Poor periodontal health: A cancer risk?

Intratumoral Microbiota Changes with Tumor Stage and Influences the Immune Signature of Oral Squamous Cell Carcinoma

Characterization of the oral microbiota profile through various studies has shown an association between the microbiome and oral cancer; however, stage-specific determinants of dynamic changes in microbial communities of oral cancer remain elusive. Additionally, the influence of the intratumoral microbiota on the intratumoral immune system remains largely unexplored. Therefore, this study aims to stratify microbial abundance in the early-onset and subsequent stages of oral cancer and analyze their influence on clinical-pathological and immunological features. The microbiome composition of tissue biopsy samples was identified using 16S rRNA amplicon sequencing, while intratumoral and systemic immune profiling was done with flow cytometry and immunohistochemistry-based analysis. The bacterial composition differed significantly among precancer, early cancer, and late cancer stages with the enrichment of genera Capnocytophaga, Fusobacterium, and Treponema in the cancer group, while Streptococcus and Rothia were enriched in the precancer group. Late cancer stages were significantly associated with Capnocytophaga with high predicting accuracy, while Fusobacterium was associated with early stages of cancer. A dense intermicrobial and microbiome-immune network was observed in the precancer group. At the cellular level, intratumoral immune cell infiltration of B cells and T cells (CD4+ and CD8+) was observed with enrichment of the effector memory phenotype. Naive and effector subsets of tumor-infiltrating lymphocytes (TILs) and related gene expression were found to be distinctly associated with bacterial communities; most importantly, highly abundant bacterial genera of the tumor microenvironment were either negatively correlated or not associated with the effector lymphocytes, which led to the conclusion that the tumor microenvironment favors an immunosuppressive and nonimmunogenic microbiota. IMPORTANCE The gut microbiome has been explored extensively for its importance in the modulation of systemic inflammation and immune response; in contrast, the intratumoral microbiome is less studied for its influence on immunity in cancer. Given the established correlation between intratumoral lymphocyte infiltration and patient survival in cases of solid tumors, it was pertinent to explore the extrinsic factor influencing immune cell infiltration in the tumor. Modulation of intratumoral microbiota could have a beneficial effect on the antitumor immune response. This study stratifies the microbial profile of oral squamous cell carcinoma starting from precancer to late-stage cancer and provides evidence for their immunomodulatory role in the tumor microenvironment. Our results suggest combining microbiome study with immunological signatures of tumors for their prognostic and diagnostic application.

The role of Fusobacteria in oral cancer and immune evasion

PURPOSE OF REVIEW

There is growing evidence that suggests a possible role for bacteria in the progression of cancer. Fusobacteria have been detected in different types of cancers, including colorectal and oral cancers. Fusobacteria are common opportunistic oral bacteria known to cause various infections. In this review, we focus on the association between Fusobacteria and cancer, specifically oral cancer, and provide insight into the role of Fusobacteria in carcinogenesis and immune evasion.

RECENT FINDINGS

Recently, it has been suggested that Fusobacteria are among the bacteria that contribute to the progression of cancer and might affect disease prognosis and treatment outcome. Moreover, Fusobacteria might alter tumor microenvironment and have an impact on tumor immune response. Thus, understanding the effect of Fusobacteria on cancer cells and tumor microenvironment is crucial to improve treatment outcome.

SUMMERY

Recent evidences suggest that Fusobacteria not only have an impact on tumor progression, but might also affect tumor immune response. Moreover, Fusobacteria presence in the tumor microenvironment might have an impact on treatment outcome and might be used as a prognostic factor.

Molecular Mechanisms Leading from Periodontal Disease to Cancer

Periodontitis is prevalent in half of the adult population and raises critical health concerns as it has been recently associated with an increased risk of cancer. While information about the topic remains somewhat scarce, a deeper understanding of the underlying mechanistic pathways promoting neoplasia in periodontitis patients is of fundamental importance. This manuscript presents the literature as well as a panel of tables and figures on the molecular mechanisms of Porphyromonas gingivalis and Fusobacterium nucleatum, two main oral pathogens in periodontitis pathology, involved in instigating tumorigenesis. We also present evidence for potential links between the RANKL–RANK signaling axis as well as circulating cytokines/leukocytes and carcinogenesis. Due to the nonconclusive data associating periodontitis and cancer reported in the case and cohort studies, we examine clinical trials relevant to the topic and summarize their outcome.

A Deep Learning-Based Approach for the Detection of Early Signs of Gingivitis in Orthodontic Patients Using Faster Region-Based Convolutional Neural Networks

Computer-based technologies play a central role in the dentistry field, as they present many methods for diagnosing and detecting various diseases, such as periodontitis. The current study aimed to develop and evaluate the state-of-the-art object detection and recognition techniques and deep learning algorithms for the automatic detection of periodontal disease in orthodontic patients using intraoral images. In this study, a total of 134 intraoral images were divided into a training dataset (n = 107 [80%]) and a test dataset (n = 27 [20%]). Two Faster Region-based Convolutional Neural Network (R-CNN) models using ResNet-50 Convolutional Neural Network (CNN) were developed. The first model detects the teeth to locate the region of interest (ROI), while the second model detects gingival inflammation. The detection accuracy, precision, recall, and mean average precision (mAP) were calculated to verify the significance of the proposed model. The teeth detection model achieved an accuracy, precision, recall, and mAP of 100 %, 100%, 51.85%, and 100%, respectively. The inflammation detection model achieved an accuracy, precision, recall, and mAP of 77.12%, 88.02%, 41.75%, and 68.19%, respectively. This study proved the viability of deep learning models for the detection and diagnosis of gingivitis in intraoral images. Hence, this highlights its potential usability in the field of dentistry and aiding in reducing the severity of periodontal disease globally through preemptive non-invasive diagnosis.

