The Clinical Potential of Oral Microbiota as a Screening Tool for Oral Squamous Cell Carcinomas

Salivary Microbiome Relates to Neoadjuvant Immunotherapy Response in OSCC

Most patients diagnosed with oral squamous cell carcinoma (OSCC) present with locally advanced stages, which are typically associated with poor outcomes. Although immunotherapy offers potential improvements in patient survival, its efficacy is hampered by low response rates. The microbiome is widely involved in tumor immunity and may play a role in immunotherapy. This study aimed to investigate the potential association between the oral (salivary) microbiome and immunotherapy response in patients with OSCC. Salivary metagenome sequencing was performed on 47 patients with OSCC undergoing neoadjuvant immunotherapy (NAIT) in a clinical trial (NCT04649476). Patients were divided into responders and nonresponders based on their pathological responses. The results showed that the species richness of the salivary microbiome was lower in the nonresponders before NAIT than in the responders. Differential analysis revealed that nonresponders exhibited a lower relative abundance of 34 bacterial species and a higher relative abundance of 4 bacterial species. Notably, low levels of Eubacterium infirmum, Actinobaculum, and Selenomas (EAS) in the saliva may be associated with the nonresponse of patients with OSCC to NAIT. A nomogram based on EAS was developed and validated to determine the efficacy of NAIT. The area under the curve for the training cohort was 0.81 (95% confidence interval, 0.66 to 0.81). Quantitative polymerase chain reaction confirmed that low levels of salivary EAS effectively identified nonresponders to NAIT. Furthermore, the low abundance of salivary EAS was closely correlated with a low density of intratumoral CD4+, CD14+, CD68+, and FOXP3+ cells. Metabolic functional annotation revealed numerous biosynthetic processes associated with EAS that were more active in responders. In summary, this study provides valuable data resources for the salivary microbiome and reveals that nonresponders have different salivary microbiome profiles than responders do before NAIT. Low salivary EAS levels can serve as potential biomarkers for distinguishing nonresponders from responders.

The intratumor microbiome varies by geographical location and anatomical site in head and neck squamous cell carcinoma

Head and Neck Squamous Cell Carcinoma (HNSCC) is a highly heterogeneous cancer that is characterized by distinct phenotypes based on anatomical site and etiological agents. Recently, the intratumor microbiome has been implicated in cancer pathogenesis and progression. Although it is well established that the gut microbiome varies with geographical location and is highly influenced by factors such as diet, environment, and genetics, the intratumor microbiome is not very well characterized. In this review, we aim to characterize the HNSCC intratumor microbiome by geographical location and anatomical site. We conducted a review of primary literature from PubMed and assessed studies based on relevancy and recency. To the best of our knowledge, we are the first to comprehensively examine the tumor microenvironment of HNSCC with respect to these two primary factors on a large scale. Our results suggest that there are unique bacterial and fungal biomarkers for HNSCC for each of the following geographical locations: North America, Asia, Europe, Australia, and Africa. We also identified a panel of microbial biomarkers that are unique to two primary HNSCC anatomic sites, as well as microbial biomarkers associated with various etiological agents of HNSCC. Future study of these microbes may improve HNSCC diagnostic and therapeutic modalities by accounting for differences based on geographic regions and anatomical sites.

A review of machine learning methods for cancer characterization from microbiome data

Recent studies have shown that the microbiome can impact cancer development, progression, and response to therapies suggesting microbiome-based approaches for cancer characterization. As cancer-related signatures are complex and implicate many taxa, their discovery often requires Machine Learning approaches. This review discusses Machine Learning methods for cancer characterization from microbiome data. It focuses on the implications of choices undertaken during sample collection, feature selection and pre-processing. It also discusses ML model selection, guiding how to choose an ML model, and model validation. Finally, it enumerates current limitations and how these may be surpassed. Proposed methods, often based on Random Forests, show promising results, however insufficient for widespread clinical usage. Studies often report conflicting results mainly due to ML models with poor generalizability. We expect that evaluating models with expanded, hold-out datasets, removing technical artifacts, exploring representations of the microbiome other than taxonomical profiles, leveraging advances in deep learning, and developing ML models better adapted to the characteristics of microbiome data will improve the performance and generalizability of models and enable their usage in the clinic.

