Metabolite Profiling of Preneoplastic and Neoplastic Lesions of Oral Cavity Tissue Samples Revealed a Biomarker Pattern

Abstract

Oral cancer is a major health challenge in the Indian subcontinent and a dreadful form of cancers worldwide. The current study is focused on the identification of distinguished metabolites of oral cancer tissue samples in comparison with precancerous and control tissue samples using gas chromatography coupled with triple quadrupole tandem mass spectrometry and chemometric analyses. Metabolites obtained were identified through National Institute of Standards and Technology (NIST) mass spectral (Wiley registry) library. Mass Profiler Professional (MPP) software was used for the alignment and for all the statistical analysis. 31 compounds out of 735 found distinguishing among oral cancer, precancerous and control group samples using p-value ≤ 0.05. Partial Least Square Discriminant Analysis (PLSDA) model was generated using statistically significant metabolites gave an overall accuracy of 90.2%. Down-regulated amino acid levels appear to be the result of enhanced energy metabolism or up-regulation of the appropriate biosynthetic pathways, and required cell proliferation in cancer tissues. These results suggest that tissue metabolic profiles have great potential in detecting oral cancer and may aid in understanding its underlying mechanisms.

Figure 1. Comparison of three groups i.e., controls, pre cancer, oral cancer patients using normalized intensities of thirty one significance metabolites.

The dendrogram was produced by applying a hierarchical clustering algorithm (Pearson’s centered- absolute distance metric, Complete Linkage).

Figure 2. Three dimensional PCA score plot for all samples using thirty one identified and unidentified differentiative peaks.

Figure 3. PLSDA score scatter plot discriminating among controls and oral cancer patients based on the thirty one significantly differentiate metabolite profiling data.

The red, blue and brown squares indicate control, oral cancer and pre cancer patients, respectively.

Figure 4. Summary of pathway analysis of metabolites found dysregulated in cancer patients as compared to healthy controls (the annotations are based on serial number given to each pathway in Table 3 and Supplementary Table 4).

Figure 5. Bar graph showing normalized intensities of differentiated nine amino acids in control, pre-cancerous and oral cancer tissue samples (error bars are standard deviations in biological replicates).