PROTEOMICS – Clinical Applications最新文献

{"title":"A Comparison of Emotionally Stimulated and Conventionally Collected Tears Using Bottom-Up, Label-Free Quantitative Proteomic Analysis-A Pilot Study.","authors":"Campbell Bruce Mousseau, Alena R Veigl-Lunsford, Rhonda L Pitsch, Sean W Harshman","doi":"10.1002/prca.70023","DOIUrl":"https://doi.org/10.1002/prca.70023","url":null,"abstract":"<p><p>Proteomic analysis of biofluids is central for identifying disease biomarkers. Tears have become popular targets for biomarker discovery and biosensor development, largely because they can be collected noninvasively and are rich sources of biomarkers for ocular and systemic diseases. Although basal and reflex tears have been well characterized, the proteome of psycho-emotionally stimulated tears remains largely unexplored, hindering their applicability in biomarker discovery studies and the advancement of tear-based biosensors. Comprehensive proteomic analysis across different tear types is crucial for identifying novel biomarkers and improving disease diagnosis and monitoring. In this pilot study, tears collected via conventional stimulation techniques (\"standard\") versus those elicited through emotional stimuli (\"emotional\") were purchased from single donors through two vendors. We compared the proteomic profiles of emotional (n = 6) and standard (n = 14) single donor human tears to better understand the biochemical composition and functional roles of different tear types. In total, 907 proteins were identified from all tear samples. Fifty-two tear proteins were significantly enriched in emotionally stimulated tears. Functional characterization of enriched proteins revealed that most were extracellular or secreted. Many were also involved in host defense or immune responses, including members of the S100A and neutrophil defensin protein families. SUMMARY: Although emotional tears are known to differ from basal and reflex tears in both composition and function, the specific biochemical characteristics and functional roles of emotional tears remain poorly understood. This gap in knowledge is largely due to the limited research conducted on emotional tears, despite their distinct origins. A more complete understanding of all tear types is necessary for the continuation of biomarker discovery and the development of tear fluid-based biosensors. In this exploratory study, tears collected via a conventional/standard protocol and those collected from emotional stimulus were obtained from two vendors and subjected to proteomic profiling and comparison. A bottom-up proteomic approach was utilized to analyze tear samples, facilitating a comparison between tear types and contributing to the characterization of psycho-emotional tears.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70023"},"PeriodicalIF":2.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hormonal Contraceptives and Depression: A Proteomic Analysis Using Neuronal Models.","authors":"Sam Thilmany, Andreas Thomas, Yvonne Reinders, Farhad Shakeri, Matthias Vogel, Albert Sickmann, Catharina Scholl, Mario Thevis","doi":"10.1002/prca.70017","DOIUrl":"https://doi.org/10.1002/prca.70017","url":null,"abstract":"<p><strong>Purpose: </strong>Hormonal contraceptives are linked to a higher prevalence of depressive symptoms. Given their popularity in Western countries, understanding the biochemical effects on neuronal cells is crucial to minimizing mental health risks.</p><p><strong>Experimental design: </strong>Neural progenitor cells were treated with ethinyl estradiol (EE) and levonorgestrel (LNG), two synthetic sex hormones commonly used in oral contraception, and S-23, a selective androgen receptor modulator developed as a potential synthetic sex hormone for male hormonal contraception. Label-based quantitative proteomics with the TMTpro 16plex tandem mass tags were used to assess protein expression changes between treated and untreated cells.</p><p><strong>Results: </strong>Treatment of human neural progenitor cells with EE, LNG, EE + LNG, and S-23 led to distinct and overlapping proteomic changes, with enrichment in pathways related to inflammation, oxidative stress, transcriptional regulation, and cell death. Disease association analyses linked these changes to neurodegenerative and psychiatric conditions, including mechanisms relevant to depression.