J. Proteome Res. [JOURNAL]
Sun
200 papers
Pan-Cancer Proteomic and Transcriptomic Meta-Analysis of PD-1/PD-L1 Signaling Reveals Predictive Biomarkers for Anti-PD-1 Therapy in Lung Cancer.
Suo Y, Song Y, Zhou H … +1 more , Liu Q
J Proteome Res · 2026 May · PMID 41906732 · Publisher ↗
Programmed death-ligand 1 (PD-L1) is an immune checkpoint molecule that enables tumor cells to escape immune surveillance, and its blockade by immune checkpoint inhibitors has become an effective therapeutic strategy in...
Programmed death-ligand 1 (PD-L1) is an immune checkpoint molecule that enables tumor cells to escape immune surveillance, and its blockade by immune checkpoint inhibitors has become an effective therapeutic strategy in various cancers. Previous studies have primarily focused on genomic and transcriptomic features within specific cancer types, while proteomic analyses remain relatively limited. Here, we conducted a comprehensive pan-cancer meta-analysis encompassing 12 human cancer types to systematically characterize PD-1/PD-L1 signaling pathways at both the proteomic and transcriptomic levels. We observed clear cancer-type-specific patterns of PD-1/PD-L1 expression. Pathway-crosstalk analyses further revealed multiple pathways and phosphorylation events influencing PD-1/PD-L1 activity. Immune-infiltration profiling identified MMP9 neutrophils as key immune subsets associated with PD-1/PD-L1 pathway activity. Using proteomic data, we constructed a PD-L1-centered protein-protein interaction network and identified TAP proteins as potential predictive biomarkers in small-cell lung cancer. We also established a biomarker signature capable of predicting clinical response to anti-PD-1 therapy in non-small-cell lung cancer and validated this gene set in two independent previously published cohorts. Finally, we developed an interactive web application (https://yuyingsuo-simm.shinyapps.io/PD-L1_Profiling/) to facilitate visualization of PD-L1 features and exploration of its associations with genes and pathways of interest.
Artificial Intelligence and Multiomics Beyond PSA Screening in African and Middle Eastern Prostate Cancer Patients.
Al-Shahrabi R, Alkhnbashi OS, Almarri RSB … +3 more , Ahmad S, Soares NC, Al Shareef Z
J Proteome Res · 2026 May · PMID 41894385 · Publisher ↗
Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specific heterogeneity of PCa underscores the urgent need for advanced strate...
Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specific heterogeneity of PCa underscores the urgent need for advanced strategies to improve detection and risk stratification. This review highlights how multiomics integration, including transcriptomics, DNA methylation, proteomics, and metabolomics, combined with artificial intelligence (AI), can validate biological mechanisms across molecular layers, thereby enhancing diagnostic reliability and biological relevance. While prostate-specific antigen (PSA) testing has significantly shaped PCa epidemiology, its limited specificity and sensitivity have led to widespread overdiagnosis and overtreatment, particularly of indolent tumors. These limitations are especially pronounced in underrepresented populations, notably men of African descent and those in the Middle East and North Africa (MENA) region, where PSA-based screening demonstrates reduced effectiveness. Despite advances in biomarker discovery, current datasets lack sufficient ethnic and regional diversity, raising concerns about the clinical validity and equity of AI-driven models. We argue that equitable precision oncology requires not only technological innovation but also the development of inclusive, demographically representative datasets. This review offers a forward-looking perspective on advancing PCa screening and stratification beyond PSA, with a particular emphasis on addressing the unmet clinical needs of African and Middle Eastern patients.
A Multiplexed Quantitative Analysis of Germline Single Amino Acid Variants by Targeted Proteomics in Nondepleted Human Plasma.
Dakup PP, Lin TT, Sarkar S … +6 more , Schepmoes AM, Fillmore TL, Shi T, Qian WJ, Jacobs JM, Consortium AC
J Proteome Res · 2026 May · PMID 41887668 · Full text
Single amino acid variants (SAAVs) in protein sequences are often a direct result of single-nucleotide polymorphisms (SNPs). Certain germline SAAVs have shown biological relevance in different disease conditions but lack...
