Current Insights into Oral Cancer Diagnostics

A novel saliva-based miRNA profile to diagnose and predict oral cancer

Oral cancer (OC) is the most common form of head and neck cancer. Despite the high incidence and unfavourable patient outcomes, currently, there are no biomarkers for the early detection of OC. This study aims to discover, develop, and validate a novel saliva-based microRNA signature for early diagnosis and prediction of OC risk in oral potentially malignant disorders (OPMD). The Cancer Genome Atlas (TCGA) miRNA sequencing data and small RNA sequencing data of saliva samples were used to discover differentially expressed miRNAs. Identified miRNAs were validated in saliva samples of OC (n = 50), OPMD (n = 52), and controls (n = 60) using quantitative real-time PCR. Eight differentially expressed miRNAs (miR-7-5p, miR-10b-5p, miR-182-5p, miR-215-5p, miR-431-5p, miR-486-3p, miR-3614-5p, and miR-4707-3p) were identified in the discovery phase and were validated. The efficiency of our eight-miRNA signature to discriminate OC and controls was: area under curve (AUC): 0.954, sensitivity: 86%, specificity: 90%, positive predictive value (PPV): 87.8% and negative predictive value (NPV): 88.5% whereas between OC and OPMD was: AUC: 0.911, sensitivity: 90%, specificity: 82.7%, PPV: 74.2% and NPV: 89.6%. We have developed a risk probability score to predict the presence or risk of OC in OPMD patients. We established a salivary miRNA signature that can aid in diagnosing and predicting OC, revolutionising the management of patients with OPMD. Together, our results shed new light on the management of OC by salivary miRNAs to the clinical utility of using miRNAs derived from saliva samples.

Effectiveness of adjunctive screening tools for potentially malignant oral disorders and oral cancer: A systematic review

Background and objectives

To enhance the abilities of healthcare professionals to make informed treatment decisions and establish accurate diagnoses, it is essential to assess the diagnostic reliability of different adjunctive aids. This systematic review aimed to compare the accuracy of various adjunctive methods for diagnosing suspected oral cancer (OC) or potentially malignant oral disorders (OPMD) in adults against histopathological investigative results.

Materials and methods

The review protocol registered in the PROSPERO database (CRD42023463525) was developed in strict accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis-Diagnostic Test Accuracy checklist. A comprehensive electronic search was conducted to identify relevant research articles published between January 2014 and April 2023 using the PubMed and EBSCO databases. The research question was meticulously structured following the participants' index test, reference standard, target condition, and study setting framework. To evaluate methodological quality and assess the risk of bias (RoB), the Quality Assessment for Diagnostic Accuracy Studies-2 tool was used.

Results

An initial search yielded 483 publications, which were reduced to 278 after removal of duplicates. Finally, 85 publications underwent full-text review by two investigators, which lead to 29 studies that met the inclusion criteria. Among these, 7% had a low RoB, 72% had an unclear RoB, and 21% had a high RoB. Applicability concerns were expressed in 59% of the studies with low concern, 31% with unclear quality evidence of concern, and 10% with high concern.

Conclusion

The review findings support the use of these diagnostic methods as valuable adjuncts to biopsy for the early detection of various OPMD and OC. They also highlight the importance of regular screening and awareness in reducing the global burden of OC, while acknowledging that they cannot replace the gold standards of surgical biopsy and histopathological evaluation.

Identification of salivary metabolic biomarker signatures for oral tongue squamous cell carcinoma

OBJECTIVE

To identify the salivary metabolites associated with squamous cell carcinoma of the tongue to develop easy and non-invasive potential biomarkers for disease diagnosis.

DESIGN

Initially, the study utilized untargeted metabolomics to analyze 20 samples of tongue squamous cell carcinoma and 10 control samples. The objective was to determine the salivary metabolites that exhibited differential expression in tongue squamous cell carcinoma. Then the selected metabolites were validated using targeted metabolomics in saliva samples of 100 patients diagnosed with squamous cell carcinoma of the tongue, as well as 30 healthy control individuals.