</p><p><strong>Conclusions and clinical relevance: </strong>These findings suggest that hormonal compounds used in contraception and performance enhancement may influence molecular pathways implicated in mental health, particularly depression. Although not directly translatable to clinical outcomes, the results support the need for further investigation into the neuropsychiatric effects of hormonal treatments.</p><p><strong>Summary: </strong>This study addresses a pressing clinical need to better understand the potential mental health impacts of widely used hormonal contraceptives. While highly effective for pregnancy prevention, compounds such as ethinyl estradiol and levonorgestrel have repeatedly been associated with increased risk of depressive symptoms, highlighting the importance of investigating their molecular effects on neural systems. To explore this, we applied label-based quantitative proteomics in an undifferentiated human neural progenitor cell model treated with ethinyl estradiol, levonorgestrel, their combination, and the selective androgen receptor modulator S-23. The treatments induced distinct and overlapping changes in protein expression, with enrichment in pathways related to inflammation, oxidative stress, cell adhesion, chromatin dynamics, and programmed cell death-biological processes known to intersect with mechanisms implicated in depression. These findings offer insight into how synthetic hormones and hormone-like compounds may modulate neuronal biology, potentially contributing to adverse mental health outcomes. However, due to limitations of the in vitro model-such as the absence of systemic context, pharmacokinetics, and mature neuronal function-these results are primarily hypothesis-generating. They underscore the importance of further research to clarify the pathophysiologi","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70017"},"PeriodicalIF":2.5,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable Machine Learning for Proteomics-Based Subtyping and Tumor Mutational Burden Prediction in Endometrial Cancer.","authors":"Thi-My-Trang Luong, Xuan Lam Bui, Chii-Ruey Tzeng, Nguyen Quoc Khanh Le","doi":"10.1002/prca.70024","DOIUrl":"https://doi.org/10.1002/prca.70024","url":null,"abstract":"<p><strong>Background: </strong>Endometrial carcinoma (EC) represents a significant clinical challenge due to its pronounced molecular heterogeneity, directly influencing prognosis and therapeutic responses. Accurate classification of molecular subtypes (CNV-high, CNV-low, MSI-H, POLE) and precise tumor mutational burden (TMB) assessment is crucial for guiding personalized therapeutic interventions. Integrating proteomics data with advanced machine learning (ML) techniques offers a promising strategy for achieving precise, clinically actionable classification and biomarker discovery in EC.</p><p><strong>Materials and methods: </strong>Using proteomic data from 95 EC patients (83 endometrioid, 12 serous), sourced from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), we developed an ML pipeline integrating proteomic feature selection (Lasso-penalized logistic regression), classification modeling, and interpretability analysis. The dataset was divided into training (70%) and test (30%) sets, with synthetic minority oversampling (SMOTE) applied to address the class imbalance. Logistic regression models were trained for molecular subtypes classification, and the TMB prediction model performance was evaluated using accuracy, AUC, precision, recall, and F1-score. Model interpretability was enhanced using explainable AI (XAI) techniques: SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME).</p><p><strong>Results: </strong>Feature selection reduced the proteomic dataset from 11,000 to eight key proteins. The proteomics-based ML model demonstrated robust predictive performance, accurately classifying EC molecular subtypes (accuracy: 82.8%; AUC: 0.990) and distinguishing high (≥10 mutations/Mb) versus low TMB (<10 mutations/Mb) cases (accuracy: 89.7%; AUC: 0.984). SHAP analysis highlighted clinically recognized biomarkers (MLH1, PMS2, STAT1) and identified novel protein candidates (MTHFD2, MAST4, RPL22L1, MX2, SEC16A). LIME analysis provided individualized prediction interpretations, clarifying each protein biomarker's influence on model decisions.