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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38925550 DOI: 10.1002/mas.21873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/05/2024] [Accepted: 02/12/2024] [Indexed: 06/28/2024]
Abstract
The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.
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2
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Kekki H, Montoya Perez I, Taimen P, Boström PJ, Gidwani K, Pettersson K. Lectin-nanoparticle concept for free PSA glycovariant providing superior cancer specificity. Clin Chim Acta 2024; 559:119689. [PMID: 38677453 DOI: 10.1016/j.cca.2024.119689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/19/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND Using lectins to target cancer-associated modifications of PSA glycostructure for identification of clinically significant prostate cancers, e.g., Gleason score (GS) ≥ 7, from benign and indolent cancers (GS 6), is highly promising yet technically challenging. From previous findings to quantify increased PSA fucosylation in urine, we set out to construct a robust, specific test concept suitable for plasma samples. METHODS Macrophage galactose-binding lectin (MGL) coupled to 100 nm Eu3 + -nanoparticles was used to probe PSA captured from cancer cell lines, seminal plasma, and plasma samples from 249 patients with a clinical suspicion of prostate cancer onto 3 mm dense spots of free PSA antibody fab fragments. Results were compared to four kallikrein tests: tPSA, fPSA, iPSA and hK2. RESULTS The fPSAMGLglycovariant provided superior discrimination of the GS ≥ 7 and benign + GS 6 groups (p 0.0003) compared to fPSA (NS). The corresponding AUC in ROC analysis was 0.70 compared to 0.66 for tPSA. In contrast to all four kallikrein tests, the fPSAMGLGV was independent of prostate gland volume. Using a logistic regression analysis the fPSAMGLGV significantly improved on the four-kallikrein model. CONCLUSIONS Due to Eu-nanoparticles and a dense fPSA capture spot, the fPSAMGL glycovariant identifies an fPSA subform with the highest cancer specificity compared to the four conventional kallikreins.
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Affiliation(s)
- H Kekki
- Biotechnology Unit, Department of Life Technologies, University of Turku, Finland.
| | - I Montoya Perez
- Department of Diagnostic Radiology, University of Turku, Turku, Finland; Department of Computing, University of Turku, Turku, Finland
| | - P Taimen
- Institute of Biomedicine, Department of Pathology, University of Turku, Turku University Hospital, Turku, Finland
| | - P J Boström
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - K Gidwani
- Biotechnology Unit, Department of Life Technologies, University of Turku, Finland
| | - K Pettersson
- Biotechnology Unit, Department of Life Technologies, University of Turku, Finland
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3
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Zhao YX, Zhao HP, Zhao MY, Yu Y, Qi X, Wang JH, Lv J. Latest insights into the global epidemiological features, screening, early diagnosis and prognosis prediction of esophageal squamous cell carcinoma. World J Gastroenterol 2024; 30:2638-2656. [PMID: 38855150 PMCID: PMC11154680 DOI: 10.3748/wjg.v30.i20.2638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 04/26/2024] [Accepted: 05/13/2024] [Indexed: 05/27/2024] Open
Abstract
As a highly invasive carcinoma, esophageal cancer (EC) was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in 2020. Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of EC, and its incidence and mortality rates are decreasing globally. Due to the lack of specific early symptoms, ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis, and the incidence and mortality rates are still high in many countries, especially in China. Therefore, enormous challenges still exist in the management of ESCC, and novel strategies are urgently needed to further decrease the incidence and mortality rates of ESCC. Although the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated, certain promising biomarkers are being investigated to facilitate clinical decision-making. With the advent and advancement of high-throughput technologies, such as genomics, proteomics and metabolomics, valuable biomarkers with high sensitivity, specificity and stability could be identified for ESCC. Herein, we aimed to determine the epidemiological features of ESCC in different regions of the world, especially in China, and focused on novel molecular biomarkers associated with ESCC screening, early diagnosis and prognosis prediction.