Salivary Metabolites Produced by Oral Microbes in Oral Diseases and Oral Squamous Cell Carcinoma: A Review

In recent years, salivary metabolome studies have provided new biological information and salivary biomarkers to diagnose different diseases at early stages. The saliva in the oral cavity is influenced by many factors that are reflected in the salivary metabolite profile. Oral microbes can alter the salivary metabolite profile and may express oral inflammation or oral diseases. The released microbial metabolites in the saliva represent the altered biochemical pathways in the oral cavity. This review highlights the oral microbial profile and microbial metabolites released in saliva and its use as a diagnostic biofluid for different oral diseases. The importance of salivary metabolites produced by oral microbes as risk factors for oral diseases and their possible relationship in oral carcinogenesis is discussed.

Identification of consensus head and neck cancer-associated microbiota signatures: a systematic review and meta-analysis of 16S rRNA and The Cancer Microbiome Atlas datasets

Introduction. Multiple reports have attempted to describe the tumour microbiota in head and neck cancer (HNSC).Gap statement. However, these have failed to produce a consistent microbiota signature, which may undermine understanding the importance of bacterial-mediated effects in HNSC.Aim. The aim of this study is to consolidate these datasets and identify a consensus microbiota signature in HNSC.Methodology. We analysed 12 published HNSC 16S rRNA microbial datasets collected from cancer, cancer-adjacent and non-cancer tissues to generate a consensus microbiota signature. These signatures were then validated using The Cancer Microbiome Atlas (TCMA) database and correlated with the tumour microenvironment phenotypes and patient's clinical outcome.Results. We identified a consensus microbial signature at the genus level to differentiate between HNSC sample types, with cancer and cancer-adjacent tissues sharing more similarity than non-cancer tissues. Univariate analysis on 16S rRNA datasets identified significant differences in the abundance of 34 bacterial genera among the tissue types. Paired cancer and cancer-adjacent tissue analyses in 16S rRNA and TCMA datasets identified increased abundance in Fusobacterium in cancer tissues and decreased abundance of Atopobium, Rothia and Actinomyces in cancer-adjacent tissues. Furthermore, these bacteria were associated with different tumour microenvironment phenotypes. Notably, high Fusobacterium signature was associated with high neutrophil (r=0.37, P<0.0001), angiogenesis (r=0.38, P<0.0001) and granulocyte signatures (r=0.38, P<0.0001) and better overall patient survival [continuous: HR 0.8482, 95 % confidence interval (CI) 0.7758-0.9273, P=0.0003].Conclusion. Our meta-analysis demonstrates a consensus microbiota signature for HNSC, highlighting its potential importance in this disease.

Artificial intelligence in salivary biomarker discovery and validation for oral diseases

Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.

Mechanisms and Potential Clinical Implications of Oral Microbiome in Oral Squamous Cell Carcinoma

Microorganisms in the oral cavity are abundant in the human body. At present, more than 700 species of oral microorganisms have been identified. Recently, a lot of literature has indicated that the oral microbiota plays an important role in the occurrence, development, and prognosis of oral squamous cell carcinoma (OSCC) through various mechanisms. And researchers are now trying to utilize oral microbiota in cancer diagnosis and treatment. However, few articles systematically summarize the effects of oral microbes in the diagnosis, treatment, and disease outcomes of oral cancer. Herein, we made a summary of the microbial changes at cancerous sites and placed more emphasis on the mechanisms by which the oral microbiome promotes cancerization. Moreover, we aimed to find out the clinical value of the oral microbiome in OSCC.

Experimental Modeling of Host-Bacterial Interactions in Head and Neck Squamous Cell Carcinoma

The microscopic species colonizing the human body, collectively referred to as the microbiome, play a crucial role in the maintenance of tissue homeostasis, immunity, and the development of disease. There is evidence to suggest associations between alterations in the microbiome and the development of head and neck squamous cell carcinomas (HNSCC). The use of two-dimensional (2D) modeling systems has made significant strides in uncovering the role of microbes in carcinogenesis; however, direct mechanistic links remain in their infancy. Patient-derived three-dimensional (3D) HNSCC organoid and organotypic models have recently been described. Compared to 2D models, 3D organoid culture systems effectively capture the genetic and epigenetic features of parent tissue in a patient-specific manner and may offer a more nuanced understanding of the role of host-microbe responses in carcinogenesis. This review provides a topical literature review assessing the current state of the field investigating the role of the microbiome in HNSCC; including in vivo and in vitro modeling methods that may be used to characterize microbiome-epithelial interactions.

