Proteomes

22 pages, 5091 KB

Open AccessArticle

Surveying the Proteome-Wide Landscape of Mitoxantrone and Examining Drug Sensitivity in BRCA1-Deficient Ovarian Cancer Using Quantitative Proteomics

by 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 [...] Read more.

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. Full article

(This article belongs to the Section Identification of Potential Biomarkers and Potential Therapeutic Targets)

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35 pages, 1439 KB

Open AccessReview

Proteomics in Allopolyploid Crops: Stress Resilience, Challenges and Prospects

by 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

Viewed by 435

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Plant Genomics and Proteomics)

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32 pages, 3386 KB

Open AccessArticle

Proteomic Analysis of Plant-Derived hIGF-1-Fc Reveals Proteome Abundance Changes Associated with Wound Healing and Cell Proliferation

by 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

Viewed by 307

Abstract

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. [...] Read more.

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. Full article

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12 pages, 1559 KB

Open AccessArticle

TCEPVDB: Artificial Intelligence-Based Proteome-Wide Screening of Antigens and Linear T-Cell Epitopes in the Poxviruses and the Development of a Repository

by 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

Viewed by 205

Abstract

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 [...] Read more.

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. Full article

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22 pages, 1055 KB

Open AccessArticle

Integrated Analysis of Proteomic Marker Databases and Studies Associated with Aging Processes and Age-Dependent Conditions: Optimization Proposals for Biomedical Research

by Mikhail S. Arbatskiy, Dmitriy E. Balandin and Alexey V. Churov

Proteomes 2025, 13(4), 57; https://doi.org/10.3390/proteomes13040057 - 6 Nov 2025

Viewed by 383

Abstract

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 [...] Read more.

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. Full article

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26 pages, 879 KB

Open AccessArticle

Mimicry in the Bite: Shared Sequences Between Aedes aegypti Salivary Proteins and Human Proteins

by Andrea Arévalo-Cortés and Daniel Rodriguez-Pinto

Proteomes 2025, 13(4), 56; https://doi.org/10.3390/proteomes13040056 - 3 Nov 2025

Viewed by 330

Abstract

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 [...] Read more.

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. Full article

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23 pages, 3109 KB

Open AccessArticle

Identification of Protein Markers for Chronic Ischemic Heart Disease Through Integrated Analysis of the Human Plasma Proteome and Genome-Wide Association Data

by 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

Viewed by 337

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 [...] Read more.

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. Full article

(This article belongs to the Section Identification of Potential Biomarkers and Potential Therapeutic Targets)

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21 pages, 1149 KB

Open AccessReview

Recent Advances and Application of Machine Learning for Protein–Protein Interaction Prediction in Rice: Challenges and Future Perspectives

by 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

Viewed by 439

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Plant Genomics and Proteomics)

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22 pages, 2520 KB

Open AccessReview

Marine Bioactive Peptides in the Regulation of Inflammatory Responses: Current Trends and Future Directions

by 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

Viewed by 1007

Abstract

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 [...] Read more.

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. Full article

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18 pages, 950 KB

Open AccessArticle

Temporal and Spatial Profiling of Escherichia coli O157:H7 Surface Proteome: Insights into Intestinal Colonisation Dynamics In Vivo

by 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

Viewed by 431

Abstract

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 [...] Read more.

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. Full article

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11 pages, 215 KB

Open AccessArticle

Protein-Predicted Obesity Phenotypes and Cardiovascular Events: A Secondary Analysis of UK Biobank Proteomics Data

by 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

Viewed by 787

Abstract

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 (PPS_BMI), body fat percentage (PPS_BFP), and waist–hip ratio (PPS_WHR) to estimate risk [...] Read more.

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 (PPS_BMI), body fat percentage (PPS_BFP), and waist–hip ratio (PPS_WHR) to estimate risk for major adverse cardiovascular events (MACEs). Methods: We used data from the UK Biobank with proteome profiling. PPS_BMI, PPS_BFP, and PPS_WHR 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 PPS_BFP and PPS_WHR, but not PPS_BMI, 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. Full article

17 pages, 3880 KB

Open AccessArticle

Protein Structural Modeling Explains Rapid Oxidation in Poultry and Fish Myoglobins Compared to Livestock Myoglobins

by 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

Viewed by 718

Abstract

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 [...] Read more.

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. Full article

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30 pages, 1280 KB

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 | Viewed by 759

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 [...] Read more.

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. Full article

(This article belongs to the Topic Multi-Omics in Precision Medicine)

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22 pages, 2176 KB

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

Viewed by 489

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: [...] Read more.

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. Full article

(This article belongs to the Special Issue Proteomics in Chronic Diseases: Issues and Challenges)

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47 pages, 1051 KB

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 | Viewed by 1808

Abstract

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 [...] Read more.

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. Full article

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