Clinical proteomics最新文献

{"title":"Proteomic analyses reveal cystatin c is a promising biomarker for evaluation of systemic lupus erythematosus.","authors":"He Huang, Yukun Zhang, Lan Gui, Li Zhang, Minglong Cai, Yujun Sheng","doi":"10.1186/s12014-023-09434-9","DOIUrl":"10.1186/s12014-023-09434-9","url":null,"abstract":"<p><strong>Background: </strong>Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple organ involvement, especially the kidneys. However, the underlying mechanism remains unclear, and accurate biomarkers are still lacking. This study aimed to identify biomarkers to assess organ damage and disease activity in patients with SLE using quantitative proteomics.</p><p><strong>Methods: </strong>Proteomic analysis was performed using mass spectrometry in 15 patients with SLE and 15 age-matched healthy controls. Proteomic profiles were compared in four main subtypes: SLE with proteinuria (SLE-PN), SLE without proteinuria (SLE-non-PN), SLE with anti-dsDNA positivity (SLE-DP), and SLE with anti-dsDNA negativity (SLE-non-DP). Gene ontology biological process analysis revealed differentially expressed protein networks. Cystatin C (CysC) levels were measured in 200 patients with SLE using an immunoturbidimetric assay. Clinical and laboratory data were collected to assess their correlation with serum CysC levels.</p><p><strong>Results: </strong>Proteomic analysis showed that upregulated proteins in both the SLE-PN and SLE-DP groups were mainly mapped to neutrophil activation networks. Moreover, CysC from neutrophil activation networks was upregulated in both the SLE-PN and SLE-DP groups. The associations of serum CysC level with proteinuria, anti-dsDNA positivity, lower complement C3 levels, and SLE disease activity index score in patients with SLE were further validated in a large independent cohort.</p><p><strong>Conclusions: </strong>Neutrophil activation is more prominent in SLE with proteinuria and anti-dsDNA positivity, and CysC is a promising marker for monitoring organ damage and disease activity in SLE.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49675092","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":"Redefining serological diagnostics with immunoaffinity proteomics.","authors":"Jonathan Walter, Zicki Eludin, Andrei P Drabovich","doi":"10.1186/s12014-023-09431-y","DOIUrl":"10.1186/s12014-023-09431-y","url":null,"abstract":"<p><p>Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41193666","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":"A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.","authors":"Ankit Halder, Deeptarup Biswas, Aparna Chauhan, Adrita Saha, Shreeman Auromahima, Deeksha Yadav, Mehar Un Nissa, Gayatri Iyer, Shashwati Parihari, Gautam Sharma, Sridhar Epari, Prakash Shetty, Aliasgar Moiyadi, Graham Roy Ball, Sanjeeva Srivastava","doi":"10.1186/s12014-023-09426-9","DOIUrl":"10.1186/s12014-023-09426-9","url":null,"abstract":"<p><strong>Background: </strong>Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective.</p><p><strong>Methods: </strong>A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins.</p><p><strong>Results: </strong>A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades.</p><p><strong>Conclusions: </strong>The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41126306","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":"Development of an ID-LC-MS/MS method using targeted proteomics for quantifying cardiac troponin I in human serum.","authors":"Meltem Asicioglu, Merve Oztug, Nevin Gul Karaguler","doi":"10.1186/s12014-023-09430-z","DOIUrl":"10.1186/s12014-023-09430-z","url":null,"abstract":"<p><strong>Background: </strong>Cardiac troponin is a complex protein consisting of the three subunits I, T and C located in heart muscle cells. When the heart muscle is damaged, it is released into the blood and can be detected. Cardiac troponin I (cTnI) is considered the most reliable and widely accepted test for detecting and confirming acute myocardial infarction. However, there is no current standardization between the commercial assays for cTnI quantification. Our work aims to create a measurement procedure that is traceable to the International System of Units for accurately measuring cardiac cTnI levels in serum samples from patients.</p><p><strong>Methods: </strong>The workflow begins with immobilizing anti-cTnI antibodies onto magnetic nanoparticles to form complexes. These complexes are used to isolate cTnI from serum. Next, trypsin is used to enzymatically digest the isolated cTnI. Finally, the measurement of multiple cTnI peptides is done simultaneously using isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS).