability to form amyloid fibrils, lead to pathological conditions when they undergo abnormal folding and self-assembly. Missense single-nucleotide polymorphisms (msSNPs) may occur in their sequence, disrupting the normal structure and function of these proteins, pushing them towards amyloidogenesis. Methods: A comprehensive dataset of amyloidogenic proteins was created and their msSNPs were collected and mapped on their amino acid sequence. The chi squared test, logistic regression and the bootstrap method were used to ascertain the statistical significance of the results. Results: The distribution of pathogenic and benign msSNPs highlighted the predicted amyloidogenic segments as hotspots for pathogenic msSNPs. Analysis of the change in residue properties and pathogenicity status revealed that the substitution of negatively charged residues by any other type of residue tends to be pathogenic. Furthermore, certain substitutions were found to be more likely pathogenic than average. Additionally, a case study of APP, a key protein in Alzheimer’s disease, is used as an example. Conclusions: This study will hopefully showcase the importance of amyloidogenic protein msSNPs as well as spark an interest in research of the mechanisms that lead to the formation of amyloid deposits under the scope of pathogenic msSNPs.
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Open AccessArticle
Azidohomoalanine (AHA) Metabolic Labeling Reveals Unique Proteomic Insights into Protein Synthesis and Degradation in Response to Bortezomib Treatment
by
Lina Alhourani, Yasser Tabana, Ashwin Anand and Richard P. Fahlman
Proteomes 2025, 13(4), 63; https://doi.org/10.3390/proteomes13040063 - 25 Nov 2025
Abstract
Background: Multiple myeloma (MM) is essentially an incurable cancer, but treatments with proteasome inhibitors are widely used clinically to extend patient survival. While the mechanisms of proteasome inhibition by Bortezomib are well known, the cellular responses to this proteotoxic stress that leads to
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Background: Multiple myeloma (MM) is essentially an incurable cancer, but treatments with proteasome inhibitors are widely used clinically to extend patient survival. While the mechanisms of proteasome inhibition by Bortezomib are well known, the cellular responses to this proteotoxic stress that leads to sensitivity by MM are not fully elucidated. This study reports on the application of an emerging method to investigate proteostasis by proteomics. Methods: We utilized metabolic labeling with azidohomoalanine (AHA) in a MM cell line in combination with Bortezomib treatment. AHA labeling facilitates the selective isolation and identification of proteins for investigations of protein synthesis or protein degradation. Results: The data collected reveals significant changes in gene protein synthesis upon Bortezomib treatment, including protein neddylation. The data also reveals a global increase in protein degradation, which suggests the induction of an autophagy-related process. The resulting data collected reveals significant changes upon Bortezomib treatment in protein synthesis of genes, including protein neddylation, and protein degradation data reveals a global increase in protein degradation, suggesting an induction of an autophagy-related process. Subsequent cellular and proteomic analysis investigated the additional treatment of an autophagy inhibitor, hydroxychloroquine, in combination with Bortezomib treatment by label-free proteomics to further characterize the proteome-wide changes in these two proteotoxic stresses. Conclusions: AHA metabolic labeling proteomics to investigate protein synthesis and degradation enables novel complementary insights into complex cellular responses compared to that of traditional label-free proteomics.
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(This article belongs to the Section Proteomics Technology and Methodology Development)
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Open AccessArticle
Comparative Proteomic Analysis of Aqueous Humor, Anterior Lens Capsules, and Crystalline Lenses in Different Human Cataract Subtypes Versus Healthy Controls
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Christina Karakosta, Martina Samiotaki, Anastasios Bisoukis, Konstantinos I. Bougioukas, George Panayotou, Nantieznta Kyriakidou, Konstantinos Moschou and Marilita M. Moschos
Proteomes 2025, 13(4), 62; https://doi.org/10.3390/proteomes13040062 - 21 Nov 2025
Abstract
Background: The aim of this study is to investigate the pathophysiology of cataract by analyzing signaling pathways in three sample types obtained from four different lens groups: age-related (ARC), diabetic (DC), post-vitrectomy cataract (PVC) and clear control lenses. Methods: Three sample types—the aqueous
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Background: The aim of this study is to investigate the pathophysiology of cataract by analyzing signaling pathways in three sample types obtained from four different lens groups: age-related (ARC), diabetic (DC), post-vitrectomy cataract (PVC) and clear control lenses. Methods: Three sample types—the aqueous humor, the anterior capsule and the phaco cassette content—were collected during cataract surgery from 39 participants (ARC = 12, DC = 11, PVC = 7 and control = 9). The samples were prepared based on Sp3 protocol. The recognition and quantification of proteins were performed with liquid chromatography online with tandem mass spectrometry using the DIA-NN software. Perseus software (v1.6.15.0) was used for statistical analysis. Data are available via ProteomeXchange with identifiers PXD045547, PXD045554, PXD045557, and PXD069667. Results: In total, 1986 proteins were identified in the aqueous humor, 2804 in the anterior capsule, and 3337 in the phaco cassette samples. Proteins involved in actin and microtubule cytoskeleton organization, including ACTN4, were downregulated in all three cataract groups compared to controls. Proteins involved in glycolipid metabolic process, including GAL3ST1, GAL3ST4, and GLA, were upregulated in ARC compared to controls. Proteins involved in the non-canonical Wnt receptor signaling pathway, including FRZB, SFRP1, SFRP2, SFRP5, WNT5A, and WNT7A, were upregulated in ARC compared to DC, PVC, and controls. Conclusions: Comprehensive proteomic profiles were generated using DIA proteomics by comparing ARC, DC, and PVC versus controls. This is the first study to use phaco cassette contents to investigate cataract formation in comparison to controls. Our findings significantly enhance the current understanding of human cataract pathophysiology and provide novel insights into the mechanisms underlying cataract formation.
