Expert Review of Proteomics最新文献

Protein biomarkers for subtyping breast cancer and implications for future research: a 2024 update. 用于乳腺癌亚型鉴定的蛋白质生物标志物及其对未来研究的影响：2024 年更新。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-11-03 DOI: 10.1080/14789450.2024.2423625

Claudius Mueller, Justin B Davis, Virginia Espina

{"title":"Protein biomarkers for subtyping breast cancer and implications for future research: a 2024 update.","authors":"Claudius Mueller, Justin B Davis, Virginia Espina","doi":"10.1080/14789450.2024.2423625","DOIUrl":"10.1080/14789450.2024.2423625","url":null,"abstract":"Introduction: Breast cancer subtyping is used clinically for diagnosis, prognosis, and treatment decisions. Subtypes are categorized by cell of origin, histomorphology, gene expression signatures, hormone receptor status, and/or protein levels. Categorizing breast cancer based on gene expression signatures aids in assessing a patient's recurrence risk. Protein biomarkers, on the other hand, provide functional data for selecting therapies for primary and recurrent tumors. We provide an update on protein biomarkers in breast cancer subtypes and their application in prognosis and therapy selection.Areas covered: Protein pathways in breast cancer subtypes are reviewed in the context of current protein-targeted treatment options. PubMed, Science Direct, Scopus, and Cochrane Library were searched for relevant studies between 2017 and 17 August 2024.Expert opinion: Post-translationally modified proteins and their unmodified counterparts have become clinically useful biomarkers for defining breast cancer subtypes from a therapy perspective. Tissue heterogeneity influences treatment outcomes and disease recurrence. Spatial profiling has revealed complex cellular subpopulations within the breast tumor microenvironment. Deciphering the functional relationships between and within tumor clonal cell populations will further aid in defining breast cancer subtypes and create new treatment paradigms for recurrent, drug resistant, and metastatic disease.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of glycopeptide enrichment techniques for the identification of clinical biomarkers. 优化糖肽富集技术以鉴定临床生物标记物。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-31 DOI: 10.1080/14789450.2024.2418491

Sherifdeen Onigbinde, Cristian D Gutierrez Reyes, Vishal Sandilya, Favour Chukwubueze, Odunayo Oluokun, Sarah Sahioun, Ayobami Oluokun, Yehia Mechref

{"title":"Optimization of glycopeptide enrichment techniques for the identification of clinical biomarkers.","authors":"Sherifdeen Onigbinde, Cristian D Gutierrez Reyes, Vishal Sandilya, Favour Chukwubueze, Odunayo Oluokun, Sarah Sahioun, Ayobami Oluokun, Yehia Mechref","doi":"10.1080/14789450.2024.2418491","DOIUrl":"10.1080/14789450.2024.2418491","url":null,"abstract":"Introduction: The identification and characterization of glycopeptides through LC-MS/MS and advanced enrichment techniques are crucial for advancing clinical glycoproteomics, significantly impacting the discovery of disease biomarkers and therapeutic targets. Despite progress in enrichment methods like Lectin Affinity Chromatography (LAC), Hydrophilic Interaction Liquid Chromatography (HILIC), and Electrostatic Repulsion Hydrophilic Interaction Chromatography (ERLIC), issues with specificity, efficiency, and scalability remain, impeding thorough analysis of complex glycosylation patterns crucial for disease understanding.Areas covered: This review explores the current challenges and innovative solutions in glycopeptide enrichment and mass spectrometry analysis, highlighting the importance of novel materials and computational advances for improving sensitivity and specificity. It outlines the potential future directions of these technologies in clinical glycoproteomics, emphasizing their transformative impact on medical diagnostics and therapeutic strategies.Expert opinion: The application of innovative materials such as Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), functional nanomaterials, and online enrichment shows promise in addressing challenges associated with glycoproteomics analysis by providing more selective and robust enrichment platforms. Moreover, the integration of artificial intelligence and machine learning is revolutionizing glycoproteomics by enhancing the processing and interpretation of extensive data from LC-MS/MS, boosting biomarker discovery, and improving predictive accuracy, thus supporting personalized medicine.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Eleven shades of PASEF. 十一种颜色的 PASEF。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-24 DOI: 10.1080/14789450.2024.2413092

Marta L Mendes, Klara F Borrmann, Gunnar Dittmar

引用次数: 0

Glycosylation in cancer as a source of biomarkers. 癌症中的糖基化是生物标记物的来源。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-24 DOI: 10.1080/14789450.2024.2409224

Sara Khorami-Sarvestani, Samir M Hanash, Johannes F Fahrmann, Ricardo A León-Letelier, Hiroyuki Katayama