RESULTS

From the analysis of untargeted metabolomics, 10 metabolites were selected as potential biomarkers. In the subsequent targeted metabolomics study on these selected metabolites, it was observed that N-Acetyl-D-glucosamine, L-Pipecolic acid, L-Carnitine, Phosphorylcholine, and Deoxyguanosine exhibited significant differences. The receiver operating characteristic curve analysis indicates a combination of three important metabolites such as N-Acetyl-D-glucosamine, L-Pipecolic acid and L-Carnitine provided the best prediction with an area under the curve of 0.901.

CONCLUSIONS

The present result reveals that the N-Acetyl-D-glucosamine, L-Pipecolic acid and L-Carnitine are the signature diagnostic biomarkers for oral tongue squamous cell carcinoma. These findings can be used to develop a rapid and non-invasive method for disease monitoring and prognosis in oral tongue cancer.

High expression of novel biomarker TBRG4 promotes the progression and invasion of oral squamous cell carcinoma

BACKGROUND

Transforming growth factor β regulator 4 (TBRG4) is a potential prognostic indicator in various cancers, especially squamous cell carcinomas, and is associated with disease amelioration and poor outcomes. The study aimed to assess the expression pattern of TBRG4 in patients with operable oral squamous cell carcinoma (OSCC) to understand its role in tumour progression using indicators of disease outcome like tumour stage, grade, nodal metastasis, and pattern of invasion.

METHODS

TBRG4 expression was assessed by analyzing 51 cancer and adjacent non-cancerous tissues of OSCC patients using quantitative real-time PCR, and Western blot. TBRG4 expression was also analysed in The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset using the UALCAN tool (http://ualcan.path.uab.edu/). The relationship between TBRG4 expression and the patient's prognosis was analysed using Kaplan-Meier plotter.

RESULTS

Both mRNA and protein levels of TBRG4 were significantly increased in OSCC tissues. The TBGR4 expression was significantly associated with advanced stages (III and IV) and the worst pattern of invasion (WPOI-4 and 5). High TBRG4 expression was also significantly associated with reduced overall survival (p = 0.011). In addition, the analysis of TBRG4 gene expression and clinical data from TCGA, identified that TBRG4 was highly expressed in HPV negative OSCC patients and positively correlated with worst overall survival.

CONCLUSION

The present study suggests that the high expression of TBRG4 might serve as a novel prognostic biomarker for HPV-negative OSCC, which can be validated by future additional investigations in larger cohorts along with functional studies.

Oral Cancer Awareness Among Princess Nourah bint Abdulrahman University Dental Students and Interns

BACKGROUND

Dentists have a very important role in the early diagnosis of oral cancer premalignancy. This aspect of dental practice requires an adequate level of knowledge.

OBJECTIVE

This study aimed to assess the level of knowledge of undergraduate dental students and dental interns about early diagnosis and risk factors of oral cancer.

METHODS

The present cross-sectional study was conducted at the Dental College, Princess Nourah bint Abdulrahman University, Saudi Arabia. Fourth-year and fifth-year students and dental interns were enrolled in the study. The participants were recruited using a convenient, non-probability sampling method. A total of 103 participants filled out a close-ended, online questionnaire. We used descriptive and analytical statistics to analyze the responses to the questionnaire.

RESULTS

The level of general knowledge was moderate (67%). More than half of the participants gave complete responses to questions related to early signs of oral cancer (67%), risk factors (54%), risk sites (75%), treatment plans for leukoplakia (66%), and unhealed ulcer management (58%). We found significant associations between the correct responses and the year of the study regarding early signs of oral cancer (p=0.0001), high malignant potential lesions (p=0.00001), and chronic unhealed ulcer management (p=0.015).  Conclusion: A more satisfactory level of awareness is needed among future dentists, to prevent missing patients undiagnosed with early oral cancerous lesions during routine screening. Consequently, upgrading theoretical curricula, clinical experience, and post-graduate participation in cancer prevention programs is highly recommended.

