Clinical proteomics最新文献

{"title":"A multi-omics study reveals pathway-level insights and predictive biomarkers in pediatric TB.","authors":"Zaynab Mousavian, Mark R Segal, Roger I Calderon, Juaneta Luiz, Esin Nkereuwem, Peter Wambi, Mandar Paradkar, Molly F Franke, Gunilla Källenius, Beate Kampmann, Aarti Kinikar, George B Sigal, Christopher Sundling, Danielle L Swaney, Eric Wobudeya, Heather J Zar, Jeffrey M Collins, Adithya Cattamanchi, Joel D Ernst, Devan Jaganath","doi":"10.1186/s12014-026-09614-3","DOIUrl":"10.1186/s12014-026-09614-3","url":null,"abstract":"<p><strong>Background: </strong>Tuberculosis (TB) remains a global health threat, affecting over a million children under the age of 15 annually. Many children with TB do not receive treatment due to challenges in diagnosis.</p><p><strong>Methods: </strong>We performed a multi-omics analysis for pediatric TB by integrating plasma proteomics and metabolomics data from children with presumptive TB across four high-burden countries. Pathway enrichment analysis was conducted using multiGSEA to identify relevant immune and metabolic pathways. We also applied mixOmics and multiview approaches for diagnostic biomarker discovery and compared the performance of multi-omics signatures with those derived from single-omics datasets.</p><p><strong>Results: </strong>Enrichment analysis revealed several immune and metabolic pathways, including PTEN and RUNX2 regulation pathways, as well as arginine and proline metabolism, that were uniquely identified through data integration. While the multi-omics model showed marginal improvement over single-omics models, proteomics alone generally outperformed metabolomics and demonstrated greater potential for accurately classifying Confirmed TB versus Unlikely TB in children.</p><p><strong>Conclusion: </strong>These findings demonstrate the advantage of combining complementary molecular layers to gain a deeper understanding of disease mechanisms and highlight the potential of proteomics for improving pediatric TB diagnosis.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13277094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148204406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative tandem mass tag-based serum proteomics for longitudinal biomarker monitoring in Duchenne muscular dystrophy.","authors":"Ahmed Naveed, Elissa Recinos, Dexter Chow, Chiara Degan, Roula Tsonaka, Michela Guglieri, Cristina Al-Khalili Szigyarto, Pietro Spitali, Yuri E M van der Burgt, Jordi Diaz-Manera, Utkarsh J Dang, Yetrib Hathout","doi":"10.1186/s12014-026-09613-4","DOIUrl":"10.1186/s12014-026-09613-4","url":null,"abstract":"<p><strong>Background: </strong>Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder characterized by progressive and severe muscle degeneration. Motor function tests are commonly used to evaluate treatment efficacy in clinical trials. However, they are subject to interobserver variability and may lack sensitivity for detecting early changes in disease progression. These limitations highlight the need for blood-based biomarkers to monitor disease status and progression. In this study, we used tandem mass tag-based mass spectrometry to quantify proteins in longitudinal serum samples from patients with DMD and to identify proteins associated with motor function performance.</p><p><strong>Methods: </strong>Serum samples collected at three time points (baseline, 12, and 24 months) were obtained from participants in the FOR-DMD trial (NCT01603407) and processed for multiplexed analysis using TMT 6-plex isobaric tags and LC-MS/MS. Protein intensities were log2-transformed and analyzed using linear mixed-effects models to assess their associations with age and repeated functional outcome measurements, such as the North Star Ambulatory Assessment (NSAA) score, 6-minute walk test (6MWT), rise from supine velocity (RSV), and 10-meter run/walk velocity (10mRWV). P-values were adjusted for multiple comparisons, with FDR < 0.05 considered statistically significant.</p><p><strong>Results: </strong>Mixed-model analysis identified 22 proteins associated with age and 77 proteins associated with at least 1 functional outcome, including 26 associated with 2 clinical outcomes after FDR correction. Most associations were observed with NSAA (73 proteins), followed by the 6MWT (28 proteins) and RSV (3 proteins). These proteins spanned multiple disease-relevant categories, including muscle-associated proteins, extracellular matrix (ECM), complement and inflammatory pathways, coagulation/hemostasis, carrier proteins, proteolysis, and cell adhesion.