Zihui Li, Jie Deng, Fei Yan, Li Liu, Yanling Ma, Jianhai Sun
{"title":"Inflammatory Serum Olink Proteomics in Cancer-Related Pain Treated with Opioids: A Pilot Cross-Sectional and Longitudinal Study","authors":"Zihui Li, Jie Deng, Fei Yan, Li Liu, Yanling Ma, Jianhai Sun","doi":"10.1021/acs.jproteome.6c00052","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00052","url":null,"abstract":"<p>Opioid analgesia shows substantial interindividual variabilityin cancer patients, yet the underlying serum inflammatory alterationsremain poorly characterized. This study collected plasma samples from44 cancer pain patients before and after opioid initiation, quantifying92 immunoinflammation proteins by Olink proteomics. Cross-sectionalanalysis identified nine differentially expressed proteins betweenresponders and nonresponders. A five-protein nomogram involving TGF-α,EN-RAGE, CASP-8, ST1A1, and IL-10RA demonstrated superior predictiveperformance for opioid efficacy (AUC 0.902) compared to traditionalCRP (AUC 0.625). Longitudinal analysis of this population revealedupregulation of β-NGF, MCP-4, IL-1alpha, and IL-13, and downregulationof CD6, IL-12beta, and SCF after treatment. STRING analysis clusteredthese proteins into three functional groups: efficacy-related (NGF),bowel-inflammation-related (IL-12/IL-13), and CD6-related. Notably,expression of IL-12β showed a significant efficacy–constipationinteraction: constipation completely reversed the efficacy-IL-12 association,and higher IL-12 levels predicted favorable response only in nonconstipatedpatients. These findings established a pretreatment protein signaturefor predicting opioid efficacy and revealed systemic immune reprogrammingfollowing opioid therapy.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4589–4598"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Choa Yun, Ji Qiu, M. Constanza Camargo, Lusheng Song, Joshua LaBaer, Hyokyoung G. Hong, Maddy Edie-Booker, Byunghyun Kang, Ilze Konrade, Adam Schiffenbauer, Lisa G. Rider, Frederick W. Miller, Sarfaraz Hasni, Blake M. Warner, Marcis Leja, Minkyo Song
{"title":"Immunoproteomic Profiling of Autoantibodies and Antibodies against Infectious Agents in Autoimmune Diseases","authors":"Choa Yun, Ji Qiu, M. Constanza Camargo, Lusheng Song, Joshua LaBaer, Hyokyoung G. Hong, Maddy Edie-Booker, Byunghyun Kang, Ilze Konrade, Adam Schiffenbauer, Lisa G. Rider, Frederick W. Miller, Sarfaraz Hasni, Blake M. Warner, Marcis Leja, Minkyo Song","doi":"10.1021/acs.jproteome.5c00950","DOIUrl":"https://doi.org/10.1021/acs.jproteome.5c00950","url":null,"abstract":"<p>Priorresearch investigated limited antibody sets within individualautoimmune diseases. Using the Nucleic-Acid Programmable Protein Arrayplatform, we measured antibodies against 280 human, 40 viral, and15 bacterial antigens in serum from 237 patients with 8 autoimmunediseases, including autoimmune gastritis (AG), autoimmune thyroiditis(AT), celiac disease (CD), idiopathic inflammatory myopathies (IIM),type 1 diabetes mellitus (T1D), rheumatoid arthritis (RA), Sjögren’sdisease (SjD), and systemic lupus erythematosus (SLE), and 112 controls.Candidate antibodies were identified by combining Firth logistic regressionand machine learning. We identified disease-specific antibodies, rangingfrom 3 in IIM to 13 in SLE for IgG and 1 in CD to 13 in AG for IgA.Additionally, 63 IgG and 44 IgA antibodies were shared across twoor more diseases. Notably, two IgG autoantibodies overlapped in upto five diseases: directed against STNM4 (SLE, SjD, T1D, CD, and RA)and TRIM21 (SLE, SjD, IIM, CD, and RA); and three IgA antibodies inup to seven diseases: directed against H1N1 Influenza A virus NP (IIM,SjD, AG, T1D, CD, RA, and AT) and Coxsackievirus B3MK012537 and EnterovirusC PVgp1 (IIM, SjD, AG, T1D, CD, SLE, and RA). These findings underscorethe potential of antibody profiling in autoimmune disease characterizationand biomarker discovery.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4407–4418"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guillermo Carrillo-Martin, Johanna Krueger, Tomas Marques-Bonet, Esther Lizano