{"title":"Glycosylation in cancer as a source of biomarkers.","authors":"Sara Khorami-Sarvestani, Samir M Hanash, Johannes F Fahrmann, Ricardo A León-Letelier, Hiroyuki Katayama","doi":"10.1080/14789450.2024.2409224","DOIUrl":"10.1080/14789450.2024.2409224","url":null,"abstract":"Introduction: Glycosylation, the process of glycan synthesis and attachment to target molecules, is a crucial and common post-translational modification (PTM) in mammalian cells. It affects the protein's hydrophilicity, charge, solubility, structure, localization, function, and protection from proteolysis. Aberrant glycosylation in proteins can reveal new detection and therapeutic Glyco-biomarkers, which help to improve accurate early diagnosis and personalized treatment. This review underscores the pivotal role of glycans and glycoproteins as a source of biomarkers in human diseases, particularly cancer.Areas covered: This review delves into the implications of glycosylation, shedding light on its intricate roles in cancer-related cellular processes influencing biomarkers. It is underpinned by a thorough examination of literature up to June 2024 in PubMed, Scopus, and Google Scholar; concentrating on the terms: (Glycosylation[Title/Abstract]) OR (Glycan[Title/Abstract]) OR (glycoproteomics[Title/Abstract]) OR (Proteoglycans[Title/Abstract]) OR (Glycomarkers[Title/Abstract]) AND (Cancer[Title/Abstract]) AND ((Diagno*[Title/Abstract]) OR (Progno*[Title/Abstract])).Expert opinion: Glyco-biomarkers enhance early cancer detection, allow early intervention, and improve patient prognoses. However, the abundance and complex dynamic glycan structure may make their scientific and clinical application difficult. This exploration of glycosylation signatures in cancer biomarkers can provide a detailed view of cancer etiology and instill hope in the potential of glycosylation to revolutionize cancer research.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142394827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding metabolic resistance strategy of clinically isolated antibiotic-resistant bacteria by proteomic approach. 通过蛋白质组学方法了解临床分离的抗生素耐药细菌的代谢耐药策略。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-14 DOI: 10.1080/14789450.2024.2413439

Bo Peng, Hui Li, Xuanxian Peng

引用次数: 0

Digitalomics - digital transformation leading to omics insights. 数字组学--数字转型带来全息洞察。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-11 DOI: 10.1080/14789450.2024.2413107

Nandha Kumar Balasubramaniam, Scott Penberthy, David Fenyo, Nina Viessmann, Christoph Russmann, Christoph H Borchers

{"title":"Digitalomics - digital transformation leading to omics insights.","authors":"Nandha Kumar Balasubramaniam, Scott Penberthy, David Fenyo, Nina Viessmann, Christoph Russmann, Christoph H Borchers","doi":"10.1080/14789450.2024.2413107","DOIUrl":"10.1080/14789450.2024.2413107","url":null,"abstract":"Introduction: Biomarker discovery is increasingly moving from single omics to multiomics, as well as from multi-cell omics to single-cell omics. These transitions have increasingly adopted digital transformation technologies to accelerate the progression from data to insight. Here, we will discuss the concept of 'digitalomics' and how digital transformation directly impacts biomarker discovery. This will ultimately assist clinicians in personalized therapy and precision-medicine treatment decisions.Areas covered: Genotype-to-phenotype-based insight generation involves integrating large amounts of complex multiomic data. This data integration and analysis is aided through digital transformation, leading to better clinical outcomes. We also highlight the challenges and opportunities of Digitalomics, and provide examples of the application of Artificial Intelligence, cloud- and high-performance computing, and use of tensors for multiomic analysis workflows.Expert opinion: Biomarker discovery, aided by digital transformation, is having a significant impact on cancer, cardiovascular, infectious, immunological, and neurological diseases, among others. Data insights garnered from multiomic analyses, combined with patient meta data, aids patient stratification and targeted treatment across a broad spectrum of diseases. Digital transformation offers time and cost savings while leading to improved patent healthcare. Here, we highlight the impact of digital transformation on multiomics- based biomarker discovery with specific applications related to oncology.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Formation of the Canadian Artificial Intelligence and Mass Spectrometry for systems biology (CAN-AIMS) consortium. 成立加拿大人工智能和质谱系统生物学联合会（CAN-AIMS）。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-09 DOI: 10.1080/14789450.2024.2413441

Jennifer Geddes-McAlister, Arnaud Droit

引用次数: 0

Validating proteomic biomarkers in saliva: distinguishing between health and periodontal diseases. 验证唾液中的蛋白质组生物标记物：区分健康与牙周疾病。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-10-09 DOI: 10.1080/14789450.2024.2413099

