20 minute read
Embracing Precision and Data Science in Dentistry
Nam Nguyen, BS; Andrew H. Jheon, PhD, DDS; and Michael S. Reddy, DMD
AUTHORS
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Nam Nguyen, BS, is a third-year predoctoral student at the University of California, San Francisco, School of Dentistry. He is a past John C. Greene Society research fellow at the UCSF Biomaterials and Bioengineering Correlative Microscopy Core and currently conducting active research for the UCSF Program in Craniofacial Biology. Conflict of Interest Disclosure: None reported.
Andrew H. Jheon, PhD, DDS, is an orthodontist and assistant professor in the University of California, San Francisco, School of Dentistry program of orthodontics and orofacial sciences. As a clinician-scientist, he is always looking to translate knowledge from the laboratory into the clinic. Conflict of Interest Disclosure: None reported.
Michael S. Reddy, DMD, is an educator, clinician and researcher currently serving as dean and professor at the University of California, San Francisco, School of Dentistry. Conflict of Interest Disclosure: None reported.
ABSTRACT
The National Institutes of Health (NIH) defines precision medicine (previously referred to as personalized medicine) as “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment and lifestyle.” Advances in precision medicine presage similar progress in dentistry and will be increasingly harnessed to improve dental care. This article discusses some of the ongoing and projected developments in health information technology, clinical diagnosis frameworks, biomedicine and biotechnology and highlights their current and future applications in precision dentistry. Innovations in artificial intelligence, machine learning, high-throughput sequencing and other molecular techniques (e.g., genomics, metabolomics, pharmacogenomics and transcriptomics) may be fully incorporated into the clinic within the next few decades. Nevertheless, it is imperative to understand that while technology usage can enhance the rate at which clinical success can be achieved, it does not equate to or guarantee clinical success. As dentistry transitions toward a data-augmented model that customizes treatment options, including preventive care, precision dentistry will continue to benefit from advances in many fields to improve health care delivery and clinical outcomes.
Keywords: Precision dentistry, periodontics, orthodontics, oral cancers, big data
In the 2021 executive summary “Oral Health in America: Advances and Challenges,” the National Institutes of Health (NIH) states that “although microbial infections continue to be the primary cause of the most prevalent oral diseases, profound disparities in the experience of these diseases persist and can be explained only in terms of a complex interplay among risk factors and social determinants.” Precision dentistry (also referred to as augmented or individualized dentistry) is an emerging revolutionary model of treatment that proposes to customize oral health care based on the individual’s unique genetic, environmental and behavioral profiles. 1 The precision dentistry model goes beyond traditional patient care with similar clinical exams or phenotypes by attempting to understand the patient as a whole. Thus, a successful clinical outcome applying precision dentistry results from a combination of the patient’s treatment delivery, genetics, social and physical environment and behavior/ compliance. Given the advances in health information technology, computational power and versatility, innovative highthroughput sequencing and “omic” analyses (i.e., genomics, metabolomics, pharmacogenomics and transcriptomics) and an improved understanding of periodontal and craniofacial bone biology beyond phenotypic representation, precision dentistry is fast becoming a reality. This article discusses some of the ongoing and projected developments in health information technology, clinical diagnosis frameworks, biomedicine and biotechnology as well as highlighting the current and future applications in precision dentistry.
Data-Derived Dentistry
Dental appointments are primarily viewed as wellness checks, and recurring, nonemergency visits help establish and collect background information on the patient’s oral and overall health. 1 Dentistry is a dynamic network for data (FIGURE 1). Optimal treatments based on the patient’s medical history, genetics, environment and lifestyle can then be generated. Clinical head, neck and oral diagnostic exams open a window into the patient’s systemic health information based on signs of “pre-diseases” and ongoing oral health issues. 1 Chairside oral and systemic health tests (e.g., SARS CoV-2 diagnostic test, subgingival microbiome analysis) use saliva and oral fluids such as gingival crevicular fluid to establish dynamic biomarker profiles, which may enable early detection of disease and further provide decision-making information to improve upon current diagnostic, prognostic and management of care. 2 Other sources of data include eHealth records, surveys, lab tests, social media and even datagenerating devices, such as wearables or sensors. 3 When dentists collect and factor health data into their clinical care decisions, clinical success rates will increase because a comprehensive realtime assessment of the patient’s dynamic health profile can be readily performed. Thus, shared health care data will aid in delivering optimal, individualized care.
