Clinical proteomics最新文献

{"title":"Proteomic profiling of prostate cancer reveals molecular signatures under antiandrogen treatment.","authors":"Yurun Huang, Guanglin Yang, Xinpeng Yao, Yue Fang, Qiliang Lin, Menghan Zhou, Yiping Yang, Qinggui Meng, Qingyun Zhang, Shan Wang","doi":"10.1186/s12014-024-09490-9","DOIUrl":"10.1186/s12014-024-09490-9","url":null,"abstract":"<p><strong>Background: </strong>Tumorigenesis and progression of prostate cancer (PCa) are indispensably dependent on androgen receptor (AR). Antiandrogen treatment is the principal preference for patients with advanced PCa. However, the molecular characteristics of PCa with antiandrogen intervention have not yet been fully uncovered.</p><p><strong>Methods: </strong>We first performed proteome analysis with 32 PCa tumor samples and 10 adjacent tissues using data-independent acquisition (DIA)- parallel accumulation serial fragmentation (PASEF) proteomics. Then label-free quantification (LFQ) mass spectrometry was employed to analyze protein profiles in LNCaP and PC3 cells.</p><p><strong>Results: </strong>M-type creatine kinase CKM and cartilage oligomeric matrix protein COMP were demonstrated to have the potential to be diagnostic biomarkers for PCa at both mRNA and protein levels. Several E3 ubiquitin ligases and deubiquitinating enzymes (DUBs) were significantly altered in PCa and PCa cells under enzalutamide treatment, and these proteins might reprogram proteostasis at protein levels in PCa. Finally, we discovered 127 significantly varied proteins in PCa samples with antiandrogen therapy and further uncovered 4 proteins in LNCaP cells upon enzalutamide treatment.</p><p><strong>Conclusions: </strong>Our research reveals new potential diagnostic biomarkers for prostate cancer and might help resensitize resistance to antiandrogen therapy.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"44"},"PeriodicalIF":2.8,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11202386/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141449930","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":"Frontiers in plasma proteome profiling platforms: innovations and applications.","authors":"Rajesh Kumar Soni","doi":"10.1186/s12014-024-09497-2","DOIUrl":"10.1186/s12014-024-09497-2","url":null,"abstract":"<p><p>Biomarkers play a crucial role in advancing precision medicine by enabling more targeted and individualized approaches to diagnosis and treatment. Various biofluids, including serum, plasma, cerebrospinal fluid (CSF), saliva, tears, pancreatic cyst fluids, and urine, have been identified as rich sources of potential for the early detection of disease biomarkers in conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. The analysis of plasma and serum in proteomics research encounters challenges due to their high complexity and the wide dynamic range of protein abundance. These factors impede the sensitivity, coverage, and precision of protein detection when employing mass spectrometry, a widely utilized technology in discovery proteomics. Conventional approaches such as Neat Plasma workflow are inefficient in accurately quantifying low-abundant proteins, including those associated with tissue leakage, immune response molecules, interleukins, cytokines, and interferons. Moreover, the manual nature of the workflow poses a significant hurdle in conducting large cohort studies. In this study, our focus is on comparing workflows for plasma proteomic profiling to establish a methodology that is not only sensitive and reproducible but also applicable for large cohort studies in biomarker discovery. Our investigation revealed that the Proteograph XT workflow outperforms other workflows in terms of plasma proteome depth, quantitative accuracy, and reproducibility while offering complete automation of sample preparation. Notably, Proteograph XT demonstrates versatility by applying it to various types of biofluids. Additionally, the proteins quantified widely cover secretory proteins in peripheral blood, and the pathway analysis enriched with relevant components such as interleukins, tissue necrosis factors, chemokines, and B and T cell receptors provides valuable insights. These proteins, often challenging to quantify in complex biological samples, hold potential as early detection markers for various diseases, thereby contributing to the improvement of patient care quality.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"43"},"PeriodicalIF":2.8,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11191172/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141431579","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 brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis.","authors":"Lincoln I Wurtz, Evdokiya Knyazhanskaya, Dorsa Sohaei, Ioannis Prassas, Sean Pittock, Maria Alice V Willrich, Ruba Saadeh, Ruchi Gupta, Hunter J Atkinson, Diane Grill, Martin Stengelin, Simon Thebault, Mark S Freedman, Eleftherios P Diamandis, Isobel A Scarisbrick","doi":"10.1186/s12014-024-09494-5","DOIUrl":"10.1186/s12014-024-09494-5","url":null,"abstract":"<p><strong>Background: </strong>Multiple sclerosis (MS) is a clinically and biologically heterogenous disease with currently unpredictable progression and relapse. After the development and success of neurofilament as a cerebrospinal fluid (CSF) biomarker, there is reinvigorated interest in identifying other markers of or contributors to disease. The objective of this study is to probe the predictive potential of a panel of brain-enriched proteins on MS disease progression and subtype.