The Kinetics of COVID-19 Vaccine Response in a Community-Vaccinated Population.

We used a noninvasive electrochemical quantitative assay for IgG Abs to SARS-CoV-2 S1 Ag in saliva to investigate the kinetics of Ab response in a community-based population that had received either the Pfizer or Moderna mRNA-based vaccine. Samples were received from a total of 97 individuals, including a subset of 42 individuals who collected samples twice weekly for 3 mo or longer. In all, >840 samples were collected and analyzed. In all individuals, salivary SARS-CoV-2 S1 IgG Ab levels rose sharply in the 2-wk period after their second vaccination, with peak Ab levels seen at 10-20 d after vaccination. We observed that 20%, 10%, and 2.4% of individuals providing serial samples had a 90%, 95%, and 99% drop, respectively, from peak levels during the duration of monitoring, and in two patients, Abs fell to prevaccination levels (5%). The use of noninvasive quantitative salivary Ab measurement can allow widespread, cost-effective monitoring of vaccine response.

Integrated Multiomics Analysis of Salivary Exosomes to Identify Biomarkers Associated with Changes in Mood States and Fatigue.

Fatigue and other deleterious mood alterations resulting from prolonged efforts such as a long work shift can lead to a decrease in vigilance and cognitive performance, increasing the likelihood of errors during the execution of attention-demanding activities such as piloting an aircraft or performing medical procedures. Thus, a method to rapidly and objectively assess the risk for such cognitive fatigue would be of value. The objective of the study was the identification in saliva-borne exosomes of molecular signals associated with changes in mood and fatigue that may increase the risk of reduced cognitive performance. Using integrated multiomics analysis of exosomes from the saliva of medical residents before and after a 12 h work shift, we observed changes in the abundances of several proteins and miRNAs that were associated with various mood states, and specifically fatigue, as determined by a Profile of Mood States questionnaire. The findings herein point to a promising protein biomarker, phosphoglycerate kinase 1 (PGK1), that was associated with fatigue and displayed changes in abundance in saliva, and we suggest a possible biological mechanism whereby the expression of the PGK1 gene is regulated by miR3185 in response to fatigue. Overall, these data suggest that multiomics analysis of salivary exosomes has merit for identifying novel biomarkers associated with changes in mood states and fatigue. The promising biomarker protein presents an opportunity for the development of a rapid saliva-based test for the assessment of these changes.

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

Motivation: Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. Results: We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Availability and implementation: Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. Contact: dtww@ucla.edu.

Identification of salivary metabolites for oral squamous cell carcinoma and oral epithelial dysplasia screening from persistent suspicious oral mucosal lesions.

OBJECTIVE: To identify salivary metabolite biomarkers to differentiate patients with oral squamous cell carcinoma and oral epithelial dysplasia (OSCC/OED) from those with persistent suspicious oral mucosal lesions (PSOML). SUBJECTS AND METHODS: Whole unstimulated saliva samples were collected from age-, sex-, and race-matched patients who had a lesion in the oral cavity and for whom open biopsies were performed. The patients included OSCC (n = 6), OED (n = 10), and PSOML (n = 32). Hydrophilic metabolites in saliva samples were comprehensively analyzed using capillary electrophoresis mass spectrometry. To evaluate the discrimination ability of a combination of multiple markers, a multiple logistic regression (MLR) model was developed to differentiate OSCC/OED from PSOML. RESULTS: Six metabolites were significantly different in OSCC/OED compared with PSOML. From these six metabolites, ornithine, o-hydroxybenzoate, and ribose 5-phosphate (R5P) were used to develop the MLR model, which resulted in a high value for the area under receiver operating characteristic curve (AUC 0.871, 95% confidential interval (CI) 0.760-0.982; p < 0.001) to discriminate OSCC/OED from PSOML. CONCLUSIONS: This is the first study to identify salivary metabolites that discriminate OSCC/OED from PSOML rather than from healthy controls. The profiles of salivary metabolites were significantly different between OSCC/OED and PSOML. The ability to discriminate OSCC/OED from PSOML is important for dentists who are not oral surgery specialists. These salivary metabolites showed potential for non-invasive screening to discriminate OSCC/OED from PSOML. CLINICAL RELEVANCE: Salivary metabolites in this study showed potential for non-invasive screening to discriminate OSCC/OED from PSOML.

Characterization of Human Salivary Extracellular RNA by Next-generation Sequencing.

BACKGROUND: It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential. METHODS: We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated. RESULTS: The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%). CONCLUSIONS: Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.

Discovery and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer.