The Association of Oral Microbiome Dysbiosis with Gastrointestinal Cancers and Its Diagnostic Efficacy

BACKGROUND

The second leading mortality cause in the world is cancer, making it a critical issue that impacts human health. As a result, scientists are looking for novel biomarkers for cancer detection. The oral microbiome, made up of approximately 700 species-level taxa, is a significant source for discovering novel biomarkers. In this review, we aimed to prepare a summary of research that has investigated the association between the oral microbiome and gastrointestinal cancers.

METHODS

We searched online scientific datasets including Web of Science, PubMed, Scopus, and Google Scholar. Eligibility criteria included human studies that reported abundances of the oral microbiome, or its diagnostic/prognostic performance in patients with gastrointestinal cancers.

RESULTS

Some phyla of the oral microbiome have a relationship with cancers. Some particular phyla of the oral microbiome that may be related to gastrointestinal cancers consist of Firmicutes, Actinobacteria, Bacteroidetes, Proteobacteria, and Fusobacteria. Changes in the abundances of Porphyromonas, Fusobacterium, Prevotella, and Veillonella are correlated with carcinogenesis, and may be used for distinguishing cancer patients from healthy subjects. Oral, colorectal, pancreatic, and esophageal cancers are the most important cancers related to the oral microbiome.

CONCLUSION

The results of this study may help future research to select bacteria as an early diagnostic or prognostic biomarker of gastrointestinal cancer. Given the current state of our knowledge, additional research is required to comprehend the multiplex processes underlying the role of bacterial microbiota upon cancer progression and to characterize the complex microbiota-host interaction network.

Influence of pathogens on host genome and epigenome in development of head and neck cancer

BACKGROUND

Head and neck cancer (HNSCC) is a heterogeneous group of cancers, affecting multiple regions such as oral cavity, pharynx, larynx, and nasal region, each showing a distinct molecular profile. HNSCC accounts for more than 6 million cases worldwide, soaring mainly in the developing countries.

RECENT FINDINGS

The aetiology of HNSCC is complex and multifactorial, involving both genetic and environmental factors. The critical role of microbiome, which includes bacteria, viruses, and fungi, is under spotlight due to the recent reports on their contribution in the development and progression of HNSCC. This review focuses on the effect of opportunistic pathogens on the host genome and epigenome, which contributes to the disease progression. Drawing parallels from the host-pathogen interactions observed in other tumour types arising from the epithelial tissue such as colorectal cancer, the review also calls attention to the potential explorations of the role of pathogens in HNSCC biology and discusses the clinical implications of microbiome research in detection and treatment of HNSCC.

CONCLUSION

Our understanding of the genomic effects of the microbes on the disease progression and the mechanistic insights of the host-pathogen interaction will pave way to novel treatment and preventive approaches in HNSCC.

Oral Microbiota: The Influences and Interactions of Saliva, IgA, and Dietary Factors in Health and Disease

Recent advances in metagenomic analyses have made it easier to analyze microbiota. The microbiota, a symbiotic community of microorganisms including bacteria, archaea, fungi, and viruses within a specific environment in tissues such as the digestive tract and skin, has a complex relationship with the host. Recent studies have revealed that microbiota composition and balance particularly affect the health of the host and the onset of disease. Influences such as diet, food preferences, and sanitation play crucial roles in microbiota composition. The oral cavity is where the digestive tract directly communicates with the outside. Stable temperature and humidity provide optimal growth environments for many bacteria. However, the oral cavity is a unique environment that is susceptible to pH changes, salinity, food nutrients, and external pathogens. Recent studies have emphasized the importance of the oral microbiota, as changes in bacterial composition and balance could contribute to the development of systemic diseases. This review focuses on saliva, IgA, and fermented foods because they play critical roles in maintaining the oral bacterial environment by regulating its composition and balance. More attention should be paid to the oral microbiota and its regulatory factors in oral and systemic health.