</p><p><strong>Methods: </strong>This study includes 40 individuals with MS and 14 headache controls. The MS cohort consists of 20 relapsing remitting (RR) and 20 primary progressive (PP) patients. The CSF of all individuals was analyzed for 63 brain enriched proteins using a method of liquid-chromatography tandem mass spectrometry. Wilcoxon rank sum test, Kruskal-Wallis one-way ANOVA, logistic regression, and Pearson correlation were used to refine the list of candidates by comparing relative protein concentrations as well as relation to known imaging and molecular biomarkers.</p><p><strong>Results: </strong>We report 30 proteins with some relevance to disease, clinical subtype, or severity. Strikingly, we observed widespread protein depletion in the disease CSF as compared to control. We identified numerous markers of relapsing disease, including KLK6 (kallikrein 6, OR = 0.367, p < 0.05), which may be driven by active disease as defined by MRI enhancing lesions. Other oligodendrocyte-enriched proteins also appeared at reduced levels in relapsing disease, namely CNDP1 (carnosine dipeptidase 1), LINGO1 (leucine rich repeat and Immunoglobin-like domain-containing protein 1), MAG (myelin associated glycoprotein), and MOG (myelin oligodendrocyte glycoprotein). Finally, we identified three proteins-CNDP1, APLP1 (amyloid beta precursor like protein 1), and OLFM1 (olfactomedin 1)-that were statistically different in relapsing vs. progressive disease raising the potential for use as an early biomarker to discriminate clinical subtype.</p><p><strong>Conclusions: </strong>We illustrate the utility of targeted mass spectrometry in generating potential targets for future biomarker studies and highlight reductions in brain-enriched proteins as markers of the relapsing remitting disease stage.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"42"},"PeriodicalIF":3.8,"publicationDate":"2024-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11181608/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141330462","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":"Glial fibrillary acidic protein, neurofilament light, matrix metalloprotease 3 and fatty acid binding protein 4 as non-invasive brain tumor biomarkers.","authors":"Atefeh Ghorbani, Miyo K Chatanaka, Lisa M Avery, Mingyue Wang, Jermaine Brown, Rachel Cohen, Taron Gorham, Salvia Misaghian, Nikhil Padmanabhan, Daniel Romero, Martin Stengelin, Anu Mathew, George Sigal, Jacob Wohlstadter, Craig Horbinski, Katy McCortney, Wei Xu, Gelareh Zadeh, Alireza Mansouri, George M Yousef, Eleftherios P Diamandis, Ioannis Prassas","doi":"10.1186/s12014-024-09492-7","DOIUrl":"10.1186/s12014-024-09492-7","url":null,"abstract":"<p><strong>Background: </strong>Gliomas are aggressive malignant tumors, with poor prognosis. There is an unmet need for the discovery of new, non-invasive biomarkers for differential diagnosis, prognosis, and management of brain tumors. Our objective is to validate four plasma biomarkers - glial fibrillary acidic protein (GFAP), neurofilament light (NEFL), matrix metalloprotease 3 (MMP3) and fatty acid binding protein 4 (FABP4) - and compare them with established brain tumor molecular markers and survival.</p><p><strong>Methods: </strong>Our cohort consisted of patients with benign and malignant brain tumors (GBM = 77, Astrocytomas = 26, Oligodendrogliomas = 23, Secondary tumors = 35, Meningiomas = 70, Schwannomas = 15, Pituitary adenomas = 15, Normal individuals = 30). For measurements, we used ultrasensitive electrochemiluminescence multiplexed immunoassays.</p><p><strong>Results: </strong>High plasma GFAP concentration was associated with GBM, low GFAP and high FABP4 were associated with meningiomas, and low GFAP and low FABP4 were associated with astrocytomas and oligodendrogliomas. NEFL was associated with progression of disease. Several prognostic genetic alterations were significantly associated with all plasma biomarker levels. We found no independent associations between plasma GFAP, NEFL, FABP4 and MMP3, and overall survival. The candidate biomarkers could not reliably discriminate GBM from primary or secondary CNS lymphomas.</p><p><strong>Conclusions: </strong>GFAP, NEFL, FABP4 and MMP3 are useful for differential diagnosis and prognosis, and are associated with molecular changes in gliomas.