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Hu H, Leung WK. Mass Spectrometry-Based Proteomics for Discovering Salivary Biomarkers in Periodontitis: A Systematic Review. Int J Mol Sci 2023; 24:14599. [PMID: 37834046 PMCID: PMC10572407 DOI: 10.3390/ijms241914599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 10/15/2023] Open
Abstract
Periodontitis is one of the primary causes of tooth loss, and is also related to various systemic diseases. Early detection of this condition is crucial when it comes to preventing further oral damage and the associated health complications. This study offers a systematic review of the literature published up to April 2023, and aims to clearly explain the role of proteomics in identifying salivary biomarkers for periodontitis. Comprehensive searches were conducted on PubMed and Web of Science to shortlist pertinent studies. The inclusion criterion was those that reported on mass spectrometry-driven proteomic analyses of saliva samples from periodontitis cohorts, while those on gingivitis or other oral diseases were excluded. An assessment for risk of bias was carried out using the Newcastle-Ottawa Scale and Quality Assessment of Diagnostic Accuracy Studies or the NIH quality assessment tool, and a meta-analysis was performed for replicable candidate biomarkers, i.e., consistently reported candidate biomarkers (in specific saliva samples, and periodontitis subgroups, reported in ≥2 independent cohorts/reports) were identified. A Gene Ontology enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resources, which consistently expressed candidate biomarkers, to explore the predominant pathway wherein salivary biomarkers consistently manifested. Of the 15 studies included, 13 were case-control studies targeting diagnostic biomarkers for periodontitis participants (periodontally healthy/diseased, n = 342/432), while two focused on biomarkers responsive to periodontal treatment (n = 26 participants). The case-control studies were considered to have a low risk of bias, while the periodontitis treatment studies were deemed fair. Summary estimate and confidence/credible interval, etc. determination for the identified putative salivary biomarkers could not be ascertained due to the low number of studies in each case. The results from the included case-control studies identified nine consistently expressed candidate biomarkers (from nine studies with 230/297 periodontally healthy/diseased participants): (i) those that were upregulated: alpha-amylase, serum albumin, complement C3, neutrophil defensin, profilin-1, and S100-P; and (ii) those that were downregulated: carbonic anhydrase 6, immunoglobulin J chain, and lactoferrin. All putative biomarkers exhibited consistent regulation patterns. The implications of the current putative marker proteins identified were reviewed, with a focus on their potential roles in periodontitis diagnosis and pathogenesis, and as putative therapeutic targets. Although in its early stages, mass spectrometry-based salivary periodontal disease biomarker proteomics detection appeared promising. More mass spectrometry-based proteomics studies, with or without the aid of already available clinical biochemical approaches, are warranted to aid the discovery, identification, and validation of periodontal health/disease indicator molecule(s). Protocol registration number: CRD42023447722; supported by RD-02-202410 and GRF17119917.
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Affiliation(s)
- Hongying Hu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Oral Medical Imaging, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China;
| | - Wai Keung Leung
- Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China
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Chiou SH, Huang CH, Liang SS. From Chemistry to Translational Medicine: The Application of Proteomics to Cancer Biomarker Discovery and Diagnosis. J CHIN CHEM SOC-TAIP 2015. [DOI: 10.1002/jccs.201400350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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Farina A, Delhaye M, Lescuyer P, Dumonceau JM. Bile proteome in health and disease. Compr Physiol 2014; 4:91-108. [PMID: 24692135 DOI: 10.1002/cphy.c130016] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The study of bile proteins could improve the understanding of physiological processes involved in the regulation of the hepato-biliary system. Researchers have tried for years to investigate the bile proteome but, until recently, only a few tens of proteins were known. The advent of proteomics, availing of large-scale analytical devices paired with potent bioinformatic resources, lately allowed the identification of thousands of proteins in bile. Nevertheless, the knowledge of their role in the hepato-biliary system still represents almost a "blank page in the book of physiology." In this review, we first guide the reader through the historical phases of the analysis of bile protein content, emphasizing the recent progresses achieved through the use of proteomic techniques. Thereafter, we deeply explore the involvement of bile proteins in health and disease, with a particular focus on the discovery of biomarkers for biliary tract malignancies.