Single amino acid variants (SAAVs) in protein sequences are often a direct result of single-nucleotide polymorphisms (SNPs). Certain germline SAAVs have shown biological relevance in different disease conditions but lack precise quantification in circulation, which could hinder functional investigations and progress in biomarker development. Here, we have developed a multiplexed liquid chromatography-selected reaction monitoring (LC-SRM) assay that monitors 5 wild-type and variant peptide pairs (Complement Factor B: CFB-R32Q/R32W, Clusterin: CLU-N317H, Fetuin B: FETUB-K360R, and Kininogen: KNG1-L212P) in nondepleted human plasma. The assay was optimized for imprecision, linearity, stability, and calibration assessments with CVs of under 20%. The wild-type and variant peptide pairs were characterized in a set of healthy individual plasma samples. These target identifications were also validated by SNP genotyping with more than 99% accuracy. For all protein targets, we observed significantly lower concentrations of WT species in the presence variant peptides. In CFB, the concentration of R32Q was significantly lower than its counterpart R32W variant and WT species. Furthermore, our results distinguished phenotypes of homozygosity and heterozygosity of the SAAV presence through direct concentration level characterization. These findings provide some insights into how SAAVs affect quantitative assessments of target peptides. The assay demonstrates a platform for proteogenomic analyses with potential applications in both research and clinical settings.
Quantitative Glycoproteomics Reveals Distinctive -Glycosylation Patterns in Human Kidney Tissues with Minor Glomerular Abnormalities.
Ling Y, Liu M, Cai F … +9 more , Su T, Jin Y, Yang H, Liu F, Li G, Xie X, Singla RK, Li L, Zhang Y
J Proteome Res · 2026 May · PMID 41885815 · Publisher ↗
Kidney diseases present substantial clinical challenges, with aberrant glycoproteins emerging as key pathogenic drivers. Minor glomerular abnormalities (MGAs), a category of unclassified glomerular lesions defined by sub...
Kidney diseases present substantial clinical challenges, with aberrant glycoproteins emerging as key pathogenic drivers. Minor glomerular abnormalities (MGAs), a category of unclassified glomerular lesions defined by subtle structural changes, are commonly detected in patients with persistent, asymptomatic, isolated proteinuria or microhematuria. Still their site-specific -glycosylation patterns remain unexplored. To address this gap, a laboratory-developed pressure cycling technology-based quantitative glycoproteomics workflow was applied to compare intact -glycopeptides (IGPs) among distant non-neoplastic tissues (DNTs; = 24) and trace renal biopsy samples from MGA patients ( = 27). Integrated with high-resolution mass spectrometry, 672 upregulated IGPs (FC > 1.5, < 0.05) and 573 downregulated IGPs (FC < 0.67, < 0.05) in MGA tissues were quantified. Compared with DNTs, 24 glycoproteins associated with the PI3K-Akt signaling pathway exhibited broadly elevated IGP abundances in MGA samples. Site-specific -glycosylation analysis further revealed distinct patterns among IgG subclasses and complement-related markers that distinguish MGA from DNT, offering new mechanistic insights into MGA pathogenesis. These novel glyco-signatures clarify the role of -glycosylation in renal disease and validate this workflow as a powerful tool for trace-tissue analysis. This study lays the groundwork for translating -glycosylation findings into clinical applications to improve MGA diagnosis and management.
Quantitative DIA-MS Uncovers Functional Impact of SMARCA4 Knockdown in Group 3 Medulloblastoma.
Pai MGJ, Singh A, Patra S … +5 more , Narang D, Bapat P, Bharambe HS, Shirsat N, Srivastava S
J Proteome Res · 2026 May · PMID 41885501 · Publisher ↗
Medulloblastoma, a pediatric brain tumor, frequently features chromatin modifier mutations, including SMARCA4 loss in the aggressive Group 3 subgroup. While SMARCA4 is considered a tumor suppressor, the functional impact...
Medulloblastoma, a pediatric brain tumor, frequently features chromatin modifier mutations, including SMARCA4 loss in the aggressive Group 3 subgroup. While SMARCA4 is considered a tumor suppressor, the functional impact of its loss on the oncogenic programs in Group 3 MB remains poorly understood. Using doxycycline-inducible shRNA constructs in HD-MB03 cells (a MYC-amplified Group MB model) to achieve SMARCA4 knockdown, we applied quantitative mass spectrometry to profile the resulting proteomic changes. DIA-MS with an in-house library achieved superior proteome depth over DDA and proved optimal for detecting subtle chromatin remodeler effects. Key findings include dysregulation of multiple subunits of the SWI/SNF complex including SMARCA2 overexpression, upregulation of histones, and PRMT5 disrupting chromatin architecture. GSEA revealed cell cycle, spindle and kinetochore organization, DNA replication/repair, and amino acid catabolism to be suppressed. SMARCA4 loss also led to a striking lipid metabolism reprogramming, with steroid biosynthesis, fatty acid biosynthesis, and other peroxisomal lipid pathways being enriched. The overexpression of top candidates like SMARCA2, CRABP2, FABP5, TAGLN2, CYP27A1, and SCP2 was validated in a separate validatory set. Our study reveals the proteomic landscape of Group 3 medulloblastoma following SMARCA4 loss, highlighting novel therapeutic targets for functional validation and exploitation.
