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Biomarker Discovery in Oral Cancer (OSMF & OSCC) and its severity

ABSTRACT:

Oral squamous cell carcinoma (OSCC) is frequently the outcome of oral submucous fibrosis (OSMF), a common possibly premalignant disease. In our study, a cohort of 50 patients with OSCC and OSMF, along with 50 healthy controls, was analyzed to identify significant metabolic differences between the patient and control groups through multivariate statistical analysis using NMR-based metabolomics in saliva samples. The 2D scatter plot of PC1 versus PC2 scores clearly shows a distinction between the groups, with the principal component analysis (PCA) explaining 24.6% of the variance. Partial least-squares discriminant analysis (PLS-DA) demonstrated R2 and Q2 values of 0.94 and 0.90, respectively, indicating a robust model fit. A total of 20 distinct metabolites were identified, including 5 that were up-regulated and 5 down-regulated. Univariate ROC curve analysis identified 9 salivary metabolites with AUC values exceeding 0.70, including acetone, tryptophan, 5-aminopentanoic acid, betaine, aspartic acid, ethanol, acetoacetate, adipic acid and citrate. Notably, the distinct presence of three metabolites - acetone, tryptophan and 5-aminopentanoic acid - yielded AUC values of 0.98123, 0.95358 and 0.91506, respectively. The refined statistical model was subjected to metabolic pathway analysis, revealing interconnected pathways. We could also predict the disease's severity, specifically distinguishing between Stage I and Stage II OSCC. This differentiation was highlighted by the PCA score plot, which explained 28.6% of the variance. PLS-DA further confirmed these results. These insights pave the way for early diagnosis and predicting severity in oral cancer patients, enabling better management of the disease.

INSTRUMENT(S): Nuclear Magnetic Resonance (NMR) -

PROVIDER: MTBLS11009 | MetaboLights | 2024-10-23

REPOSITORIES: MetaboLights

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Project description:Differentially methylated oral squamous cell carcinoma (OSCC) biomarkers, identified in-vitro and validated in well-characterized surgical specimens, have shown poor clinical correlation in cohorts with different risk profiles. To overcome this lack of relevance we used the HumanMethylation27 BeadChip, publicly available methylation and expression array data, and Quantitative Methylation Specific PCR to uncover differential methylation in OSCC clinical samples with heterogeneous risk profiles. A two stage-design consisting of Discovery and Prevalence screens was used to identify differential promoter methylation and deregulated pathways in patients diagnosed with OSCC and head and neck squamous cell carcinoma. Promoter methylation of KIF1A (k=0.64), HOXA9 (k=0.60), NID2 (k=0.60), and EDNRB (k=0.60) had a moderate to substantial agreement with clinical diagnosis in the Discovery screen. HOXA9 had 68% sensitivity, 100% specificity and a 0.81 AUC. NID2 had 71% sensitivity, 100% specificity and a 0.79 AUC. In the Prevalence screen HOXA9 (k=0.82) and NID2 (k=0.80) had an almost perfect agreement with histologic diagnosis. HOXA9 had 85% sensitivity, 97% specificity and a 0.95 AUC. NID2 had 87% sensitivity, 95% specificity and a 0.91 AUC. A HOXA9 and NID2 gene panel had 94% sensitivity, 97% specificity and a 0.97 AUC. In saliva from OSCC cases and controls HOXA9 had 75% sensitivity, 53% specificity and a 0.75 AUC. NID2 had 87% sensitivity, 21% specificity and a 0.73 AUC. This Phase I Biomarker Development Trial identified a panel of differentially methylated genes in normal and OSCC clinical samples from patients with heterogeneous risk profiles. This panel may be useful for early detection and cancer prevention studies. The 12 samples analyzed comprise equal numbers of three tissue-types: Primary oral squamous cell carcinoma, Oral leukoplakia and Normal oral mucosa. Gender, age and smoking-status were approximately equally represented in these goups. Normal oral mucosa served as a control.

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	103.zip	Other
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	105.zip	Other
	106.zip	Other

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Biomarker Discovery in Oral Cancer (OSMF & OSCC) and its severity

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