Potential biomarkers and therapeutic targets in cervical cancer: Insights from the meta-analysis of transcriptomics data within network biomedicine perspective

The malignant neoplasm of the cervix, cervical cancer, has effects on the reproductive tract. Although infection with oncogenic human papillomavirus is essential for cervical cancer development, it alone is insufficient to explain the development of cervical cancer. Therefore, other risk factors such as host genetic factors should be identified, and their importance in cervical cancer induction should be determined. Although gene expression profiling studies in the last decade have made significant molecular findings about cervical cancer, adequate screening and effective treatment strategies have yet to be achieved. In the current study, meta-analysis was performed on cervical cancer-associated transcriptome data and reporter biomolecules were identified at RNA (mRNA, miRNA), protein (receptor, transcription factor, etc.), and metabolite levels by the integration of gene expression profiles with genome-scale biomolecular networks. This approach revealed already-known biomarkers, tumor suppressors and oncogenes in cervical cancer as well as various receptors (e.g. ephrin receptors EPHA4, EPHA5, and EPHB2; endothelin receptors EDNRA and EDNRB; nuclear receptors NCOA3, NR2C1, and NR2C2), miRNAs (e.g., miR-192-5p, miR-193b-3p, and miR-215-5p), transcription factors (particularly E2F4, ETS1, and CUTL1), other proteins (e.g., KAT2B, PARP1, CDK1, GSK3B, WNK1, and CRYAB), and metabolites (particularly, arachidonic acids) as novel biomarker candidates and potential therapeutic targets. The differential expression profiles of all reporter biomolecules were cross-validated in independent RNA-Seq and miRNA-Seq datasets, and the prognostic power of several reporter biomolecules, including KAT2B, PCNA, CD86, miR-192-5p and miR-215-5p was also demonstrated. In this study, we reported valuable data for further experimental and clinical efforts, because the proposed biomolecules have significant potential as systems biomarkers for screening or therapeutic purposes in cervical carcinoma.

Salivary exRNA biomarkers to detect gingivitis and monitor disease regression

AIM

This study tests the hypothesis that salivary extracellular RNA (exRNA) biomarkers can be developed for gingivitis detection and monitoring disease regression.

MATERIALS AND METHODS

Salivary exRNA biomarker candidates were developed from a total of 100 gingivitis and non-gingivitis individuals using Affymetrix's expression microarrays. The top 10 differentially expressed exRNAs were tested in a clinical cohort to determine whether the discovered salivary exRNA markers for gingivitis were associated with clinical gingivitis and disease regression. For this purpose, unstimulated saliva was collected from 30 randomly selected gingivitis subjects, the gingival and plaque indexes scores were taken at baseline, 3 and 6 weeks and salivary exRNAs were assayed by means of reverse transcription quantitative polymerase chain reaction.

RESULTS

Eight salivary exRNA biomarkers developed for gingivitis were statistically significantly changed over time, consistent with disease regression. A panel of four salivary exRNAs [SPRR1A, lnc-TET3-2:1, FAM25A, CRCT1] can detect gingivitis with a clinical performance of 0.91 area under the curve, with 71% sensitivity and 100% specificity.

CONCLUSIONS

The clinical values of the developed salivary exRNA biomarkers are associated with gingivitis regression. They offer strong potential to be advanced for definitive validation and clinical laboratory development test.

The Hospice Patient's Right to Oral Care: Making Time for the Mouth

The hospice philosophy embraces palliative care for the terminally ill, for whom quality of life is the central focus of comfort care management. Often, caregivers hesitate or simply do not elect to extend oral care for patients nearing the end of life, due to difficulties encountered in patient compliance, a sense of futility in doing so, staff time constraints in prioritizing care, underfunding, or a lack of education as to how and why such care should be delivered to the hospice patient. This article aims to show physiological and psychosocial reasons why the hospice patient has a need for properly and regularly implemented oral care and why dental professionals have an ethical responsibility to address the current void that exists in hospice-centered oral care. Varying viewpoints are discussed regarding the need for oral health monitoring and maintenance in both the capable patient with capacity and in the patient who lacks capacity and is totally dependent, yet who exhibits no particular signs of oral distress nor desire for hygiene measures. Consideration is given to family dynamics in such care. Oral care of the elderly patients and terminally ill is sorely lacking, and dental educators are challenged to cultivate in students a sense of professional duty toward caring for the vulnerable elderly patients. Dental professionals should create initiatives in developing, promoting, and implementing an appropriate standard of oral care for the hospice patient.