What Does Next-Generation Mass Spectrometry Offer for Proteomics? A Comprehensive Platform Comparison.
Blasco Tavares Pereira Lopes F, Schlatzer D, Sudhadevi T … +4 more , Harijith A, Ayati M, Koyutürk M, Chance MR
J Proteome Res · 2026 Apr · PMID 41882496 · Full text
Next-generation mass spectrometry platforms (Orbitrap Astral, timsTOF Ultra) are reshaping proteomics by enhancing analytical depth and sensitivity. We compared these platforms against Orbitrap Exploris 480 using neonata...
Next-generation mass spectrometry platforms (Orbitrap Astral, timsTOF Ultra) are reshaping proteomics by enhancing analytical depth and sensitivity. We compared these platforms against Orbitrap Exploris 480 using neonatal mouse lung tissues from a bronchopulmonary dysplasia model ( = 12), employing four acquisition strategies: Exploris 480 DDA/DIA, Astral HR-DIA, and timsTOF Ultra DIA-PASEF. All platforms identified ∼4000 proteins in common, with 98% proteome coverage of data-dependent acquisition (DDA) identifications using data-independent (DIA) methods and 92% concordance between next-generation systems. Orbitrap Astral and timsTOF Ultra quantified >225,000 peptides and 13,000 proteins, representing ∼800% and ∼300% greater depth than Exploris 480 DDA, respectively. Furthermore, new-generation platforms cut recommended sample size by ∼66%. Enhanced proteome depth improved subcellular compartment annotations from 30% (DDA) to 66% (next-generation platforms) and reactome pathway coverage from 58% (DDA) to 90% (next-generation platforms). Differential expression analysis identified up to four times more phenotype-associated proteins in DIA data sets, enriched in mitochondrial, ribosomal, and extracellular components, with up to 44 enriched pathways. Importantly, proteins uniquely detected showed no functional annotation bias. These findings demonstrate that DIA acquisition on multivendor next-generation platforms provides superior proteome coverage and more complete systems biology assessment without introducing bias, enabling enhanced understanding of complex biological systems.
Impact of Variations in Commercial Standard Operating Procedure on Plasma Proteome Recovery.
Kasai T, Weiss L, Wohlfahrt J … +6 more , Matamalas JT, Shlayen G, Kirsch ZJ, Aikawa M, Aikawa E, Singh SA
J Proteome Res · 2026 Apr · PMID 41879802 · Full text
Advancements in mass spectrometry and complementary technologies now enable comprehensive, high-resolution plasma proteomics. Plasma is a key biofluid for clinical research, harboring potential disease-informative biomar...
Advancements in mass spectrometry and complementary technologies now enable comprehensive, high-resolution plasma proteomics. Plasma is a key biofluid for clinical research, harboring potential disease-informative biomarkers. Commercial sources of nondiseased, healthy donor plasma samples are often used for proteomic workflow development and as controls for clinical studies. The overarching assumption is that standard operating procedures for plasma preparation are comparable across different sources. In this study, we investigated the effectiveness of a particle-based protein enrichment strategy against a conventional proteomics workflow on plasma samples from five commonly used commercial sources. We aimed to characterize the extent of variability in plasma proteomes when factors such as freeze-thaw cycles, choice of anticoagulant, and operator-to-operator performance were accounted for in the study setup. Plasma samples were analyzed in data-independent acquisition mode by using two distinct instruments (Exploris 480, timsTOF HT) and search algorithms (CHIMERYS, DIA-NN). Plasma proteome enrichment yields ranged from 2.8- to 6.2-fold more compared to the conventional workflow, achieving yields exceeding 5000 proteins (timsTOF HT). Notably, the observed variability in proteome composition was largely attributable to differences in whole blood-to-plasma operating procedures across commercial sources. While these distinct proteomes remained undetectable with conventional workflows, particle-dependent proteome profiling successfully revealed the procedural differences.
Route-Dependent Proteomic Landscape in Mouse Models of Carbon Tetrachloride-Induced Hepatic Fibrosis.
Tao P, Du Z, Lin Y … +9 more , Lin H, Qu H, Bai H, Chen H, Zhang X, Yao Z, Chen K, Sun J, Hong J
J Proteome Res · 2026 Apr · PMID 41873577 · Publisher ↗
Hepatic fibrosis, a pathological consequence of chronic liver injury, is characterized by excessive extracellular matrix (ECM) deposition, increasing the risk of hepatocellular carcinoma. The carbon tetrachloride (CCl)-i...