{"title":"ProteoParc: A Reference Protein Database Builder for Ancient and Nonmodel Organisms","authors":"Guillermo Carrillo-Martin, Johanna Krueger, Tomas Marques-Bonet, Esther Lizano","doi":"10.1021/acs.jproteome.5c01107","DOIUrl":"https://doi.org/10.1021/acs.jproteome.5c01107","url":null,"abstract":"<p>Over the past few years, the increasing interest in analyzingtheproteome of extinct and nonmodel organisms has generated a new fieldof research expanding the scope of proteomics. The lack of curateddatabases and/or molecular data from these organisms forces researchersto manually search in different public repositories for related proteinsequences, either for MS/MS peptide identification or ZooMS markerannotation. This can lead to format incongruences and hinder reproducibilitybetween studies. To address this issue, we introduce ProteoParc, auser-friendly software that builds reference databases by systematicallydownloading and processing protein sequences from the most widelyused public repositories. The pipeline’s output is a nonredundantprotein database, formatted in a way to be interpreted by typicalpeptide identification software. Moreover, the user can adjust thedatabase dimension and composition by applying different criteriato include only a certain number of genes or species. Thus, ProteoParcis an easy and fast, custom-made bioinformatic tool useful for futurepaleoproteomics analysis in ancient samples related to understudiedorganisms.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4463–4469"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farnaz Fatahian, Seyed Mohammad Jafar Seyed Golestan, Clizia Chinello, Lisa Pagani, Hassan Rezadoost, Hossein Behboudi, Alireza Ghassempour, Andrew Smith
{"title":"Time- and Dose-Resolved DIA-PASEF Proteomics Maps the Transition from Adaptive Stress to Apoptotic Collapse in Melittin-Treated MDA-MB-231 Cells","authors":"Farnaz Fatahian, Seyed Mohammad Jafar Seyed Golestan, Clizia Chinello, Lisa Pagani, Hassan Rezadoost, Hossein Behboudi, Alireza Ghassempour, Andrew Smith","doi":"10.1021/acs.jproteome.6c00241","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00241","url":null,"abstract":"<p>Melittin, the cytolytic peptide of honeybee venom, exhibitspotentanticancer activity in triple-negative breast cancer (TNBC), yet themolecular programs underlying its cytotoxic effects remain incompletelydefined. To address this gap, MDA-MB-231 TNBC cells were exposed tomelittin at half-maximal inhibitory concentration(half IC<sub>50</sub>) and IC<sub>50</sub> across early(0.5, 1, and 2 h), mid(3, 4 h),and late (12, 24 h) time windows. Proteomic profiling was performedusing label-free data-independent acquisition(DIA) parallel accumulation–serialfragmentation(PASEF). Approximately 5800 proteins were quantified,revealing distinct dose-dependent stress responses. An integrativeexploratory framework combining time-resolved log<sub>2</sub> fold-changetrajectories, area-under-the-curve(AUC) based temporal prioritization,and independent heatmap visualization identified proteins associatedwith melittin-induced stress remodeling. Half IC<sub>50</sub> exposureshowed a transient stress-adaptive signature characterized by chromatinremodeling(HMGN2, H2AZ1), structural and RNA-associated buffering(LRRC7),and indirect mitochondrial quality-control signaling(CPAMD8, SPATA4),which progressively weakened over time. In contrast, IC<sub>50</sub> treatment induced rapid chromatin remodeling dominated by histoneH1 variants(H1.4, H1.2), early RNA instability(LRRC7), and late-stagecytoskeletal disassembly marked by MICAL3 induction, consistent withprogression toward apoptosis. These trajectories paralleled dose-dependentapoptotic phenotypes. Overall, data suggest that melittin elicitsdose- and time-dependent proteomic stress responses in TNBC cellsand identify candidate trajectory-associated proteins and pathwayslinked to adaptive stress remodeling or progression toward cytotoxiccollapse.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4704–4718"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lee S. Cantrell, Seth Just, Alexey Stukalov, Omid C. Farokhzad, Serafim Batzoglou