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(This article belongs to the Special Issue Proteomics in Chronic Diseases: Issues and Challenges)
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Open AccessArticle
Surveying the Proteome-Wide Landscape of Mitoxantrone and Examining Drug Sensitivity in BRCA1-Deficient Ovarian Cancer Using Quantitative Proteomics
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Savanna Wallin, Sneha Pandithar, Sarbjit Singh, Siddhartha Kumar, Amarnath Natarajan, Gloria E. O. Borgstahl and Nicholas Woods
Proteomes 2025, 13(4), 61; https://doi.org/10.3390/proteomes13040061 - 14 Nov 2025
Abstract
Background: Mitoxantrone (MX) is regularly used to treat several cancers. Despite its long history in the clinic, recent studies continue to unveil novel protein targets. These targets may contribute to the cytotoxic effects of the drug, as well as potential non-canonical antitumor
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Background: Mitoxantrone (MX) is regularly used to treat several cancers. Despite its long history in the clinic, recent studies continue to unveil novel protein targets. These targets may contribute to the cytotoxic effects of the drug, as well as potential non-canonical antitumor activity. A better understanding of MX’s cellular targets is required to fully comprehend the molecular consequences of treatment and to interpret MX sensitivity in homologous recombination (HR)-deficient cancer. Methods: Here, we evaluated MX activity in HR-deficient UWB1.289 (BRCA1−) ovarian cancer cells and surveyed the binding profile of MX using TMT-labeled quantitative proteomics and chemoproteomics. Results: Mass spectrometry (MS) analysis of cellular extracts from MX-treated BRCA1−UWB1.289 cells revealed unique downregulation of pathways instrumental in maintaining genomic stability, including single-strand annealing. Moreover, the BRCA1− cells exhibited a significant upregulation of proteins involved in ribosome biogenesis and RNA processing. Additional MS analyses following affinity-purification using a biotinylated-mitoxantrone probe corroborated these findings, which showed considerable targeting of proteins involved in genome maintenance and RNA processing. Conclusions: Our results suggest that an interplay of both canonical and non-canonical MX-antitumor activity overwhelms the BRCA1− UWB1.289 cells. Furthermore, this study characterizes the target landscape of MX, providing insights into off-target effects and MX action in HR-deficient cancer.
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(This article belongs to the Section Identification of Potential Biomarkers and Potential Therapeutic Targets)
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Open AccessReview
Proteomics in Allopolyploid Crops: Stress Resilience, Challenges and Prospects
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Tanushree Halder, Roopali Bhoite, Shahidul Islam, Guijun Yan, Md. Nurealam Siddiqui, Md. Omar Kayess and Kadambot H. M. Siddique
Proteomes 2025, 13(4), 60; https://doi.org/10.3390/proteomes13040060 - 11 Nov 2025
Abstract
Polyploid crops such as wheat, Brassica, and cotton are critical in the global agricultural and economic system. However, their productivity is threatened increasingly by biotic stresses such as disease, and abiotic stresses such as heat, both exacerbated by climate change. Understanding the molecular
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Polyploid crops such as wheat, Brassica, and cotton are critical in the global agricultural and economic system. However, their productivity is threatened increasingly by biotic stresses such as disease, and abiotic stresses such as heat, both exacerbated by climate change. Understanding the molecular basis of stress responses in these crops is crucial but remains challenging due to their complex genetic makeup—characterized by large sizes, multiple genomes, and limited annotation resources. Proteomics is a powerful approach to elucidate molecular mechanisms, enabling the identification of stress-responsive proteins; cellular localization; physiological, biochemical, and metabolic pathways; protein–protein interaction; and post-translational modifications. It also sheds light on the evolutionary consequences of genome duplication and hybridization. Breeders can improve stress tolerance and yield traits by characterizing the proteome of polyploid crops. Functional and subcellular proteomics, and identification and introgression of stress-responsive protein biomarkers, are promising for crop improvement. Nevertheless, several challenges remain, including inefficient protein extraction methods, limited organelle-specific data, insufficient protein annotations, low proteoform coverage, reproducibility, and a lack of target-specific antibodies. This review explores the genomic complexity of three key allopolyploid crops (wheat, oilseed Brassica, and cotton), summarizes recent proteomic insights into heat stress and pathogen response, and discusses current challenges and future directions for advancing proteomics in polyploid crop improvement through proteomics.