Hepatic fibrosis, a pathological consequence of chronic liver injury, is characterized by excessive extracellular matrix (ECM) deposition, increasing the risk of hepatocellular carcinoma. The carbon tetrachloride (CCl)-induced mouse model is well-established for studying the pathogenesis and treatment of hepatic fibrosis, yet the effect of administration routes on fibrotic development and characteristics remains unclear. This study employed comparative proteomics to evaluate fibrosis induced via three CCl delivery methods: intraperitoneal (IP), subcutaneous (SC), and intragastric (IG) administration. The results demonstrated that the administration route critically determined fibrotic severity, with IG causing the most severe fibro-inflammatory injury, followed by SC and IP. Proteomic profiling identified distinct molecular pathways: IG and SC were closely associated with tissue remodeling, while IP was correlated with immune activation. Cross-species analysis further highlighted conserved profibrotic mechanisms and the hub gene patterns of hepatic ECM remodeling and metabolism differing from mice and humans. These findings underscore the importance of the CCl administration method as a crucial variable influencing the extent and nature of fibrosis in mouse models, and identify IG as the most effective modeling for advanced fibrosis. These insights offer a valuable foundation for refining experimental approaches to better mimic human hepatic fibrosis and enhance the translational relevance of research outcomes.
Impact of Prematurity on Metabolic Maturation.
Pearse K, Young A, Johnson MJ … +3 more , Beattie RM, Swann JR, Marino LV
J Proteome Res · 2026 Apr · PMID 41870539 · Full text
Growth failure in infants born preterm is a significant issue, increasing the risk of poorer neurodevelopmental outcomes and metabolic syndrome later in life. The aim of this study was to characterize patterns associated...
Growth failure in infants born preterm is a significant issue, increasing the risk of poorer neurodevelopmental outcomes and metabolic syndrome later in life. The aim of this study was to characterize patterns associated with urinary metabolites in extremely preterm and very preterm infants and to explore relationships with growth over time. Untargeted hydrogen-1 nuclear magnetic resonance (H NMR) spectroscopy was used to characterize changes in urinary metabolites over time and explore relationships with growth and nutritional intake. Partial least-squares regression models were constructed to identify metabolic variation associated with age, growth, and nutrition. Biochemical aging differed between very (mean 29.4 weeks ± 1.08 gestational age; = 21) and extremely (≤28 weeks gestational age; = 33) preterm infants, but these differences were not apparent when urinary metabolites were aligned to postmenstrual age. Citrate was the only metabolite significantly positively associated with weight-for-age Z-score. At weeks 1 and 2, citrate was positively associated with gestational age and a greater increase in WAZ from birth to discharge. Biochemical aging aligned to chronological age differed between very and extremely preterm infants, but this variation was lost when aligned to postmenstrual age. Urinary citrate excretion in the first two weeks of life was associated with weight gain and may be a future modifiable biomarker to improve growth outcomes.
Inflammaging-Induced Bioenergetic Gap Exhausts Pulmonary Nucleotide Pools to Exacerbate SARS-CoV-2 Outcomes in Early Stage Aging.
Li X, Wu ZE, Wang X … +13 more , Luo F, Deng C, Chen Y, Wan H, Tang X, Zhang Y, Shi P, Wu Z, Ning C, Yang W, Yang H, Liu J, Li F
J Proteome Res · 2026 Apr · PMID 41870358 · Publisher ↗
Age is a key risk factor for morbidity in coronavirus disease 2019 (COVID-19). This study investigates how "inflammaging" predisposes older hosts to severe SARS-CoV-2 outcomes through systemic and localized metabolic shi...
Age is a key risk factor for morbidity in coronavirus disease 2019 (COVID-19). This study investigates how "inflammaging" predisposes older hosts to severe SARS-CoV-2 outcomes through systemic and localized metabolic shifts. SARS-CoV-2 infection experiments were conducted respectively on 8 week-old mice and 16 week-old mice. An integrated multiomics approach was employed to delineate age-dependent molecular signatures and metabolic-immune crosstalk. 16 week-old mice exhibited significantly exacerbated weight loss and pulmonary pathology, successfully recapitulating age-related susceptibility. Multiomics integration revealed a "systemic bioenergetic gap": suppressed plasma TCA cycle metabolites correlated with depleted pulmonary nucleotide pools (AMP, GMP, UMP and uracil). This metabolic failure led to a paradoxical proteomic profile: despite interferon pathway activation, key antiviral effectors (RSAD2, ISG15, IFIT3B) were downregulated, while stress markers (CYP1A1, MAPK8) increased. Furthermore, threonic acid, betaine, and d-ribose were identified as robust, age-dependent biomarkers of infection severity. Our findings suggest that COVID-19 severity in the aging host is driven by the failure of a systemic-to-local metabolic-immune axis. The exhaustion of circulating energetic precursors constrains localized pulmonary nucleotide metabolism, thereby impairing essential antiviral responses and tissue repair. This study identifies the "systemic bioenergetic gap" as a novel therapeutic target, suggesting that systemic metabolic resuscitation may improve clinical outcomes in elderly populations.