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Affiliation(s)
- Yi-Xin Zhao
- Department of Clinical Laboratory, Honghui Hospital, Xi’an Jiaotong University, Xi’an 710054, Shaanxi Province, China
| | - He-Ping Zhao
- Department of Clinical Laboratory, Honghui Hospital, Xi’an Jiaotong University, Xi’an 710054, Shaanxi Province, China
| | - Meng-Yao Zhao
- Department of Clinical Laboratory, Honghui Hospital, Xi’an Jiaotong University, Xi’an 710054, Shaanxi Province, China
| | - Yan Yu
- Department of Clinical Laboratory, Honghui Hospital, Xi’an Jiaotong University, Xi’an 710054, Shaanxi Province, China
| | - Xi Qi
- Department of Clinical Laboratory, Honghui Hospital, Xi’an Jiaotong University, Xi’an 710054, Shaanxi Province, China
| | - Ji-Han Wang
- Institute of Medical Research, Northwestern Polytechnical University, Xi’an 710072, Shaanxi Province, China
| | - Jing Lv
- Department of Clinical Laboratory, Honghui Hospital, Xi’an Jiaotong University, Xi’an 710054, Shaanxi Province, China
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Molnarova K, Krizek T, Kozlik P. The potential of polyaniline-coated stationary phase in hydrophilic interaction liquid chromatography-based solid-phase extraction for glycopeptide enrichment. J Chromatogr B Analyt Technol Biomed Life Sci 2024; 1237:124099. [PMID: 38547700 DOI: 10.1016/j.jchromb.2024.124099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/06/2024] [Accepted: 03/17/2024] [Indexed: 04/13/2024]
Abstract
Glycopeptide enrichment is a crucial step in glycoproteomic analysis, often achieved through solid-phase extraction (SPE) on polar stationary phases in hydrophilic interaction liquid chromatography (HILIC). This study explores the potential of polyaniline (PANI)-coated silica gel for enriching human immunoglobulin G (IgG). Experimental conditions were varied to assess their impact on glycopeptide enrichment efficiency, comparing PANI-cotton wool SPE with conventional cotton wool as SPE sorbents. Two formic acid concentrations (0.1% and 1%) in elution solvent were tested, revealing that higher concentrations led to earlier elution of studied glycopeptides, especially for sialylated glycopeptides. Substituting formic acid with acetic acid increased the interaction of neutral glycopeptides with the PANI-modified sorbent, while sialylated glycopeptides showed no significant change in enrichment efficiency. Acetonitrile concentration in the elution solvent (5%, 10%, and 20%) affected the enrichment efficiency with most glycopeptides eluting at the lowest acetonitrile concentration. The acetonitrile concentration in conditioning and washing solutions (65%, 75%, and 85%) played a crucial role; at 65% acetonitrile, glycopeptides were least retained on the stationary phase, and neutral glycopeptides were even detected in the flow-through fraction. This study shows the potential of in-house-prepared PANI-modified sorbents for SPE-HILIC glycopeptide enrichment, highlighting the crucial role of tuning experimental conditions in sample preparation to enhance enrichment efficiency and selectivity.
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Affiliation(s)
- Katarina Molnarova
- Department of Analytical Chemistry, Faculty of Science, Charles University, Prague, Czech Republic
| | - Tomas Krizek
- Department of Analytical Chemistry, Faculty of Science, Charles University, Prague, Czech Republic
| | - Petr Kozlik
- Department of Analytical Chemistry, Faculty of Science, Charles University, Prague, Czech Republic.
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Bashyal A, Brodbelt JS. Uncommon posttranslational modifications in proteomics: ADP-ribosylation, tyrosine nitration, and tyrosine sulfation. MASS SPECTROMETRY REVIEWS 2024; 43:289-326. [PMID: 36165040 PMCID: PMC10040477 DOI: 10.1002/mas.21811] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
Posttranslational modifications (PTMs) are covalent modifications of proteins that modulate the structure and functions of proteins and regulate biological processes. The development of various mass spectrometry-based proteomics workflows has facilitated the identification of hundreds of PTMs and aided the understanding of biological significance in a high throughput manner. Improvements in sample preparation and PTM enrichment techniques, instrumentation for liquid chromatography-tandem mass spectrometry (LC-MS/MS), and advanced data analysis tools enhance the specificity and sensitivity of PTM identification. Highly prevalent PTMs like phosphorylation, glycosylation, acetylation, ubiquitinylation, and methylation are extensively studied. However, the functions and impact of less abundant PTMs are not as well understood and underscore the need for analytical methods that aim to characterize these PTMs. This review focuses on the advancement and analytical challenges associated with the characterization of three less common but biologically relevant PTMs, specifically, adenosine diphosphate-ribosylation, tyrosine sulfation, and tyrosine nitration. The advantages and disadvantages of various enrichment, separation, and MS/MS techniques utilized to identify and localize these PTMs are described.