The evolution of economic, demographic and epidemiologic facets and advances in technology in the past century have shifted the population toward preventive measures and personalized care. As population health transforms into precision health and dentistry, availability and access to records among all health care providers for one patient become increasingly necessary for optimal treatment decisions. Comprehensive and continuous monitoring of a patient’s health involving different medical and dental disciplines enhances the clinical success of a planned treatment procedure.
However, while the concept of precision dentistry holds incredible potential, there is an educational divide that makes its application difficult for most practicing dentists. Many dentists are not formally trained in “omics” analysis or the practice of caries management by risk assessment (CAMBRA) that factor social health determinants into clinical care decisions. 5,6 As dental care transitions from a surgical, population-based model toward a medical, personalized model that customizes treatment options and enhances the opportunity for preventive care, it is imperative that teaching institutions consider further or additional training in some areas as well as switching to a centralized health care management platform where providers from different major health care systems can readily access the same health information data (e.g., Epic, Epic Systems Corporation). Implementing a comprehensive, dynamic network of data will facilitate the exchange of data between providers for improved patient care and leverage datadriven research into links between dental and systemic health. 3
Examples of Precision Dentistry in Clinical Success
Precision dentistry is not a new concept. Some current examples of precision dentistry in periodontics, orthodontics and oral medicine/oncology are discussed.
Periodontics
Tonetti et al. (2018) proposed a case definition that appropriately defined an individual’s periodontitis based on stage and grade. 7 The new framework extended beyond the 1999 classification based on severity to include the disease’s biological characteristics in diagnosis, prognosis and treatment planning. 7 The newly proposed framework splits periodontitis classification into four stages, each of which corresponds to the disease severity and complexity of management. Similar to how the “staging” concept is used in precision oncology to determine the precise condition of a malignant tumor, periodontal staging will transform how oral health clinicians communicate the current extent of periodontitis and more accurately define the state and progression of the disease at different points in time. Staging not only applied the traditional method of classification based on severity and extent of past periodontal destruction and tissue damage, but it also factors in the multidimensional complexity of shortterm suppression of symptoms, long-term management and permanent impacts on functional and aesthetic aspects of the patient’s dentition. 7 Periodontitis staging, therefore, enables individualized patient care and represents a crucial step toward precision care in dentistry.
Within each periodontitis staging, each individual’s level of severity and complexity of management may progress at different rates, have different risk factors for progression and may or may not affect the patient’s systemic health. 7,8 Thus, the 2018 periodontal framework proposed that each “stage” of periodontitis be further classified into “grades” that contain information about the inherent biological nature of the disease. Within each stage, the seriousness and complexity of the disease are greater as the grade increases. Grading a stage of periodontitis helps oral health clinicians estimate the risk of progression and impact on systemic health and guide the appropriate therapeutic approach. Grading also lays the foundation for implementing biomarkers and soft tissue imaging technologies, in conjunction with periodontal probing, to improve early detection of stage I periodontitis, guide selection of stage- and grade-specific drug therapies and ultimately improve the patient’s oral health-related quality of life.
Overall, the framework of staging and grading of periodontitis represented one of the critical implementations of precision dentistry in periodontics. This framework goes beyond the traditional classification of disease based on the severity of periodontal damage by also including the risk and prognosis of future complications. By enabling practitioners to use more signs, symptoms and other associated factors when placing a patient in a diagnostic category, the framework promoted more personalized care for patients and may result in a more favorable clinical outcome. In the context of dentistry as a dynamic network of data, a matrix of periodontitis stage and periodontitis grade will assist oral health clinicians in communicating better with other health professionals and third parties’ eHealth platforms that have had much success with the conceptual use of staging and grading in cancer diagnosis, prognosis and management.
Orthodontics
Jheon et al. (2017) presented emerging advances in digital technology and biomedicine in the promise of customized orthodontic treatment.
Briefly, innovations in digital hardware and software, as well as 3D imaging and printing, are currently being applied to fabricate aligners, retainers and customized orthodontic brackets. As well, smart devices (e.g., to remotely document patient’s retainer wear) are gaining some traction, although it is unclear whether the benefits offset the effort and cost.
Furthermore, the oral microbiome differs dramatically between individuals and even within each individual’s tooth before and during orthodontic treatment. 1 Biomedical research is advancing the understanding of cartilage growth and bone biology, which will be utilized to modify mandibular growth and modulate tooth movement in animal models. This is an exciting time in the field of orthodontics.