</p><p><strong>Conclusion: </strong>Our proteomics-driven ML approach demonstrates high accuracy and interpretability in EC subtype classification and TMB prediction. By identifying validated and novel biomarkers, this strategy provides essential biological insights and a strong foundation for the future development of non-invasive diagnostics, personalized treatments, and precision medicine in EC.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70024"},"PeriodicalIF":2.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145016070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic Biomarkers Are Linked to QTc Interval in Patients With Chronic Heart Failure.","authors":"Mylène Barry-Loncq de Jong, Teun B Petersen, Sabrina Abou Kamar, Navin Suthahar, Nick van Boven, K Martijn Akkerhuis, Peter J van der Spek, Peter D Katsikis, Rudolf A de Boer, Victor A W M Umans, Eric Boersma, Folkert W Asselbergs, Jasper J Brugts, Sing-Chien Yap, Isabella Kardys","doi":"10.1002/prca.70020","DOIUrl":"10.1002/prca.70020","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study investigates the link between circulating proteins and rate-corrected QT (QTc) interval in patients with heart failure with reduced ejection fraction (HFrEF) and their association with cardiovascular outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods and results: &lt;/strong&gt;We analyzed 197 HFrEF patients from the prospective Serial Biomarker Measurements and New Echocardiographic Techniques in Chronic Heart Failure Patients Result in Tailored Prediction of Prognosis (Bio-SHiFT) study, all in sinus rhythm at baseline. Baseline QTc intervals were calculated and corrected for broad QRS complexes (&gt;120 ms) using Bogossian's formula. Using the Somalogic-SomaScan Assay, 1105 cardiovascular-related proteins were measured in baseline blood samples. Linear regression identified 11 biomarkers significantly associated with QTc interval (false discovery rate [FDR] &lt; 0.05), adjusted for age, sex, and QT-prolonging medications. These included interleukin-1 receptor-like 1 (ST2) and angiopoietin-2. An additional four biomarkers showed potential relevance (FDR &lt; 0.1). Cox regression analysis revealed that five biomarkers-ST2, angiopoietin-2, atrial natriuretic factor, insulin-like growth factor-binding protein 7 (IGFBP7), and carbonic anhydrase 4 (CA4)-were significantly associated with the composite clinical endpoint of cardiovascular death, heart transplantation, left ventricular assist device implantation, and heart failure hospitalization.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Several cardiovascular proteins are associated with the QTc interval and adverse cardiovascular events in HFrEF patients. The observed associations highlight pathways such as inflammation, fibrosis, and angiogenesis, which may contribute to QTc prolongation and adverse outcomes in HFrEF. Further research is warranted to reveal underlying mechanisms and clinical applicability.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Summary: &lt;/strong&gt;This study is the first to investigate the association between QTc interval and a broad panel of over 1000 plasma proteins in patients with heart failure with reduced ejection fraction (HFrEF). We identified 11 proteins significantly linked to QTc interval, five of which also demonstrated prognostic relevance for adverse cardiovascular outcomes. The associated biomarkers are linked to inflammation, fibrosis, and angiogenesis-related pathways. These findings provide novel insights into the multifactorial mechanisms associated with QTc prolongation, potentially due to direct or indirect effects. The results emphasize the potential of circulating biomarkers as tools for understanding the pathophysiological processes associated with QTc prolongation and arrhythmogenesis in heart failure. Moreover, the identification of interleukin-1 receptor-like 1 (ST2), angiopoietin-2, atrial natriuretic factor, IGFBP7, and carbonic anhydrase 4 (CA4) as shared markers of QTc interval prolongation and adverse outcomes underscores their clinical utility as both diagnostic and prognosti","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70020"},"PeriodicalIF":2.5,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeted Proteomic Analysis of Sickle Cell Disease Patients With Elevated Tricuspid Regurgitation Velocity.","authors":"Varshini Babu, Jane A Little, Claudia R Morris, Roberto Machado, Simon Gibbs, Gregory J Kato, Victor R Gordeuk, Mark T Gladwin, Yingze Zhang, Seyed Mehdi Nouraie","doi":"10.1002/prca.70019","DOIUrl":"10.1002/prca.70019","url":null,"abstract":"<p><strong>Purpose: </strong>Pulmonary hypertension (PH) is a chronic complication of sickle cell disease (SCD) with limited known biomarkers, beyond increases in plasma brain natriuretic peptide levels.