Specific Oral Microbial Differences in Proteobacteria and Bacteroidetes Are Associated with Distinct Sites When Moving from Healthy Mucosa to Oral Dysplasia-A Microbiome and Gene Profiling Study and Focused Review

Oral potentially malignant disorders (OPMDs) are a group of conditions that carry a risk of oral squamous cell carcinoma (OSCC) development. Recent studies indicate that periodontal disease-associated pathogenic bacteria may play a role in the transition from healthy mucosa to dysplasia and to OSCC. Yet, the microbial signatures associated with the transition from healthy mucosa to dysplasia have not been established. To characterize oral microbial signatures at these different sites, we performed a 16S sequencing analysis of both oral swab and formalin-fixed, paraffin-embedded tissue (FFPE) samples. We collected oral swabs from healthy mucosa (from healthy patients), histologically normal mucosa adjacent to dysplasia, and low-grade oral dysplasia. Additionally, FFPE samples from histologically normal mucosa adjacent to OSCC, plus low grade and high-grade oral dysplasia samples were also collected. The collected data demonstrate significant differences in the alpha and beta microbial diversities of different sites in oral mucosa, dysplasia, and OSCC, as well as increased dissimilarities within these sites. We found that the Proteobacteria phyla abundance increased, concurrent with a progressive decrease in the Firmicutes phyla abundance, as well as altered levels of Enterococcus cecorum, Fusobacterium periodonticum, Prevotella melaninogenica, and Fusobacterium canifelinum when moving from healthy to diseased sites. Moreover, the swab sample analysis indicates that the oral microbiome may be altered in areas that are histologically normal, including in mucosa adjacent to dysplasia. Furthermore, trends in specific microbiome changes in oral swab samples preceded those in the tissues, signifying early detection opportunities for clinical diagnosis. In addition, we evaluated the gene expression profile of OSCC cells (HSC-3) infected with either P. gingivalis, T. denticola, F. nucelatum, or S. sanguinis and found that the three periodontopathogens enrich genetic processes related to cancer progression, including skin keratinization/cornification, while the commensal enriched processes related to RNA processing and adhesion. Finally, we reviewed the dysplasia microbiome literature and found a significant decrease in commensal bacteria, such as the Streptococci genus, and a simultaneous increase in pathogenic bacteria, mainly Bacteroidetes phyla and Fusobacterium genus. These findings suggest that features of the oral microbiome can serve as novel biomarkers for dysplasia and OSCC disease progression.

No Clear Clustering Dysbiosis from Salivary Microbiota Analysis by Long Sequencing Reads in Patients Affected by Oral Squamous Cell Carcinoma: A Single Center Study

BACKGROUND

Advancements in DNA sequencing technology have facilitated the assessment of the connection between the oral microbiome and various diseases. The aim of the present study was to investigate the salivary microbiota composition employing for the first time in the literature the Oxford Nanopore Technology in patients affected by oral squamous cell carcinoma (OSCC).

METHODS

Unstimulated saliva samples of 31 patients were collected (24 OSCC patients and 7 controls). DNA was extracted using the QIAamp DNA Blood Kit and metagenomic long sequencing reads were performed using the MinION device.

RESULTS

In the OSCC group, 13 were males and 11 were females, with a mean age of 65.5 ± 13.9 years; in the control group, 5 were males and 2 were females, with a mean age of 51.4 ± 19.2 years. The border of the tongue was the most affected OSCC site. The microorganisms predominantly detected in OSCC patients were Prevotella, Chlamydia, Tissierellia, Calothrix, Leotiomycetes, Firmicutes and Zetaproteobacteria.

CONCLUSIONS

This study confirmed the predominance of periodontopathic bacteria in the salivary microbiome in the OSCC group. If a direct correlation between oral dysbiosis and OSCC onset was proven, it could lead to new prevention strategies and early diagnostic tools.

Systematic review on oral microbial dysbiosis and its clinical associations with head and neck squamous cell carcinoma

OBJECTIVES

The relationship between head and neck squamous cell carcinoma (HNSCC) and the oral microbiome has been drawn in various studies. Microbial diversities, microbiome profiles, metagenomic analysis, and host-pathogen interactions were collected from these studies to highlight similarities and account for inconsistencies. We also evaluate the possible clinical applications of the microbiome regarding screening and diagnosis of HNSCC.