</p><p><strong>Conclusion: </strong>Using longitudinal serum proteome profiles and clinical outcome data, we identified proteins that associate with age and functional outcomes, particularly NSAA and 6MWT, highlighting key molecular pathways in DMD disease progression.</p><p><strong>Trial registration: </strong>The FOR-DMD clinical trial was registered on ClinicalTrials.gov (registration no. NCT01603407). First submission: 03/04/2012.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13459337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148175525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasma protein signatures altered before and after tuberculosis diagnosis in a population-based cohort.","authors":"Natalia Koziar, Anthony D Whetton, Nophar Geifman","doi":"10.1186/s12014-026-09602-7","DOIUrl":"10.1186/s12014-026-09602-7","url":null,"abstract":"<p><p>Tuberculosis (TB) continues to be a major public health concern. Thus, identifying individuals at risk of progression to active disease is important for community health but remains difficult. To address this issue, we analysed plasma proteomic data from the UK Biobank to investigate host protein signatures associated with TB. The size of the prospective cohort (~ 500,000) combined with deep proteomic analysis (2,920 plasma proteins) allowed us to perform analysis on 42 individuals diagnosed with TB either before or after sampling, alongside matched controls with no history of TB. Using this approach, we identified significantly differentially expressed proteins (e.g. CDCP1, GAST) in individuals affected by TB, suggesting proteomics alternations that precede clinical onset and persist years after diagnosis. Functional annotation of significant proteins indicated involvement of immune and signalling pathways associated with chronic inflammatory responses and host defence mechanisms. These findings help advance the understanding of TB pathology and offer the potential for use of specific plasma proteins in the development of point of care risk assessment and diagnostic tools.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"23 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13242133/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148194551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nipple aspirate fluid as a proximal breast liquid biopsy platform: advancing precision risk management in breast cancer.","authors":"Senyang Guo, Jianhua Liu, Hongmei Zheng, Xinhong Wu","doi":"10.1186/s12014-026-09612-5","DOIUrl":"10.1186/s12014-026-09612-5","url":null,"abstract":"<p><strong>Background: </strong>Current breast cancer (BC) risk management relies primarily on imaging and blood‑based liquid biopsies. However, these approaches are constrained by morphological blind spots, limited sensitivity for early lesions, and an inability to directly capture the biology of the ductal microenvironment where most tumors originate. There is a pressing need for novel strategies that provide direct, local insight into breast tissue risk.</p><p><strong>Main body: </strong>This review repositions nipple aspirate fluid (NAF) as a proximal, breast-specific liquid biopsy platform. Emerging evidence demonstrates that NAF, obtained by nipple aspiration from non-lactating breasts and not limited to cases of spontaneous nipple discharge, originates from a functionally autonomous ductal microenvironment and provides rich multi-omics information, including proteins, metabolites, epigenetic alterations, extracellular vesicles, inflammatory/oxidative mediators, microbiome-associated signals, and other local regulatory readouts, rather than simply representing a filtrate of blood. We summarize the biological foundations of NAF and its multi-omics landscape, highlighting its potential in three key clinical scenarios: (1) molecular risk stratification for pathologic nipple discharge, (2) individualized biological risk profiling in women with high-risk or dense breasts, and (3) proximal monitoring of treatment response and microenvironmental dynamics in patients with diagnosed BC.</p><p><strong>Conclusion: </strong>Although standardization and prospective validation remain essential challenges, the development of robust collection protocols, integration of multi‑omics data, and execution of well‑designed clinical trials could enable NAF to shift BC management from a paradigm of \"early detection\" toward one of \"precision risk insight and intervention,\" ultimately aiming to improve patient outcomes and net benefit.