PROTEOMICS – Clinical Applications最新文献

{"title":"Subcellular proteomics insights into Alzheimer's disease development.","authors":"Zhiyuan Liang, Hongbin Zhuang, Xueshan Cao, Guanwei Ma, Liming Shen","doi":"10.1002/prca.202200112","DOIUrl":"10.1002/prca.202200112","url":null,"abstract":"<p><p>Alzheimer's disease (AD), one of the most common dementias, is a neurodegenerative disease characterized by cognitive impairment and decreased judgment function. The expected number of AD patient is increasing in the context of the world's advancing medical care and increasing human life expectancy. Since current molecular mechanism studies on AD pathogenesis are incomplete, there is no specific and effective therapeutic agent. Mass spectrometry (MS)-based unbiased proteomics studies provide an effective and comprehensive approach. Many advances have been made in the study of the mechanism, diagnostic markers, and drug targets of AD using proteomics. This paper focus on subcellular level studies, reviews studies using proteomics to study AD-associated mitochondrial dysfunction, synaptic, and myelin damage, the protein composition of amyloid plaques (APs) and neurofibrillary tangles (NFTs), changes in tissue extracellular vehicles (EVs) and exosome proteome, and the protein changes in ribosomes and lysosomes. The methods of sample separation and preparation and proteomic analysis as well as the main findings of these studies are involved. The results of these proteomics studies provide insights into the pathogenesis of AD and provide theoretical resource and direction for future research in AD, helping to identify new biomarkers and drugs targets for AD.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e2200112"},"PeriodicalIF":2.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10121341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of novel biomarkers for frailty diagnosis via serum amino acids metabolomic analysis using UPLC-MS/MS.","authors":"Mengyuan Zhou, Wenjing Sun, Jiaojiao Chu, Yingping Liao, Pengfei Xu, Xujiao Chen, Meng Li","doi":"10.1002/prca.202300035","DOIUrl":"10.1002/prca.202300035","url":null,"abstract":"<p><strong>Purpose: </strong>This study was aimed to analyze serum amino acid metabolite profiles in frailty patients, gain a better understanding of the metabolic mechanisms in frailty, and assess the diagnostic value of metabolomics-based biomarkers of frailty.</p><p><strong>Experimental design: </strong>This study utilized the ultra-performance liquid chromatography tandem mass spectrometry to examine amino acids associated with frailty. Additionally, we employed multivariate statistical methods, metabolomic data analysis, receiver operating characteristic (ROC) curve analysis, and pathway enrichment analysis.</p><p><strong>Results: </strong>Among the assayed amino acid metabolites, we identified biomarkers for frailty. ROC curve analysis for frailty diagnosis based on the modified Fried's frailty index showed that the areas under ROC curve of tryptophan, phenylalanine, aspartic acid, and combination were 0.775, 0.679, 0.667, and 0.807, respectively. ROC curve analysis for frailty diagnosis based on Frail Scale showed that the areas under ROC curve of cystine, phenylalanine, and combination of amino acids (cystine, L-Glutamine, citrulline, tyrosine, kynurenine, phenylalanine, glutamin acid) were 0.834, 0.708, and 0.854 respectively.</p><p><strong>Conclusion and clinical relevance: </strong>In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.</p><p><strong>Clinical significance: </strong>Frailty is a clinical syndrome, as a consequence it is challenging to identify at early course of the disease, even based on the existing frailty scales. Early diagnosis and appropriate patient management are the key to improve the survival and limit disabilities in frailty patients. Proven by the extensive laboratory and clinical studies on frailty, comprehensive analysis of metabolic levels in frail patients, identification of biomarkers and study of pathogenic pathways of metabolites contribute to the prediction and early diagnosis of frailty. In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e2300035"},"PeriodicalIF":2.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139404069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative analysis of transcriptome and proteome profiles in primary and recurrent glioblastoma.","authors":"Jiajie Zhang, Guowei Wang, Bo Yan, Ge Yang, Qianqian Yang, Yaqin Hu, Jiuru Guo, Ningning Zhao, Liang Wang, Huijuan Wang","doi":"10.1002/prca.202200085","DOIUrl":"10.1002/prca.202200085","url":null,"abstract":"<p><strong>Purpose: </strong>Glioblastoma (GBM) is the most common and aggressive primary brain tumor characterized by poor prognosis and high recurrence. The underlying molecular mechanism that drives tumor progression and recurrence is unclear. This study is intended to look for molecular and biological changes that play a key role in GBM recurrence.</p><p><strong>Experimental design: </strong>An integrative transcriptomic and proteomic analysis was performed on three primary GBM and three recurrent GBM tissues. Omics analyses were conducted using label-free quantitative proteomics and whole transcriptome sequencing.