METHODS

Systematic analysis of studies regarding HNSCC and the microbiome was done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. Articles were retrieved from four databases (PubMed, ScienceDirect, CUHK Full-Text Journals, and Cochrane database) and were screened using predefined criteria.

RESULTS

Twenty studies were chosen after screening for full-text review. α-diversity comparison was inconsistent whereas β-diversity between HNSCC and normal samples showed distinct clustering. Microbial dysbiosis characterized by change in the relative abundances of several bacterial species were also seen in HNSCC patients. At a phylum level, inconsistencies were seen between studies using HNSCC tumor tissue samples and saliva samples. At a genus level, Fusobacterium, Peptostreptococcus, Alloprevotella, Capnocytophaga, Catonella, and Prevotella were differentially enriched in HNSCC while Streptococcus, Actinomyces Veillonella, and Rothia were differentially depleted. Co-occurrence network analysis revealed a positive correlation of HNSCC with periodontal pathogens and a negative correlation with commensal bacteria. Metagenomic analysis of microbiota revealed a differential enrichment of pro-inflammatory genomic pathways which was consistent across various studies. Microbial dysbiosis was applied in clinical use as a tool for HNSCC screening. Random-forest analysis was adopted to differentiate between tumor and normal tissue, at 95.7% and 70.0% accuracies respectively in two studies. Microbial dysbiosis index was also used to predict prognosis.

CONCLUSIONS

Oral microbial dysbiosis could be a promising tool for HNSCC screening and diagnosis. However, more research should be conducted pertaining to clinical applications to improve diagnostic accuracy and explore other clinical uses.

A decade of progress: bibliometric analysis of trends and hotspots in oral microbiome research (2013-2022)

Background

Over the past decade, a plethora of studies have delved into the oral microbiome. Our objective was to evaluate the trends in oral microbiome research employing a quantitative approach.

Materials and methods

We extracted clinical studies on the oral microbiome published between 2013 and 2022 from the Web of Science database, yielding 3024 articles. The assembled literature was visually scrutinized using VOSviewer 1.6.18, Citespace 6.1.6, Pajek, Scimago Graphica, and other specialized software to assess authors, institutions, countries, journals, co-cited literature, keywords, genes, and diseases.

Results

Our analysis identified a total of 3024 articles. The volume and rate of annual publications steadily increased, with research interest in the oral microbiome progressively intensifying. The United States, China, and the UK contributed the highest number of publications. Growth rates of publications varied among countries over time. The Forsyth Institute emerged as the most collaborative institution, boasting the highest number of relevant papers (135) and securing the top rank, followed by Sichuan University and Harvard University. Paster Bruce J, Zhou Xuedong, and He Xuesong were pioneers in the field of oral microbiome research. This analysis demonstrates that the homeostatic balance of the oral microbiome, advanced microbial sequencing technology, connections with gut microbiota, and tumorigenesis, including oral cancer, have become emerging topics in the oral microbiome field.

Conclusions

This study delineated a comprehensive landscape of hotspots and frontiers in oral microbiome research, thus facilitating the identification of interdisciplinary advancements. We sincerely hope that our bibliometric analysis will enable researchers to leverage the oral microbiome to ultimately improve human oral health.

The interaction between innate immunity and oral microbiota in oral diseases

INTRODUCTION

Innate immunity serves as the frontline to combat invading pathogens. Oral microbiota is the total collection of microorganisms colonized within the oral cavity. By recognizing the resident microorganisms through pattern recognition receptors, innate immunity is capable of interacting with oral microbiota and maintaining homeostasis. Dysregulation of interaction may lead to the pathogenesis of several oral diseases. Decoding the crosstalk between oral microbiota and innate immunity may be contributory to developing novel therapies for preventing and treating oral diseases.

AREAS COVERED

This article reviewed pattern recognition receptors in the recognition of oral microbiota, the reciprocal interaction between innate immunity and oral microbiota, and discussed how the dysregulation of this relationship leads to the pathogenesis and development of oral diseases.

EXPERT OPINION

Many studies have been conducted to illustrate the relationship between oral microbiota and innate immunity and its role in the occurrence of different oral diseases. The impact and mechanisms of innate immune cells on oral microbiota and the mechanisms of dysbiotic microbiota in altering innate immunity are still needed to be investigated. Altering the oral microbiota might be a possible solution for treating and preventing oral diseases.