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13435563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148101224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of preanalytical factors on cerebrospinal fluid and plasma proteomics: a systematic experimental study.","authors":"Megumi Tatsumi, Tomoko Miyakawa, Takako Enokida, Haruna Kaneko, Kosuke Saito, Shinsuke Hidese, Yuji Takahashi, Yuichi Goto, Hiroshi Kunugi, Kotaro Hattori","doi":"10.1186/s12014-026-09604-5","DOIUrl":"10.1186/s12014-026-09604-5","url":null,"abstract":"<p><strong>Background: </strong>Preanalytical variations (PAVs) are a major source of irreproducibility in biomarker studies. While their effects on blood have been widely examined, their impact on cerebrospinal fluid (CSF) proteomics remains less well characterized. We systematically evaluated common PAVs to inform biobanking and biomarker research.</p><p><strong>Methods: </strong>CSF and plasma samples were collected at an ISO 20387-accredited biobank. For each condition, three or four independent paired samples were analyzed. PAVs included storage temperature, processing delay, centrifugation speed, storage tube type, freeze-thaw cycles, and blood contamination. Protein abundance was quantified using SomaScan. Selected analytes were further evaluated using orthogonal immunoassays. Fold changes were calculated as linear RFU ratios relative to baseline. Paired t-tests with false discovery rate (FDR) correction were performed. Analytes showing detectable or larger changes were defined based on predefined fold-change thresholds with nominal p < 0.05.</p><p><strong>Results: </strong>Plasma proteomes were highly sensitive to delays and temperature, with 969 analytes showing large changes after 24 h at 25 °C (counts refer to large changes), compared to 26 analytes in CSF. At 4 °C, CSF remained stable for 24 h (4 changes), whereas plasma showed extensive changes after 24 h (465) and 72 h (813). Storage at - 20 °C caused substantial shifts in both matrices (CSF: 144; plasma: 1,164), whereas no analytes differed in plasma stored at - 50 °C relative to - 80 °C. Freeze-thaw cycles up to three resulted in few altered analytes, whereas 11 cycles led to pronounced changes (CSF: 198; plasma: 21). Hemolysis in plasma induced 28 changes, whereas CSF blood contamination ≤ 500 cells/mm³ was associated with few changes. After FDR correction, no analytes remained significant in CSF, whereas multiple analytes remained significant in plasma under selected conditions.</p><p><strong>Conclusions: </strong>Storage temperature and processing delay were the most influential PAVs, with plasma more susceptible than CSF. For optimal quality, CSF should be processed within 4 h or kept at 4 °C, plasma within 2 h, and both stored at ≤ - 80 °C. Freeze-thaw cycles should be limited to three.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13383461/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148004723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wound fluid proteomics reveal elevated alpha-1 antitrypsin levels are associated with healing of medical device related pressure injury.","authors":"Haydn A Fox, Daniel A Broszczak, Anna Doubrovsky, Annabel Levido, Jennifer Palmer, Fiona Coyer, Tony J Parker","doi":"10.1186/s12014-026-09609-0","DOIUrl":"10.1186/s12014-026-09609-0","url":null,"abstract":"<p><p>The Medical Device Related Pressure Injuries (MDRPIs) are a wound type that has been extensively tracked and recorded within observational studies, with a global patient prevalence of 19.3% [Zhang N et al. in Eur J Med Res 1:425, 2024] and 28.1% in acute care patients [Brophy S et al. in J Tissue Viability 4:489-498, 2021]. Yet, despite being an injury caused directly by medical intervention, to the author's knowledge, no in-depth proteomic analysis in this wound type has been published previously. This study represents a novel proteomic analysis of clinical MDRPI samples providing initial characterization of a protein pathway significant to wound healing in the context of MDRPIs developed in an ICU setting (Fig. 1). To investigate the proteomic changes associated with the healing outcomes of medical device related pressure injuries through comprehensive proteome characterisation. Clinical wound fluid samples were collected from Intensive Care Unit (ICU) patients with MDRPIs. These samples underwent analysis using Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH-MS) mass spectrometry. The severity and healing trajectories of the injuries were assessed using the Pressure Ulcer Scale for Healing (PUSH) scores, facilitating the comparison of protein abundances to identify key pathways involved in healing and non-healing MDRPIs. The study identified a significant