Oral Cancers
In 2020, 377,713 new oral cancer cases were diagnosed globally, with 177,757 deaths and a five-year mortality rate of 39% to 65%, making oral cancer the sixth most common cancer. 11 Between 80% and 90% of all oral cancers were squamous cell carcinomas that appeared most frequently around the tongue, followed by the floor of the mouth, buccal mucosa, alveolar mucosa and hard palate. And 10% to 20% of oral cancers were human papilloma virus (HPV)- associated carcinomas that manifested on the tonsil and the oropharynx. In the U.S., oropharyngeal cancer has now surpassed cervical cancer as the most common site of HPV-induced cancer. 11,12
Despite being a significant risk factor, HPV-16 infection alone does not warrant the development of oropharyngeal and tonsil cancer in all individuals. 13 Conversely, despite the success of campaigns for tobacco cessation, a known significant risk factor in the development of oral squamous cell carcinomas, there remains a significant trend of increased tongue and oropharyngeal cancers with unknown or unclear causes. 13,14 Zhu et al. (2018) performed meta-analysis and confirmed that patients with clinically similar head and neck tumors have different responses to treatment and different clinical outcomes. 15 Thus, oral cancers possess complex growth, regulation and metastatic processes that are dependent on each individual’s unique environmental background and genetic predisposition. 16,17
A comprehensive oral and head examination is essential for health care. Many suspicious lesions are identified through visualization via incisional or excisional biopsy. To date, surgical biopsies are the most common diagnostic methods for oral cancers despite ~20% of these biopsies being unusable due to technical errors. 18 Moreover, tissue damage created by the biopsy may promote inflammation, which alters the microenvironment and may enhance the invasive nature of oral cancers. Thus, many noninvasive biopsies are being considered, such as liquid and radiologic imaging.
Liquid biopsies in oral cancers show much promise. Biomarkers in oral cavity fluids such as saliva have been associated with a tumor’s unique characteristics (e.g., tumor dimension, pattern, degree of invasion). 20 Salivary biopsy can show the dynamics of specific biomarkers over time, which in turn can be used by clinicians to diagnose, monitor and customize treatment. For example, the Viome saliva test was developed and approved by the Food and Drug Administration to screen for oral squamous cell carcinoma and oropharyngeal cancer. Using machine learning and an RNA signature that incorporates taxonomic and functional oral microbiomes related to oral cancer, this test can spot early signs of stage 1 oral cancer with a sensitivity of over 93% and a specificity of 97.9%.
Another noninvasive, diagnostic modality called radiomics uses mathematically defined parameters to generate quantitative diagnostic and prognostic biomarkers from clinical images (e.g., computed tomography, positron emission tomography, magnetic resonance imaging). 22 When combined with traditional clinical predictors, radiomics can help advance oral cancer diagnosis toward more personalized precision care. In particular, radiomics utilizes recent advancements in computational power, machine learning and artificial intelligence to capture various properties of head and neck squamous cell carcinomas. This information predicts the current and future morphologic, metabolic and spatial aspects of the primary tumor and metastatic lymph nodes, ultimately increasing the chance for favorable treatment outcomes. To date, only a handful of studies on the application of radiomics in oral cancer have been published, as radiomics is still being evaluated and validated.
Advancing Treatment of Oral Cancers
Current treatment options for patients with oral cancer mainly consist of initial surgeries followed by radiation and chemotherapy. 24 Each of these therapies has several side effects, and even when combined, a significant number of patients still experience disease recurrence and metastasis with mortality in less than 12 months. 25 Oral cancer tumors eventually resist available pharmacological regimens. 26 To more effectively prevent and treat oral squamous cell carcinoma and oropharyngeal cancers, scientists and clinicians have been investigating novel pharmacogenomic therapy targets, alternative treatment modalities and expanding the role of oral health primary care clinicians in HPV vaccination and HPV-related oral cancer protection.
Epidermal growth factor receptor (EGFR) is often expressed in oral squamous cell carcinoma and is one of the most popular targets for antitumor pharmacology. However, as discussed previously, many tumors inevitably become resistant to anti-EGFR therapy over time. 26 The search for novel targets for pharmacogenomic therapy becomes more crucial than ever. A tumor sequencing effort by The Cancer Genome Atlas (TCGA) program remarkably revealed a few conserved molecular signaling networks among cells affected by oropharyngeal and oral squamous cell carcinomas; one of such is the downstream PI3K/mTOR signaling pathway. 27 This discovery provides the rationale for further studies in the clinical effectiveness of PI3K/mTOR inhibitors. One example of such studies is rapamycin, a neoadjuvant therapy that inhibits PI3K/ mTOR activity and shrinks the tumor before physical removal by surgery. Another ongoing study investigates the use of metformin, which indirectly blocks mTOR activities and prevents the progression of premalignant lesions to full-blown oral squamous cell carcinoma.