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"41"},"PeriodicalIF":3.8,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11179213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141327245","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":"Elevated level of multibranched complex glycan reveals an allergic tolerance status.","authors":"Ran Zhao, Chao Wang, Feidie Li, Zeyu Zeng, Yijing Hu, Xiaoyan Dong","doi":"10.1186/s12014-024-09491-8","DOIUrl":"10.1186/s12014-024-09491-8","url":null,"abstract":"<p><strong>Background: </strong>Allergen immunotherapy (AIT) is the only disease-modifying therapy that can achieve immune tolerance in patients through long-term allergen stimulation. Glycans play crucial roles in allergic disease, but no information on changes in glycosylation related to an allergic tolerance status has been reported.</p><p><strong>Methods: </strong>Fifty-seven patients with house dust mite (HDM) allergies were enrolled. Twenty-eight patients were not treated with AIT, 19 patients had just entered the AIT maintenance treatment phase, and 10 patients had been in the AIT maintenance phase for more than 1 year. Serum protein N-glycans were analyzed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), which included linkage-specific sialylation information.</p><p><strong>Results: </strong>Eighty-four N-glycans were identified in all three groups. Compared with the patients treated without AIT, the patients treated with AIT for a shorter time showed downregulated expression of high-mannose glycans and upregulated expression of α2,6 sialic acid. The patients treated with AIT in the maintenance phase for over 1 year, which was considered the start of immunological tolerance, showed downregulated expression of biantennary N-glycans and upregulated expression of multibranched and complex N-glycans. Nine N-glycans were changed between allergic and allergic-tolerant patients.</p><p><strong>Conclusions: </strong>The glycan form changed from mannose to a more complex type as treatment time increased, and multibranched complex glycans have the potential to be used as a monitoring indicator of immune tolerance. This serum N-glycome analysis provided important information for a deeper understanding of AIT treatment at the molecular level.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"40"},"PeriodicalIF":3.8,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11161957/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141287843","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 profiling of extracellular vesicles derived from human serum for the discovery of biomarkers in Avascular necrosis.","authors":"Soo-Eun Sung, Ju-Hyeon Lim, Kyung-Ku Kang, Joo-Hee Choi, Sijoon Lee, Minkyoung Sung, Wook-Tae Park, Young-In Kim, Min-Soo Seo, Gun Woo Lee","doi":"10.1186/s12014-024-09489-2","DOIUrl":"10.1186/s12014-024-09489-2","url":null,"abstract":"<p><strong>Background: </strong>Avascular necrosis (AVN) is a medical condition characterized by the destruction of bone tissue due to a diminished blood supply. When the rate of tissue destruction surpasses the rate of regeneration, effective treatment becomes challenging, leading to escalating pain, arthritis, and bone fragility as the disease advances. A timely diagnosis is imperative to prevent and initiate proactive treatment for osteonecrosis. We explored the potential of differentially expressed proteins in serum-derived extracellular vesicles (EVs) as biomarkers for AVN of the femoral head in humans. We analyzed the genetic material contained in serum-derived exosomes from patients for early diagnosis, treatment, and prognosis of avascular necrosis.</p><p><strong>Methods: </strong>EVs were isolated from the serum of both patients with AVN and a control group of healthy individuals. Proteomic analyses were conducted to compare the expression patterns of these proteins by proteomic analysis using LC-MS/MS.</p><p><strong>Results: </strong>Our results show that the levels of IGHV3-23, FN1, VWF, FGB, PRG4, FCGBP, and ZSWIM9 were upregulated in the EVs of patients with AVN compared with those of healthy controls. ELISA results showed that VWF and PRG4 were significantly upregulated in the patients with AVN.</p><p><strong>Conclusions: </strong>These findings suggest that these EV proteins could serve as promising biomarkers for the early detection and diagnosis of AVN. Early diagnosis is paramount for effective treatment, and the identification of new osteonecrosis biomarkers is essential to facilitate swift diagnosis and proactive intervention. Our study provides novel insights into the identification of AVN-related biomarkers that can enhance clinical management and treatment outcomes.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"39"},"PeriodicalIF":3.8,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11145856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141199649","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":"Differentiation between descending thoracic aortic diseases using machine learning and plasma proteomic signatures.","authors":"Amanda Momenzadeh, Simion Kreimer, Dongchuan Guo, Matthew Ayres, Daniel Berman, Kuang-Yuh Chyu, Prediman K Shah, Dianna Milewicz, Ali Azizzadeh, Jesse G Meyer, Sarah Parker","doi":"10.1186/s12014-024-09487-4","DOIUrl":"10.1186/s12014-024-09487-4","url":null,"abstract":"<p><strong>Background: </strong>Descending thoracic aortic aneurysms and dissections can go undetected until severe and catastrophic, and few clinical indices exist to screen for aneurysms or predict risk of dissection.