Symptom Duration-Dependent Protein Abundance Changes in Symptomatic and Asymptomatic Tendons in Early Stage Unilateral Patellar Tendinopathy.
Steffen D, Schjerling P, Flannery S … +7 more , Fischer R, Tran PHT, Malmgaard-Clausen NM, Merkel MFR, Dakin SG, Kjaer M, Yeung CC
J Proteome Res · 2026 Apr · PMID 41869870 · Publisher ↗
Tendinopathy is a painful overuse disorder marked by a progressive functional decline. Although chronic disease mechanisms have been described, early molecular changes remain poorly defined. Here, we performed temporal p...
Tendinopathy is a painful overuse disorder marked by a progressive functional decline. Although chronic disease mechanisms have been described, early molecular changes remain poorly defined. Here, we performed temporal proteomic profiling of human patellar tendon biopsies across one, two, and three months of symptom duration and evaluated proteome differences between symptomatic and nonsymptomatic contralateral tendons. Biopsies were collected from participants with unilateral patellar tendinopathy and symptoms lasting three months or less for analysis by data-independent acquisition liquid chromatography-mass spectrometry. Peptide- and protein-level abundances were quantified as part of a bottom-up proteomics workflow and assessed using two-way ANOVA with factors of symptom status and symptom duration. Symptom duration had a significant main effect: 12 proteins and 14 peptides changed significantly over time, with most peptides corresponding to the altered proteins. However, there was no interaction between the symptom status and symptom duration, no sex differences, and no detectable proteomic difference between symptomatic and contralateral tendons. These findings indicate that protein-level changes are detectable within the first three months of tendinopathy, and similar proteomic changes were also observed in contralateral tendons. Together, these observations suggest that early phase patellar tendinopathy is associated with time-dependent proteomic changes that are not confined to the symptomatic tendon.
Systematic Evaluation of the Impact of Storage Time on Label-Free Proteomics of Colorectal Adenocarcinoma Formalin-Fixed Paraffin-Embedded Tissues.
Li Y, Zhou L, Xia L … +5 more , Fu Q, Wu X, Dai S, Xia W, Meng L
J Proteome Res · 2026 Apr · PMID 41847895 · Publisher ↗
Mass spectrometry (MS)-based proteomics has empowered comprehensive protein profiling of biological specimens. However, formalin-fixed paraffin-embedded (FFPE) tissues─critical resources for clinical biomarker discovery-...
Mass spectrometry (MS)-based proteomics has empowered comprehensive protein profiling of biological specimens. However, formalin-fixed paraffin-embedded (FFPE) tissues─critical resources for clinical biomarker discovery-remain underexplored in the setting of long-term storage (>15 years). Herein, we systematically evaluated the impact of storage time on proteomic analyses of 80 colorectal adenocarcinoma (CRC) FFPE samples, which were stratified by two key variables: storage time (>15 years vs <1 year) and tissue type (tumor vs adjacent normal tissue). We adopted a standardized protein extraction strategy, and subsequent proteomic profiling was performed via data-dependent acquisition and data-independent acquisition MS workflows. Our results demonstrated that FFPE tissue storage time impacts protein extraction efficiency, peptide yields, PTM identification, and protein quantification. The impacts were more pronounced on the peptide level. However, the biological enrichments (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis) from the global proteome profile and from differentially expressed proteins in CRC tissues were independent of archival time. Five clinically relevant biomarkers of CRC were further validated via immunohistochemistry. Collectively, our findings confirm that FFPE tissues retain stability for proteomic analyses even following >15 years of storage, thereby providing critical insights for leveraging archival FFPE biobanks to advance clinical proteomics and archival pathology research.
Comparative H NMR Lipoprotein Profiling of Rheumatoid Arthritis and Systemic Lupus Erythematosus Patients Highlights Disease-Specific Lipoprotein Dysregulation.