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Affiliation(s)
- Aarti Bashyal
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA
| | - Jennifer S Brodbelt
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA
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Bi B, Qiu M, Liu P, Wang Q, Wen Y, Li Y, Li B, Li Y, He Y, Zhao J. Protein post-translational modifications: A key factor in colorectal cancer resistance mechanisms. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2023; 1866:194977. [PMID: 37625568 DOI: 10.1016/j.bbagrm.2023.194977] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 07/16/2023] [Accepted: 08/16/2023] [Indexed: 08/27/2023]
Abstract
Colorectal cancer (CRC) is one of the leading causes of cancer-related death. Despite advances in treatment, drug resistance remains a critical impediment. Post-translational modifications (PTMs) regulate protein stability, localization, and activity, impacting vital cellular processes. Recent research has highlighted the essential role of PTMs in the development of CRC resistance. This review summarizes recent advancements in understanding PTMs' roles in CRC resistance, focusing on the latest discoveries. We discuss the functional impact of PTMs on signaling pathways and molecules involved in CRC resistance, progress in drug development, and potential therapeutic targets. We also summarize the primary enrichment methods for PTMs. Finally, we discuss current challenges and future directions, including the need for more comprehensive PTM analysis methods and PTM-targeted therapies. This review identifies potential therapeutic interventions for addressing medication resistance in CRC, proposes prospective therapeutic options, and gives an overview of the function of PTMs in CRC resistance.
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Affiliation(s)
- Bo Bi
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Miaojuan Qiu
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Peng Liu
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Qiang Wang
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Yingfei Wen
- Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - You Li
- Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Binbin Li
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Yongshu Li
- Hubei Normal University, College of Life Sciences Huangshi, Hubei, China.
| | - Yulong He
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China.
| | - Jing Zhao
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China; Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Shenzhen, Guangdong, China.
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Gabriele C, Aracri F, Prestagiacomo LE, Rota MA, Alba S, Tradigo G, Guzzi PH, Cuda G, Damiano R, Veltri P, Gaspari M. Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables. Clin Proteomics 2023; 20:52. [PMID: 37990292 PMCID: PMC10662699 DOI: 10.1186/s12014-023-09439-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/18/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Prostate Cancer (PCa) represents the second leading cause of cancer-related death in men. Prostate-specific antigen (PSA) serum testing, currently used for PCa screening, lacks the necessary sensitivity and specificity. New non-invasive diagnostic tools able to discriminate tumoral from benign conditions and aggressive (AG-PCa) from indolent forms of PCa (NAG-PCa) are required to avoid unnecessary biopsies. METHODS In this work, 32 formerly N-glycosylated peptides were quantified by PRM (parallel reaction monitoring) in 163 serum samples (79 from PCa patients and 84 from individuals affected by benign prostatic hyperplasia (BPH)) in two technical replicates. These potential biomarker candidates were prioritized through a multi-stage biomarker discovery pipeline articulated in: discovery, LC-PRM assay development and verification phases. Because of the well-established involvement of glycoproteins in cancer development and progression, the proteomic analysis was focused on glycoproteins enriched by TiO2 (titanium dioxide) strategy. RESULTS Machine learning algorithms have been applied to the combined matrix comprising proteomic and clinical variables, resulting in a predictive model based on six proteomic variables (RNASE1, LAMP2, LUM, MASP1, NCAM1, GPLD1) and five clinical variables (prostate dimension, proPSA, free-PSA, total-PSA, free/total-PSA) able to distinguish PCa from BPH with an area under the Receiver Operating Characteristic (ROC) curve of 0.93. This model outperformed PSA alone which, on the same sample set, was able to discriminate PCa from BPH with an AUC of 0.79. To improve the clinical managing of PCa patients, an explorative small-scale analysis (79 samples) aimed at distinguishing AG-PCa from NAG-PCa was conducted. A predictor of PCa aggressiveness based on the combination of 7 proteomic variables (FCN3, LGALS3BP, AZU1, C6, LAMB1, CHL1, POSTN) and proPSA was developed (AUC of 0.69). CONCLUSIONS To address the impelling need of more sensitive and specific serum diagnostic tests, a predictive model combining proteomic and clinical variables was developed. A preliminary evaluation to build a new tool able to discriminate aggressive presentations of PCa from tumors with benign behavior was exploited. This predictor displayed moderate performances, but no conclusions can be drawn due to the limited number of the sample cohort. Data are available via ProteomeXchange with identifier PXD035935.