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(This article belongs to the Special Issue Plant Genomics and Proteomics)
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Proteomic Analysis of Plant-Derived hIGF-1-Fc Reveals Proteome Abundance Changes Associated with Wound Healing and Cell Proliferation
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Kittinop Kittirotruji, Utapin Ngaokrajang, Visarut Buranasudja, Ittichai Sujarittham, San Yoon Nwe, Pipob Suwanchaikasem, Kaewta Rattanapisit, Christine Joy I. Bulaon and Waranyoo Phoolcharoen
Proteomes 2025, 13(4), 59; https://doi.org/10.3390/proteomes13040059 - 7 Nov 2025
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Background: Human insulin-like growth factor 1 (hIGF-1) plays a key role in cell proliferation and tissue repair. While plant expression systems offer a cost-effective and scalable alternative for recombinant protein production, the molecular effects of plant-derived hIGF-1 on mammalian cells remain largely unexplored.
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Background: Human insulin-like growth factor 1 (hIGF-1) plays a key role in cell proliferation and tissue repair. While plant expression systems offer a cost-effective and scalable alternative for recombinant protein production, the molecular effects of plant-derived hIGF-1 on mammalian cells remain largely unexplored. Methods: In this study, a recombinant fusion protein of hIGF-1 with human Fc (hIGF-1-Fc) was transiently expressed in Nicotiana benthamiana using the geminiviral pBYR2e system and purified by Protein A affinity chromatography. SDS-PAGE and Western blotting confirmed the predicted molecular weight, and LC-MS identified N-glycosylation at the Fc N229 site with plant-type glycans such as GnMXF, GnGnXF, and MMXF. Bioactivity was evaluated using MCF-7 cell proliferation and NIH3T3 wound healing assays. Label-free quantitative proteomics was performed on NIH3T3 fibroblasts to assess molecular changes. Results: hIGF-1 Fc significantly promoted cancer cell migration and fibroblast proliferation. Proteomic profiling revealed an abundance of cytoskeletal proteins such as actin and tubulin and metabolic enzymes related to energy production. Gene ontology and pathway enrichment analyses indicated significant modulation of ribosome biogenesis and carbon metabolism. Conclusions: This study presents the first proteome-level investigation of plant-produced hIGF-1-Fc in mouse fibroblasts and reveals its impact on cytoskeletal organization and metabolic pathways involved in proliferation and wound healing.
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TCEPVDB: Artificial Intelligence-Based Proteome-Wide Screening of Antigens and Linear T-Cell Epitopes in the Poxviruses and the Development of a Repository
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Mansi Dutt, Anuj Kumar, Ali Toloue Ostadgavahi, David J. Kelvin and Gustavo Sganzerla Martinez
Proteomes 2025, 13(4), 58; https://doi.org/10.3390/proteomes13040058 - 6 Nov 2025
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Background: Poxviruses constitute a family of large dsDNA viruses that can infect a plethora of species including humans. Historically, poxviruses have caused a health burden in multiple outbreaks. The large genome of poxviruses favors reverse vaccinology approaches that can determine potential antigens and
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Background: Poxviruses constitute a family of large dsDNA viruses that can infect a plethora of species including humans. Historically, poxviruses have caused a health burden in multiple outbreaks. The large genome of poxviruses favors reverse vaccinology approaches that can determine potential antigens and epitopes. Here, we propose the modeling of a user-friendly database containing the predicted antigens and epitopes of a large cohort of poxvirus proteomes using the existing PoxiPred method for reverse vaccinology of poxviruses. Methods: In the present study, we obtained the whole proteomes of as many as 37 distinct poxviruses. We utilized each proteome to predict both antigenic proteins and T-cell epitopes of poxviruses with the aid of an Artificial Intelligence method, namely the PoxiPred method. Results: In total, we predicted 3966 proteins as potential antigen targets. Of note, we considered that this protein may exist in a set of proteoforms. Subsets of these proteins constituted a comprehensive repository of 54,291 linear T-cell epitopes. We combined the outcome of the predictions in the format of a web tool that delivers a database of antigens and epitopes of poxviruses. We also developed a comprehensive repository dedicated to providing access to end-users to obtain AI-based screened antigens and T-cell epitopes of poxviruses in a user-friendly manner. These antigens and epitopes can be utilized to design experiments for the development of effective vaccines against a plethora of poxviruses. Conclusions: The TCEPVDB repository, already deployed to the web under an open-source coding philosophy, is free to use, does not require any login, does not store any information from its users.
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Integrated Analysis of Proteomic Marker Databases and Studies Associated with Aging Processes and Age-Dependent Conditions: Optimization Proposals for Biomedical Research
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Mikhail S. Arbatskiy, Dmitriy E. Balandin and Alexey V. Churov
Proteomes 2025, 13(4), 57; https://doi.org/10.3390/proteomes13040057 - 6 Nov 2025
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Background: The search for reliable aging biomarkers using proteomic databases and large-scale proteomic studies presents a significant challenge in biogerontology. Existing proteomic databases and studies contain valuable information; however, there is inconsistency in approaches to biomarker selection and data integration. This creates
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Background: The search for reliable aging biomarkers using proteomic databases and large-scale proteomic studies presents a significant challenge in biogerontology. Existing proteomic databases and studies contain valuable information; however, there is inconsistency in approaches to biomarker selection and data integration. This creates barriers to translating existing knowledge into clinical practice and use in biomedical research. This work analyzed experimental proteomic studies, the content of proteomic databases, and proposed recommendations for optimization and improvement of proteomic database formation and enrichment. Methods: The study utilized publications devoted to proteomic data acquisition methods, proteomic databases, and experimental studies. Results: Methods for obtaining proteomic data were analyzed (Protein Pathway Array (PPA), Tissue Microarray (TMA), Luminex (Bead Array), MSD (Meso Scale Discovery), Simoa (Quanterix), SOMAscan (SomaLogic), Olink (PEA), Alamar NULISA (PEA+), and Oxford Nanopore. A total of 16 proteomic databases were investigated (HAGR, KEGG, STRING, Aging Atlas, HALL, Human Protein Atlas, UniProt, AgeAnnoMO, AgeFactDB, AgingBank, iProX, jMorp, jPOSTrepo, MassIVE, MetaboAge DB, PRIDE Archive). Additionally, 22 proteomic studies devoted to aging and age-associated diseases were analyzed. Conclusions: Proteomic databases and experimental studies individually contain valuable information about aging biomarkers. Using data from different sources within biomedical research poses challenges for improving and optimizing methodological solutions for publication selection, database formation, and marker development.
