Salivary exRNA biomarkers to detect gingivitis and monitor disease regression

MicroRNAs Function in Dental Stem Cells as a Promising Biomarker and Therapeutic Target for Dental Diseases

Undifferentiated, highly proliferative, clonogenic, and self-renewing dental stem cells have paved the way for novel approaches to mending cleft palates, rebuilding lost jawbone and periodontal tissue, and, most significantly, recreating lost teeth. New treatment techniques may be guided by a better understanding of these cells and their potential in terms of the specificity of the regenerative response. MicroRNAs have been recognized as an essential component in stem cell biology due to their role as epigenetic regulators of the processes that determine stem cell destiny. MicroRNAs have been proven to be crucial in a wide variety of molecular and biological processes, including apoptosis, cell proliferation, migration, and necrocytosis. MicroRNAs have been recognized to control protein translation, messenger RNA stability, and transcription and have been reported to play essential roles in dental stem cell biology, including the differentiation of dental stem cells, the immunological response, apoptosis, and the inflammation of the dental pulp. Because microRNAs increase dental stem cell differentiation, they may be used in regenerative medicine to either preserve the stem cell phenotype or to aid in the development of tooth tissue. The development of novel biomarkers and therapies for dental illnesses relies heavily on progress made in our knowledge of the roles played by microRNAs in regulating dental stem cells. In this article, we discuss how dental stem cells and their associated microRNAs may be used to cure dental illness.

Does smoking influence tryptophan metabolism in periodontal inflammation? A cross-sectional study

OBJECTIVES

The aim of this study was to identify the effects of smoking and periodontal inflammation on tryptophan-kynurenine metabolism as well as the correlation between these findings and clinical periodontal parameters.

BACKGROUND

It has been shown that the tryptophan amino acid's primary catabolic pathway, the kynurenine pathway (KP), may serve as a key biomarker for periodontal disease. Although there are studies investigating the effect of smoking on KYN-TRP metabolism, the effect of smoking on periodontal disease through KP has not been revealed so far.

METHODS

The salivary and serum samples were gathered from 24 nonsmoker (NS-P) stage III, grade B generalized periodontitis and 22 smoker (S-P) stage III, grade C generalized periodontitis patients, in addition to 24 nonsmoker (NS-C) and 24 smoker (S-C) periodontally healthy control individuals. Saliva and serum IL-6, kynurenine (KYN), and tryptophan (TRP) values, and KYN/TRP ratio were analyzed by liquid chromatography-mass spectrometry. Clinical periodontal measurements were recorded.

RESULTS

Salivary TRP values were significantly higher in both periodontitis groups than control groups (p < .05). Salivary KYN values were highest in NS-P group (p < .05). Salivary KYN values did not differ significantly between periodontitis groups (p = .84). Salivary KYN/TRP ratio was significantly lower in NS-P group compared to other groups (p < .001). Serum TRP value is higher in S-P group than other groups; however, significant difference was found in S-C group (p < .05). Serum KYN values were significantly lower in smokers than nonsmokers. Serum KYN/TRP ratio is higher in NS-P group. NS-P group has the highest salivary IL-6 levels, NS-C group has the lowest values (p < .05).

CONCLUSIONS

Our results point out that smoking exacerbates inflammation in the periodontium and increases TRP destruction and decreases IDO activity by suppressing KP in serum. As a result, kynurenine and its metabolites may be significant biomarkers in the link between smoking and periodontal disease.

Salivary macrophage chemokines as potential biomarkers of gingivitis

OBJECTIVE

The present study aimed to analyze the salivary levels of macrophage-activating factor (MAF), macrophage-chemotactic factor (MCF), and macrophage migration inhibitory factor (MIF) in healthy and gingivitis patients, and to correlate between the concentrations of these chemo attractants with the intensity of gingival inflammation clinically.