</p><p><strong>Results: </strong>The maximum antibody immobilization was achieved by combining 1 mg of nanoparticles with 100 μg of antibody, resulting in an average of 59.2 ± 5.7 μg/mg of immobilized antibody. Subsequently, the anti-cTnI-magnetic nanoparticle complex was utilized to develop and validate a method for quantifying cTnI in human serum using ID-LC-MS/MS and a protein calibration approach. The analytical method was assessed regarding linearity and recovery. The developed method enables the quantification of cTnI from 0.7 to 24 μg/L (R > 0.996). The limit of quantification was 1.8 μg/L and the limit of detection was 0.6 μg/L. Intermediate precision was ≤ 9.6% and repeatability was 2.0-8.7% for all quality control materials. The accuracy of the analyzed quality control materials was between 90 and 110%. Total measurement uncertainties for target value assignment (n = 6) were found to be ≤ 12.5% for all levels.</p><p><strong>Conclusions: </strong>The analytical method demonstrated high analytical performance in accurately quantifying cardiac troponin I levels in human serum. The proposed analytical method has the potential to facilitate the harmonization of cTnI results between clinical laboratories, assign target values to secondary certified reference materials and support reliable measurement of cTnI.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41106982","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":"Identification of potential molecular targets for the treatment of cluster 1 human pheochromocytoma and paraganglioma via comprehensive proteomic characterization.","authors":"Ondrej Vit, Pavel Talacko, Zdenek Musil, Igor Hartmann, Karel Pacak, Jiri Petrak","doi":"10.1186/s12014-023-09428-7","DOIUrl":"10.1186/s12014-023-09428-7","url":null,"abstract":"<p><strong>Background: </strong>Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors. New drug targets and proteins that would assist sensitive PPGL imagining could improve therapy and quality of life of patients with PPGL, namely those with recurrent or metastatic disease. Using a combined proteomic strategy, we looked for such clinically relevant targets among integral membrane proteins (IMPs) upregulated on the surface of tumor cells and non-membrane druggable enzymes in PPGL.</p><p><strong>Methods: </strong>We conducted a detailed proteomic analysis of 22 well-characterized human PPGL samples and normal chromaffin tissue from adrenal medulla. A standard quantitative proteomic analysis of tumor lysate, which provides information largely on non-membrane proteins, was accompanied by specific membrane proteome-aimed methods, namely glycopeptide enrichment using lectin-affinity, glycopeptide capture by hydrazide chemistry, and enrichment of membrane-embedded hydrophobic transmembrane segments.</p><p><strong>Results: </strong>The study identified 67 cell surface integral membrane proteins strongly upregulated in PPGL compared to control chromaffin tissue. We prioritized the proteins based on their already documented direct role in cancer cell growth or progression. Increased expression of the seven most promising drug targets (CD146, CD171, ANO1, CD39, ATP8A1, ACE and SLC7A1) were confirmed using specific antibodies. Our experimental strategy also provided expression data for soluble proteins. Among the druggable non-membrane enzymes upregulated in PPGL, we identified three potential drug targets (SHMT2, ARG2 and autotaxin) and verified their upregulated expression.</p><p><strong>Conclusions: </strong>Application of a combined proteomic strategy recently presented as \"Pitchfork\" enabled quantitative analysis of both, membrane and non-membrane proteome, and resulted in identification of 10 potential drug targets in human PPGL. Seven membrane proteins localized on the cell surface and three non-membrane druggable enzymes proteins were identified and verified as significantly upregulated in PPGL. All the proteins have been previously shown to be upregulated in several human cancers, and play direct role in cancer progression. Marked upregulation of these proteins along with their localization and established direct roles in tumor progression make these molecules promising candidates as drug targets or proteins for sensitive PPGL imaging.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41112587","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":"Systematic review of type 1 diabetes biomarkers reveals regulation in circulating proteins related to complement, lipid metabolism, and immune response.","authors":"Soumyadeep Sarkar, Emily C Elliott, Hayden R Henry, Ivo Díaz Ludovico, John T Melchior, Ashley Frazer-Abel, Bobbie-Jo Webb-Robertson, W Sean Davidson, V Michael Holers, Marian J Rewers, Thomas O Metz, Ernesto S Nakayasu","doi":"10.1186/s12014-023-09429-6","DOIUrl":"10.1186/s12014-023-09429-6","url":null,"abstract":"<p><strong>Background: </strong>Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development.