Saliva - a new opportunity for fluid biopsy

Saliva is a complex biological fluid with a variety of biomolecules, such as DNA, RNA, proteins, metabolites and microbiota, which can be used for the screening and diagnosis of many diseases. In addition, saliva has the characteristics of simple collection, non-invasive and convenient storage, which gives it the potential to replace blood as a new main body of fluid biopsy, and it is an excellent biological diagnostic fluid. This review integrates recent studies and summarizes the research contents of salivaomics and the research progress of saliva in early diagnosis of oral and systemic diseases. This review aims to explore the value and prospect of saliva diagnosis in clinical application.

Microbial dysbiosis in oral squamous cell carcinoma: A systematic review and meta-analysis

Objective

The aim of this study was to summarize previously published data and assess the alterations in the composition of the oral microbiome in OSCC using a systematic review and meta-analysis.

Design

Electronic databases were systematically searched for studies on the oral microbiome in OSCC published before December 2021. Qualitative assessments of compositional variations at the phylum level were performed. The meta-analysis on abundance changes of bacteria genera was performed via a random-effects model.

Results

A total of 18 studies involving 1056 participants were included. They consisted of two categories of studies: 1) case-control studies (n = 9); 2) nine studies that compared the oral microbiome between cancerous tissues and paired paracancerous tissues. At the phylum level, enrichment of Fusobacteria but depletion in Actinobacteria and Firmicutes in the oral microbiome was demonstrated in both categories of studies. At the genus level, Fusobacterium showed an increased abundance in OSCC patients (SMD = 0.65, 95% CI: 0.43-0.87, Z = 5.809, P = 0.000) and in cancerous tissues (SMD = 0.54, 95% CI: 0.36-0.72, Z = 5.785, P = 0.000). The abundance of Streptococcus was decreased in OSCC (SMD = -0.46, 95% CI: -0.88-0.04, Z = -2.146, P = 0.032) and in cancerous tissues (SMD = -0.45, 95% CI: -0.78-0.13, Z = -2.726, P = 0.006).

Conclusions

Disturbances in the interactions between enriched Fusobacterium and depleted Streptococcus may participate in or prompt the occurrence and development of OSCC and could be potential biomarkers for detection of OSCC.

The human oral - nasopharynx microbiome as a risk screening tool for nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a common head and neck cancer with a poor prognosis. There is an urgent need to develop a simple and convenient screening tool for early detection and risk screening of NPC. 139 microbial samples were collected from 40 healthy people and 39 patients with nasopharyngeal biopsy. A total of 40 and 39 oral, eight and 27 nasal cavity, nine and 16 nasopharyngeal microbial samples were collected from the two sets of individuals. A risk screening tool for NPC was established by 16S rDNA sequencing and random forest. Patients with nasopharyngeal biopsy had significantly lower nasal cavity and nasopharynx microbial diversities than healthy people. The beta diversity of the oral microbiome was significantly different between the two groups. The NPC screening tools based on nasopharyngeal and oral microbiomes have 88% and 77.2% accuracies, respectively. The nasopharyngeal biopsy patients had significantly higher Granulicatella abundance in their oral cavity and lower Pseudomonas and Acinetobacter in the nasopharynx than healthy people. This study established microbiome-based non-invasive, simple, no radiation, and low-cost NPC screening tools. Individuals at a high risk of NPC should be advised to seek further examination, which might improve the early detection of NPC and save public health costs.

Oral Microbiota and Tumor-A New Perspective of Tumor Pathogenesis

Microorganisms have long been known to play key roles in the initiation and development of tumors. The oral microbiota and tumorigenesis have been linked in epidemiological research relating to molecular pathology. Notably, some bacteria can impact distal tumors by their gastrointestinal or blood-borne transmission under pathological circumstances. Certain bacteria drive tumorigenesis and progression through direct or indirect immune system actions. This review systemically discusses the recent advances in the field of oral microecology and tumor, including the oncogenic role of oral microbial abnormalities and various potential carcinogenesis mechanisms (excessive inflammatory response, host immunosuppression, anti-apoptotic activity, and carcinogen secretion) to introduce future directions for effective tumor prevention.