A Current Review of Machine Learning and Deep Learning Models in Oral Cancer Diagnosis: Recent Technologies, Open Challenges, and Future Research Directions

Cancer is a problematic global health issue with an extremely high fatality rate throughout the world. The application of various machine learning techniques that have appeared in the field of cancer diagnosis in recent years has provided meaningful insights into efficient and precise treatment decision-making. Due to rapid advancements in sequencing technologies, the detection of cancer based on gene expression data has improved over the years. Different types of cancer affect different parts of the body in different ways. Cancer that affects the mouth, lip, and upper throat is known as oral cancer, which is the sixth most prevalent form of cancer worldwide. India, Bangladesh, China, the United States, and Pakistan are the top five countries with the highest rates of oral cavity disease and lip cancer. The major causes of oral cancer are excessive use of tobacco and cigarette smoking. Many people’s lives can be saved if oral cancer (OC) can be detected early. Early identification and diagnosis could assist doctors in providing better patient care and effective treatment. OC screening may advance with the implementation of artificial intelligence (AI) techniques. AI can provide assistance to the oncology sector by accurately analyzing a large dataset from several imaging modalities. This review deals with the implementation of AI during the early stages of cancer for the proper detection and treatment of OC. Furthermore, performance evaluations of several DL and ML models have been carried out to show that the DL model can overcome the difficult challenges associated with early cancerous lesions in the mouth. For this review, we have followed the rules recommended for the extension of scoping reviews and meta-analyses (PRISMA-ScR). Examining the reference lists for the chosen articles helped us gather more details on the subject. Additionally, we discussed AI’s drawbacks and its potential use in research on oral cancer. There are methods for reducing risk factors, such as reducing the use of tobacco and alcohol, as well as immunization against HPV infection to avoid oral cancer, or to lessen the burden of the disease. Additionally, officious methods for preventing oral diseases include training programs for doctors and patients as well as facilitating early diagnosis via screening high-risk populations for the disease.

Status and Determinants of Early Detection of Oral Premalignant and Malignant Lesions in India

It has been over four decades since the launch of the National Cancer Control Programme in India, yet the cancer screening rates for oral cancer remain unremarkable. Moreover, India is bracing a large burden of oral cancer with poor survival rates. An effective public health programme implementation relies on a multitude of factors related to cost-effective evidence-based interventions, the healthcare delivery system, public health human resource management, community behaviour, partnership with stakeholders, identifying opportunities and political commitment. In this context, we discuss the various challenges in the early detection of oral premalignant and malignant lesions and potential solutions.

Salivary protein kinase C alpha and novel microRNAs as diagnostic and therapeutic resistance markers for oral squamous cell carcinoma in Indian cohorts

Oral squamous cell carcinoma (OSCC) is the second leading cause of cancer-related morbidity and mortality in India. Tobacco, alcohol, poor oral hygiene, and socio-economic factors remain causative for this high prevalence. Identification of non-invasive diagnostic markers tailored for Indian population can facilitate mass screening to reduce overall disease burden. Saliva offers non-invasive sampling and hosts a plethora of markers for OSCC diagnosis. Here, to capture the OSCC-specific salivary RNA markers suitable for Indian population, we performed RNA-sequencing of saliva from OSCC patients (n = 9) and normal controls (n = 5). Differential gene expression analysis detected an array of salivary RNAs including mRNAs, long non-coding RNAs, transfer-RNAs, and microRNAs specific to OSCC. Computational analysis and functional predictions identified protein kinase c alpha (PRKCA), miR-6087, miR-449b-5p, miR-3656, miR-326, miR-146b-5p, and miR-497-5p as potential salivary indicators of OSCC. Notably, higher expression of PRKCA, miR-6087 and miR-449b-5p were found to be associated with therapeutic resistance and poor survival, indicating their prognostic potential. In addition, sequencing reads that did not map to the human genome, showed alignments with microbial reference genomes. Metagenomic and statistical analysis of these microbial reads revealed a remarkable microbial dysbiosis between OSCC patients and normal controls. Moreover, the differentially abundant microbial taxa showed a significant association with tumor promoting pathways including inflammation and oxidative stress. Summarily, we provide an integrated landscape of OSCC-specific salivary RNAs relevant to Indian population which can be instrumental in devising non-invasive diagnostics for OSCC.