inverse correlation between the severity of non-healing MDRPIs and the levels of alpha-1 antitrypsin (A1AT) (R = -0.43; P = 0.035). A1AT functions as an inhibitor of neutrophil elastase (NE), which targets kininogen-1 (KNG-1). This relationship was further substantiated by a strong positive correlation between A1AT and KNG-1 levels (R = 0.76; Q < 6.8 × 10^- 10), indicating a protective function of A1AT over KNG-1 from NE. Given that KNG-1 contributes to early wound healing through its derivative, bradykinin, the misregulation of A1AT may disrupt the healing process of MDRPIs. The findings suggest that decreased levels of A1AT are associated with increased severity in non-healing MDRPIs, potentially due to the disruption of KNG-1 activity. These insights offer a foundation for further research into targeted therapeutic strategies aimed at enhancing the healing of MDRPIs.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13374189/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147959772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Noninvasive early detection and grading of pneumoconiosis via plasma proteomics and machine learning: PRSS3 as a potential biomarker.","authors":"Yizhuo Tian, Mingyao Wang, Zhifei Hou, Wenfeng Zhu, Yong Gao, Jing Geng, Xinran Zhang, Kaiyuan Min, Jiangfeng Liu, Juntao Yang, Huaping Dai","doi":"10.1186/s12014-026-09591-7","DOIUrl":"10.1186/s12014-026-09591-7","url":null,"abstract":"<p><strong>Background: </strong>Coal-dust, a persistent airborne pollutant, induces dose-related pulmonary fibrosis; however, plasma biomarkers for pre-clinical toxicity remain lacking.</p><p><strong>Methods: </strong>We enrolled 158 participants, including 28 healthy controls (HCs), 30 dust-exposed workers (DEWs), and 100 patients with coal workers' pneumoconiosis (CWP) at different stages (n _CWP-I=40, n _CWP-II=30, n _CWP-III=30). Plasma proteomic profiling was performed via data-independent acquisition (DIA) mass spectrometry. Differentially expressed proteins were identified and functionally annotated. Key proteins were selected and multiple machine learning algorithms were employed to construct and validate predictive models.</p><p><strong>Results: </strong>We identified 1,239 plasma proteins, including 645 high-confidence candidates. Functional enrichment revealed significant associations between disease progression and pathways such as PPAR signaling, cholesterol metabolism, Epstein-Barr virus infection, and the pentose phosphate pathway. These alterations converge on dysregulated lipid metabolism, chronic inflammatory signaling and virus-induced immune evasion, suggesting a metabolic-immune axis that orchestrates early fibrotic progression. We successfully constructed the first plasma proteomics-based machine learning models for pneumoconiosis grading and early screening. Notably, a single biomarker, PRSS3, demonstrated exceptional performance in distinguishing DEW patients from early-stage pneumoconiosis patients (CWP-I), achieving an area under the curve (AUC) of 1.00 and an accuracy of 1.00 in the training set and an AUC of 1.00 with an accuracy between 0.93 and 1.00 in the validation set.</p><p><strong>Conclusion: </strong>This study establishes innovative machine learning-based models for the grading and early screening of pneumoconiosis via plasma proteomics. The identification of PRSS3 as a potential biomarker highlights the clinical utility of our approach. These findings provide a foundation for noninvasive diagnostic strategies and future translational research in occupational lung diseases.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13374243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147948171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic biomarkers of distant metastasis following curative-intent resection of early-stage rectal cancer.","authors":"Vo Van Anh Pham, Matthew J McKay, Benita C Y Tse, Anthony J Gill, Justin Evans, Yasser Salama, Kah Hoong Chang, Alexander Engel, Mark P Molloy","doi":"10.1186/s12014-026-09608-1","DOIUrl":"10.1186/s12014-026-09608-1","url":null,"abstract":"<p><strong>Background: </strong>Curative-intent surgery is the standard treatment for node-negative, early-stage rectal cancer. Although distant recurrence is uncommon in this setting, it carries a markedly poor prognosis. There is limited understanding of tumour biology linked to this aggressive cancer and no biomarkers to aid clinical practice. The aim of this pilot study was to demonstrate feasibility to identify putative prognostic biomarkers of distant metastasis following curative-intent surgery for early rectal cancer.