Diagnostic salivary biomarkers in oral cancer and oral potentially malignant disorders and their relationships to risk factors – A systematic review

Piyarathne, Nadisha Sewwandi; Rasnayake, R.M.S.G.K; Angammana, Randilini; Chandrasekera, Pushpika; Ramachandra, Samantha; Weerasekera, Manjula; Yasawardene, S.G.; Eid, Rasha Abu; Jayasinghe, Jaya Archacilage Premasiri; Gupta, Ekta

doi:10.1080/14737159.2021.1944106

Cited by 26 publications

(17 citation statements)

References 85 publications

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“…Saliva-Based Biomarkers Saliva contains various biomarkers that signal disease, and it has great potential for early cancer diagnosis with cost-effective and easy collection, storage, transport and processing. A systematic literature review [25] has evaluated studies regarding possible saliva markers for PMOD and oral cancer in both unstimulated and stimulated morning saliva. These studies showed that most of the possible markers are proteins.…”

Section: Liquid Biopsiesmentioning

confidence: 99%

Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges

Haj‐Hosseini

Lindblad

Hasséus

et al. 2022

J. Maxillofac. Oral Surg.

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Oral cancer is a cancer type that is widely prevalent in low-and middle-income countries with a high mortality rate, and poor quality of life for patients after treatment. Early treatment of cancer increases patient survival, improves quality of life and results in less morbidity and a better prognosis. To reach this goal, early detection of malignancies using technologies that can be used in remote and low resource areas is desirable. Such technologies should be affordable, accurate, and easy to use and interpret. This review surveys different technologies that have the potentials of implementation in primary health and general dental practice, considering global perspectives and with a focus on the population in India, where oral cancer is highly prevalent. The technologies reviewed include both sample-based methods, such as saliva and blood analysis and brush biopsy, and more direct screening of the oral cavity including fluorescence, Raman techniques, and optical coherence tomography. Digitalisation, followed by automated artificial intelligence based analysis, are key elements in facilitating wide access to these technologies, to non-specialist personnel and in rural areas, increasing quality and objectivity of the analysis while simultaneously reducing the labour and need for highly trained specialists.

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Section: Liquid Biopsiesmentioning

confidence: 99%

Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges

Haj‐Hosseini

Lindblad

Hasséus

et al. 2022

J. Maxillofac. Oral Surg.

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“…The improved diagnostic technologies based on molecular biology highlighted the potential use of salivary biomarkers in the early detection of OSCC [ 102 ]. Proteomic platforms described around 200 peptides and proteins present in saliva and differentiated them into physiological and pathological conditions; furthermore, the salivary proteome for oral lesions and OSCC has been characterized [ 103 ], and over 100 potential salivary biomarkers for OSCC were identified [ 104 ].…”

Section: The Use Of Salivary Mmps As Biomarkers For Osccmentioning

confidence: 99%

The Use of Salivary Levels of Matrix Metalloproteinases as an Adjuvant Method in the Early Diagnosis of Oral Squamous Cell Carcinoma: A Narrative Literature Review

Monea

Pop

2022

CIMB

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Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with increased mortality, in which the early diagnosis is the most important step in increasing patients’ survival rate. Extensive research has evaluated the role of saliva as a source of diagnostic biomarkers, among which matrix metalloproteinases (MMPs) have shown a valuable potential for detecting even early stages of OSCC. The aim of this review was to present recent clinical data regarding the significance of salivary MMPs in the detection of early malignant transformation of the oral mucosa. A narrative review was conducted on articles published in PubMed, Cochrane Library, Web of Science, EBSCO and SciELO databases, using specific terms. Our search revealed that MMP-1, MMP-2, MMP-3, MMP-8, MMP-9, MMP-10, MMP-12 and MMP-13 had significantly higher levels in saliva from patients with OSCC compared to controls. However, the strength of evidence is limited, as most information regarding their use as adjuvant diagnostic tools for OSCC comes from studies with a low number of participants, variable methodologies for saliva sampling and diagnostic assays, and insufficient adjustment for all covariates. MMP-1, MMP-3 and MMP-9 were considered the most promising candidates for salivary diagnosis of OSCC, but larger studies are needed in order to validate their clinical application.

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“…Explorations into the use of salivary molecular markers that are specific to or preferential for oral cancer have suggested potential candidates for clinical applications, with transcriptomic and epigenomic markers being the most promising [12][13][14][15][16]. Furthermore, for epigenetic markers, our group and others have reported a better diagnostic accuracy when biomarker panels were used as opposed to single biomarkers [9,17,18]. However, it was observed that true genome-wide techniques, such as whole-genome bisulfite sequencing (WGBS) and reduced-representation bisulfite sequencing (RRBS), were not being utilized during methylome biomarker discovery, which may have limited the optimal biomarker selection [9,13].…”

Section: Introductionmentioning

confidence: 96%

Machine Learning-Based Genome-Wide Salivary DNA Methylation Analysis for Identification of Noninvasive Biomarkers in Oral Cancer Diagnosis

Adeoye

Wan

Zheng

et al. 2022

Cancers

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This study aims to examine the feasibility of ML-assisted salivary-liquid-biopsy platforms using genome-wide methylation analysis at the base-pair and regional resolution for delineating oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). A nested cohort of patients with OSCC and OPMDs was randomly selected from among patients with oral mucosal diseases. Saliva samples were collected, and DNA extracted from cell pellets was processed for reduced-representation bisulfite sequencing. Reads with a minimum of 10× coverage were used to identify differentially methylated CpG sites (DMCs) and 100 bp regions (DMRs). The performance of eight ML models and three feature-selection methods (ANOVA, MRMR, and LASSO) were then compared to determine the optimal biomarker models based on DMCs and DMRs. A total of 1745 DMCs and 105 DMRs were identified for detecting OSCC. The proportion of hypomethylated and hypermethylated DMCs was similar (51% vs. 49%), while most DMRs were hypermethylated (62.9%). Furthermore, more DMRs than DMCs were annotated to promoter regions (36% vs. 16%) and more DMCs than DMRs were annotated to intergenic regions (50% vs. 36%). Of all the ML models compared, the linear SVM model based on 11 optimal DMRs selected by LASSO had a perfect AUC, recall, specificity, and calibration (1.00) for OSCC detection. Overall, genome-wide DNA methylation techniques can be applied directly to saliva samples for biomarker discovery and ML-based platforms may be useful in stratifying OSCC during disease screening and monitoring.

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Diagnostic salivary biomarkers in oral cancer and oral potentially malignant disorders and their relationships to risk factors – A systematic review

Cited by 26 publications

References 85 publications

Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges

Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges

The Use of Salivary Levels of Matrix Metalloproteinases as an Adjuvant Method in the Early Diagnosis of Oral Squamous Cell Carcinoma: A Narrative Literature Review

Machine Learning-Based Genome-Wide Salivary DNA Methylation Analysis for Identification of Noninvasive Biomarkers in Oral Cancer Diagnosis

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