Expression of Epstein-Barr virus among oral potentially malignant disorders and oral squamous cell carcinomas in the South Indian tobacco-chewing population

Prevalence of Epstein Barr Virus and Herpes Simplex Virus Among Human Papillomavirus Negative Oral Cancer Patients: A Cross-Sectional Study from South India

The high incidence of oral carcinomas is due to its multifactorial etiology and the presence of various risk factors. Human Papillomavirus (HPV) has a proven role in the pathogenesis of oral carcinomas, but in the recent times there has been an increasing incidence of oral cancers who are negative for HPV infection. Also, these patients are non-smokers and non-drinkers so it could be speculated that these oral cancers are due to some other etiological factor probably of other viral infections. Therefore, this study examined the prevalence of Epstein Barr Virus (EBV) and Herpes Simplex Virus (HSV) among oral cancer patients. This cross-sectional study was conducted from January 2019 to June 2020. Biopsy samples from 47 newly diagnosed untreated patients with oral malignancies were collected along with their demographic and clinicopathological information. DNA extracted from the biopsies was processed for nested PCR for the detection of EBV and HSV. All the samples tested negative for HPV and HSV infection. Nested PCR detected 29 cases (70.7%) to be positive for EBV. The non-cancerous adjacent tissues also were negative for HPV, EBV and HSV. The prevalence of EBV was found to be more in males (62.1%) and the highest number of cases was of the left buccal mucosa compromising 34% of the total cases. From the present study it can be concluded that EBV but not HSV infection is associated with an increased risk of developing oral cancers. Although, 70.7% of the patients were found to be positive for EBV whether the viral infection played any role in the driving the malignancy needs to be further elucidated.

Analysis of Epstein-Barr Virus Infection in Oral Potentially Malignant Disorders and Oral Cancer: A Cross-Sectional Study

Aims and Objectives

The primary objective of this study is to determine the prevalence of Epstein-Barr virus (EBV) in oral potentially malignant disorders (OPMDs) and oral cancer (OC) in a group of Thais using polymerase chain reaction (PCR) and Epstein-Barr encoding regions (EBERs) in situ hybridization (ISH). The secondary objective is to investigate the risk factors of OC and the association between the presence of EBV and risk factors of OC/site of oral lesions.

Materials and Methods

Sixty-one participants attending the screening project for OC and OPMDs at the Northeastern district hospitals of Thailand were recruited. Information related to risk factors and biopsy tissues for histopathological diagnosis was collected. Sixty-seven paraffin tissue blocks, including 52 OPMDs and 15 OC specimens, were investigated for EBV infection, using PCR analysis with latent membrane protein-1 (LMP-1) primer and EBERs ISH. Pearson's Chi-square or Fisher's exact test was used to analyze the differences in variables between participants with OPMDs and OC, as appropriate. The association between EBV infection and related risk factors was analyzed using logistic regression with a significant level at 0.05.

Results

Using PCR analysis, 8 of 67 specimens (11.94%) were positive for LMP-1. Three cases of OPMDs were positive for both LMP-1 PCR and EBERs ISH. Regarding risk factors of OC, the two most common risk factors were betel nut chewing (52.46%) and working in sunlight (42.62%). The habit of taking alcohol was significantly different between the OC and the OPMDs groups (p = 0.009). The association between LMP-1 and the lesion at the tongue was statistically significant, with odds ratio = 4.900 (95% confidence interval = 1.046-22.943; p = 0.044).

Conclusions

The prevalence of EBV infection in this group of participants was low. However, OPMDs at the tongue exhibited a significant association with EBV infection.

Potential Role of Epstein–Barr Virus in Oral Potentially Malignant Disorders and Oral Squamous Cell Carcinoma: A Scoping Review

Though the oral cavity is anatomically proximate to the nasal cavity and acts as a key reservoir of EBV habitation and transmission, it is still unclear whether EBV plays a significant role in oral carcinogenesis. Many studies have detected EBV DNA in tissues and exfoliated cells from OSCC patients. However, very few studies have investigated the expression of functional EBV proteins implicated in its oncogenicity. The most studied are latent membrane protein 1 (LMP-1), a protein associated with the activation of signalling pathways; EBV determined nuclear antigen (EBNA)-1, a protein involved in the regulation of gene expression; and EBV-encoded small non-polyadenylated RNA (EBER)-2. LMP-1 is considered the major oncoprotein, and overexpression of LMP-1 observed in OSCC indicates that this molecule might play a significant role in oral carcinogenesis. Although numerous studies have detected EBV DNA and proteins from OSCC and oral potentially malignant disorders, heterogeneity in methodologies has led to discrepant results, hindering interpretation. Elucidating the exact functions of EBV and its proteins when expressed is vital in establishing the role of viruses in oral oncogenesis. This review summarises the current evidence on the potential role of EBV in oral oncogenesis and discusses the implications as well as recommendations for future research.