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Affiliation(s)
- Caterina Gabriele
- Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy.
| | - Federica Aracri
- Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Licia Elvira Prestagiacomo
- Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | | | | | | | - Pietro Hiram Guzzi
- Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Giovanni Cuda
- Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Rocco Damiano
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Pierangelo Veltri
- Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, Italy
- Department of Computer Engineering, Modeling, Electronics and Systems, University of Calabria, 87036 Rende, Italy
| | - Marco Gaspari
- Research Centre for Advanced Biochemistry and Molecular Biology, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy.
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Prestagiacomo LE, Tradigo G, Aracri F, Gabriele C, Rota MA, Alba S, Cuda G, Damiano R, Veltri P, Gaspari M. Data-Independent Acquisition Mass Spectrometry of EPS-Urine Coupled to Machine Learning: A Predictive Model for Prostate Cancer. ACS OMEGA 2023; 8:6244-6252. [PMID: 36844540 PMCID: PMC9948177 DOI: 10.1021/acsomega.2c05487] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 12/06/2022] [Indexed: 06/18/2023]
Abstract
Prostate cancer (PCa) is annually the most frequently diagnosed cancer in the male population. To date, the diagnostic path for PCa detection includes the dosage of serum prostate-specific antigen (PSA) and the digital rectal exam (DRE). However, PSA-based screening has insufficient specificity and sensitivity; besides, it cannot discriminate between the aggressive and indolent types of PCa. For this reason, the improvement of new clinical approaches and the discovery of new biomarkers are necessary. In this work, expressed prostatic secretion (EPS)-urine samples from PCa patients and benign prostatic hyperplasia (BPH) patients were analyzed with the aim of detecting differentially expressed proteins between the two analyzed groups. To map the urinary proteome, EPS-urine samples were analyzed by data-independent acquisition (DIA), a high-sensitivity method particularly suitable for detecting proteins at low abundance. Overall, in our analysis, 2615 proteins were identified in 133 EPS-urine specimens obtaining the highest proteomic coverage for this type of sample; of these 2615 proteins, 1670 were consistently identified across the entire data set. The matrix containing the quantified proteins in each patient was integrated with clinical parameters such as the PSA level and gland size, and the complete matrix was analyzed by machine learning algorithms (by exploiting 90% of samples for training/testing using a 10-fold cross-validation approach, and 10% of samples for validation). The best predictive model was based on the following components: semaphorin-7A (sema7A), secreted protein acidic and rich in cysteine (SPARC), FT ratio, and prostate gland size. The classifier could predict disease conditions (BPH, PCa) correctly in 83% of samples in the validation set. Data are available via ProteomeXchange with the identifier PXD035942.
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Affiliation(s)
- Licia E. Prestagiacomo
- Research
Centre for Advanced Biochemistry and Molecular Biology, Department
of Experimental and Clinical Medicine, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | | | - Federica Aracri
- Department
of Surgical and Medical Sciences, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | - Caterina Gabriele
- Research
Centre for Advanced Biochemistry and Molecular Biology, Department
of Experimental and Clinical Medicine, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | | | | | - Giovanni Cuda
- Research
Centre for Advanced Biochemistry and Molecular Biology, Department
of Experimental and Clinical Medicine, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | - Rocco Damiano
- Department
of Experimental and Clinical Medicine, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | - Pierangelo Veltri
- Department
of Surgical and Medical Sciences, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
| | - Marco Gaspari
- Research
Centre for Advanced Biochemistry and Molecular Biology, Department
of Experimental and Clinical Medicine, Magna
Graecia University of Catanzaro, 88100 Catanzaro, Italy
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Doud EH, Yeh ES. Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery. Technol Cancer Res Treat 2023; 22:15330338221148811. [PMID: 36740994 PMCID: PMC9903044 DOI: 10.1177/15330338221148811] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.
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Affiliation(s)
- Emma H. Doud
- Center for Proteome Analysis, Indiana University School of Medicine, Indianapolis, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, USA
- IU Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, USA
| | - Elizabeth S. Yeh
- IU Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, USA
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Wang Y, Lih TSM, Höti N, Sokoll LJ, Chesnut G, Petrovics G, Kohaar I, Zhang H. Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer. Proteomics 2022; 23:e2200023. [PMID: 36479985 DOI: 10.1002/pmic.202200023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 11/26/2022] [Accepted: 11/28/2022] [Indexed: 12/13/2022]
Abstract
Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.