Büşra Yılmaz, Gülnur Emingil

{"title":"Validating proteomic biomarkers in saliva: distinguishing between health and periodontal diseases.","authors":"Büşra Yılmaz, Gülnur Emingil","doi":"10.1080/14789450.2024.2413099","DOIUrl":"https://doi.org/10.1080/14789450.2024.2413099","url":null,"abstract":"Introduction: Periodontitis is a chronic inflammatory disease characterized by progressive soft tissue and alveolar bone loss due to interactions between microbial dental plaque and the host response. Despite extensive research on biomarkers from saliva or gingival crevicular fluid (GCF) for diagnosing periodontitis, clinical and radiological parameters remain the primary diagnostic tools.Areas covered: This review discusses the ongoing research into salivary biomarkers for periodontitis diagnosis, emphasizing the need for reliable biomarkers to differentiate between periodontal health and disease. Salivary biomarker research has gained momentum with advancements in proteomic technologies, enabling noninvasive sample collection and revealing potential candidate biomarkers.Expert opinion: Proteomic research since the early 2000s has identified promising biomarkers and provided insights into the pathogenesis of periodontitis. Bioinformatic analysis of proteomic data elucidates underlying biological mechanisms. This review summarizes key findings and highlights common potential biomarkers identified through proteomic research in periodontology.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142394829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cellular thermal shift assay: an approach to identify and assess protein target engagement. 细胞热转移试验：一种识别和评估蛋白质目标参与的方法。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-09-29 DOI: 10.1080/14789450.2024.2406785

Liying Zhang, Yuchuan Wang, Chang Zheng, Zihan Zhou, Zhe Chen

{"title":"Cellular thermal shift assay: an approach to identify and assess protein target engagement.","authors":"Liying Zhang, Yuchuan Wang, Chang Zheng, Zihan Zhou, Zhe Chen","doi":"10.1080/14789450.2024.2406785","DOIUrl":"https://doi.org/10.1080/14789450.2024.2406785","url":null,"abstract":"Introduction: A comprehensive and global knowledge of protein target engagement is of vital importance for mechanistic studies and in drug development. Since its initial introduction, the cellular thermal shift assay (CETSA) has proven to be a reliable and flexible technique that can be widely applied to multiple contexts and has profound applications in facilitating the identification and assessment of protein target engagement.Areas covered: This review introduces the principle of CETSA, elaborates on western blot-based CETSA and MS-based thermal proteome profiling (TPP) as well as the major applications and prospects of these approaches.Expert opinion: CETSA primarily evaluates a given ligand binding to a particular target protein in cells and tissues with the protein thermal stabilities analyzed by western blot. When coupling mass spectrometry with CETSA, thermal proteome profiling allows simultaneous proteome-wide experiment that greatly increased the efficiency of target engagement evaluation, and serves as a promising strategy to identify protein targets and off-targets as well as protein-protein interactions to uncover the biological effects. The CETSA approaches have broad applications and potentials in drug development and clinical research.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142331641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-independent acquisition in metaproteomics. 元蛋白质组学中与数据无关的采集。

IF 3.8 3区生物学

Expert Review of Proteomics Pub Date : 2024-07-01 Epub Date: 2024-08-21 DOI: 10.1080/14789450.2024.2394190

Enhui Wu, Guanyang Xu, Dong Xie, Liang Qiao

{"title":"Data-independent acquisition in metaproteomics.","authors":"Enhui Wu, Guanyang Xu, Dong Xie, Liang Qiao","doi":"10.1080/14789450.2024.2394190","DOIUrl":"10.1080/14789450.2024.2394190","url":null,"abstract":"Introduction: Metaproteomics offers insights into the function of complex microbial communities, while it is also capable of revealing microbe-microbe and host-microbe interactions. Data-independent acquisition (DIA) mass spectrometry is an emerging technology, which holds great potential to achieve deep and accurate metaproteomics with higher reproducibility yet still facing a series of challenges due to the inherent complexity of metaproteomics and DIA data.Areas covered: This review offers an overview of the DIA metaproteomics approaches, covering aspects such as database construction, search strategy, and data analysis tools. Several cases of current DIA metaproteomics studies are presented to illustrate the procedures. Important ongoing challenges are also highlighted. Future perspectives of DIA methods for metaproteomics analysis are further discussed. Cited references are searched through and collected from Google Scholar and PubMed.Expert opinion: Considering the inherent complexity of DIA metaproteomics data, data analysis strategies specifically designed for interpretation are imperative. From this point of view, we anticipate that deep learning methods and de novo sequencing methods will become more prevalent in the future, potentially improving protein coverage in metaproteomics. Moreover, the advancement of metaproteomics also depends on the development of sample preparation methods, data analysis strategies, etc. These factors are key to unlocking the full potential of metaproteomics.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141996860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0