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Mimicry in the Bite: Shared Sequences Between Aedes aegypti Salivary Proteins and Human Proteins
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Andrea Arévalo-Cortés and Daniel Rodriguez-Pinto
Proteomes 2025, 13(4), 56; https://doi.org/10.3390/proteomes13040056 - 3 Nov 2025
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Background: Molecular mimicry contributes to the development of unwanted responses to self-antigens. Autoimmune phenomena have been observed in diseases caused by Aedes aegypti-transmitted arboviruses, but the occurrence of mimicry between salivary and human proteins has been unexplored. Methods: We used bioinformatic tools
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Background: Molecular mimicry contributes to the development of unwanted responses to self-antigens. Autoimmune phenomena have been observed in diseases caused by Aedes aegypti-transmitted arboviruses, but the occurrence of mimicry between salivary and human proteins has been unexplored. Methods: We used bioinformatic tools to determine if peptides from Aedes aegypti salivary proteins were present in the human proteome. We further characterized the potential of shared sequences to induce immunity by analyzing their predicted binding to MHC molecules and their occurrence in peptides from the Immune Epitope Database (IEDB). Results: We analyzed 9513 octapeptides from 29 Aedes aegypti salivary proteins against the human proteome and found 47 peptides identical to sequences from 52 human proteins, ranging in length from 8 to 18 amino acids. We found 302 matches of peptides predicted to bind with high affinity to MHC-I and MHC-II alleles associated with autoimmune diseases, and 14 human peptides containing shared sequences with Aedes aegypti salivary proteins validated as immunogenic in the IEDB. Conclusions: These results support the existence of molecular mimicry between Aedes aegypti salivary proteins and human antigens and provide a framework for studies to determine its contribution to responses directed to self-antigens in the context of arboviral infections.
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Open AccessArticle
Identification of Protein Markers for Chronic Ischemic Heart Disease Through Integrated Analysis of the Human Plasma Proteome and Genome-Wide Association Data
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Chunyang Ren, Gan Qiao, Jianping Wu, Yongxiang Lu, Minghua Liu and Chunxiang Zhang
Proteomes 2025, 13(4), 55; https://doi.org/10.3390/proteomes13040055 - 3 Nov 2025
Abstract
Background: Chronic ischemic heart disease (CIHD) is characterized by persistent myocardial ischemic due to long-term reduced coronary blood flow. In the past, we mainly relied on surgical intervention or drug therapy to alleviate symptoms, but effective targeted treatments were scarce. Proteomics serves as
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Background: Chronic ischemic heart disease (CIHD) is characterized by persistent myocardial ischemic due to long-term reduced coronary blood flow. In the past, we mainly relied on surgical intervention or drug therapy to alleviate symptoms, but effective targeted treatments were scarce. Proteomics serves as a key tool to identify novel therapeutic targets. Methods: This study performed a bidirectional Mendelian randomization (MR) analysis by integrating genome-wide association study (GWAS) data on CIHD (10,894,596 single-nucleotide polymorphisms) with plasma proteomic data encompassing 4907 proteins. We conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify pathways linked to candidate protein biomarkers, searched the National Genomics Data Center (NGDC) database for existing evidence of their association with CIHD, and evaluated druggability through multi-dimensional analysis integrating the DSIGDB, ChEMBL, and clinical trial databases. Results: After eliminating the reverse effect, ultimately identifying 28 protein markers, including 16 risk-associated and 12 protective proteins. We also investigated their roles in the pathways related to CIHD. Meanwhile, the search confirmed that five of them were newly discovered protein markers. Ultimately, through evaluation, three priority therapeutic targets (CXCL12, PLAU, CD14) were identified for development. Conclusions: This study identified some biomarkers related to CIHD and analyzed the possible pathways involved. It also provided some new insights into the identification of the target and druggability.