The clinical implications of circulating microRNAs as potential biomarkers in screening oral squamous cell carcinoma

Background

Recent studies have highlighted the biomarker role of circulating miRNAs in oral squamous cell carcinoma (OSCC), indicating their potential application as early diagnostic markers for OSCC. However, the diagnostic results have proven inconclusive. This study was conducted to evaluate the diagnostic value of circulating miRNAs for OSCC diagnosis.

Methods

Eligible published studies were identified by a literature search carried out in several databases by using combinations of keywords associated with OSCC, circulating miRNAs, and diagnosis. The bivariate meta-analysis model was adopted to summarize the pooled parameters. Afterwards, we thoroughly explored the sources of heterogeneity after evaluating the risk of bias.

Results

A total of 60 studies focusing on 41 circulating miRNAs were included. The pooled sensitivity, specificity, and AUC were 0.75 (95%CI: 0.69-0.80), 0.76 (0.70-0.81), 0.82 (0.79-0.85), respectively. Subgroup analyses showed that miRNA combinations were more accurate than single miRNAs. Additionally, plasma may be a better matrix for miRNAs assays in OSCC diagnosis as the plasma-based miRNA assay had a higher level of diagnostic accuracy than serum-based miRNA assay. Subgroup analyses also suggested that using circulating miRNAs for OSCC diagnosis is more effective in Caucasians than in Asian ethnic groups. Finally, circulating miRNA assays based on large sample sizes have superior diagnostic accuracy than small sample sizes.

Conclusion

Circulating miRNAs might be applied as effective surrogate biomarkers for early diagnosis of OSCC. Nevertheless, future larger-scale prospective studies should be performed to enhance the diagnostic efficiency and investigate the miRNA combinations with more pronounced accuracy.

Identifying anal and cervical tumorigenesis-associated methylation signaling with machine learning methods

Cervical and anal carcinoma are neoplastic diseases with various intraepithelial neoplasia stages. The underlying mechanisms for cancer initiation and progression have not been fully revealed. DNA methylation has been shown to be aberrantly regulated during tumorigenesis in anal and cervical carcinoma, revealing the important roles of DNA methylation signaling as a biomarker to distinguish cancer stages in clinics. In this research, several machine learning methods were used to analyze the methylation profiles on anal and cervical carcinoma samples, which were divided into three classes representing various stages of tumor progression. Advanced feature selection methods, including Boruta, LASSO, LightGBM, and MCFS, were used to select methylation features that are highly correlated with cancer progression. Some methylation probes including cg01550828 and its corresponding gene RNF168 have been reported to be associated with human papilloma virus-related anal cancer. As for biomarkers for cervical carcinoma, cg27012396 and its functional gene HDAC4 were confirmed to regulate the glycolysis and survival of hypoxic tumor cells in cervical carcinoma. Furthermore, we developed effective classifiers for identifying various tumor stages and derived classification rules that reflect the quantitative impact of methylation on tumorigenesis. The current study identified methylation signals associated with the development of cervical and anal carcinoma at qualitative and quantitative levels using advanced machine learning methods.