</p><p><strong>Methods: </strong>This systematic review was registered with Open Science Framework ( https://doi.org/10.17605/OSF.IO/N8TSA ). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria.</p><p><strong>Results: </strong>A total of 13 studies met our inclusion criteria, resulting in the identification of 266 unique proteins, with 31 (11.6%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found 2 subsets: 17 proteins (C3, C1R, C8G, C4B, IBP2, IBP3, ITIH1, ITIH2, BTD, APOE, TETN, C1S, C6A3, SAA4, ALS, SEPP1 and PI16) and 3 proteins (C3, CLUS and C4A) have consistent regulation in at least 2 independent studies at post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development.</p><p><strong>Conclusions: </strong>Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10512508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41132484","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":"Identification and verification of plasma protein biomarkers that accurately identify an ectopic pregnancy.","authors":"Lynn A Beer, Xiangfan Yin, Jianyi Ding, Suneeta Senapati, Mary D Sammel, Kurt T Barnhart, Qin Liu, David W Speicher, Aaron R Goldman","doi":"10.1186/s12014-023-09425-w","DOIUrl":"10.1186/s12014-023-09425-w","url":null,"abstract":"<p><strong>Background: </strong>Differentiating between a normal intrauterine pregnancy (IUP) and abnormal conditions including early pregnancy loss (EPL) or ectopic pregnancy (EP) is a major clinical challenge in early pregnancy. Currently, serial β-human chorionic gonadotropin (β-hCG) and progesterone are the most commonly used plasma biomarkers for evaluating pregnancy prognosis when ultrasound is inconclusive. However, neither biomarker can predict an EP with sufficient and reproducible accuracy. Hence, identification of new plasma biomarkers that can accurately diagnose EP would have great clinical value.</p><p><strong>Methods: </strong>Plasma was collected from a discovery cohort of 48 consenting women having an IUP, EPL, or EP. Samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by a label-free proteomics analysis to identify significant changes between pregnancy outcomes. A panel of 14 candidate biomarkers were then verified in an independent cohort of 74 women using absolute quantitation by targeted parallel reaction monitoring mass spectrometry (PRM-MS) which provided the capacity to distinguish between closely related protein isoforms. Logistic regression and Lasso feature selection were used to evaluate the performance of individual biomarkers and panels of multiple biomarkers to predict EP.</p><p><strong>Results: </strong>A total of 1391 proteins were identified in an unbiased plasma proteome discovery. A number of significant changes (FDR ≤ 5%) were identified when comparing EP vs. non-EP (IUP + EPL). Next, 14 candidate biomarkers (ADAM12, CGA, CGB, ISM2, NOTUM, PAEP, PAPPA, PSG1, PSG2, PSG3, PSG9, PSG11, PSG6/9, and PSG8/1) were verified as being significantly different between EP and non-EP in an independent cohort (FDR ≤ 5%). Using logistic regression models, a risk score for EP was calculated for each subject, and four multiple biomarker logistic models were identified that performed similarly and had higher AUCs than models with single predictors.</p><p><strong>Conclusions: </strong>Overall, four multivariable logistic models were identified that had significantly better prediction of having EP than those logistic models with single biomarkers. Model 4 (NOTUM, PAEP, PAPPA, ADAM12) had the highest AUC (0.987) and accuracy (96%). However, because the models are statistically similar, all markers in the four models and other highly correlated markers should be considered in further validation studies.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10289222","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":"Proteome analysis of CD5-positive diffuse large B cell lymphoma FFPE tissue reveals downregulation of DDX3X, DNAJB1, and B cell receptor signaling pathway proteins including BTK and Immunoglobulins.","authors":"Takuya Hiratsuka, Shinji Ito, Rika Sakai, Tomoyuki Yokose, Tatsuya Endo, Yataro Daigo, Yohei Miyagi, Tatsuaki Tsuruyama","doi":"10.1186/s12014-023-09422-z","DOIUrl":"10.1186/s12014-023-09422-z","url":null,"abstract":"<p><strong>Background: </strong>The molecular pathology of diffuse large B cell lymphoma (DLBCL) has been extensively studied. Among DLBCL subtypes, the prognosis of CD5-positive DLBCL is worse than that of CD5-negative DLBCL, considering the central nervous system relapse and poor response to R-CHOP therapy. However, the molecular mechanisms underlying the tumorigenesis and progression of CD5-positive DLBCL remain unknown.