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(This article belongs to the Section Identification of Potential Biomarkers and Potential Therapeutic Targets)
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Open AccessReview
Recent Advances and Application of Machine Learning for Protein–Protein Interaction Prediction in Rice: Challenges and Future Perspectives
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Sarah Bernard Merumba, Habiba Omar Ahmed, Dong Fu and Pingfang Yang
Proteomes 2025, 13(4), 54; https://doi.org/10.3390/proteomes13040054 - 27 Oct 2025
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Protein–protein interactions (PPIs) are significant in understanding the complex molecular processes of plant growth, disease resistance, and stress responses. Machine learning (ML) has recently emerged as a powerful tool that can predict and analyze PPIs, offering complementary insights into traditional experimental approaches. It
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Protein–protein interactions (PPIs) are significant in understanding the complex molecular processes of plant growth, disease resistance, and stress responses. Machine learning (ML) has recently emerged as a powerful tool that can predict and analyze PPIs, offering complementary insights into traditional experimental approaches. It also accounts for proteoforms, distinct molecular variants of proteins arising from alternative splicing, or genetic variations and modifications, which can significantly influence PPI dynamics and specificity in rice. This review presents a comprehensive summary of ML-based methods for PPI predictions in rice (Oryza sativa) based on recent developments in algorithmic innovation, feature extraction processes, and computational resources. We present applications of these models in the discovery of candidate genes, unknown protein annotations, identification of plant–pathogen interactions, and precision breeding. Case studies demonstrate the utility of ML-based methods in improving rice resistance to abiotic and biotic stresses. Additionally, this review highlights key challenges like data limits, model generalizability, and future directions like multi-omics, deep learning and artificial intelligence (AI). This review provides a roadmap for researchers aiming to use ML to generate predictive and mechanistic insights on rice PPI networks, hence helping to achieve enhanced crop improvement programs.
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(This article belongs to the Special Issue Plant Genomics and Proteomics)
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Open AccessReview
Marine Bioactive Peptides in the Regulation of Inflammatory Responses: Current Trends and Future Directions
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D. M. N. M. Gunasekara, H. D. T. U. Wijerathne, Lei Wang, Hyun-Soo Kim and K. K. A. Sanjeewa
Proteomes 2025, 13(4), 53; https://doi.org/10.3390/proteomes13040053 - 13 Oct 2025
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Marine-derived bioactive peptides (MBPs) are emerging as promising natural agents for regulating inflammatory responses. MBPs, typically obtained through enzymatic hydrolysis of proteins from various marine organisms such as fish, mollusks, and algae, exhibit diverse biological activities, including antioxidant, immunomodulatory, and anti-inflammatory effects. The
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Marine-derived bioactive peptides (MBPs) are emerging as promising natural agents for regulating inflammatory responses. MBPs, typically obtained through enzymatic hydrolysis of proteins from various marine organisms such as fish, mollusks, and algae, exhibit diverse biological activities, including antioxidant, immunomodulatory, and anti-inflammatory effects. The ability of MBPs to modulate key inflammatory mediators such as TNF-α, IL-6, and COX-2, primarily through pathways like NF-κB and MAPK, highlights the therapeutic potential of MBPs in managing chronic inflammatory diseases. However, most existing studies are confined to in vitro assays or animal models, with limited translation to human clinical applications. This review explores the stability, bioavailability, and metabolic rate of MBPs under physiological conditions, which remain poorly understood. In addition, a lack of standardized protocols for peptide extraction, purification, and efficacy evaluation hinders comparative analysis across studies and also different proteomics approaches for separation, purification, identification, and quantification of marine-derived peptides with therapeutic properties. The structure–function relationship of MBPs is also underexplored, limiting rational design and targeted applications in functional foods or therapeutic products. These limitations are largely due to a lack of consolidated information and integrated research efforts. To address these challenges, this review summarizes recent progress in identifying MBPs with anti-inflammatory potentials, outlines key mechanisms, and highlights current limitations. Additionally, this review also emphasizes the need to enhance mechanistic understanding, optimize delivery strategies, and advance clinical validation to fully realize the therapeutic potential of MBPs.
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Open AccessArticle
Temporal and Spatial Profiling of Escherichia coli O157:H7 Surface Proteome: Insights into Intestinal Colonisation Dynamics In Vivo
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Ricardo Monteiro, Ingrid Chafsey, Charlotte Cordonnier, Valentin Ageorges, Didier Viala, Michel Hébraud, Valérie Livrelli, Alfredo Pezzicoli, Mariagrazia Pizza and Mickaël Desvaux
Proteomes 2025, 13(4), 52; https://doi.org/10.3390/proteomes13040052 - 10 Oct 2025
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Background: EHEC O157:H7 causes severe gastrointestinal illness by first colonizing the large intestine. It intimately attaches to the epithelial lining, orchestrating distinctive “attaching and effacing” lesions that disrupt the host’s cellular landscape. While much is known about the well-established virulence factors, there are
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Background: EHEC O157:H7 causes severe gastrointestinal illness by first colonizing the large intestine. It intimately attaches to the epithelial lining, orchestrating distinctive “attaching and effacing” lesions that disrupt the host’s cellular landscape. While much is known about the well-established virulence factors, there are much to learn about the surface proteins’ roles in a living host. Methods: This study presents the first in vivo characterisation of the surface proteome, i.e., proteosurfaceome, of Escherichia coli O157:H7 EDL933 during intestinal infection, revealing spatial and temporal adaptations critical for colonisation and survival. Using a murine ileal loop model, surface proteomic profiles were analysed at early (3 h) and late (10 h) infection stages across the ileum and colon. Results: In total, 272 proteins were identified, with only 13 shared across all conditions, reflecting substantial niche-specific adaptations. Gene ontology enrichment analyses highlighted dominant roles in metabolic, cellular, and binding functions, while subcellular localisation prediction uncovered cytoplasmic moonlighting proteins with surface activity. Comparative analyses revealed dynamic changes in protein abundance. Conclusions: These findings indicate a coordinated shift from stress adaptation and virulence to nutrient acquisition and persistence and provide a comprehensive view of EHEC O157:H7 surface proteome dynamics during infection, highlighting key adaptive proteins that may serve as targets for future therapeutic and vaccine strategies.