Duarte-Delgado NP, Rodríguez C LS, Cacciatore S
J Proteome Res · 2026 Apr · PMID 41843662 · Publisher ↗
Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are systemic autoimmune diseases associated with increased cardiovascular risk and metabolic alterations. We applied H NMR spectroscopy to profile lipoprot...
Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are systemic autoimmune diseases associated with increased cardiovascular risk and metabolic alterations. We applied H NMR spectroscopy to profile lipoproteins and metabolites in women with RA, SLE, and healthy controls. Both RA and SLE showed shared alterations in HDL metabolism, including reduced HDL particle size and lower concentrations of small HDL particles compared with controls. RA exhibited additional changes, notably a significant reduction in small LDL particle concentration. Metabolite profiling further differentiated RA, revealing significantly lower circulating levels of glutamine, alanine, and GlycB. Correlation analyses demonstrated that in RA, LDL particle concentrations were positively associated with disease activity (DAS28-ESR), and large LDL particles correlated positively with IFN-γ and VEGF. In SLE, HDL particle measures were associated with complement components, with small HDL particles positively correlated with C3 and HDL particle size inversely correlated with C3, while large LDL particles correlated positively with IL-6 and negatively with MDC. Together, these results indicate that RA and SLE share common lipoprotein alterations, while RA displays additional metabolic changes. NMR-derived lipoprotein and metabolite profiles may provide complementary information for assessing inflammation and cardiovascular risk in autoimmune diseases.
Concordant and Fluid-Specific Glycosylation Alterations in Serum and Saliva Enable Non-Invasive Diagnosis of Colorectal Cancer.
Shu J, Yue L, Zhu Y … +8 more , Yu H, Dang L, Wang X, Zhang C, Song W, Hu X, Zhang H, Li Z
J Proteome Res · 2026 Apr · PMID 41843472 · Publisher ↗
Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, highlighting the need for accurate, noninvasive biomarkers. This study investigated protein glycopatterns in saliva and serum from CRC patients...
Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, highlighting the need for accurate, noninvasive biomarkers. This study investigated protein glycopatterns in saliva and serum from CRC patients compared with healthy controls, and evaluated their diagnostic potential individually and in combination using machine learning. Paired serum and saliva samples from 44 CRC patients and 45 healthy volunteers were analyzed using lectin microarrays, identifying 15 lectins with distinctive binding profiles in serum and 18 in saliva. Nine lectins (e.g., ACA, PNA, HHL) exhibited consistent patterns across both fluids, indicating systemic CRC-associated glycoprotein remodeling, whereas others (e.g., DBA, PTL-II) displayed opposite trends, reflecting fluid-specific responses. Interfluid correlations were further examined through paired analyses, highlighting both shared and distinct glycosylation characteristics. Random forest models achieved diagnostic accuracies of 92.6% using either serum or saliva alone and 96.3% when combining both, demonstrating the enhanced predictive power of integrated analysis. These findings establish glycosylation profiling of saliva and serum as a promising noninvasive approach for CRC detection and support its potential application in population screening pending validation in larger cohorts.
19-Hydroxybufalin Inhibits Gastric Cancer Cell Proliferation by Modulating Metabolic Reprogramming.
Liang X, Liu Y, Ma X … +9 more , Jiang S, Sun Z, Sun X, Qin Y, Wu D, Wang S, Lv L, Zhong W, Wang Q
J Proteome Res · 2026 Apr · PMID 41842934 · Publisher ↗
OBJECTIVE: 19-Hydroxybufalin (19-H) is a natural bioactive compound with anticancer potential, but its molecular target and mechanism of action remain unclear. This study aimed to systematically evaluate its antigastric...
OBJECTIVE: 19-Hydroxybufalin (19-H) is a natural bioactive compound with anticancer potential, but its molecular target and mechanism of action remain unclear. This study aimed to systematically evaluate its antigastric cancer activity and identify potential molecular targets. METHODS: The antitumor effect of 19-H was evaluated in both in vitro and in vivo models. Multiomics analysis, thermal proteome profiling, molecular docking, and molecular dynamics simulations were employed to elucidate the mechanism of action. Functional assays were further conducted to validate the key target. RESULTS: 19-H exhibited nanomolar-level inhibitory activity against various gastric cancer cell lines, significantly suppressing tumor growth in subcutaneous xenograft and patient-derived xenograft models. Multiomics analysis revealed that 19-H reshaped metabolic pathways in gastric cancer. TPP screening identified PLPP2 as a potential target with significantly increased thermal stability upon 19-H treatment. Molecular simulations further revealed that 19-H binds stably to the α-helical region of PLPP2. CONCLUSIONS: 19-H exerts its antigastric cancer effect by targeting PLPP2 and remodeling the metabolic network. PLPP2 may represent a novel therapeutic target for gastric cancer.