</p><p><strong>Methods: </strong>To identify molecular markers that can be targeted for treating DLBCL, a proteomic study was performed using liquid chromatography-mass spectrometry with chemically pretreated formalin-fixed paraffin-embedded specimens from CD5-positive (n = 5) and CD5-negative DLBCL patients (n = 6).</p><p><strong>Results: </strong>Twenty-one proteins showed significant downregulation in CD5-positive DLBCL compared to CD5-negative DLBCL. Principal component analysis of protein expression profiling in CD5-positive and CD5-negative DLBCL revealed that DNAJB1, DDX3X, and BTK, which is one of the B cell phenotypic proteins, were the most significantly downregulated proteins and served as biomarkers that distinguished both groups. Additionally, a set of immunoglobulins, including IgG4, exhibited significant downregulation. Immunohistochemistry analysis for BTK demonstrated reduced staining in CD5-positive DLBCL compared to CD5-negative DLBCL.</p><p><strong>Conclusions: </strong>In conclusion, DNAJB1 and DDX3X, BTK, and a set of immunoglobulins are promising biomarkers. Probably, the suppression of BCR signaling is the unique phenotype of CD5-positive DLBCL. This formalin-fixed paraffin-embedded (FFPE)-based profiling may help to develop novel therapeutic molecularly targeted drugs for treating DLBCL.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498596/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10259075","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":"New mechanisms and biomarkers of lymph node metastasis in cervical cancer: reflections from plasma proteomics.","authors":"Sai Han, Xiaoli Liu, Shuang Ju, Wendi Mu, Gulijinaiti Abulikemu, Qianwei Zhen, Jiaqi Yang, Jingjing Zhang, Yi Li, Hongli Liu, Qian Chen, Baoxia Cui, Shuxia Wu, Youzhong Zhang","doi":"10.1186/s12014-023-09427-8","DOIUrl":"10.1186/s12014-023-09427-8","url":null,"abstract":"<p><strong>Objective: </strong>Lymph node metastasis (LNM) and lymphatic vasculature space infiltration (LVSI) in cervical cancer patients indicate a poor prognosis, but satisfactory methods for diagnosing these phenotypes are lacking. This study aimed to find new effective plasma biomarkers of LNM and LVSI as well as possible mechanisms underlying LNM and LVSI through data-independent acquisition (DIA) proteome sequencing.</p><p><strong>Methods: </strong>A total of 20 cervical cancer plasma samples, including 7 LNM-/LVSI-(NC), 4 LNM-/LVSI + (LVSI) and 9 LNM + /LVSI + (LNM) samples from a cohort, were subjected to DIA to identify differentially expressed proteins (DEPs) for LVSI and LNM. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for DEP functional annotation. Protein-protein interaction (PPI) and weighted gene coexpression network analysis (WGCNA) were used to detect new effective plasma biomarkers and possible mechanisms.</p><p><strong>Results: </strong>A total of 79 DEPs were identified in the cohort. GO and KEGG analyses showed that DEPs were mainly enriched in the complement and coagulation pathway, lipid and atherosclerosis pathway, HIF-1 signal transduction pathway and phagosome and autophagy. WGCNA showed that the enrichment of the green module differed greatly between groups. Six interesting core DEPs (SPARC, HPX, VCAM1, TFRC, ERN1 and APMAP) were confirmed to be potential plasma diagnostic markers for LVSI and LNM in cervical cancer patients.</p><p><strong>Conclusion: </strong>Proteomic signatures developed in this study reflected the potential plasma diagnostic markers and new possible pathogenesis mechanisms in the LVSI and LNM of cervical cancer.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10492398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10211039","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":"Correction to: Proteomic analysis of human synovial fluid reveals potential diagnostic biomarkers for ankylosing spondylitis.","authors":"Ji-Hyun Lee, Jae Hun Jung, Jeesoo Kim, Won-Ki Baek, Jinseol Rhee, Tae-Hwan Kim, Sang-Hyon Kim, Kwang Pyo Kim, Chang-Nam Son, Jong-Seo Kim","doi":"10.1186/s12014-023-09423-y","DOIUrl":"10.1186/s12014-023-09423-y","url":null,"abstract":"","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10160142","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}