Advances in the Diagnosis, Monitoring, and Progression of Oral Cancer through Saliva: An Update

Biological biomarkers of oral cancer

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per year from 2005 to 2017, with higher survival rates when detected at early stages. Based on histopathological grading of oral dysplasia, it is estimated that severe dysplasia has a malignant transformation rate of 7%-50%. Despite these numbers, oral dysplasia grading does not reliably predict its clinical behavior. Thus, more accurate markers predicting oral dysplasia progression to cancer would enable better targeting of these lesions for closer follow-up, especially in the early stages of the disease. In this context, molecular biomarkers derived from genetics, proteins, and metabolites play key roles in clinical oncology. These molecular signatures can help predict the likelihood of OSCC development and/or progression and have the potential to detect the disease at an early stage and, support treatment decision-making and predict treatment responsiveness. Also, identifying reliable biomarkers for OSCC detection that can be obtained non-invasively would enhance management of OSCC. This review will discuss biomarkers for OSCC that have emerged from different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, and microbiomics.

Realizing the clinical utility of saliva for monitoring oral diseases

In the era of personalized/precision health care, additional effort is being expended to understand the biology and molecular mechanisms of disease processes. How these mechanisms are affected by individual genetics, environmental exposures, and behavioral choices will encompass an expanding role in the future of optimally preventing and treating diseases. Considering saliva as an important biological fluid for analysis to inform oral disease detection/description continues to expand. This review provides an overview of saliva as a diagnostic fluid and the features of various biomarkers that have been reported. We emphasize the use of salivary biomarkers in periodontitis and transport the reader through extant literature, gaps in knowledge, and a structured approach toward validating and determine the utility of biomarkers in periodontitis. A summation of the findings support the likelihood that a panel of biomarkers including both host molecules and specific microorganisms will be required to most effectively identify risk for early transition to disease, ongoing disease activity, progression, and likelihood of response to standard periodontal therapy. The goals would be to develop predictive algorithms that serve as adjunctive diagnostic tools which provide the clinician and patient important information for making informed clinical decisions.

The emerging role of liquid biopsy in oral squamous cell carcinoma detection: advantages and challenges

INTRODUCTION

Oral Squamous Cell Carcinoma (OSCC), the sixth most widespread malignancy in the world, accounts for 90% of all cases of oral cancer. The primary risk factors are tobacco chewing, alcohol consumption, viral infection, and genetic modifications. OSCC has a high morbidity rate due to the lack of early diagnostic methods. Nowadays, liquid biopsy plays a vital role in the initial diagnosis of oral cancer. ctNAs extracted from saliva and serum/plasma offer meaningful insights into tumor genetics and dynamics. The interplay of these elements in saliva and serum/plasma showcases their significance in advancing noninvasive, effective OSCC detection and monitoring.

AREAS COVERED

This review mainly focused on the role of liquid biopsy as an emerging point in the diagnosis and prognosis of OSCC and the current advancements and challenges associated with liquid biopsy.

EXPERT OPINION

Liquid biopsy is regarded as a new, minimally invasive, real-time monitoring tool for cancer diagnosis and prognosis. Many biomolecules found in bodily fluids, including ctDNA, ctRNA, CTCs, and EVs, are significant biomarkers to identify cancer in its early stages. Despite these groundbreaking strides, challenges persist. Standardization of sample collection, isolation, processing, and detection methods is imperative for ensuring result reproducibility across diverse studies.

Ethical considerations on artificial intelligence in dentistry: A framework and checklist

OBJECTIVE

Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and intellectual human tasks. In dentistry, AI offers the potential to enhance diagnostic accuracy, improve patient outcomes and streamline workflows. The present study provides a framework and a checklist to evaluate AI applications in dentistry from this perspective.

METHODS

Lending from existing guidance documents, an initial draft of the checklist and an explanatory paper were derived and discussed among the groups members.

RESULTS

The checklist was consented to in an anonymous voting process by 29 Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health's members. Overall, 11 principles were identified (diversity, transparency, wellness, privacy protection, solidarity, equity, prudence, law and governance, sustainable development, accountability, and responsibility, respect of autonomy, decision-making).

CONCLUSIONS

Providers, patients, researchers, industry, and other stakeholders should consider these principles when developing, implementing, or receiving AI applications in dentistry.

CLINICAL SIGNIFICANCE

While AI has become increasingly commonplace in dentistry, there are ethical concerns around its usage, and users (providers, patients, and other stakeholders), as well as the industry should consider these when developing, implementing, or receiving AI applications based on comprehensive framework to address the associated ethical challenges.