Systematic Evaluation of Depletion and Enrichment Technologies for Platelet-Free Plasma Proteomics.
Al Siblani S, Armengaud J, Lozano C
J Proteome Res · 2026 Jun · PMID 41842586 · Full text
Plasma proteomics is a rapid, noninvasive, and highly informative approach for identifying disease biomarkers. However, the wide dynamic range of protein concentration limits the depth of liquid chromatography-tandem mas...
Plasma proteomics is a rapid, noninvasive, and highly informative approach for identifying disease biomarkers. However, the wide dynamic range of protein concentration limits the depth of liquid chromatography-tandem mass spectrometry proteomics. To address this challenge, we evaluated, with an Orbitrap Astral instrument using DIA, the performance of several protein depleting and enriching technologies on platelet-free plasma. Specifically, we assessed: perchloric acid depletion, immunodepletion, ProteoMiner, MagNet-SAX, ENRICHplus, Proteonano and the combination of ProteoMiner and immunodepletion. All methods were assessed in terms of proteomic depths, protein quantification precision, and functional analysis. Proteonano exhibited the most effective enrichment for the lowest abundance proteins, confidently identifying 299 proteins with mapped blood concentrations below 10 pg/L. Immunodepletion yielded the highest proteome coverage in the moderate abundance range (660 confident proteins). Also, ENRICHplus quantitative profile closely matched that of the neat plasma (93% correlation). Additionally, high repeatability (median coefficient of variation) was demonstrated by MagNet-SAX (13%), ProteoMiner (15%), and immunodepletion (16%). Combining ProteoMiner and immunodepletion reduced the plasma protein dynamic range, enabling deeper low abundance protein analysis but decreased repeatability. These results obtained on platelet-free plasma deviate from previously reported results on platelet-rich plasma, highlighting the crucial sample preparation stage for plasma proteomics.
Metabolomics Highlights Reduced Glutamate and Acetylcarnitine in the Amniotic Fluid of Cytomegalovirus-Infected Pregnant Women.
Costanzo M, Miceli M, Campesi I … +9 more , Bianco S, Mazzarelli LL, Migliorini S, Sarno L, Malesci R, Salomè S, Raimondi F, Guida M, Maruotti GM
J Proteome Res · 2026 Apr · PMID 41841159 · Full text
Cytomegalovirus (CMV) is a major cause of morbidity in immunocompromised individuals and represents the leading infectious cause of neonatal congenital deafness. When acquired during pregnancy, CMV can be vertically tran...
Cytomegalovirus (CMV) is a major cause of morbidity in immunocompromised individuals and represents the leading infectious cause of neonatal congenital deafness. When acquired during pregnancy, CMV can be vertically transmitted to the fetus, potentially resulting in permanent sequelae characterized by intellectual and neurosensory impairments. To investigate metabolic alterations associated with primary maternal CMV infection, we conducted a metabolomics-based analysis of amniotic fluid (AF) from pregnant women who acquired CMV infection during the first trimester, as confirmed by IgG seroconversion, IgM positivity, and low-to-moderate IgG avidity indices. Our findings revealed that the AF metabolomic profiles from CMV transmitter and nontransmitter mothers were remarkably similar. In contrast, both the CMV-exposed groups showed profound metabolic dysregulation compared to uninfected controls, suggesting that CMV-related metabolic disparities may persist irrespective of vertical transmission. Specifically, we observed a significant downregulation of glutamate ( < 0.0001) and acetylcarnitine ( < 0.0001) in CMV groups compared to control AF samples. Notably, the combined reduction of these two metabolites emerged as a surrogate biomarker signature of recent primary CMV infection of the mother, indicating that AF from both transmitting and nontransmitting pregnancies may share common metabolic adaptations. These alterations may reflect early perturbations of neurobiochemical pathways with unknown effects on babies negative at birth, supporting the need for risk assessment and clinical monitoring even in the absence of congenital CMV infection.
Proteomic Analysis of Human Dentine Matrix Extracts by Peptide-Level High-pH Reversed-Phase Fractionation.
Khalil M, Gull B, Alhimairi S … +2 more , Giddey AD, Jamal M
J Proteome Res · 2026 Apr · PMID 41839003 · Publisher ↗
Proteomics research has increasingly focused on human cells, tissues, and fluids; however, comprehensive data on dental tissues remain limited. Dentine, a mineralized component of teeth, contains structural proteins and...