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Protein-Predicted Obesity Phenotypes and Cardiovascular Events: A Secondary Analysis of UK Biobank Proteomics Data
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Chang Liu, Bojung Seo, Qin Hui, Peter W. F. Wilson, Arshed A. Quyyumi and Yan V. Sun
Proteomes 2025, 13(4), 51; https://doi.org/10.3390/proteomes13040051 - 9 Oct 2025
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Background: Proteomic profiling may improve the understanding of obesity and cardiovascular risk prediction. This study explores the use of protein-predicted scores for body mass index (PPSBMI), body fat percentage (PPSBFP), and waist–hip ratio (PPSWHR) to estimate risk
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Background: Proteomic profiling may improve the understanding of obesity and cardiovascular risk prediction. This study explores the use of protein-predicted scores for body mass index (PPSBMI), body fat percentage (PPSBFP), and waist–hip ratio (PPSWHR) to estimate risk for major adverse cardiovascular events (MACEs). Methods: We used data from the UK Biobank with proteome profiling. PPSBMI, PPSBFP, and PPSWHR were derived using the LASSO algorithm. The association between these protein scores and incident MACEs was evaluated using a competing risk model. Results: Strong to moderate correlations were observed between protein-predicted obesity phenotypes and their measured counterparts (R2: BMI = 0.78, BFP = 0.85, WHR = 0.63). Each standard deviation increment of PPSBFP and PPSWHR, but not PPSBMI, was associated with greater risk of MACEs (hazard ratio [HR] 1.25, 95% CI 1.14–1.38, p < 0.0001; HR 1.15, 95% CI 1.06–1.24, p = 0.001, respectively). For predicting MACEs, compared with the PREVENT equation (C statistic 0.694), the models adjusted for only age, sex, current smoking, and protein scores showed comparable performance (C statistics 0.684–0.688). Conclusion: Protein-predicted scores of obesity showed strong independent associations and predictive performance for MACEs, suggesting they may capture additional biological risk beyond anthropometry. These scores may complement existing risk models by providing a biologically informed approach to assessing obesity-related cardiovascular risk and improving risk stratification.
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Open AccessArticle
Protein Structural Modeling Explains Rapid Oxidation in Poultry and Fish Myoglobins Compared to Livestock Myoglobins
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Greeshma Sreejesh, Surendranath P. Suman, Gretchen G. Mafi, Morgan M. Pfeiffer and Ranjith Ramanathan
Proteomes 2025, 13(4), 50; https://doi.org/10.3390/proteomes13040050 - 8 Oct 2025
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Background: This study aimed to investigate rapid oxidation in poultry and fish myoglobin compared to livestock myoglobin using protein structural differences and bioinformatics tools. Methods: Myoglobins from beef (Bos taurus), bison (Bos bison), sheep (Ovis aries), goat
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Background: This study aimed to investigate rapid oxidation in poultry and fish myoglobin compared to livestock myoglobin using protein structural differences and bioinformatics tools. Methods: Myoglobins from beef (Bos taurus), bison (Bos bison), sheep (Ovis aries), goat (Capra hircus), red deer (Cervus elaphus), pork (Sus scrofa), chicken (Gallus gallus), turkey (Meleagris gallopavo), yellowfin tuna (Thunnus albacares), and tilapia (Oreochromis niloticus) were analyzed to understand differences in structure and function that may influence oxidative behavior. Results: Fish and poultry had shorter or absent D-helix in their myoglobin structure than other species. Tilapia showed the largest heme cavity surface area, indicating significant internal void space, while yellowfin tuna had the largest heme cavity volume, which could affect ligand binding dynamics compared with poultry and other livestock species. However, the heme solvent-accessible area was greater in chicken and turkey than in fish and other livestock species. Tuna myoglobin contains a cysteine and fish myoglobins have fewer amino acids compared to other species. Limited knowledge is currently available on the effects of proteoform, especially post-translational modifications, on the oxidation of myoglobin from different species. Conclusions: The bioinformatics approach used in this study suggests that, in addition to physiological reasons, shorter D-helix, larger heme cavity in tilapia and yellowfin tuna, and greater solvent-accessible area in poultry contribute to increased oxidation in myoglobin from poultry and fish compared with myoglobin from livestock species.