</p><p><strong>Methods: </strong>Treatment-naïve patients who developed distant metastases after total mesorectal excision for Stage I/IIA rectal cancer were identified from our centre over a 7-year period. A cohort matched for clinicopathological features without subsequent metastasis was used as control. Formalin-fixed paraffin embedded primary tumour was laser microdissected and proteins extracted for mass-spectrometry based proteomics. Separately, intratumoural CD3⁺, CD3⁺CD8⁺ and CD3⁺CD8^- T cells densities were measured using immunohistochemistry.</p><p><strong>Results: </strong>In our cohort, the frequency of distant metastasis was 8.4%. 5,473 proteins were quantified in all samples, with 69 proteins differentially expressed between primary tumours with or without subsequent distant metastasis. TGF-β signaling, epithelial-mesenchymal transition, and coagulation pathways were enriched in primary tumours that developed distant metastases. Total T cells and CD8^- T cell densities were lower in both the epithelium and stroma of patients with distant metastasis. CD8⁺ T cell density was also lower in the tumour epithelial regions of patients who developed distant metastases.</p><p><strong>Conclusions: </strong>We demonstrated feasibility to detect putative protein and T cell infiltrate biomarkers of distant metastasis in early-stage rectal cancer. A multi-centre validation study is now required to identify higher risk patients where adjuvant chemotherapy may improve outcomes.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13371534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147873606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic and phosphoproteomic signatures of disease progression in unmutated IGHV chronic lymphocytic leukemia.","authors":"Renee C Tschumper, Neil E Kay, Sameer A Parikh, Kari G Rabe, Partho Sen, Akhilesh Pandey, Richard K Kandasamy, Diane F Jelinek","doi":"10.1186/s12014-026-09607-2","DOIUrl":"10.1186/s12014-026-09607-2","url":null,"abstract":"<p><strong>Background: </strong>Chronic lymphocytic leukemia (CLL) patients with an unmutated (UM) immunoglobulin heavy chain variable region gene (IGHV) typically have poorer prognosis and require earlier treatment compared to those with mutated IGHV. Nevertheless, disease progression among UM-CLL patients is heterogeneous, with some experiencing stable disease and prolonged time to first treatment (TTFT). Because the cellular proteome directly reflects cell function, comprehensive proteomic and phosphoproteomic profiling may improve prediction of progression of UM-CLL and uncover novel biomarkers.</p><p><strong>Methods: </strong>We applied mass spectrometry-based quantitative proteomics and phosphoproteomics to peripheral blood mononuclear cells from 18 UM‑CLL patients, comparing those with a TTFT of ≤ 2 years (progressive disease) to those with TTFT ≥ 4 years (stable disease).</p><p><strong>Results: </strong>We quantified over 6,300 proteins across all samples. The top 100 differentially expressed proteins clearly distinguished progressive from stable UM-CLL. Phosphoproteomic analysis identified over 15,000 phosphorylation sites across 4,200 proteins, with the top 100 phosphopeptides similarly separating patient groups. Gene set enrichment analysis of proteins up‑regulated in progressive UM‑CLL revealed strong enrichment for RNA processing and ribosome biogenesis, together with mitochondrial translation and oxidative phosphorylation pathways, underscoring dysregulated RNA metabolism and energy production as key features of disease progression.</p><p><strong>Conclusions: </strong>Specific proteins and phosphopeptides identified here, upon further validation, may serve as biomarkers for early intervention in UM‑CLL. More broadly, our study demonstrates the value of integrated proteomic and phosphoproteomic profiling which may lead to refining risk stratification and advancing understanding of the complex biology underlying CLL progression.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13366893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147856089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative Proteomic and Phosphoproteomic Analysis Reveals Altered Vesicle Transport in Systemic Lupus Erythematosus.","authors":"Lingling Zhou, Yixi Li, Mengyao Wu, Donge Tang, Wei Zhang, Yong Dai","doi":"10.1186/s12014-026-09599-z","DOIUrl":"10.1186/s12014-026-09599-z","url":null,"abstract":"","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13361604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147764650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}