In addition to finding novel molecular targets, a new alternative treatment modality known as immunotherapies draws on the potential reactivation of the patient’s antitumor immune response. Head and neck squamous cell carcinoma cells, in particular, often avoid immune recognition and antitumor immune response through manipulation of their immunogenicity, production of immunosuppressive mediators (e.g., IL-6, IL-10 and TGF-ß) and promotion of immunomodulatory cell types (e.g., immunosuppressive T-regs and M2 tumorassociated macrophage). 30 The recent development of new immunotherapeutic agents, such as pembrolizumab and nivolumab, has demonstrated the capability of inhibiting tumor activity by reactivating the patient’s T-cell antitumor response in 13% to 20% of head and neck cancer patients. 31 The full potential of precision care using immunotherapy may become a reality in only a few years, as more and more biomarkers and their associated molecular mechanisms are identified.
Genome Editing
HPV-16 is responsible for more than 80% of HPV-induced new cases of oropharyngeal cancer per year. 32 Continuous efforts in investigating the molecular alterations in HPV-induced oropharyngeal cancer revealed that the virus replicates differently in oral keratinocytes compared to the cervical site of infection. Specifically, > 70% of HPV-16+ head and neck cancer cells replicate autonomously as an episomal genome. In contrast, the viral genome often integrates into the host’s genome in HPV-16 positive cervical cancer. Specific alternative transcripts, such as the dominant variant E6*I, are responsible for the induction of cellular oxidative stress, uniquely expressed in HPV-related cancer, and not observed in any other types of tumors. 33 Such findings pave the way for the development of new pharmacologic and genome editing therapies, which directly target these unique regions and either reduce the viral load by promoting apoptosis in HPVinfected head and neck cancer cell lines or enhancing the sensitivity of these cells to available pharmacogenomic and immunotherapies. One extensively used genome editing technology is the clustered regularly interspaced short palindromic repeats (CRISPR) and their associated proteins (Cas proteins). Yee et al. used CRISPR/Cas9 technology to discover new signature regions of the Hippo signaling pathway associated with biomarkers of favorable response toward PI3K/mTOR immunotherapy in oral carcinoma cell lines. 34 Zeng et al. (2022) used CRISPR/ Cas9 to screen for genomic regions, also in cell lines, that can compensate and enhance the sensitivity of previously tumor-resistant EGFR-targeting pharmacogenomic therapies. 35 Efforts will be made to utilize these data to improve upon current clinical treatment.
HPV Vaccinations by a Dental Professional
Vaccinations are the primary prevention method to protect patients against HPV infection and HPV-induced oral cancers. Bleacher et al. (2016) confirmed that vaccination against HPV is 83% effective among women with no prior HPV exposure, 58% among women with previous HPV exposure and 25% among women with active cervical HPV- 16/18. 36 The Centers for Disease Control and Prevention (CDC) recommends two doses of vaccines between six to 12 months apart before age 15 for maximum preventive effectiveness. For older teens and adults, the CDC guidelines recommend three doses. Unfortunately, the overall vaccination rate in U.S. adolescents with the two- or three-dose series remains relatively low at 48.6%. Strauss et al. (2012) indicated that of the children and adults who did not visit a primary care practitioner in 2008, approximately 34.7% of these children and 23.1% of adults did visit a dental health provider in the same year. For these reasons, dentists should be crucial providers recommending up-to-date HPV vaccination and discussing the risk of HPV-related oral cancers. To support this cause, the American Dental Association (ADA) recently published guidelines suggesting an expanded role for dental professionals in HPV vaccination and HPV-related oral cancer education and counseling. We included this discussion on vaccinations because the next “golden age” in vaccinology will be to personalize vaccinations based on the subject’s age, sex, comorbidity, immune system and genetic background rather than a one-size- fits-all approach.
