Salivary Metabolomics for Prognosis of Oral Squamous Cell Carcinoma.
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ABSTRACT:
SUBMITTER: Ishikawa S
PROVIDER: S-EPMC8769065 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Melatonin's role in circadian rhythm is well documented, as are its' anti-oxidant, oncostatic and anti-inflammatory properties. Poor sleep quality has been associated as a potential risk factor for several malignancies, including head and neck cancers. The purpose of this study is to determine salivary melatonin (MLT) levels in oral squamous cell carcinoma (OSCC) patients, compare the salivary MLT levels with those in healthy individuals and compare the salivary and serum levels in OSCC patients. Furthermore, the aim is to investigate the potential relationship between sleep quality and salivary MLT levels in OSCC patients. Unstimulated (UWS) and stimulated (SWS) whole saliva was sampled from patients with T1N0M0 and T2N0M0 OSCC (N = 34) and 33 sex and age matched healthy subjects. Serum samples were taken from 11 OSCC patients. Sleep quality was measured using Pittsburgh Sleep Quality Index (PSQI) questionnaire. Melatonin levels in UWS and SWS were significantly higher in the OSCC group. Sleep quality was significantly lower in patients with OSCC (P = 0.0001). ROC analysis was found to be significant (P < 0.001) in evaluating MLT concentration limit in diagnosing OSCC. The expected relationship between sleep quality and salivary MLT levels in OSCC patients was not observed. Our results suggest salivary MLT as a potential biomarker that might facilitate non-invasive detection of early stage OSCC.
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Project description:Oral cancer refers to the malignancies that occur in the oral cavity, lip and pharynx with 90% of oral cancers being squamous cell carcinomas (OSCC). OSCC has the highest mortality ratio compared to other carcinomas. Although oral cavity is easily accessible, most oral cancers are detected at a later stage leading to lower survival rates. Early detection of OSCC is a key factor in improving the prognosis and survival rate of the patient. Rapid advancement in the field of diagnosis has enabled early diagnosis of many potentially malignant conditions even before its clinical manifestations. One such diagnostic modality that has gained much relevance in the field of molecular biology has been the discovery of salivary biomarkers (DNA, RNA and protein markers). These salivary biomarkers have been shown to play a non-invasive role in the diagnosis and surveillance of oral cancer. The direct contact between the saliva and the oral cancer lesions makes it a most sensitive and specific, screening method in diagnosis, staging and follow-up. This review aims to discuss the effectiveness and the potential of salivary biomarkers as a screening tool in OSCC.
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Project description:Oral squamous cell carcinoma (OSCC) is a widespread malignancy with high mortality. In particular, a delay in its diagnosis dramatically decreases the survival rate. The aim of this systematic review was to investigate and summarize clinical results in the literature, regarding the potential use of salivary microRNAs (miRNAs) as diagnostic and prognostic biomarkers for OSCC patients. Twelve papers were selected, including both case-control and cohort studies, and all of them detected significantly dysregulated miRNAs in OSCC patients compared to healthy controls. Based on our results, salivary miRNAs might provide a non-invasive and cost-effective method in the diagnosis of OSCC, and also to monitor more easily its evolution and therapeutic response and therefore aid in the establishment of specific therapeutic strategies.