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Affiliation(s)
- Yuefan Wang
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Naseruddin Höti
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lori J Sokoll
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Gregory Chesnut
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.,Urology Service, Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Gyorgy Petrovics
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.,Henry Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, Maryland, USA
| | - Indu Kohaar
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.,Henry Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, Maryland, USA
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA
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Brodbelt JS. Deciphering combinatorial post-translational modifications by top-down mass spectrometry. Curr Opin Chem Biol 2022; 70:102180. [PMID: 35779351 PMCID: PMC9489649 DOI: 10.1016/j.cbpa.2022.102180] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 12/15/2022]
Abstract
Post-translational modifications (PTMs) create vast structural and functional diversity of proteins, ultimately modulating protein function and degradation, influencing cellular signaling, and regulating transcription. The combinatorial patterns of PTMs increase the heterogeneity of proteins and further mediates their interactions. Advances in mass spectrometry-based proteomics have resulted in identification of thousands of proteins and allowed characterization of numerous types and sites of PTMs. Examination of intact proteins, termed the top-down approach, offers the potential to map protein sequences and localize multiple PTMs on each protein, providing the most comprehensive cataloging of proteoforms. This review describes some of the dividends of using mass spectrometry to analyze intact proteins and showcases innovative strategies that have enhanced the promise of top-down proteomics for exploring the impact of combinatorial PTMs in unsurpassed detail.
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Affiliation(s)
- Jennifer S Brodbelt
- Department of Chemistry, University of Texas at Austin, Austin, TX 78712, USA.
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12
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Zhu G, Jin L, Sun W, Wang S, Liu N. Proteomics of post-translational modifications in colorectal cancer: Discovery of new biomarkers. Biochim Biophys Acta Rev Cancer 2022; 1877:188735. [PMID: 35577141 DOI: 10.1016/j.bbcan.2022.188735] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 05/08/2022] [Accepted: 05/09/2022] [Indexed: 02/07/2023]
Abstract
Colorectal cancer (CRC) is one of the costliest health problems and ranks second in cancer-related mortality in developed countries. With the aid of proteomics, many protein biomarkers for the diagnosis, prognosis, and precise management of CRC have been identified. Furthermore, some protein biomarkers exhibit structural diversity after modifications. Post-translational modifications (PTMs), most of which are catalyzed by a variety of enzymes, extensively increase protein diversity and are involved in many complex and dynamic cellular processes through the regulation of protein function. Accumulating evidence suggests that abnormal PTM events are associated with a variety of human diseases, such as CRC, thus highlighting the need for studying PTMs to discover both the molecular mechanisms and therapeutic targets of CRC. In this review, we begin with a brief overview of the importance of protein PTMs, discuss the general strategies for proteomic profiling of several key PTMs (including phosphorylation, acetylation, glycosylation, ubiquitination, methylation, and citrullination), shift the emphasis to describing the specific methods used for delineating the global landscapes of each of these PTMs, and summarize the recent applications of these methods to explore the potential roles of the PTMs in CRC. Finally, we discuss the current status of PTM research on CRC and provide future perspectives on how PTM regulation can play an essential role in translational medicine for early diagnosis, prognosis stratification, and therapeutic intervention in CRC.
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Affiliation(s)
- Gengjun Zhu
- Department Oncology and Hematology, The Second Hospital of Jilin University, Changchun, China
| | - Lifang Jin
- Department Oncology and Hematology, The Second Hospital of Jilin University, Changchun, China
| | - Wanchun Sun
- Key Laboratory of Zoonosis Research, Ministry of Education, Jilin University, Changchun, China
| | - Shuang Wang
- Dermatological department, The Second Hospital of Jilin University, Changchun, China.
| | - Ning Liu
- Key Laboratory of Zoonosis Research, Ministry of Education, Jilin University, Changchun, China; Central Laboratory, The Second Hospital of Jilin University, Changchun, China.