</p><p><strong>Results: </strong>A significant difference was found between primary GBM and recurrent GBM at the transcriptional level. Similar to other omics studies of cancer, a weak overlap was observed between transcriptome and proteome, and Procollagen C-Endopeptidase Enhancer 2 (PCOLCE2) was observed to be upregulated at mRNA and protein levels. Analysis of public cancer database revealed that high expression of PCOLCE2 is associated with poor prognosis of patients with GBM and that it may be a potential prognostic indicator. Functional and environmental enrichment analyses revealed significantly altered signaling pathways related to energy metabolism, including mitochondrial ATP synthesis-coupled electron transport and oxidative phosphorylation.</p><p><strong>Conclusions and clinical relevance: </strong>This study provides new insights into the recurrence process of GBM through combined transcriptomic and proteomic analyses, complementing the existing GBM transcriptomic and proteomic data and suggesting that integrated multi-omics analyses may reveal new disease features of GBM.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e2200085"},"PeriodicalIF":2.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138462203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics.","authors":"Ce Wang, Gang Feng, Jie Zhao, Yang Xu, Yang Li, Lin Wang, Meng Wang, Miao Liu, Yilin Wang, Hong Mu, Chunlei Zhou","doi":"10.1002/prca.202300047","DOIUrl":"10.1002/prca.202300047","url":null,"abstract":"<p><strong>Background: </strong>Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection.</p><p><strong>Methods: </strong>The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA).</p><p><strong>Results: </strong>A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis.</p><p><strong>Conclusions: </strong>Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e2300047"},"PeriodicalIF":2.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139432881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive characterization of protein modifications using mass spectrometry and dry blood spots.","authors":"Sofia Guedes, Luís Perpétuo, Jacinta Veloso, Tânia Lima, Ana F Ferreira, Inês Pires, Francisca Savaiva, André Lourenço, Liliana Moreira-Costa, Adelino Leite-Moreira, Antonio Barros, Fábio Trindade, Rui Vitorino","doi":"10.1002/prca.202300102","DOIUrl":"10.1002/prca.202300102","url":null,"abstract":"<p><strong>Purpose: </strong>The main objective of this study is to characterize and analyze modified peptides in DBS samples. This includes deciphering their specific PTMs and understanding their potential impact on the population or disease cohort under study.</p><p><strong>Experimental design: </strong>Using mass spectrometry-based proteomic approaches, we performed a comprehensive analysis of DBS samples. Our focus was on the identification and quantification of modified peptides. We also took advantage of recent advances in DBS mass spectrometry to ensure accurate detection and quantification.</p><p><strong>Results: </strong>A comprehensive analysis identified 972 modified peptides in DBS samples. Of these, a subset of 211 peptides was consistently present in all samples, highlighting their potential biological importance and relevance. This indicates a diverse spectrum of PTMs in the proteome of DBS samples.</p><p><strong>Conclusions and clinical relevance: </strong>Integration of mass spectrometry and proteomics has revealed a broad spectrum of modified peptides in DBS samples and highlighted their importance in biological processes and disease progression. Accurate detection of these PTMs may be critical for risk stratification and disease management. This study improves the understanding of molecular mechanisms underlying biological processes and disease development, providing important insights for clinical applications.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e2300102"},"PeriodicalIF":2.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139088133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential functionality of Cutibacterium acnes extracellular vesicles in atopic dermatitis and acne vulgaris: A comparative proteomic analysis","authors":"Tianze Yu, Jin Chen, Shi Wu, Min Jiang, Ling Han, Ying Ma","doi":"10.1002/prca.202300106","DOIUrl":"https://doi.org/10.1002/prca.202300106","url":null,"abstract":"Background<jats:italic>Cutibacterium acnes</jats:italic> is a commensal bacterium residing in healthy skin and plays a critical role in maintaining skin homeostasis. <jats:italic>C. acnes</jats:italic> has been considered closely related to acne vulgaris, while recent studies suggest that <jats:italic>C. acnes</jats:italic> and its metabolites may have a protective role in atopic dermatitis (AD) by modulating the immune system and maintaining skin homeostasis. Extracellular vesicles (EVs) are small membranous vesicles secreted by bacteria that participate in bacteria‐host interactions.MethodsThis study first compared <jats:italic>C. acnes</jats:italic> EVs from AD lesions (AD‐EVs), acne lesions (Acne‐EVs), and healthy skin (NC‐EVs), using Label‐free quantitative LC‐MS/MS and validated differently expressed proteins by parallel reaction monitoring (PRM). Then Normal Human Epidermal Keratinocytes (NHEK) and human primary keratinocytes (KC) were treated with <jats:italic>C. acnes</jats:italic> EVs isolated from different groups, and the expressions of inflammatory factors were measured by quantitative real‐time PCR and Western blotting.ResultsCompared with the acne group, the AD group showed greater downregulation of proteins related to energy metabolism and carbon source utilization pathway. Differences in protein profile in AD and acne lesion‐separated <jats:italic>C. acnes</jats:italic> EVs correspond to the abnormal sebum secretion pattern in both diseases. <jats:italic>C. acnes</jats:italic> EVs from different groups affected different expressions of Th1 and Th2 inflammatory factors and epidermal barrier markers in NHEK and KC, indicating different immunomodulatory potentials.ConclusionsThis study observed distinct proteomic differences between AD‐EVs and Acne‐EVs, and provided insights into the functional differences of <jats:italic>C. acnes</jats:italic> EVs in AD and acne.","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":"98 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140627933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic and metabolomic characterization of bone, liver, and lung metastases in plasma of breast cancer patients","authors":"Hui Ye, Xiabo Shen, Yaohan Li, Weibin Zou, Syed Shams ul Hassan, Yue Feng, Xiaojia Wang, Jingkui Tian, Xiying Shao, Yi Tao, Wei Zhu","doi":"10.1002/prca.202300136","DOIUrl":"https://doi.org/10.1002/prca.202300136","url":null,"abstract":"BackgroundBreast cancer (BC) is the second leading cause of cancer‐related deaths among women, primarily due to metastases to other organs rather than the primary tumor.MethodsIn this study, a comprehensive analysis of plasma proteomics and metabolomics was conducted on a cohort of 51 BC patients. Potential biomarkers were screened by the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest algorithm. Additionally, enzyme‐linked immunosorbent assay (ELISA) kits and untargeted metabolomics were utilized to validate the prognostic biomarkers in an independent cohort.ResultsIn the study, extracellular matrix (ECM)‐related functional enrichments were observed to be enriched in BC cases with bone metastases. Proteins dysregulated in retinol metabolism in liver metastases and leukocyte transendothelial migration in lung metastases were also identified. Machine learning models identified specific biomarker panels for each metastasis type, achieving high diagnostic accuracy with area under the curve (AUC) of 0.955 for bone, 0.941 for liver, and 0.989 for lung metastases.ConclusionsFor bone metastasis, biomarkers such as leucyl‐tryptophan, LysoPC(P‐16:0/0:0), FN1, and HSPG2 have been validated. dUDP, LPE(18:1/0:0), and aspartylphenylalanine have been confirmed for liver metastasis. For lung metastasis, dUDP, testosterone sulfate, and PE(14:0/20:5) have been established.","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":"17 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140603350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Masthead: Proteomics 2'24","authors":"","doi":"10.1002/prca.202470023","DOIUrl":"https://doi.org/10.1002/prca.202470023","url":null,"abstract":"","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":"87 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140106254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial Board: Proteomics 2'24","authors":"","doi":"10.1002/prca.202470022","DOIUrl":"https://doi.org/10.1002/prca.202470022","url":null,"abstract":"","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":"82 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140106334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"Hide and seek\": Misleading transferrin variants in PMM2-CDG complicate diagnostics.","authors":"Alexandre Raynor, Arnaud Bruneel, Pieter Vermeersch, Sophie Cholet, Sebastian Friedrich, Matthias Eckenweiler, Anke Schumann, Simone Hengst, Ali Tunç Tuncel, François Fenaille, Christian Thiel, Daisy Rymen","doi":"10.1002/prca.202300040","DOIUrl":"10.1002/prca.202300040","url":null,"abstract":"<p><strong>Purpose: </strong>Congenital disorders of glycosylation (CDG) are one of the fastest growing groups of inborn errors of metabolism. Despite the availability of next-generation sequencing techniques and advanced methods for evaluation of glycosylation, CDG screening mainly relies on the analysis of serum transferrin (Tf) by isoelectric focusing, HPLC or capillary electrophoresis. The main pitfall of this screening method is the presence of Tf protein variants within the general population. Although reports describe the role of Tf variants leading to falsely abnormal results, their significance in confounding diagnosis in patients with CDG has not been documented so far. Here, we describe two PMM2-CDG cases, in which Tf variants complicated the diagnostic.</p><p><strong>Experimental design: </strong>Glycosylation investigations included classical screening techniques (capillary electrophoresis, isoelectric focusing and HPLC of Tf) and various confirmation techniques (two-dimensional electrophoresis, western blot, N-glycome, UPLC-FLR/QTOF MS with Rapifluor). Tf variants were highlighted following neuraminidase treatment. Sequencing of PMM2 was performed.</p><p><strong>Results: </strong>In both patients, Tf screening pointed to CDG-II, while second-line analyses pointed to CDG-I. Tf variants were found in both patients, explaining these discrepancies. PMM2 causative variants were identified in both patients.</p><p><strong>Conclusion and clinical relevance: </strong>We suggest that a neuraminidase treatment should be performed when a typical CDG Tf pattern is found upon initial screening analysis.</p>","PeriodicalId":20571,"journal":{"name":"PROTEOMICS – Clinical Applications","volume":" ","pages":"e2300040"},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50158637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}