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Project description:Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide with the maximum number of incidences and deaths reported from India. One of the major causes of poor survival rate associated with OSCC has been attributed to late presentation due to non-availability of a biomarker. Identification of early diagnostic biomarker will help in reducing the disease morbidity and mortality. We validated 12 salivary proteins using targeted proteomics, identified initially by relative quantification of salivary proteins on LC-MS, in OSCC patients and controls. Salivary AHSG (p = 0.0041**) and KRT6C (p = 0.002**) were upregulated in OSCC cases and AZGP1 (p ≤ 0.0001***), KLK1 (p = 0.006**) and BPIFB2 (p = 0.0061**) were downregulated. Regression modelling resulted in a significant risk prediction model (p < 0.0001***) consisting of AZGP1, AHSG and KRT6C for which ROC curve had AUC, sensitivity and specificity of 82.4%, 78% and 73.5% respectively for all OSCC cases and 87.9%, 87.5% and 73.5% respectively for late stage (T3/T4) OSCC. AZGP1, AHSG, KRT6C and BPIFB2 together resulted in ROC curve (p < 0.0001***) with AUC, sensitivity and specificity of 94%, 100% and 77.6% respectively for N0 cases while KRT6C and AZGP1 for N+ cases with ROC curve (p < 0.0001***) having AUC sensitivity and specificity of 76.8%, 73% and 69.4%. Our data aids in the identification of biomarker panels for the diagnosis of OSCC cases with a differential diagnosis between early and late-stage cases.
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Project description:Early detection of oral squamous cell cancer (OSCC) is the key to improve the low 5-year survival rate. Using proteomic and genomic technologies we have previously discovered and validated salivary OSCC markers in American patients. The question arises whether these biomarkers are discriminatory in cohorts of different ethnic background. Six transcriptome (DUSP1, IL8, IL1B, OAZ1, SAT1, and S100P) and three proteome (IL1B, IL8, and M2BP) biomarkers were tested on 18 early and 17 late stage OSCC patients and 51 healthy controls with quantitative PCR and ELISA. Four transcriptome (IL8, IL1B, SAT1, and S100P) and all proteome biomarkers were significantly elevated (p<0.05) in OSCC patients. The combination of markers yielded an AUC of 0.86, 0.85 and 0.88 for OSCC total, T1-T2, and T3-T4, respectively. The sensitivity/specificity for OSCC total was 0.89/0.78, for T1-T2 0.67/0.96, and for T3-T4 0.82/0.84. In conclusion, seven of the nine salivary biomarkers (three proteins and four mRNAs) were validated and performed strongest in late stage cancer. Patient-based salivary diagnostics is a highly promising approach for OSCC detection. This study shows that previously discovered and validated salivary OSCC biomarkers are discriminatory and reproducible in a different ethnic cohort. These findings support the feasibility to implement multi-center, multi-ethnicity clinical trials towards the pivotal validation of salivary biomarkers for OSCC detection.
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Project description:The prognosis of patients with oral squamous carcinoma (OSCC) largely depends on the stage at diagnosis, the 5-year survival rate being approximately 30% for advanced tumors. Early diagnosis, including the detection of lesions at risk for malignant transformation, is crucial for limiting the need for extensive surgery and for improving disease-free survival. Saliva has gained popularity as a readily available source of biomarkers (including cytokines) useful for diagnosing specific oral and systemic conditions. Particularly, the close interaction between oral dysplastic/neoplastic cells and saliva makes such fluid an ideal candidate for the development of non-invasive and highly accurate diagnostic tests. The present review has been designed to answer the question: "Is there evidence to support the role of specific salivary cytokines in the diagnosis of OSCC?" We retrieved 27 observational studies satisfying the inclusion and exclusion criteria. Among the most frequent cytokines investigated as candidates for OSCC biomarkers, IL-6, IL-8, TNF-α are present at higher concentration in the saliva of OSCC patients than in healthy controls and may therefore serve as basis for the development of rapid tests for early diagnosis of oral cancer.
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Project description:Oral squamous cell carcinoma (OSCC) is the seventh most common malignancy and the ninth most frequent cause of cancer death in Europe. Within Europe, Hungary has one of the highest rates of OSCC incidence and mortality. Thus, there is an urgent need to improve early detection. Saliva, as a readily available body fluid, became an increasingly important substance for the detection of biomarkers for many diseases. Different research groups have identified salivary biomarkers specific for OSCC for different countries. In this study, saliva samples of Hungarian patients with OSCC were studied to discover disease-specific and perhaps region-specific biomarkers. LC-mass spectrometry (MS)/MS analysis on a linear ion trap-Orbitrap mass spectrometer was used for qualitative and quantitative salivary protein profiling. More than 500 proteins were identified from saliva by shotgun proteomics. The up- and downregulated proteins in the saliva of patients with OSCC highlighted the importance of protein-protein interaction networks involving the immune system and proteolysis in disease development. Two potential biomarkers from our shotgun analysis and a third candidate reported earlier by a Taiwanese group were further examined by ELISA on a larger reference set of samples. Resistin, a biomarker reported in Taiwan but not validated in our study, highlights the necessity of application of standardized analysis methods in different ethnic or geographical populations to identify biomarkers with sufficient specificity and sensitivity.