</p><p><strong>Experimental design: </strong>We conducted a proof-of-concept study to identify serum protein biomarkers that were differentially expressed in SCD patients with elevated tricuspid regurgitation velocity (TRV-a noninvasive marker of PH).</p><p><strong>Results: </strong>We found 41 out of 92 target proteins that were significantly different between the nonelevated (TRV ≤ 2.6 m/s; N = 35) and highly elevated TRV group (TRV ≥ 2.9 m/s; N = 35, p < 0.05). Six of them passed a Bonferroni correction (p value < 0.0005), including T-cell surface glycoprotein, lymphotactin, SLAM family member 7, galectin-9, TNF-related apoptosis-inducing ligand receptor 2, and tumor necrosis factor receptor superfamily member 11A. We observed up to a 1.2-fold increase in the high TRV group for these six proteins. These six proteins had a strong positive correlation with serum NT-proBNP levels (a positive control marker elevated in PH [r ≥ 0.44]). Additionally, these markers correlated with other clinical parameters of PH in SCD.</p><p><strong>Conclusion: </strong>Circulatory protein markers of the immune response are increased in SCD patients with elevated TRV as compared to those without elevated TRV.</p><p><strong>Summary: </strong>This study demonstrates that the circulatory protein markers of the immune response are increased in SCD patients with elevated TRV compared to those without elevated TRV. These biomarkers may be important tools for risk-stratifying patients with SCD or targets for therapeutic intervention.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70019"},"PeriodicalIF":2.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144817377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immune Landscape Changes in MASLD and the Effects of 11β-HSD1 Inhibition Revealed by Single-Cell Mass Cytometry.","authors":"Zayakhuu Gerelkhuu, Sehee Park, Yun Kim, Sang Won Lee, Dae Won Jun, Tae Hyun Yoon","doi":"10.1002/prca.70022","DOIUrl":"10.1002/prca.70022","url":null,"abstract":"<p><strong>Background: </strong>Metabolic dysfunction-associated steatotic liver disease (MASLD) affects nearly one-fourth of the global population, yet effective diagnostics and treatments remain limited. Systemic immune dysregulation plays a key role in MASLD pathogenesis, highlighting the value of immune profiling.</p><p><strong>Methods: </strong>In this study, we used high-dimensional single-cell mass cytometry (CyTOF) to analyze peripheral blood mononuclear cells (PBMCs) from healthy donors (n = 6), MASLD patients (n = 4), and MASLD patients treated with an 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) inhibitor (n = 2). PBMCs were stained with a 29-marker panel to identify 15 immune cell types and assess cytokine expression.</p><p><strong>Results: </strong>MASLD patients showed increased CD8⁺ T cells, early NK cells, and monocytes, along with reductions in T_H2, T_H1, late NK, and Treg cells. Cytokine profiling revealed elevated IL-6 expression in plasmacytoid dendritic cells and late NK cells, indicating systemic inflammation. Automated clustering (PhenoGraph, UMAP) identified NK and phagocytic subsets associated with disease and treatment. Notably, 11β-HSD1 inhibition led to downregulation of pro-inflammatory cytokines (e.g., IFN-γ, IL-6) and partial restoration of immune subsets.</p><p><strong>Conclusions: </strong>These results offer a high-resolution view of immune alterations in MASLD and suggest that 11β-HSD1 inhibition may represent a promising immunomodulatory therapeutic strategy.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70022"},"PeriodicalIF":2.