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Open AccessReview
Extracellular Vesicle (EV) Proteomics in Corneal Regenerative Medicine
by
Zohreh Arabpour, Hanieh Niktinat, Firouze Hatami, Amal Yaghmour, Zarife Jale Yucel, Seyyedehfatemeh Ghalibafan, Hamed Massoumi, Zahra Bibak Bejandi, Majid Salehi, Elmira Jalilian, Mahmood Ghassemi, Victor H. Guaiquil, Mark Rosenblatt and Ali R. Djalilian
Proteomes 2025, 13(4), 49; https://doi.org/10.3390/proteomes13040049 - 3 Oct 2025
Cited by 1
Abstract
Corneal regeneration has gained growing interest in recent years, largely due to the limitations of conventional treatments and the persistent shortage of donor tissue. Among the emerging strategies, extracellular vehicles (EVs), especially those derived from mesenchymal stromal cells (MSCs), have shown great promise
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Corneal regeneration has gained growing interest in recent years, largely due to the limitations of conventional treatments and the persistent shortage of donor tissue. Among the emerging strategies, extracellular vehicles (EVs), especially those derived from mesenchymal stromal cells (MSCs), have shown great promise as a cell-free therapeutic approach. These nanoscale vesicles contribute to corneal healing by modulating inflammation, supporting epithelial and stromal regeneration, and promoting nerve repair. Their therapeutic potential is largely attributed to the diverse and bioactive proteomic cargo they carry, including growth factors, cytokines, and proteins involved in extracellular matrix remodeling. This review presents a comprehensive examination of the proteomic landscape of EVs in the context of corneal regenerative medicine. We explore the biological functions of EVs in corneal epithelial repair, stromal remodeling, and neurodegeneration. In addition, we discuss advanced proteomic profiling techniques such as mass spectrometry (MS) and liquid chromatography–mass spectrometry (LC-MS/MS), which have been used to identify and characterize the protein contents of EVs. This review also compares the proteomic profiles of EVs derived from various MSC sources, including adipose tissue, bone marrow, and umbilical cord, and considers how environmental cues, such as hypoxia and inflammation, influence their protein composition. By consolidating current findings, this article aims to provide valuable insights for advancing the next generation of cell-free therapies for corneal repair and regeneration.
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(This article belongs to the Topic Multi-Omics in Precision Medicine)
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Open AccessArticle
Proteomic Characterization of Primary Human Pancreatic Cancer Cell Lines Following Long-Term Exposure to Gemcitabine
by
Manoj Amrutkar, Yuchuan Li, Anette Vefferstad Finstadsveen, Caroline S. Verbeke and Ivar P. Gladhaug
Proteomes 2025, 13(4), 48; https://doi.org/10.3390/proteomes13040048 - 1 Oct 2025
Abstract
Background: Gemcitabine (GEM) remains a cornerstone in the treatment of pancreatic cancer. Upon exposure to GEM, pancreatic cancer cells (PCCs) tend to adapt quickly to outcompete drug-induced cytotoxicity, thereby contributing to treatment failure. Thus, understanding GEM-induced molecular changes in PCCs is important. Methods:
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Background: Gemcitabine (GEM) remains a cornerstone in the treatment of pancreatic cancer. Upon exposure to GEM, pancreatic cancer cells (PCCs) tend to adapt quickly to outcompete drug-induced cytotoxicity, thereby contributing to treatment failure. Thus, understanding GEM-induced molecular changes in PCCs is important. Methods: Three primary PCC lines (PCC-1, PCC-2, PCC-7) and Mia PaCa-2 cultured for 40 passages (p) in the absence (control) or presence of GEM (GemR) were assessed for phenotypic changes. Proteome profiles for all PCCs at p10, p20, p25, p30, p35, and p40 were obtained using mass spectrometry (MS). Protein expression was determined using immunoblotting. Differentially abundant proteins (DAPs) were evaluated for enrichment of functional and biological attributes and protein–protein interactions. Results: GEM sensitivity and growth were both reduced in GemR versus paired controls for all four PCC lines. MS mapped > 7000 proteins in each PCC line, and the abundance of 70–83% of these was found to be significantly altered when comparing all sample groups. Proteomic changes in GemR versus paired controls differed remarkably among the PCCs and were affected by passaging and treatment duration. DAPs at p40 were mostly related to metabolic pathways, including nucleotide metabolism and diverse cell growth processes. Several closely related DAPs and multiple hub proteins in each PCC line were identified. Conclusions: Overall, this study revealed cell-line-specific, heterogeneous changes in proteome profiles of PCCs following their long-term exposure to GEM, and these were likely affected by treatment duration, dosage, and passaging.
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(This article belongs to the Special Issue Proteomics in Chronic Diseases: Issues and Challenges)
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Open AccessReview
In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy
by
Anca-Narcisa Neagu, Pathea S. Bruno, Claudiu-Laurentiu Josan, Natalie Waterman, Hailey Morrissiey, Victor T. Njoku and Costel C. Darie
Proteomes 2025, 13(4), 47; https://doi.org/10.3390/proteomes13040047 - 23 Sep 2025
Cited by 1
Abstract
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Cancer detection has made significant progress, moving from conventional methods to innovative, non-invasive or minimally invasive approaches aimed at improving early diagnosis, precision, and treatment outcomes. This review examines current and emerging diagnostic technologies, including liquid biopsy (LB), molecular biomarkers, and artificial intelligence
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Cancer detection has made significant progress, moving from conventional methods to innovative, non-invasive or minimally invasive approaches aimed at improving early diagnosis, precision, and treatment outcomes. This review examines current and emerging diagnostic technologies, including liquid biopsy (LB), molecular biomarkers, and artificial intelligence (AI). LB analyzes biomarkers in bodily fluids, showing promise in detecting tumors at molecular levels, monitoring cancer progression, and predicting treatment responses. The assignment of specific proteoforms, often linked to tumor subtype, stage, and therapy resistance, adds another layer of diagnostic precision, offering valuable insights for personalized oncology. However, the clinical application of LB faces challenges related to sensitivity, specificity, tumor heterogeneity, and a lack of standardized protocols. Relatively high costs, complex result interpretation, and privacy concerns also hinder its widespread adoption in clinical practice. Despite these challenges, advancements in AI, nanotechnology, and multi-omics strategies offer opportunities to enhance cancer diagnostic accuracy. Future developments, including wearable biosensors and lab-on-a-chip technologies, could lead to personalized, real-time cancer detection with improved patient outcomes, potentially redefining cancer care and fostering a more proactive, patient-centered healthcare approach.