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13
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Fang P, Ji Y, Oellerich T, Urlaub H, Pan KT. Strategies for Proteome-Wide Quantification of Glycosylation Macro- and Micro-Heterogeneity. Int J Mol Sci 2022; 23:ijms23031609. [PMID: 35163546 PMCID: PMC8835892 DOI: 10.3390/ijms23031609] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/26/2022] [Accepted: 01/27/2022] [Indexed: 12/03/2022] Open
Abstract
Protein glycosylation governs key physiological and pathological processes in human cells. Aberrant glycosylation is thus closely associated with disease progression. Mass spectrometry (MS)-based glycoproteomics has emerged as an indispensable tool for investigating glycosylation changes in biological samples with high sensitivity. Following rapid improvements in methodologies for reliable intact glycopeptide identification, site-specific quantification of glycopeptide macro- and micro-heterogeneity at the proteome scale has become an urgent need for exploring glycosylation regulations. Here, we summarize recent advances in N- and O-linked glycoproteomic quantification strategies and discuss their limitations. We further describe a strategy to propagate MS data for multilayered glycopeptide quantification, enabling a more comprehensive examination of global and site-specific glycosylation changes. Altogether, we show how quantitative glycoproteomics methods explore glycosylation regulation in human diseases and promote the discovery of biomarkers and therapeutic targets.
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Affiliation(s)
- Pan Fang
- Department of Biochemistry and Molecular Biology, School of Biology & Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou 215123, China;
| | - Yanlong Ji
- Bioanalytical Mass Spectrometry Group, Max Planck Institute for Multidisciplinary Sciences, 37077 Göttingen, Germany;
- Hematology/Oncology, Department of Medicine II, Johann Wolfgang Goethe University, 60590 Frankfurt am Main, Germany;
- Frankfurt Cancer Institute, Johann Wolfgang Goethe University, 60596 Frankfurt am Main, Germany
| | - Thomas Oellerich
- Hematology/Oncology, Department of Medicine II, Johann Wolfgang Goethe University, 60590 Frankfurt am Main, Germany;
- Frankfurt Cancer Institute, Johann Wolfgang Goethe University, 60596 Frankfurt am Main, Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Henning Urlaub
- Bioanalytical Mass Spectrometry Group, Max Planck Institute for Multidisciplinary Sciences, 37077 Göttingen, Germany;
- Institute of Clinical Chemistry, University Medical Center Göttingen, 37075 Göttingen, Germany
- Correspondence: (H.U.); (K.-T.P.)
| | - Kuan-Ting Pan
- Hematology/Oncology, Department of Medicine II, Johann Wolfgang Goethe University, 60590 Frankfurt am Main, Germany;
- Frankfurt Cancer Institute, Johann Wolfgang Goethe University, 60596 Frankfurt am Main, Germany
- Correspondence: (H.U.); (K.-T.P.)
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14
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Glycosylation: Rising Potential for Prostate Cancer Evaluation. Cancers (Basel) 2021; 13:cancers13153726. [PMID: 34359624 PMCID: PMC8345048 DOI: 10.3390/cancers13153726] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 07/21/2021] [Accepted: 07/21/2021] [Indexed: 12/15/2022] Open
Abstract
Simple Summary Aberrant protein glycosylation is a well-known hallmark of cancer and is associated with differential expression of enzymes such as glycosyltransferases and glycosidases. The altered expression of the enzymes triggers cancer cells to produce glycoproteins with specific cancer-related aberrations in glycan structures. Increasing number of data indicate that glycosylation patterns of PSA and other prostate-originated proteins exert a potential to distinguish between benign prostate disease and cancer as well as among different stages of prostate cancer development and aggressiveness. This review summarizes the alterations in glycan sialylation, fucosylation, truncated O-glycans, and LacdiNAc groups outlining their potential applications in non-invasive diagnostic procedures of prostate diseases. Further research is desired to develop more general algorithms exploiting glycobiology data for the improvement of prostate diseases evaluation. Abstract Prostate cancer is the second most commonly diagnosed cancer among men. Alterations in protein glycosylation are confirmed to be a reliable hallmark of cancer. Prostate-specific antigen is the biomarker that is used most frequently for prostate cancer detection, although its lack of sensitivity and specificity results in many unnecessary biopsies. A wide range of glycosylation alterations in prostate cancer cells, including increased sialylation and fucosylation, can modify protein function and play a crucial role in many important biological processes in cancer, including cell signalling, adhesion, migration, and cellular metabolism. In this review, we summarize studies evaluating the prostate cancer associated glycosylation related alterations in sialylation, mainly α2,3-sialylation, core fucosylation, branched N-glycans, LacdiNAc group and presence of truncated O-glycans (sTn, sT antigen). Finally, we discuss the great potential to make use of glycans as diagnostic and prognostic biomarkers for prostate cancer.
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