</p><p><strong>Methods: </strong>This study generated a plasma proteomic dataset from 75 patients with descending type B dissection (Type B) and 62 patients with descending thoracic aortic aneurysm (DTAA). Standard statistical approaches were compared to supervised machine learning (ML) algorithms to distinguish Type B from DTAA cases. Quantitatively similar proteins were clustered based on linkage distance from hierarchical clustering and ML models were trained with uncorrelated protein lists across various linkage distances with hyperparameter optimization using fivefold cross validation. Permutation importance (PI) was used for ranking the most important predictor proteins of ML classification between disease states and the proteins among the top 10 PI protein groups were submitted for pathway analysis.</p><p><strong>Results: </strong>Of the 1,549 peptides and 198 proteins used in this study, no peptides and only one protein, hemopexin (HPX), were significantly different at an adjusted p < 0.01 between Type B and DTAA cases. The highest performing model on the training set (Support Vector Classifier) and its corresponding linkage distance (0.5) were used for evaluation of the test set, yielding a precision-recall area under the curve of 0.7 to classify between Type B from DTAA cases. The five proteins with the highest PI scores were immunoglobulin heavy variable 6-1 (IGHV6-1), lecithin-cholesterol acyltransferase (LCAT), coagulation factor 12 (F12), HPX, and immunoglobulin heavy variable 4-4 (IGHV4-4). All proteins from the top 10 most important groups generated the following significantly enriched pathways in the plasma of Type B versus DTAA patients: complement activation, humoral immune response, and blood coagulation.</p><p><strong>Conclusions: </strong>We conclude that ML may be useful in differentiating the plasma proteome of highly similar disease states that would otherwise not be distinguishable using statistics, and, in such cases, ML may enable prioritizing important proteins for model prediction.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"38"},"PeriodicalIF":3.8,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11145886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141199646","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 snapshot of saliva samples predicts new pathways implicated in SARS-CoV-2 pathogenesis.","authors":"Elena Moreno, Sergio Ciordia, Santos Milhano Fátima, Daniel Jiménez, Javier Martínez-Sanz, Pilar Vizcarra, Raquel Ron, Matilde Sánchez-Conde, Rafael Bargiela, Sergio Sanchez-Carrillo, Santiago Moreno, Fernando Corrales, Manuel Ferrer, Sergio Serrano-Villar","doi":"10.1186/s12014-024-09482-9","DOIUrl":"10.1186/s12014-024-09482-9","url":null,"abstract":"<p><strong>Background: </strong>Information on the microbiome's human pathways and active members that can affect SARS-CoV-2 susceptibility and pathogenesis in the salivary proteome is very scarce. Here, we studied a unique collection of samples harvested from April to June 2020 from unvaccinated patients.</p><p><strong>Methods: </strong>We compared 10 infected and hospitalized patients with severe (n = 5) and moderate (n = 5) coronavirus disease (COVID-19) with 10 uninfected individuals, including non-COVID-19 but susceptible individuals (n = 5) and non-COVID-19 and nonsusceptible healthcare workers with repeated high-risk exposures (n = 5).</p><p><strong>Results: </strong>By performing high-throughput proteomic profiling in saliva samples, we detected 226 unique differentially expressed (DE) human proteins between groups (q-value ≤ 0.05) out of 3376 unambiguously identified proteins (false discovery rate ≤ 1%). Major differences were observed between the non-COVID-19 and nonsusceptible groups. Bioinformatics analysis of DE proteins revealed human proteomic signatures related to inflammatory responses, central cellular processes, and antiviral activity associated with the saliva of SARS-CoV-2-infected patients (p-value ≤ 0.0004). Discriminatory biomarker signatures from human saliva include cystatins, protective molecules present in the oral cavity, calprotectins, involved in cell cycle progression, and histones, related to nucleosome functions. The expression levels of two human proteins related to protein transport in the cytoplasm, DYNC1 (p-value, 0.0021) and MAPRE1 (p-value, 0.047), correlated with angiotensin-converting enzyme 2 (ACE2) plasma activity. Finally, the proteomes of microorganisms present in the saliva samples showed 4 main microbial functional features related to ribosome functioning that were overrepresented in the infected group.