Accuracy of artificial intelligence-assisted detection of Oral Squamous Cell Carcinoma: A systematic review and meta-analysis

Oral Squamous Cell Carcinoma (OSCC) is an aggressive tumor with a poor prognosis. Accurate and timely diagnosis is therefore essential for reducing the burden of advanced disease and improving outcomes. In this meta-analysis, we evaluated the accuracy of artificial intelligence (AI)-assisted technologies in detecting OSCC. We included studies that validated any diagnostic modality that used AI to detect OSCC. A search was performed in six databases: PubMed, Embase, Scopus, Cochrane Library, ProQuest, and Web of Science up to 15 Mar 2022. The Quality Assessment Tool for Diagnostic Accuracy Studies was used to evaluate the included studies' quality, while the Split Component Synthesis method was utilized to quantitatively synthesize the pooled diagnostic efficacy estimates. We considered 16 out of the 566 yielded studies, which included twelve different AI models with a total of 6606 samples. The summary sensitivity, summary specificity, positive and negative likelihood ratios as well as the pooled diagnostic odds ratio were 92.0 % (95 % confidence interval [CI] 86.7-95.4 %), 91.9 % (95 % CI 86.5-95.3 %), 11.4 (95 % CI 6.74-19.2), 0.087 (95 % CI 0.051-0.146) and 132 (95 % CI 62.6-277), respectively. Our findings support the capability of AI-assisted systems to detect OSCC with high accuracy, potentially aiding the histopathological examination in early diagnosis, yet more prospective studies are needed to justify their use in the real population.

Comparative Evaluation of the Salivary and Buccal Mucosal Microbiota by 16S rRNA Sequencing for Forensic Investigations

The human microbiome has emerged as a new potential biomarker for forensic investigations with the development of high-throughput sequencing and bioinformatic analysis during the last decade. The oral cavity has many different microbial habitats, with each habit colonized by specific and individualized microbiota. As saliva and buccal mucosa are common biological evidence in forensic science, understanding the differences of microbial communities between the two is important for forensic original identification. Moreover, the oral microbiota is individualized, whereas there are few studies on the application of forensic personal identification that need to be supplemented. In this study, Streptococcus was the most abundant genus, with an average relative abundance of 49.61% in the buccal mucosa, while in the saliva, Streptococcus, Veillonella, and Neisseria had similar proportions (20%, 15%, 16%) and were the dominant genera. The α and β diversity displayed a significant distinctness between the saliva and buccal mucosal groups. The community assembly mechanism stated that the deterministic process played a more significant effect in shaping the salivary bacterial community assembly than buccal mucosa, which explained the microbial differences. Of the test samples, 93.3% can be correctly classified with the random forest model based on the microbial differences. Targeting the low-abundance bacteria at the species level, 52% of experimental participants could be discriminated by using the observed unique bacterial species. In conclusion, the salivary bacterial community composition differed from that of the buccal mucosa and showed high richness and diversity. With the random forest model, the microbiota of saliva and buccal mucosa can be classified, which can be used in identifying the source of oral biological trace. Furthermore, each individual has a unique bacterial community pattern, and the presence or absence of unique bacteria and differences in the composition of the core oral microbiota are the key points for forensic personal discrimination that supplement the study of oral microbial application to forensic personal discrimination. Whether for original identification or personal discrimination, the oral microbiome has great potential for application.

Oral microbiota in human systematic diseases

Oral bacteria directly affect the disease status of dental caries and periodontal diseases. The dynamic oral microbiota cooperates with the host to reflect the information and status of immunity and metabolism through two-way communication along the oral cavity and the systemic organs. The oral cavity is one of the most important interaction windows between the human body and the environment. The microenvironment at different sites in the oral cavity has different microbial compositions and is regulated by complex signaling, hosts, and external environmental factors. These processes may affect or reflect human health because certain health states seem to be related to the composition of oral bacteria, and the destruction of the microbial community is related to systemic diseases. In this review, we discussed emerging and exciting evidence of complex and important connections between the oral microbes and multiple human systemic diseases, and the possible contribution of the oral microorganisms to systemic diseases. This review aims to enhance the interest to oral microbes on the whole human body, and also improve clinician’s understanding of the role of oral microbes in systemic diseases. Microbial research in dentistry potentially enhances our knowledge of the pathogenic mechanisms of oral diseases, and at the same time, continuous advances in this frontier field may lead to a tangible impact on human health.