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum Proteomics of Ribociclib-Mediated Cardiovascular Toxicity: An Exploratory Case-Control Study.","authors":"Oraianthi Fiste, Martina Samiotaki, Efstathios Manios, Chrysanthi Trika, Christine Ivy Liacos, Constantine Dimitrakakis, Meletios Athanasios Dimopoulos, Maria Gavriatopoulou, Flora Zagouri","doi":"10.1002/prca.70021","DOIUrl":"10.1002/prca.70021","url":null,"abstract":"<p><p>Cyclin-dependent kinase 4/6 inhibitors have transformed hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (BC) therapeutics. Ribociclib has been associated with survival gain, yet its potential cardiovascular toxicities (CVTs) remain an area of uncertainty. Our single-center study prospectively recruited adult patients in order to assess treatment-related CVT incidence and spectrum as well as decipher proteins' differential expression in affected patients by data-independent acquisition liquid chromatography-tandem mass spectrometry (DIA LC-MS/MS). After a median follow-up of 27.2 months, five cases of CVT have occurred among the 62 enrolled participants (8.06%; mean age, 67 years). CVTs were in the form of asymptomatic QTc prolongation, transient ischemic attack, deep vein thrombosis, syncope, and pericardial effusion, which developed within 7.56 months. The in-depth proteomics quantified 144 differentially expressed proteins, of which 109 and 35 were down- and up-regulated, respectively, in these five cases (enrolled participants with CVT) compared to five sex- and age-matched controls (enrolled participants without CVT). Negative regulation of endopeptidase activity, phosphatidylcholine metabolism, and immune response were the most affected signaling pathways in the subsequent functional analysis. Large-scale external validation of our hypothesis-generating findings could potentially support individualized cardiovascular prevention in BC patients under ribociclib combinational therapy. SUMMARY: Ribociclib has unequivocally revolutionized hormone-dependent metastatic breast cancer therapeutics. Its potential cardiotoxicity, however, remain inadequately characterized, whereas the underlying pathophysiological mechanisms are poorly understood so far. Our prospective case-control study revealed that despite cardiovascular toxicity was not very common (<10%), its phenotype was not limited to QTc prolongation. Moreover, utilizing mass spectrometry-based serum proteomics, we highlighted for the very first time a number of distinct proteins, which could be of predictive value to identify patients at high risk. The prospective validation of our preliminary, proof-of-concept study's results in larger cohorts could inform optimized preventive strategies.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70021"},"PeriodicalIF":2.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence and the Evolving Landscape of Immunopeptidomics.","authors":"Thanh Hoa Vo, Edel McNeela, Orla O'Donovan, Sweta Rani, Jai Prakash Mehta","doi":"10.1002/prca.70018","DOIUrl":"https://doi.org/10.1002/prca.70018","url":null,"abstract":"<p><strong>Background: </strong>Immunopeptidomics is the large-scale study of peptides presented by major histocompatibility complex (MHC) molecules and plays a central role in neoantigen discovery and cancer immunotherapy. However, the complexity of mass spectrometry data, the diversity of peptide sources, and variability in immune responses present major challenges in this field.</p><p><strong>Review focus: </strong>In recent years, artificial intelligence (AI)-based methods have become central to advancing key steps in immunopeptidomics. It has enabled advances in de novo sequencing, peptide-spectrum matching, spectrum prediction, MHC binding prediction, and T cell recognition modeling. In this review, we examine these applications in detail, highlighting how AI is integrated into each stage of the immunopeptidomics workflow.</p><p><strong>Case study: </strong>This review presents a focused case study on breast cancer, a heterogeneous and historically less immunogenic tumor type, to examine how AI may help overcome limitations in identifying actionable neoantigens.</p><p><strong>Challenges and future perspectives: </strong>We discuss current bottlenecks, including challenges in modeling noncanonical peptides, accounting for antigen processing defects, and avoiding on-target off-tumor toxicity. Finally, we outline future directions for improving AI models to support both personalized and off-the-shelf immunotherapy strategies.</p><p><strong>Summary: </strong>Artificial intelligence (AI) is reshaping the immunopeptidomics landscape by overcoming challenges in peptide identification, immunogenicity prediction, and neoantigen prioritization. This review highlights how AI-based tools enhance the detection of MHC-bound peptides-including low-abundance, noncanonical, and post-translationally modified epitopes and improve peptide-spectrum matching and T-cell epitope prediction. By demonstrating a case study on applications in breast cancer, we illustrate the potential of AI to reveal hidden immunogenic features in tumors previously likely considered immunologically \"cold.