</p><p><strong>Conclusion: </strong>Our study explores potential candidates involved in pathways implicated in SARS-CoV-2 susceptibility, although further studies in larger cohorts will be necessary.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"37"},"PeriodicalIF":3.8,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11112864/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141080914","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":"Aqueous humor proteomics analyzed by bioinformatics and machine learning in PDR cases versus controls.","authors":"Tan Wang, Huan Chen, Ningning Li, Bao Zhang, Hanyi Min","doi":"10.1186/s12014-024-09481-w","DOIUrl":"10.1186/s12014-024-09481-w","url":null,"abstract":"<p><strong>Background: </strong>To comprehend the complexities of pathophysiological mechanisms and molecular events that contribute to proliferative diabetic retinopathy (PDR) and evaluate the diagnostic value of aqueous humor (AH) in monitoring the onset of PDR.</p><p><strong>Methods: </strong>A cohort containing 16 PDR and 10 cataract patients and another validation cohort containing 8 PDR and 4 cataract patients were studied. AH was collected and subjected to proteomics analyses. Bioinformatics analysis and a machine learning-based pipeline called inference of biomolecular combinations with minimal bias were used to explore the functional relevance, hub proteins, and biomarkers.</p><p><strong>Results: </strong>Deep profiling of AH proteomes revealed several insights. First, the combination of SIAE, SEMA7A, GNS, and IGKV3D-15 and the combination of ATP6AP1, SPARCL1, and SERPINA7 could serve as surrogate protein biomarkers for monitoring PDR progression. Second, ALB, FN1, ACTB, SERPINA1, C3, and VTN acted as hub proteins in the profiling of AH proteomes. SERPINA1 was the protein with the highest correlation coefficient not only for BCVA but also for the duration of diabetes. Third, \"Complement and coagulation cascades\" was an important pathway for PDR development.</p><p><strong>Conclusions: </strong>AH proteomics provides stable and accurate biomarkers for early warning and diagnosis of PDR. This study provides a deep understanding of the molecular mechanisms of PDR and a rich resource for optimizing PDR management.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"36"},"PeriodicalIF":3.8,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11103871/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141064983","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":"Correlation between small-cell lung cancer serum protein/peptides determined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and chemotherapy efficacy.","authors":"Zhihua Li, Junnan Chen, Bin Xu, Wei Zhao, Haoran Zha, Yalin Han, Wennan Shen, Yuemei Dong, Nan Zhao, Manze Zhang, Kun He, Zhaoxia Li, Xiaoqing Liu","doi":"10.1186/s12014-024-09483-8","DOIUrl":"10.1186/s12014-024-09483-8","url":null,"abstract":"<p><strong>Background: </strong>Currently, no effective measures are available to predict the curative efficacy of small-cell lung cancer (SCLC) chemotherapy. We expect to develop a method for effectively predicting the SCLC chemotherapy efficacy and prognosis in clinical practice in order to offer more pertinent therapeutic protocols for individual patients.</p><p><strong>Methods: </strong>We adopted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinPro Tools system to detect serum samples from 154 SCLC patients with different curative efficacy of standard chemotherapy and analyze the different peptides/proteins of SCLC patients to discover predictive tumor markers related to chemotherapy efficacy. Ten peptide/protein peaks were significantly different in the two groups.</p><p><strong>Results: </strong>A genetic algorithm model consisting of four peptides/proteins was developed from the training group to separate patients with different chemotherapy efficacies. Among them, three peptides/proteins (m/z 3323.35, 6649.03 and 6451.08) showed high expression in the disease progression group, whereas the peptide/protein at m/z 4283.18 was highly expressed in the disease response group. The classifier exhibited an accuracy of 91.4% (53/58) in the validation group. The survival analysis showed that the median progression-free survival (PFS) of 30 SCLC patients in disease response group was 9.0 months; in 28 cases in disease progression group, the median PFS was 3.0 months, a statistically significant difference (χ² = 46.98, P < 0.001). The median overall survival (OS) of the two groups was 13.0 months and 7.0 months, a statistically significant difference (χ² = 40.64, P < 0.001).</p><p><strong>Conclusions: </strong>These peptides/proteins may be used as potential biological markers for prediction of the curative efficacy and prognosis for SCLC patients treated with standard regimen chemotherapy.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"35"},"PeriodicalIF":3.8,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11103996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141064988","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}