{"title":"From Peaks to Power: Systematic Evaluation of Chromatographic Sampling Reveals Determinants of Quantification and Biological Discovery in DIA Proteomics","authors":"Lee S. Cantrell, Seth Just, Alexey Stukalov, Omid C. Farokhzad, Serafim Batzoglou","doi":"10.1021/acs.jproteome.6c00415","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00415","url":null,"abstract":"<p>Modern DIA proteomics increasingly emphasizes throughputand depthfor large-cohort studies, but methods are often optimized using proxymetrics that can mask losses in quantifiable signal and statisticalpower. Here, we evaluate how data points per peak and other chromatographicfeatures jointly contribute to quantification and downstream biologicaldiscovery. Using a matrix-matched calibration curve dataset, we checkedhow the number of data points per peak (DPPP) affects the limits ofdetection and quantification (LOD/LOQ). Reduced DPPP minimally affectedLOD but substantially degraded LOQ. Feature modeling and nonparametricassociation analyses identified precursor peak area as the strongestfeature-level predictor of LOQ, whereas DPPP showed weaker and context-dependenteffects. Simulations of chromatographic peak integration recapitulatedthese trends, showing that increased sampling primarily improves integrationprecision, while quantitative accuracy is strongly governed by peakheight and peak shape. Finally, when comparing 20 cancer vs 20 controlplasma samples processed with Seer Proteograph, the decrease in DPPPled to a loss of statistical significance for proteins with low-abundanceprecursors. These findings argue that DIA optimization should prioritizeLOQ and statistical power metrics─not identifications alone─bybalancing sampling density with chromatographic peak height and qualityto maximize useful biological signal.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4919–4931"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liliia Glazutdinova, Xu Liu, Jingchun Huang, Xuyao Ji, Shuo Wang, Kaili Duan, Lixin Gao, Jing Wu, Yu Liu
{"title":"Serum Olink Proteomics Reveals Novel Biomarkers for Early Diagnosis of Hepatocellular Carcinoma","authors":"Liliia Glazutdinova, Xu Liu, Jingchun Huang, Xuyao Ji, Shuo Wang, Kaili Duan, Lixin Gao, Jing Wu, Yu Liu","doi":"10.1021/acs.jproteome.6c00384","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00384","url":null,"abstract":"<p>Hepatocellular carcinoma (HCC) isa highly prevalentmalignanttumor in China, and early diagnosis critically affects the prognosis.Current imaging and pathological biopsy techniques have limitations,including high invasiveness and limited accessibility, while the insufficientsensitivity of serum biomarkers (such as AFP) restricts their usein early screening. In this study, using the Olink proteomics platformbased on the proximity extension assay (PEA), we screened for hepatocellularcarcinoma-related differentially expressed proteins (DEPs) and constructeda multiprotein diagnostic model. In the discovery cohort, we included15 patients with newly diagnosed HCCs and 16 healthy controls. DEPswere identified using Olink, and their diagnostic performance wasanalyzed to identify the candidate biomarkers. In an independent validationcohort, including 116 HCC patients (50 early stage, 66 late stage)and 83 healthy controls, we further validated the expression levelsand diagnostic performance of identified proteins─C1QA andGFER. The C1QA and GFER expression levels were significantly higherin the serum of patients with early and late HCC stages compared tohealthy controls. By constructing a multiprotein diagnostic model,we identified C1QA, GFER, and AFP as the optimal diagnostic combination,demonstrating a combined diagnostic AUC of 0.92 and 0.99 for early-stageand advanced-stage HCC, respectively.