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Open AccessSystematic Review
Neurogranin as a Synaptic Biomarker in Mild Traumatic Brain Injury: A Systematic Review of Diagnostic and Pathophysiological Evidence
by
Ioannis Mavroudis, Foivos Petridis, Eleni Karantali and Dimitrios Kazis
Proteomes 2025, 13(3), 46; https://doi.org/10.3390/proteomes13030046 - 19 Sep 2025
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Neurogranin (NRGN), a synaptic protein essential for plasticity and memory function, is gaining recognition as a promising biomarker for mild traumatic brain injury (mTBI). This systematic review brings together findings from six studies that measured neurogranin levels in biofluids—including serum, cerebrospinal fluid (CSF),
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Neurogranin (NRGN), a synaptic protein essential for plasticity and memory function, is gaining recognition as a promising biomarker for mild traumatic brain injury (mTBI). This systematic review brings together findings from six studies that measured neurogranin levels in biofluids—including serum, cerebrospinal fluid (CSF), plasma, and exosomes—during both the acute and chronic phases following injury. In the acute phase of mTBI, elevated levels of neurogranin were consistently observed in serum samples, suggesting its potential as a diagnostic marker. These increases appear to reflect immediate synaptic disturbances caused by injury. In contrast, studies focusing on the chronic phase reported a decrease in exosomal neurogranin levels, pointing to ongoing synaptic dysfunction well after the initial trauma. This temporal shift in neurogranin expression highlights its dual utility—both as an early indicator of injury and as a longer-term marker of synaptic integrity. However, interpreting these findings is not straightforward. The studies varied considerably in terms of sample type, timing of measurements, and control for potential confounding factors such as physical activity. Such variability makes direct comparisons difficult and may influence the outcomes observed. Additionally, none of the studies included proteoform-specific analyses of neurogranin, an omission that limits our understanding of the molecular changes underlying mTBI-related synaptic alterations. Due to heterogeneity across study designs and outcome measures, a meta-analysis could not be performed. Instead, a narrative synthesis was conducted, revealing consistent patterns in neurogranin dynamics over time and underscoring the influence of biofluid selection on measured outcomes. Overall, the current evidence supports neurogranin’s potential as both a diagnostic and mechanistic biomarker for mTBI. Yet, to fully realize its clinical utility, future research must prioritize standardized protocols, the inclusion of proteoform profiling, and rigorous longitudinal validation studies.
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Open AccessArticle
Comparative Analysis of Plasma Extracellular Vesicle Isolation Methods for Purity Assessment and Biomarker Discovery
by
Alexandra T. Star, Melissa Hewitt, Amanpreet Badhwar, Wen Ding, Tammy-Lynn Tremblay, Jennifer J. Hill, William G. Willmore, Jagdeep K. Sandhu and Arsalan S. Haqqani
Proteomes 2025, 13(3), 45; https://doi.org/10.3390/proteomes13030045 - 18 Sep 2025
Abstract
Background: Extracellular vesicles (EVs) are an important source of blood biomarkers and are emerging as next-generation therapeutics. Demonstrating the purity of isolated EVs is essential for applications ranging from proteomics-based biomarker discovery to biomanufacturing. In this study, we systematically evaluated multiple EV isolation
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Background: Extracellular vesicles (EVs) are an important source of blood biomarkers and are emerging as next-generation therapeutics. Demonstrating the purity of isolated EVs is essential for applications ranging from proteomics-based biomarker discovery to biomanufacturing. In this study, we systematically evaluated multiple EV isolation methods for plasma and developed a scoring method to identify the approach best suited for proteomics. Methods: Commonly used enrichment techniques, including size-exclusion chromatography (SEC) and precipitation-based methods, were compared against the starting plasma in terms of particle yield and size, proteomic overlap, depletion of abundant plasma proteins, and enrichment of EV markers and unique proteins. To enable rigorous purity assessment, we established a targeted parallel reaction monitoring (PRM) mass spectrometry assay that quantified key EV markers and contaminant proteins across preparations. Results: Among the methods tested, SEC showed the greatest enrichment of EV markers and unique proteins, with the lowest level of contaminants, resulting in the highest overall purity scores. SEC also allowed for the detection of EV-free proteins. Other methods, by contrast, performed sub-optimally and were less reliable for proteomics-driven biomarker discovery. Conclusions: SEC provides the most EV-enriched plasma isolates for proteomics information, with minimal contamination from plasma proteins. The PRM-based purity scoring offers an objective means of benchmarking EV preparations and may help standardize EV isolation quality for both biomarker discovery and therapeutic manufacturing.
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(This article belongs to the Topic Liquid Biopsy: A Modern Method Transforming Biomedicine)
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