\" These advancements open new opportunities for expanding neoantigen discovery pipelines and optimizing cancer immunotherapies. Looking ahead, the application of deep learning, transfer learning, and integrated multi-omics models may further elevate the accuracy and scalability of immunopeptidomics, enabling more effective and inclusive vaccine and T-cell therapy development.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70018"},"PeriodicalIF":2.5,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144754118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification of Acid and Alkaline Enzymes Based on Normalized Van der Waals Volume Features.","authors":"Hao Wan, Quan Zou, Yanan Zhang","doi":"10.1002/prca.70009","DOIUrl":"10.1002/prca.70009","url":null,"abstract":"<p><strong>Objective: </strong>Acidic and alkaline enzymes play crucial roles in the food industry and environmental management. This study aims to develop a computational method for accurately distinguishing between acidic and alkaline enzymes to enhance their stability in varying pH environments.</p><p><strong>Methods: </strong>We employed AutoProp for feature extraction and the MRMD3.0 algorithm for feature selection. The most discriminative feature, the normalized Van der Waals volume (nFeat43), was identified and used for classification.</p><p><strong>Results: </strong>The selected feature (nFeat43) achieved a classification accuracy of 76.2% in distinguishing acidic from alkaline enzymes. Further analysis was conducted to interpret the physicochemical significance of this feature in enzyme discrimination.</p><p><strong>Conclusions: </strong>Our findings demonstrate that nFeat43 is a key determinant in differentiating acidic and alkaline enzymes. This method provides a rapid and reliable computational approach for enzyme characterization, which could aid in industrial and environmental applications.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70009"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144192075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of Glucocorticoids in the Treatment of Retinal Detachment With Choroidal Detachment: Analysis by Proteomics.","authors":"Pingping Li, Mengyao Han, Rui Zhang, Fangyu Chen, Yanzi Li, Jing Yuan, Ning Ma, Lu Li, Jianhua Wu","doi":"10.1002/prca.70008","DOIUrl":"10.1002/prca.70008","url":null,"abstract":"<p><strong>Purpose: </strong>Glucocorticoids are widely used for their anti-inflammatory properties, but their specific molecular mechanisms in treating rhegmatogenous retinal detachment with choroidal detachment (RRDCD) remain unclear. This study aims to identify key regulatory factors in the vitreous humor of RRDCD patients and analyze protein changes after hormonal intervention.</p><p><strong>Methods: </strong>Vitreous fluid samples were collected during surgery from patients with rhegmatogenous retinal detachment (RRD, n = 40), non-glucocorticoid treated RRDCD (nT-RRDCD, n = 35), and glucocorticoid-treated RRDCD (T-RRDCD, n = 32). Primary outcomes were retinal reattachment status and best-corrected visual acuity (BCVA) at 6 months postoperatively. Proteomic analysis was performed using data-independent acquisition (DIA), with differentially expressed proteins validated by parallel reaction monitoring (PRM) and ELISA.</p><p><strong>Results: </strong>Between RRD and nT-RRDCD, 203 differentially expressed proteins were identified, while 295 proteins were differentially expressed between nT-RRDCD and T-RRDCD. These proteins were involved in complement activation, immune response, blood coagulation, and MAPK signaling. Apolipoprotein D (APOD) and vitronectin (VTN) positively correlated with postoperative BCVA. APOD, serum amyloid A-4 (SAA4), and ubiquitin-conjugating enzyme E2 variant emerged as potential diagnostic biomarkers for RRDCD.</p><p><strong>Conclusions: </strong>RRDCD development involves multiple factors. Glucocorticoids mitigate retinal damage by suppressing inflammation, regulating oxidative stress, and promoting cell repair. APOD and VTN correlate with BCVA, while APOD, SAA4, and ubiquitin-conjugating enzyme E2 show promise as diagnostic biomarkers for RRDCD.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e70008"},"PeriodicalIF":2.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144064514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}