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Project description:ObjectivesOral cancer is the ninth most common cancer worldwide and a leading cause of cancer-related death. Oral squamous cell carcinoma (OSCC) accounts for 90% of all oral cancers. Autophagy is a conserved essential catabolic process related to OSCC. The aim of this study was to elucidate diagnostic and prognostic autophagy-related biomarkers in OSCC.MethodsThe OSCC gene expression data set was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the OSCC samples and adjacent healthy tissues were identified by R software. The Human Autophagy Database was screened, which revealed 222 autophagy-related genes. The autophagy-related DEGs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied. Protein-protein interaction network analysis was performed in the STRING database. cytoHubba in the Cytoscape software was applied to determine the top 10 hub genes. The data set of patients with OSCC from The Cancer Genome Atlas (TCGA) was used to evaluate the prognostic value of the 10 hub genes. The association between prognosis-related hub genes and immune infiltrates was explored.ResultsTwenty-seven autophagy-related DEGs were identified. The top 10 hub genes were CCL2, CDKN2A, CTSB, CTSD, CXCR4, ITGA6, MAP1LC3A, MAPK3, PARP1, and RAB11A. ITGA6 was identified as the most efficient biomarker. Receiver operating characteristic curve analysis indicated that ITGA6 had the highest diagnostic accuracy for OSCC (area under the curve = 0.925). ITGA6 expression was significantly related to immune infiltrates.ConclusionsThe autophagy-related gene ITGA6 might be an efficient diagnostic and prognostic biomarker in OSCC.
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Project description:PURPOSE:This study evaluated the discriminatory power of salivary transcriptomic and proteomic biomarkers in distinguishing oral squamous cell carcinoma cases from controls and potentially malignant oral disorders (PMOD). EXPERIMENTAL DESIGN:A total of 180 samples (60 OSCC patients, 60 controls, and 60 PMOD patients) were used in the study. Seven transcriptomic markers (IL8, IL1?, SAT1, OAZ1, DUSP1, S100P, and H3F3A) were measured using qPCR, and two proteomic markers (IL8 and IL1?) were evaluated by ELISA. RESULTS:Among 7 transcriptomic markers, transcript level of DUSP1 was significantly lower in OSCC patients than in controls and PMOD patients. Between the proteomic markers, the protein concentration of IL8 and IL1? was significantly higher in OSCC patients than controls and dysplasia patients. Univariate fractional polynomial (FP) models revealed that salivary IL8 protein (IL8p) has the highest AUC value between OSCC patients and controls (0.74) and between OSCC and PMOD patients (0.72). Applying a 2-marker FP model, salivary IL8p combined with IL1? gave the best AUC value for discrimination between OSCC patients and controls, as well as the IL8p combined with H3F3A mRNA, which gave the best AUC value for discrimination between OSCC and PMOD patients. Multivariate models analysis combining salivary analytes and risk factor exposure related to oral carcinogenesis formed the best combinatory variables for differentiation between OSCC versus PMOL (AUC = 0.80), OSCC versus controls (AUC = 0.87), and PMOD versus controls (AUC = 0.78). CONCLUSIONS:The combination of transcriptomic and proteomic salivary markers is of great value for oral cancer detection and differentiation from PMOD patients and controls. Clin Cancer Res; 22(13); 3340-7. ©2016 AACR.
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