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4945–4956"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Plasma Proteome Signatures in Sickle Cell Anemia and the Effect of Hydroxyurea Treatment","authors":"Neha Kumari, Sumit Paliwal, Anushri Umesh, Gopinath Palanisamy, Jayalakshmi Marneni, Sristi Chakroborty, Raman Bakthisaran, Kameswari Yele, Ranjith Kumar K., Suraj Singh Nongmaithem, Pasupuleti Sri Kanya Durga Bhavani Punyasri, Pradeep K. Patra, Dipty Jain, Swasti Raychaudhuri, Giriraj Ratan Chandak","doi":"10.1021/acs.jproteome.6c00158","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00158","url":null,"abstract":"<p>SickleCell Anaemia (SCA) is a monogenic blood disorder causedby a mutation in the β-globin gene, yet it presents with markedclinical variability. Although hydroxyurea (HU) is an establishedtherapy, its precise mechanism of action remains incompletely understood.Plasma proteins represent valuable biomarkers for elucidating diseasemechanisms and treatment responses. In this study, plasma proteomeprofiling of 31 healthy controls and 76 SCA patients identified 43differentially abundant proteins (DAPs) that form a highly interconnectedinteraction network. Proteins with increased abundance in SCA werelargely associated with immune and inflammatory responses, whereasthose with reduced levels were linked to coagulation and proteolyticpathways. HU therapy was associated with elevated levels of haptoglobin(HP) and hemopexin (HPX), key mediators of free hemoglobin scavenging.We also identified several previously unreported plasma proteins alteredin SCA, broadening the landscape of potential biomarkers and HU-responsivetargets. Many DAPs significantly correlated with clinical indices,such as transfusion frequency, vaso-occlusive crises, white bloodcell counts, and platelet counts, offering insights into disease mechanismsand potential utility in disease management. Notably, overlap withβ-thalassemia-associated signatures suggests shared pathophysiologicalpathways between these hemoglobinopathies. Collectively, these findingsprovide a strong foundation for translational validation in larger,independent cohorts.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4624–4635"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of a Large-Scale Serum Metabolome Relative Quantitative Method and Application for Metabolic Traits of Colon Cancer","authors":"Shuting Yu, Guifang Ye, Jiaxin Gai, Rui Wei, Xinru Huang, Runjian Ren","doi":"10.1021/acs.jproteome.6c00263","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00263","url":null,"abstract":"<p>Colon cancer (CC) is one of the malignant tumors withhigh incidenceand mortality rates worldwide, necessitating innovative diagnostictools to improve early detection and management. In this study, wedeveloped a large-scale metabolome relative quantitative method workflowusing ultrahigh-performance liquid chromatography coupled with Q-TRAPmass spectrometry to identify novel biomarkers in the serum of CCpatients. This method enables the detection of 776 metabolic features,spanning 16 chemical classes and 63 metabolic pathways. All detectedfeatures were evaluated by multiple identification criteria and assignedconfidence scores to ensure annotation reliability. Through validationand application of this method to clinical samples, we compared theserum metabolic profiles of CC patients with those of healthy controlsand screened 72 significantly altered metabolites. Pathway enrichmentanalysis revealed perturbations in tryptophan metabolism, argininebiosynthesis, and the TCA cycle. Notably, three differential metabolites(indole, tryptophan, and xanthurenic acid) were identified that couldpotentially serve as diagnostic biomarkers with area under the curvevalues exceeding 0.9. Our large-scale metabolome relative quantitativemethod demonstrates applicability in identifying potential metabolitebiomarkers for CC and provides a promising tool for both basic andclinical metabolomics research.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4734–4743"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Laurent, Gael Cobraiville, Adrien Allard, Murat Cem Köse, Arnaud Lombard, Celia Lemoine, Virginie Neirinckx, Marianne Fillet
