Abstract

Despite having numerous advances in therapeutics, mortality and morbidity due to oral cancer incidence are still very high. Early detection can improve the chances of survival in most patients. However, diagnosis at early stages can be challenging as premalignant conditions are usually asymptomatic. Currently, histological assessment remains the gold standard for diagnosis. Early diagnosis poses challenges to pathologists due to less severe morphological changes associated with early stages. Therefore, a fast and robust method of detection based on molecular changes is needed for early diagnosis. © 2021 Wiley Periodicals LLC. In the present study, Fourier transform infrared (FTIR) spectroscopic imaging has been used to differentiate early-stage oral hyperplasia from adjacent normal (AN) and oral squamous cell carcinoma (OSCC). Hyperplasia is often considered as an initial event in the pathogenesis of oral cancer and OSCC is the most common advanced stage of malignancy. Differentiating normal versus hyperplasia and hyperplasia versus OSCC can remain quite challenging on occasion using conventional staining as the histological assessment is based on morphological changes. Unsupervised hierarchical cluster analysis (UHCA) has been performed on FTIR images of multiple tissues together that provided some degree of classification among tissue groups. The AN epithelium clustered distinctively using UHCA from both hyperplasia and grades 1 and 2 of OSCC. An increase in the content of DNA, denaturation of protein, and altered lipid structures were more clearly elucidated with spectral analysis. This study demonstrates a simple strategy to differentiate early-stage oral hyperplasia from ANand OSCC using UHCA. This study also proposes a future alternative method where FTIR imaging can be used as a diagnostic tool for cancer at early stages.

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