Proteomics research has increasingly focused on human cells, tissues, and fluids; however, comprehensive data on dental tissues remain limited. Dentine, a mineralized component of teeth, contains structural proteins and bioactive molecules that can modulate pulp cell activity and support regeneration when released. Understanding its protein composition is therefore essential. Previous studies have identified relatively few dentine proteins, and technical challenges have hindered reproducibility. Traditional extraction methods also rely on strong acids that lack clinical relevance. In this technical note, we introduce a workflow combining EDTA-based dentine extraction under clinically relevant conditions with peptide-level fractionation using high-pH reversed-phase chromatography. This approach was compared with unfractionated samples, SDS-PAGE protein-level fractionation, and strong cation exchange (SCX) peptide-level fractionation, all followed by LC-MS/MS. Data are available via ProteomeXchange (PXD070849). This workflow enabled the identification of 514 proteins compared with 238 (unfractionated), 428 (SDS-PAGE), and 193 (SCX). High-pH reversed-phase chromatography contributed 217 unique identifications, exceeding those from other techniques. Although used in other proteomic systems, this methodology has not previously been applied to dentine matrix extracts and represents a promising approach for improving protein discovery.
Glucose Potentiates Florfenicol Killing of Antibiotic-Resistant by Enhancing Proton Motive Force and Reactive Oxygen Species.
Chen YT, Lin HY, Peng XX … +1 more , Li H
J Proteome Res · 2026 Apr · PMID 41838975 · Publisher ↗
Florfenicol is valued for its clinical safety, particularly its reduced bone marrow toxicity compared to other old antibiotics of chloramphenicols. However, the rise of bacterial resistance threatens its efficacy. To add...
Florfenicol is valued for its clinical safety, particularly its reduced bone marrow toxicity compared to other old antibiotics of chloramphenicols. However, the rise of bacterial resistance threatens its efficacy. To address this, we evolved a florfenicol-resistant strain of (VP-R) and used metabolomics to identify a suppressed glucose metabolic state as a key vulnerability. We found that exogenous glucose potentiated florfenicol's killing effect against the resistant strain in a dose- and time-dependent manner in vitro. It also played a role in vivo. Mechanistically, glucose reactivation rewired central carbon metabolism in two ways: (1) it fueled the pyruvate cycle, enhancing the proton motive force (PMF) to promote florfenicol uptake and (2) it stimulated the pentose phosphate pathway, increasing reactive oxygen species (ROS) production to amplify antibiotic lethality. Thus, our work identifies glucose-mediated metabolic reprogramming as a potent strategy to resensitize resistant pathogens to florfenicol by simultaneously increasing drug influx and oxidative damage.
Proteomic Snapshots of Structural Cross-Linking Rearrangements in Ca/Calmodulin-Dependent Kinase-1-Delta Associated with Its Regulation by ATP, Ca/Calmodulin, and Reduction Potential.
Mbabala L, Tshililo NO, Vlok M … +8 more , Vendrell I, Fischer R, Tabb DL, Trieber CA, Adra TRC, Overduin M, Butterworth S, Kenyon CP
J Proteome Res · 2026 Apr · PMID 41837851 · Full text
Ca/calmodulin-dependent kinase 1 delta (CaMK1δ) plays a central role in regulatory pathways associated with ATP, reduction potential, and Ca/calmodulin (CaM). Mass spectrometry (MS)-based structural proteomics incorporat...
Ca/calmodulin-dependent kinase 1 delta (CaMK1δ) plays a central role in regulatory pathways associated with ATP, reduction potential, and Ca/calmodulin (CaM). Mass spectrometry (MS)-based structural proteomics incorporating FragPipe and pLink cross-link analysis was used to reveal conformation selection induced by dialysis with ATP, reducing agents, and CaM. The structural changes were mediated via cysteine and phosphate cross-linking and loop-linking of the activation loop within the C-terminal. Phosphate loop-linking was validated by β-elimination and Michael addition (BEMAD) reactions, aligning these findings with phosphoproteomics analyses of phosphorylation events. Oxidizing conditions inhibited the functionality of CaMK1δ wild-type. A novel mechanism of autoinhibition via cysteine cross-linking between the activation loop (αT) and C-terminal (αI) helices was identified. The microenvironment associated with CaMK1δ, including ATP availability, CaM concentration, and reduction potential, modulates the structural rearrangements underlying autophosphorylation. Phosphoproteomics, cysteine and phosphate cross-linking MS, and structural molecular modeling were used to describe kinase activation, allowing the activation of regulatory kinases to be reevaluated. We propose that regulatory kinases respond to an array of kinase family-specific distinct second messengers which can be studied using this multiomics framework, giving significant new insights into PTMs as well as the associated protein structure rearrangements.
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