METHODS

Sixty saliva specimens were collected from periodontally healthy (n = 30), and gingivitis patients (n = 30). Bleeding on probing (BOP), Visible Plaque Index (VPI), and Simplified Modified Gingival Index (SMGI) were recorded through clinical examination. Salivary MAF, MCF, and MIF concentrations were assayed using enzyme-linked immunosorbent assays (ELISA). Statistical analysis was performed using SPSS (version 28). Total mean score for each biomarker was determined, and descriptive bivariate statistics were conducted to characterize the levels of biomarkers among the study groups. The difference in the biomarker levels among the study groups were analyzed by independent sample t test and one-way ANOVA. The diagnostic ability of the biomarkers was further tested by ROC curve analysis.

RESULTS

Salivary levels of MAF was not significantly different between periodontally healthy individuals and gingivitis patients. The difference in MCF and MIF levels between patients with gingivitis and those with healthy periodontium was statistically significant (p 0.05 and p 0.001, respectively). When examined across the various stages of disease progression, MIF showed statistically significant difference among the three biomarkers (p 0.05). ROC curve analysis further revealed that area under the curve (AUC) for MIF has a better diagnostic capacity than MCF (AUC 0.981 vs. 0.673).

CONCLUSIONS

Our results suggest that MIF could be considered as a potential salivary biomarker for gingivitis.

Performance of Salivary Extracellular RNA Biomarker Panels for Gastric Cancer Differs between Distinct Populations

Gastric cancer (GC) has the fifth highest incidence among cancers and is the fourth leading cause of cancer-related death GC has predominantly a higher number of cases in certain ethnic groups such as the Korean population. GC found at an early stage is more treatable and has a higher survival rate as compared with GC found at a late stage. However, a diagnosis of GC is often delayed due to the lack of early symptoms and available screening programs in United States. Extracellular RNA (exRNA) is an emerging paradigm; exRNAs have the potential to serve as biomarkers in panels aimed at early detection of cancer. We previously reported the successful use of a panel of salivary exRNA for detecting GC in a high-prevalence Korean cohort, and that genetic changes reflected cancer-associated salivary exRNA changes. The current study is a case-control study of salivary exRNA biomarkers for detecting GC in an ethnically distinct U.S. cohort. A model constructed for the U.S. cohort combined demographic characteristics and salivary miRNA and mRNA biomarkers for GC and yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.78. However, the constituents of this model differed from that constructed for the Korean cohort, thus, emphasizing the importance of population-specific biomarker development and validation.

The Role of Epigenetic and Biological Biomarkers in the Diagnosis of Periodontal Disease: A Systematic Review Approach

The aim of this systemic review was to collate and analyze existing data from published literature sources to identify the current understanding of the role of epigenetic and biological biomarkers in periodontal disease and diagnostics. A comprehensive searching strategy was undertaken in Embase, Medline, The Dentistry and Oral Sciences and CINAHL databases. Grey literature searching strategies were also employed. Articles published in the English language between 2017−2020 were included. A total of 1014 studies were returned of which 15 studies were included. All included articles were cross-sectional, case−control studies. Relevant data were extracted according to various demographic and methodological factors including cohort size, oral biofluid sampled, number of examiners, smoking status and reported outcomes. A measure of the biomarker levels and corresponding significance were documented where possible. This review identified that exRNA has the greatest diagnostic potential, with four biomarkers (SPRR1A, lnc-TET3-2:1, FAM25A, CRCT1) displaying sensitivity of >71% and specificity of 100% in the assessed samples (p < 0.001) for gingivitis. This work also identifies the need for a unified approach to future research to draw meaningful comparison. Further investigations are warranted to definitively validate exRNA data and for the development of an exRNA-specific point-of-care diagnostic test.