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Affiliation(s)
- Annarita Farina
- Biomedical Proteomics Research Group, Department of Human Protein Sciences, Geneva University, Geneva, Switzerland
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Mesri M. Advances in Proteomic Technologies and Its Contribution to the Field of Cancer. Adv Med 2014; 2014:238045. [PMID: 26556407 PMCID: PMC4590950 DOI: 10.1155/2014/238045] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2014] [Accepted: 06/30/2014] [Indexed: 12/12/2022] Open
Abstract
Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.
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Affiliation(s)
- Mehdi Mesri
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA
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Acosta-Martin AE, Lane L. Combining bioinformatics and MS-based proteomics: clinical implications. Expert Rev Proteomics 2014; 11:269-84. [PMID: 24720436 DOI: 10.1586/14789450.2014.900446] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.
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Acosta-Martin AE, Coelho Graça D, Antinori P, Clerici L, Hartmer R, Meyer M, Hochstrasser D, Samii K, Lescuyer P, Scherl A. Quantitative Mass Spectrometry Analysis of Intact Hemoglobin A2 by Precursor Ion Isolation and Detection. Anal Chem 2013; 85:7971-5. [DOI: 10.1021/ac401782t] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Adelina E. Acosta-Martin
- Department of Human Protein
Sciences, Faculty of Medicine, Geneva University, Geneva, Switzerland
- Department of Genetic and Laboratory
Medicine, Geneva University Hospitals,
Geneva, Switzerland
| | - Didia Coelho Graça
- Department of Human Protein
Sciences, Faculty of Medicine, Geneva University, Geneva, Switzerland
| | - Paola Antinori
- Department of Human Protein
Sciences, Faculty of Medicine, Geneva University, Geneva, Switzerland
| | - Lorella Clerici
- Department of Genetic and Laboratory
Medicine, Geneva University Hospitals,
Geneva, Switzerland
| | | | | | - Denis Hochstrasser
- Department of Human Protein
Sciences, Faculty of Medicine, Geneva University, Geneva, Switzerland
- Department of Genetic and Laboratory
Medicine, Geneva University Hospitals,
Geneva, Switzerland
| | - Kaveh Samii
- Division of Hematology, Geneva University Hospital, Geneva, Switzerland
| | - Pierre Lescuyer
- Department of Human Protein
Sciences, Faculty of Medicine, Geneva University, Geneva, Switzerland
- Department of Genetic and Laboratory
Medicine, Geneva University Hospitals,
Geneva, Switzerland
| | - Alexander Scherl
- Department of Human Protein
Sciences, Faculty of Medicine, Geneva University, Geneva, Switzerland
- Department of Genetic and Laboratory
Medicine, Geneva University Hospitals,
Geneva, Switzerland
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Coelho Graça D, Lescuyer P, Clerici L, Tsybin YO, Hartmer R, Meyer M, Samii K, Hochstrasser DF, Scherl A. Electron transfer dissociation mass spectrometry of hemoglobin on clinical samples. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2012; 23:1750-1756. [PMID: 22869297 DOI: 10.1007/s13361-012-0446-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2012] [Revised: 07/06/2012] [Accepted: 07/06/2012] [Indexed: 06/01/2023]
Abstract
A mass spectrometry-based assay combining the specificity of selected reaction monitoring and the protein ion activation capabilities of electron transfer dissociation was developed and employed for the rapid identification of hemoglobin variants from whole blood without previous proteolytic cleavage. The analysis was performed in a robust ion trap mass spectrometer operating at nominal mass accuracy and resolution. Subtle differences in globin sequences, resulting with mass shifts of about one Da, can be unambiguously identified. These results suggest that mass spectrometry analysis of entire proteins using electron transfer dissociation can be employed on clinical samples in a workflow compatible with diagnostic applications.