{"title":"Identification of Glioblastoma Cell Surface Proteins and Assessment of Their Expression Across Patient-Derived Stem-Like Cell Cultures","authors":"Anna Laurent, Gael Cobraiville, Adrien Allard, Murat Cem Köse, Arnaud Lombard, Celia Lemoine, Virginie Neirinckx, Marianne Fillet","doi":"10.1021/acs.jproteome.6c00267","DOIUrl":"10.1021/acs.jproteome.6c00267","url":null,"abstract":"<p>Glioblastoma (GBM) is the most common primary brain cancerin adultsand remains fatal, with a median survival of a few months. There isan urgent need to develop novel therapeutic strategies against thisaggressive malignancy. Modern cancer research increasingly focuseson personalized therapies tailored toward unique molecular featuresof each tumor or patient. In this context, cell surface proteins (CSPs)represent an attractive class of therapeutic targets due to theiraccessibility and central roles in physiological and pathologicalprocesses, making them among the most targeted proteins in currentdrug development. In this study, promising CSPs were identified throughan untargeted proteomics approach using high-resolution mass spectrometryon patient-derived GBM stem-like cell (GSC) cultures, complementedby RNA-seq data and computational database analyses. From this primarydiscovery, five CSPs, namely PTK7, PTPRZ1, OSMR, CSPG4, and IGDCC4,were selected for detailed investigation. A targeted UHPLC–multiplereaction monitoring (MRM) method was developed and optimized to assesstheir expression and evaluate their abundance variations across differentGSC cultures and cell passage levels. Beyond confirming these CSPsas potential therapeutic targets in GBM, our study demonstrates thevalue of three-dimensional GSC cultures as robust models for biomarkerresearch and target assessment.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4744–4756"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148890375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carlos A. Morales-Betanzos, Joel D. Federspiel, Jameel Syed, Smitha Pillai, Sarah Vargas, Timothy Coskran, Mireia Fernandez Ocana
{"title":"LCM-Enriched Proteomic Characterization of Antibody-Mediated Glomerular Damage and Complement Activation in Pre-Clinical Models","authors":"Carlos A. Morales-Betanzos, Joel D. Federspiel, Jameel Syed, Smitha Pillai, Sarah Vargas, Timothy Coskran, Mireia Fernandez Ocana","doi":"10.1021/acs.jproteome.6c00389","DOIUrl":"https://doi.org/10.1021/acs.jproteome.6c00389","url":null,"abstract":"<p>Biologics, lipidnanoparticles, and other therapeuticmodalitiescan result in adverse events, often detected as lesions during preclinicalpathology assessments. Characterization of these lesions providesvaluable information during drug development to contextualize mechanismsof injury and assess species translatability. Here, we investigatedthe utility of a laser capture microdissection (LCM)-enriched massspectrometry proteomics approach to analyze two well-characterizedpreclinical models of regional (glomerular) injury: Passive HeymanNephritis in rats and bovine gamma globulin-induced glomerular injuryin nonhuman primates (NHPs). Using LCM-enriched proteomics, glomeruliwere isolated from formalin-fixed paraffin-embedded kidney tissuein the rat model, enabling identification of 4,661 proteins and quantificationof 3,410. Proteinuria measurements were compared with digital pathologymetrics of glomerular morphology and proteomics results, with allmodalities yielding concordant evidence of glomerular injury and proteomicsconfirming the role of complement activation. The same LCM- enrichedproteomics workflow was applied to an NHP model of induced glomerulardamage, identifying 4,623 proteins, quantifying 3,000, and confirmingqualitative concordance with established features of complement-mediatedglomerular injury. Together, these findings illustrate the applicabilityof LCM-enriched proteomics for region-specific characterization ofantibody-mediated tissue injury and support its use as a hypothesis-generatingplatform in translational toxicologic pathology.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"25 9","pages":"4859–4869"},"PeriodicalIF":3.8,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}