Small Proline Rich Protein 1A promotes lung adenocarcinoma progression and indicates unfavorable clinical outcomes

Small Proline Rich Protein 1A (SPRR1A) plays a critical role in regulating squamous cell differentiation. It has been reported that SPRR1A overexpression was closely related to the progression of some tumors such as gastric cancer and colon cancer. However, the function of SPRR1A in lung adenocarcinoma (LUAD) has not been elucidated. Here we firstly examined the expression pattern of SPRR1A in LUAD tissues, which indicated that SPRR1A expression level was significantly elevated in LUAD tissues compared to normal lung tissues. High expression of SPRR1A was closely related to the larger tumor size. LUAD patients with higher SPRR1A expression had poorer overall survival and SPRR1A was identified as an independent unfavorable prognosis factor. In addition, the effects of SPRR1A on lung cancer cells were tested through cellular experiments and the result demonstrated that knockdown of SPRR1A can suppress proliferation and invasion capacities of tumor cells, while overexpressing SPRR1A exerted opposite effects. Finally, our findings were substantiated by the data obtained from in vivo xenografts using mice model. In conclusion, LUAD patients with higher SPRR1A expression were more predisposed to poorer clinical outcomes and unfavorable prognosis, indicating the potential role of SPRR1A as a novel clinical biomarker and therapeutic target.

Enzymatic Methods for Salivary Biomarkers Detection: Overview and Current Challenges

Early detection is a key factor in patient fate. Currently, multiple biomolecules have been recognized as biomarkers. Nevertheless, their identification is only the starting line on the way to their implementation in disease diagnosis. Although blood is the biofluid par excellence for the quantification of biomarkers, its extraction is uncomfortable and painful for many patients. In this sense, there is a gap in which saliva emerges as a non-invasive and valuable source of information, as it contains many of the biomarkers found in blood. Recent technological advances have made it possible to detect and quantify biomarkers in saliva samples. However, there are opportunity areas in terms of cost and complexity, which could be solved using simpler methodologies such as those based on enzymes. Many reviews have focused on presenting the state-of-the-art in identifying biomarkers in saliva samples. However, just a few of them provide critical analysis of technical elements for biomarker quantification in enzymatic methods for large-scale clinical applications. Thus, this review proposes enzymatic assays as a cost-effective alternative to overcome the limitations of current methods for the quantification of biomarkers in saliva, highlighting the technical and operational considerations necessary for sampling, method development, optimization, and validation.

Elevated RUNX1 is a prognostic biomarker for human head and neck squamous cell carcinoma

Runt-related transcription factors regulate many developmental processes such as proliferation and differentiation. In this study, the function of the runt-related transcription factor 1 (RUNX1) was investigated in head and neck squamous cell carcinoma (HNSCC). Our results show that RUNX1 expression was elevated in HNSCC patients, which was greatly correlated with the N stage, tumor size, and American Joint Committee on Cancer stage. Cox proportional hazard models showed that RUNX1 could be used as a prognostic indicator for the overall survival of HNSCC patients (hazard ratio, 5.572; 95% confidence interval, 1.860-9.963; P < 0.001). Moreover, suppression of RUNX1 inhibited HNSCC cell proliferation, migration, and invasion. Using the HNSCC xenograft nude mouse model, we found that the shRUNX1-transfected tumor (sh-RUNX1) was significantly smaller both in size and weight than the control vector-transfected tumor (sh-Control). In conclusion, our results show that the elevated RUNX1 expression was correlated with tumor growth and metastasis in HNSCC, indicating that RUNX1 could be used as a biomarker for tumor recurrence and prognosis.

Defining Parallels between the Salivary Glands and Pancreas to Better Understand Pancreatic Carcinogenesis

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with a dismal prognosis, largely due to its late presentation. Methods for early detection, the development of reliable screening tools, and the identification of sensitive and specific biomarkers have remained essential research priorities to improve early patient management and outcomes. The pancreas and salivary glands share histological and functional similarities, and the salivary glands have demonstrated a role in oral and systemic health. This review focuses on the similarities and differences between the pancreas and salivary glands and how these can inform our understanding of PDAC genesis and early diagnosis. In particular, chemical exposure, which alters salivary gland gene transcription and morphogenesis, may not only directly impact salivary gland regulation but alter pancreatic function via the systemic secretion of growth hormones. Diabetes and obesity are associated with an increased risk of pancreatic cancer, and a link between chemical exposure and the development of diabetes, obesity, and consequently PDAC genesis is proposed. Possible mechanisms include altering salivary or pancreatic morphology and organ function, disrupting endocrine signaling, or altering pro-inflammatory homeostasis. Finally, saliva contains putative specific biomarkers that show promise as non-invasive diagnostic tools for PDAC.

Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning

After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthritis (OA) increases with aging, and the main goal is to diagnosis before morphological degeneration occurs. Here, we address this challenge using advanced data science to capture, process and analyze 52 clinical, biological and high-resolution CBCT (radiomics) markers from TMJ OA patients and controls. We tested the diagnostic performance of four machine learning models: Logistic Regression, Random Forest, LightGBM, XGBoost. Headaches, Range of mouth opening without pain, Energy, Haralick Correlation, Entropy and interactions of TGF-β1 in Saliva and Headaches, VE-cadherin in Serum and Angiogenin in Saliva, VE-cadherin in Saliva and Headaches, PA1 in Saliva and Headaches, PA1 in Saliva and Range of mouth opening without pain; Gender and Muscle Soreness; Short Run Low Grey Level Emphasis and Headaches, Inverse Difference Moment and Trabecular Separation accurately diagnose early stages of this clinical condition. Our results show the XGBoost + LightGBM model with these features and interactions achieves the accuracy of 0.823, AUC 0.870, and F1-score 0.823 to diagnose the TMJ OA status. Thus, we expect to boost future studies into osteoarthritis patient-specific therapeutic interventions, and thereby improve the health of articular joints.

Microbial extracellular RNAs and their roles in human diseases

IMPACT STATEMENT

The number of commensal bacteria in the body surpasses the number of actual human cells. Thus, various interactions between microbes and human cells constitute an inevitable phenomenon. Recent evidence has led to bacterial extracellular RNAs (exRNAs) being proposed as good candidates for microbe-host inter-kingdom communication tools as they can modulate the expression of host genes. However, research findings on the relevance of interactions between extracellular RNA and human diseases are still in their infancy. Nevertheless, substantial data suggest that microbial exRNAs are implicated in various human diseases both at local and distant sites. By exploring various scenarios for the involvement of microbial exRNAs in human diseases, we may better understand the role of exRNAs as "communication signals" for diseases and thereby develop novel therapeutic strategies by using them and their carrier extracellular vesicles.

Salivary Small Extracellular Vesicles Associated miRNAs in Periodontal Status-A Pilot Study

This pilot study aims to investigate whether salivary small extracellular vesicle (sEV)-associated microRNAs could act as potential biomarkers for periodontal disease status. Twenty-nine participants (10 who were healthy, nine with gingivitis, 10 with stage III/IV periodontitis) were recruited and unstimulated whole saliva samples were collected. Salivary sEVs were isolated using the size-exclusion chromatography (SEC) method and characterised by morphology, EV-protein and size distribution using transmission electron microscopy (TEM), Western Blot and Nanoparticle Tracking Analysis (NTA), respectively. Ten mature microRNAs (miRNAs) in salivary sEVs and saliva were evaluated using RT-qPCR. The discriminatory power of miRNAs as biomarkers in gingivitis and periodontitis versus healthy controls was evaluated by Receiver Operating Characteristics (ROC) curves. Salivary sEVs were comparable to sEVs morphology, mode, size distribution and particle concentration in healthy, gingivitis and periodontitis patients. Compared to miRNAs in whole saliva, three significantly increased miRNAs (hsa-miR-140-5p, hsa-miR-146a-5p and hsa-miR-628-5p) were only detected in sEVs in periodontitis when compared to that of healthy controls, with a good discriminatory power (area under the curve (AUC) = 0.96) for periodontitis diagnosis. Our study demonstrated that salivary sEVs are a non-invasive source of miRNAs for periodontitis diagnosis. Three miRNAs that are selectively enriched in sEVs, but not whole saliva, could be potential biomarkers for periodontal disease status.

The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data.