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Affiliation(s)
- Didia Coelho Graça
- Biomedical Proteomics Research Group, Department of Human Protein Science, Faculty of Medicine, Geneva University, Switzerland
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Chiou SH, Wu CY. Clinical proteomics: current status, challenges, and future perspectives. Kaohsiung J Med Sci 2011; 27:1-14. [PMID: 21329886 DOI: 10.1016/j.kjms.2010.12.001] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2010] [Accepted: 09/06/2010] [Indexed: 12/20/2022] Open
Abstract
This account will give an overview and evaluation of the current advances in mass spectrometry (MS)-based proteomics platforms and technology. A general review of some background information concerning the application of these methods in the characterization of molecular sizes and related protein expression profiles associated with different types of cells under varied experimental conditions will be presented. It is intended to provide a concise and succinct overview to those clinical researchers first exposed to this foremost powerful methodology in modern life sciences of postgenomic era. Proteomic characterization using highly sophisticated and expensive instrumentation of MS has been used to characterize biological samples of complex protein mixtures with vastly different protein structure and composition. These systems are then used to highlight the versatility and potential of the MS-based proteomic strategies for facilitating protein expression analysis of various disease-related organisms or tissues of interest. Major MS-based strategies reviewed herein include (1) matrix-assisted laser desorption ionization-MS and electron-spray ionization proteomics; (2) one-dimensional or two-dimensional gel-based proteomics; (3) gel-free shotgun proteomics in conjunction with liquid chromatography/tandem MS; (4) Multiple reaction monitoring coupled tandem MS quantitative proteomics and; (5) Phosphoproteomics based on immobilized metal affinity chromatography and liquid chromatography-MS/MS.
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Affiliation(s)
- Shyh-Horng Chiou
- Graduate Institute of Medicine and Center for Research Resources and Development, Kaohsiung Medical University, Kaohsiung, Taiwan.
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Rahbar A, Rivers R, Boja E, Kinsinger C, Mesri M, Hiltke T, Rodriguez H. Realizing individualized medicine: the road to translating proteomics from the laboratory to the clinic. Per Med 2011; 8:45-57. [DOI: 10.2217/pme.10.76] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
The sequencing of the human genome has brought great promise and potential for the future of medicine, as well as providing a strong momentum for the burgeoning field of individualized medicine. Tests based on genetic information can be used to allow physicians to target therapies for those patients most likely to benefit from specific therapies and identify potential risk before the onset of disease. While advances in genomics-based molecular diagnostics are progressing, producing some useful US FDA-approved/-cleared diagnostic tests, protein-based molecular diagnostics have not met its promised potential. This article will provide an overview of protein-based analysis technologies, identify their strengths and limitations, discuss barriers to protein-based biomarker development and identify issues which must be addressed in order to successfully transfer the field of proteomics from the laboratory to the clinic.
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Affiliation(s)
- Amir Rahbar
- Office of Cancer Clinical Proteomics Research, Center for Strategic Scientific Initiatives, National Cancer Institute, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, USA
| | - Robert Rivers
- Office of Cancer Clinical Proteomics Research, Center for Strategic Scientific Initiatives, National Cancer Institute, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, USA
| | - Emily Boja
- Office of Cancer Clinical Proteomics Research, Center for Strategic Scientific Initiatives, National Cancer Institute, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, USA
| | - Christopher Kinsinger
- Office of Cancer Clinical Proteomics Research, Center for Strategic Scientific Initiatives, National Cancer Institute, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, USA
| | - Mehdi Mesri
- Office of Cancer Clinical Proteomics Research, Center for Strategic Scientific Initiatives, National Cancer Institute, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, USA
| | - Tara Hiltke
- Office of Cancer Clinical Proteomics Research, Center for Strategic Scientific Initiatives, National Cancer Institute, National Institutes of Health, 31 Center Drive, Bethesda, MD 20892, USA
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Arnott D, Emmert-Buck MR. Proteomic profiling of cancer--opportunities, challenges, and context. J Pathol 2010; 222:16-20. [PMID: 20623483 DOI: 10.1002/path.2750] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
The article by Roesch-Ely and colleagues in a recent issue of The Journal of Pathology describes the use of proteomic techniques to examine mucosal biopsies in patients with head and neck squamous cell cancer (HNSCC) and in corresponding control samples. The authors were able to determine the anatomical site of origin of the biopsies based on modelling of multiplex protein datasets, and to use the information to analyse field cancerization as a means of predicting tumour recurrence. Although the study included only a relatively small number of cases, and will require future validation in a larger patient cohort, the results point to the potential of proteomics to increase our understanding of cancer biology, and in this instance to offer clinical value.
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Affiliation(s)
- David Arnott
- Protein Chemistry Department, Genentech, Inc, South San Francisco, CA 94080, USA.
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