The Mouth Is the Window Into Overall Health 42
The oral cavity is the point of entry of nutrients and many toxins and pathogens. 43 It is bathed in fluids, such as saliva and gingival crevicular fluid, and houses > 700 bacterial species of bacteria, viruses, fungi and protozoa. Collecting and acting on the data available in the oral cavity could be a game changer for a patient’s health. The presence of specific, dynamic, liquidbased biomarkers secreted by tissues and resident microbes, such as active MMP-8 signifying the beginning of inflammation in gingival tissues, can help identify the critical transition from health baseline to a diseased state. Additionally, dysbiosis of the oral ecosystem can serve as early warning signs of oral pathosis, cancer and other systemic health complications.
An example is the distinctive and predictive nature of the oral microbiota in individuals with colorectal cancer who show increased abundance of specific pathogenic oral bacteria (e.g., F. nucleatum, Streptococcus, Peptostreptococcus stomatis, Actinomyces). Additionally, the concentration of Fusobacterium nucleatum is more abundant in individuals with inflammatory bowel disease. Current tests that screen for colorectal cancer, including the fecal immune test and the fecal occult blood test, have low sensitivity for early detection.
Oral bacteria may infect the brain via branches of the trigeminal nerve. 49 The presence of oral bacteria such as P. gingivalis and their associated byproduct secretions in the brain may result from septic infections where bacteria successfully cross the blood-brain barrier to affect brain function and promote the pathogenesis of brain-related diseases such as Alzheimer’s. Mechanisms into how dysbiosis of the oral microbiome can affect the development of systemic diseases are currently being uncovered. With such knowledge, many therapies that alter the oral microbiome, such as phototherapy and prebiotic/probiotic therapies, can improve the prognosis and treatment outcome of these pathologies.
The bidirectional relationship between oral pathologic conditions and overall health is often overlooked. Many systemic diseases such as AIDS and Sjögren’s syndrome may first manifest as mouth lesions or conditions such as dry mouth and gingivitis. Moreover, periodontitis is significantly linked to other systemic health problems, such as diabetes and cardiovascular disease. Pregnant people with periodontitis have shown a higher risk of premature birth and/or delivery of infants with lower birth weight.
Oral epidemiologic surveillance data is a cost-effective and noninvasive way to identify social determinants of health, like poverty, health literacy and access to care, which manifest in predictive overall health outcomes. Thus, all primary care providers, including dentists, should collaborate to identify all possible risk factors or early warning signs of disease to maximize the preventive aspects and deliver the care patients need.
The Promise of Artificial Intelligence
The past 10 years have marked the spectacular development and breakthrough of artificial intelligence (AI) and machine learning (ML), from how data is acquired to the methodology of data storage, processing and analysis.AI and ML have tremendous potential to optimize patient care by revolutionizing dental diagnostic and treatment approaches. For example, AI and ML have shown great potential in detecting caries, abnormal lesions and identifying abnormal anatomical structures from radiographs. Another promising application of AI and ML is to guide the clinical decision-making process. Orthodontists, for example, can utilize AI and ML in their treatment planning strategies to accurately determine the need for tooth extractions before orthodontic therapy. 56 Likewise, endodontists can optimize clinical outcomes of endodontic treatment by considering trends of morphological variations identified by deep-learning algorithms.
While technology can enhance the rate at which clinical success can be achieved, the actual clinical decision still needs to be made by the clinician. This is due to safety and accountability, the potential lack of AI algorithm transparency and confidentiality and privacy rules. To ensure the safety of patients, the FDA recently formulated a new drug category, Software as Medical Device, to regulate medical service companies that use AI and ML to make or suggest clinical decisions. This is necessary because the laws are unclear about who will be held responsible for the consequences of decisions made by AI technology. Transparency of AI algorithms and data may also lead to problems, as the intentional lack of transparency of AI algorithms from the software providers, called black-box AI, coupled with poorly processed and/or analyzed data by the AI system can repeatedly result in poor clinical decisions and place the blame on clinicians who utilize these services. 59 Lastly, AI algorithms must be trained with personal data from patients. However, because of confidentiality and privacy concerns, these data must be anonymized, which prompts incertitude in the health care community about secure data sharing and the validity of the data sets used. AI and ML should always be complementary and not replace the health providers’ clinical decisions. Thus, rather than “artificial” intelligence, health care professionals, including dentists, should start considering these systems as “augmented decision-making” intelligence.
Conclusion
Precision dentistry is an emerging revolutionary model of treatment that proposes to customize oral health care based on the individual’s unique genetic, environmental and behavioral profiles. By considering each patient’s biology, historical records, current systemic conditions, socioeconomic status and compliance, the delivery of dental care will be customized and optimized. Dentistry will play an important and expanded role in precision health care delivery.