Transcranial direct current stimulation in the treatment of anxiety and depression in patients with oral cancer during perioperative period

This study retrospectively investigated the efficacy of transcranial direct current stimulation (tDCS) in the treatment of anxiety and depression in patients with oral cancer (OC) during the perioperative period (PPP). This retrospective study reviewed the electronic medical records of patients who underwent OC surgery and experienced anxiety and depression during PPP. The patients were divided into the treatment (n = 36) and control (n = 36) groups. The patients in the treatment group received tDCS, whereas those in the control group did not receive tDCS. The primary outcomes included the Self-rating Anxiety Scale (SAS) and the Self-rating Depression Scale (SDS). Secondary outcomes included adverse events (AEs). We analyzed the outcome data before and after treatment. After treatment, patients in the treatment group achieved greater relief in SAS (P < .01) and SDS (P < .01) scores than those in the control group. Regarding safety, no electronic medical records reported any AEs in this study. The results of this study showed that tDCS may help relieve depression and anxiety in patients with OC during PPP. However, high-quality prospective randomized controlled trials are required to confirm these findings.

Improving the Diagnostic Performance by Adding Methylation Marker to Conventional Visual Examination in Identifying Oral Cancer

Background: Visual oral examination (VOE) is a conventional oral cancer screening method. This study aimed to evaluate the value of methylation marker to assist VOE in identifying oral epithelial dysplasia and oral squamous cell carcinoma (OED/OSCC) from non-cancerous lesions in a real-world situation. Methods: 201 patients with high-risk personal habits who self-perceived oral anomaly were VOE examined, ZNF582 methylation (ZNF582^m) tested, and histologically diagnosed. Results: Among them, 132 patients (65.7%) were histologically diagnosed OED/OSCC. Using VOE, 56.1% OED/OSCC patients had possible oral cancer, whereas 37.7% non-OED/OSCC patients had leukoplakia. ZNF582^m-positive was detected in 90.2% OED/OSCC patients and 44.9% non-OED/OSCC patients. Various logistic regression models were postulated to evaluate the diagnostic performance of conventional VOE and new strategies using ZNF582^m. ROC analysis and its corresponding C-index demonstrated that either triage or co-testing models of VOE and ZNF582^m could improve diagnostic performance and discriminative abilities compared with the VOE only approach. Conclusions: In conclusion, methylation marker test shows equivalent performance to an experienced judgment by oral maxillofacial surgeons and plays a significantly supplementary role in increasing the efficacy in identifying oral malignant lesions. ZNF582^m may be an especially important tool for family physicians or general dentists to properly diagnose suspicious oral lesions.

Evaluation of YouTube videos as a source of information about oral self-examination to detect oral cancer and precancerous lesions

Objectives:

The aim of this study was to investigate quality, reliability, and comprehensiveness of YouTube videos about oral self-examination to detect oral cancer and precancerous lesions and to assess whether the source, duration, quality, reliability, and/or comprehensiveness of videos influence their visibility and popularity.

Materials and Methods:

Videos on YouTube were searched using eight keywords similar to oral self-examination. The first 100 videos for each search term were included. Strict inclusion and exclusion criteria were adhered to, and videos were assessed for quality, reliability, and comprehensiveness. Upload date, views, likes, dislikes, duration, and source of the videos were noted. Viewing rate and interaction index were calculated for each video.

Results:

A total of 800 videos were analyzed, 24 of which met the inclusion criteria. Majority of videos (87%) were uploaded by the healthcare group. The visibility, quality, reliability, and comprehensiveness were higher in videos uploaded by the healthcare group when compared with the non-healthcare group, but not at a level of statistical significance. The mean interaction index score of the non-healthcare group was found to be higher than the healthcare group, with statistically significant difference. Duration of videos showed an impact on the comprehensiveness of the videos.

Conclusion:

There are relatively few videos on oral self-examination on YouTube, and most do not have satisfactory quality, reliability, and comprehensiveness. There is a potential to increase public awareness about oral self-examination by utilizing this tool. Videos with complete and accurate information regarding oral self-examination must be uploaded to YouTube, which is currently an important source of information for the general public.