Developing an Algorithm for Discriminating Oral Cancerous and Normal Tissues Using Raman Spectroscopy

The aim of this study was to investigate the clinical potential of Raman spectroscopy (RS) in detecting oral squamous cell carcinoma (OSCC) in tumor and healthy tissues in surgical resection specimens during surgery. Raman experiments were performed on cryopreserved specimens from patients with OSCC. Univariate and multivariate analysis was performed based on the fingerprint region (700-1800 cm-1) of the Raman spectra. One hundred thirty-one ex-vivo Raman experiments were performed on 131 surgical resection specimens obtained from 67 patients. The principal component analysis (PCA) and partial least square (PLS) methods with linear discriminant analysis (LDA) were applied on an independent validation dataset. Both models were able to differentiate between the tissue types, but PLS-LDA showed 100% accuracy, sensitivity, and specificity. In this study, Raman measurements of fresh resection tissue specimens demonstrated that OSCC had significantly higher nucleic acid, protein, and several amino acid contents than adjacent healthy tissues. The specific spectral information obtained in this study can be used to develop an in vivo Raman spectroscopic method for the tumor-free resection boundary during surgery.

Novel Quantitative Analysis Using Optical Imaging (VELscope) and Spectroscopy (Raman) Techniques for Oral Cancer Detection

In this study, we developed a novel quantitative analysis method to enhance the detection capability for oral cancer screening. We combined two different optical techniques, a light-based detection technique (visually enhanced lesion scope) and a vibrational spectroscopic technique (Raman spectroscopy). Materials and methods: Thirty-five oral cancer patients who went through surgery were enrolled. Thirty-five cancer lesions and thirty-five control samples with normal oral mucosa (adjacent to the cancer lesion) were analyzed. Thirty-five autofluorescence images and 70 Raman spectra were taken from 35 cancer and 35 control group cryopreserved samples. The normalized intensity and heterogeneity of the 70 regions of interest (ROIs) were calculated along with 70 averaged Raman spectra. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to differentiate the cancer and control groups (normal). The classifications rates were validated using two different validation methods, leave-one-out cross-validation (LOOCV) and k-fold cross-validation. Results: The cryopreserved normal and tumor tissues were differentiated using the PCA-LDA and PCA-QDA models. The PCA-LDA of Raman spectroscopy (RS) had 82.9% accuracy, 80% sensitivity, and 85.7% specificity, while ROIs on the autofluorescence images were differentiated with 90% accuracy, 100% sensitivity, and 80% specificity. The combination of two optical techniques differentiated cancer and normal group with 97.14% accuracy, 100% sensitivity, and 94.3% specificity. Conclusion: In this study, we combined the data of two different optical techniques. Furthermore, PCA-LDA and PCA-QDA quantitative analysis models were used to differentiate tumor and normal groups, creating a complementary pathway for efficient tumor diagnosis. The error rates of RS and VELcope analysis were 17.10% and 10%, respectively, which was reduced to 3% when the two optical techniques were combined.

Multiclass classification of autofluorescence images of oral cavity lesions based on quantitative analysis

Background

Oral cancer is one of the most common diseases globally. Conventional oral examination and histopathological examination are the two main clinical methods for diagnosing oral cancer early. VELscope is an oral cancer-screening device that exploited autofluorescence. It yields inconsistent results when used to differentiate between normal, premalignant and malignant lesions. We develop a new method to increase the accuracy of differentiation.

Materials and methods

Five samples (images) of each of 21 normal mucosae, as well as 31 premalignant and 16 malignant lesions of the tongue and buccal mucosa were collected under both white light and autofluorescence (VELscope, 400-460 nm wavelength). The images were developed using an iPod (Apple, Atlanta Georgia, USA).

Results

The normalized intensity and standard deviation of intensity were calculated to classify image pixels from the region of interest (ROI). Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) classifiers were used. The performance of both of the classifiers was evaluated with respect to accuracy, precision, and recall. These parameters were used for multiclass classification. The accuracy rate of LDA with un-normalized data was increased by 2% and 14% and that of QDA was increased by 16% and 25% for the tongue and buccal mucosa, respectively.

Conclusion

The QDA algorithm outperforms the LDA classifier in the analysis of autofluorescence images with respect to all of the standard evaluation parameters.

Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection

Raman spectroscopy (RS) is widely used as a non-invasive technique in screening for the diagnosis of oral cancer. The potential of this optical technique for several biomedical applications has been proved. This work studies the efficacy of RS in detecting oral cancer using sub-site-wise differentiation. A total of 80 samples (44 tumor and 36 normal) were cryopreserved from three different sub-sites: The tongue, the buccal mucosa, and the gingiva of the oral mucosa during surgery. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to classify the samples and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. The normal and tumor tissues were differentiated under the PCA-LDA model with an accuracy of 81.25% (sensitivity: 77.27%, specificity: 86.11%). The PCA-QDA classifier model differentiated these tissues with an accuracy of 87.5% (sensitivity: 90.90%, specificity: 83.33%). The PCA-QDA classifier model outperformed the PCA-LDA-based classifier. The model studies revealed that protein, amino acid, and beta-carotene variations are the main biomolecular difference markers for detecting oral cancer.