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Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review.

ABSTRACT: Recent advancements in mass spectrometric proteomics provide a promising result in utilizing saliva to explore biomarkers for diagnostic purposes. However, the issues of specificity or redundancy of disease-associated salivary biomarkers have not been described. This systematic review was therefore aimed to define and summarize disease-related salivary biomarkers identified by mass spectrometry proteomics. Peer-reviewed articles published through July 2009 within three databases were reviewed. Out of 243 articles, 21 studies were selected in this systematic review with conditions including Sjögren's syndrome, squamous cell carcinoma, dental caries, diabetes, breast cancer, periodontitis, gastric cancer, systemic sclerosis, oral lichen planus, bleeding oral cavity, and graft-versus-host disease. The sample size ranged from 3-41 in both diseased and control subjects, with no consensus on sample collection protocol. One hundred eighty biomarkers were identified in total; 87 upregulated, 63 downregulated, and 30 varying based on disease. Except for Sjögren's syndrome, the majority of studies with the same disease produce inconsistent biomarkers. Larger sample size and standardization of sample collection/treatment protocol may improve future studies.

SUBMITTER: Al-Tarawneh SK

PROVIDER: S-EPMC3125555 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review.

Al-Tarawneh Sandra K SK Border Michael B MB Dibble Christopher F CF Bencharit Sompop S

Omics : a journal of integrative biology 20110513 6

Recent advancements in mass spectrometric proteomics provide a promising result in utilizing saliva to explore biomarkers for diagnostic purposes. However, the issues of specificity or redundancy of disease-associated salivary biomarkers have not been described. This systematic review was therefore aimed to define and summarize disease-related salivary biomarkers identified by mass spectrometry proteomics. Peer-reviewed articles published through July 2009 within three databases were reviewed. O ...[more]

PMID: 21568728

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Project description: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.

Project description:Canine oral tumors are relatively common neoplasms in dogs. For disease monitoring and early diagnosis, salivary biomarkers are appropriate because saliva collection is non-invasive and requires no professional skills. In the era of omics, matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry (MALDI-TOF MS) coupled with liquid chromatography-tandem MS (LC-MS/MS) are suitable to identify potential disease-associated peptides and proteins. The present study aimed to use MALDI-TOF MS and LC-MS/MS to search for particular peptide mass fingerprints (PMFs) and conceivable biomarkers in saliva of dogs with early- and late-stage oral melanoma (EOM and LOM, respectively), oral squamous cell carcinoma (OSCC), benign oral tumors (BN), and periodontitis and healthy controls (CP). Pooled saliva samples in each group were used to be representative of population change. Unique PMFs were obtained and specific peptide fragments were sequenced by LC-MS/MS and BLAST-searched with mammalian protein databases. Seven peptide fragments appeared in the tumor groups (EOM, LOM, OSCC and BN) at 1096, 1208, 1322, 1794, 1864, 2354 and 2483 Da, two peptide fragments appeared in the LOM and OSCC groups at 2450 and 3492 Da, and in the CP controls at 2544 and 3026 Da. Also, protein-chemotherapy drug interaction networks were exhibited. Using western blot analysis, the expression of sentrin-specific protease 7 (SENP7), a peptide fragment at 1096 Da, in OSCC was significantly increased, as was the expression of TLR4, a peptide fragment at 3492 Da, in LOM and OSCC, compared with the CP group. The expression of nuclear factor kappa B (NF-κB), a TLR4 partner, was notably increased in OSCC compared with CP, BN and EOM. The expression was also enhanced in LOM compared with EOM. Expressed protein sequences from western blots were verified by LC-MS/MS. Western blots were then performed with individual samples in each group. The results showed the elevated expression of TLR4 in LOM and OSCC, compared with that in CP and BN, the increased expression of NF-κB in LOM and OSCC, compared with CP and in LOM compared with BN, and the enhanced expression of SENP7 in LOM and OSCC, compared with that in CP and BN. In conclusion, discrete clusters of EOM, LOM, OSCC, BN and CP groups and potential protein candidates associated with the diseases were demonstrated by salivary proteomics. Western blot analysis verified SENP7, TLR4 and NF-κB as potential salivary biomarkers of canine oral tumors.

Project description:BackgroundOsteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers.MethodsSerum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography-tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis.ResultsIn total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins from both OA groups, some of them alone would not be a suitable choice as specific OA biomarkers due to their rather non-specific role or their strong link to other pathological conditions. Altogether, data revealed that the protein CRTAC1 appears to be a strong OA biomarker candidate. Other potential new biomarker candidates are the proteins FBN1, VDBP, and possibly SERPINF1. Validation experiments revealed statistical differences between controls and OA for FBN1 (p=0.044) and VDPB (p=0.022), and a trend for SERPINF1 (p=0.064).ConclusionOur study suggests that 4 proteins, CRTAC1, FBN1, VDBP, and possibly SERPINF1, warrant further investigation as potential new biomarker candidates for the whole OA population.

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Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review.

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Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review.

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