BACKGROUND: Biomarkers are needed for noninvasive early detection of gastric cancer (GC). We investigated salivary extracellular RNA (exRNA) biomarkers as potential clinical evaluation tools for GC. METHODS: Unstimulated whole saliva samples were prospectively collected from 294 individuals (163 GC and 131 non-GC patients) who underwent endoscopic evaluation at the Samsung Medical Center in Korea. Salivary transcriptomes of 63 GC and 31 non-GC patients were profiled, and mRNA biomarker candidates were verified with reverse transcription quantitative real-time PCR (RT-qPCR). In parallel, microRNA (miRNA) biomarkers were profiled and verified with saliva samples from 10 GC and 10 non-GC patients. Candidate biomarkers were validated with RT-qPCR in an independent cohort of 100/100 saliva samples from GC and non-GC patients. Validated individual markers were configured into a best performance panel. RESULTS: We identified 30 mRNA and 15 miRNA candidates whose expression pattern associated with the presence of GC. Among them, 12 mRNA and 6 miRNA candidates were verified with the discovery cohort by RT-qPCR and further validated with the independent cohort (n = 200). The configured biomarker panel consisted of 3 mRNAs (SPINK7, PPL, and SEMA4B) and 2 miRNAs (MIR140-5p and MIR301a), which were all significantly down-regulated in the GC group, and yielded an area under the ROC curve (AUC) of 0.81 (95% CI, 0.72-0.89). When combined with demographic factors, the AUC of the biomarker panel reached 0.87 (95% CI, 0.80-0.93). CONCLUSIONS: We have discovered and validated a panel of salivary exRNA biomarkers with credible clinical performance for the detection of GC. Our study demonstrates the potential utility of salivary exRNA biomarkers in screening and risk assessment for GC.

Saliva exosomes from pancreatic tumor-bearing mice modulate NK cell phenotype and antitumor cytotoxicity.

Tumor exosomes are emerging as antitumor immunity regulators; however, their effects on secondary exosome secretion by distal organs have not been explored. We have previously demonstrated that suppression of exosomes at the distal tumor site of pancreatic ductal adenocarcinoma (PDAC) ablated the development of salivary biomarker profile. Here, we explore the function of salivary exosomes from tumor-bearing mice in immune surveillance. We provide evidence that salivary exosomes from mice with PDAC exhibit a suppressive effect that results in reduced tumor-killing capacity by NK cells. Salivary exosomes from mice with PDAC where pancreatic tumors were engineered to suppress exosome biogenesis failed to suppress NK cell cytotoxic potential against tumor cells, as opposed to salivary exosomes from mice with PDAC with normal tumor exosome biogenesis. These results reveal an important and previously unknown mechanism of antitumor immune regulation and provide new insights into our understanding of the alterations of this biofluid during tumor development.-Katsiougiannis, S., Chia, D., Kim, Y., Singh, R. P., Wong, D. T. W. Saliva exosomes from pancreatic tumor-bearing mice modulate NK cell phenotype and antitumor cytotoxicity.

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.

Emerging technologies for salivaomics in cancer detection.

Salivary diagnostics has great potential to be used in the early detection and prevention of many cancerous diseases. If implemented with rigour and efficiency, it can result in improving patient survival times and achieving earlier diagnosis of disease. Recently, extraordinary efforts have been taken to develop non-invasive technologies that can be applied without complicated and expensive procedures. Saliva is a biofluid that has demonstrated excellent properties and can be used as a diagnostic fluid, since many of the biomarkers suggested for cancers can also be found in whole saliva, apart from blood or other body fluids. The currently accepted gold standard methods for biomarker development include chromatography, mass spectometry, gel electrophoresis, microarrays and polymerase chain reaction-based quantification. However, salivary diagnostics is a flourishing field with the rapid development of novel technologies associated with point-of-care diagnostics, RNA sequencing, electrochemical detection and liquid biopsy. Those technologies will help introduce population-based screening programs, thus enabling early detection, prognosis assessment and disease monitoring. The purpose of this review is to give a comprehensive update on the emerging diagnostic technologies and tools for the early detection of cancerous diseases based on saliva.

The emerging landscape of salivary diagnostics.

Saliva contains a variety of biomolecules, including DNA, coding and noncoding RNA, proteins, metabolites and microbiota. The changes in the salivary levels of these molecular constituents can be used to develop markers for disease detection and risk assessment. Use of saliva as an early-detection tool is a promising approach because collection of saliva is easy and noninvasive. Here, we review recent developments in salivary diagnostics, accomplished using salivaomics approaches, including genomic, transcriptomic, proteomic, metabolomic and microbiomic technologies. Additionally, we illustrate the mechanisms of how diseases distal from the oral cavity can lead to the appearance of discriminatory biomarkers in saliva, and discuss the relevance of these markers for translational and clinical applications.

The landscape of microRNA, Piwi-interacting RNA, and circular RNA in human saliva.

BACKGROUND: Extracellular RNAs (exRNAs) in human body fluids are emerging as effective biomarkers for detection of diseases. Saliva, as the most accessible and noninvasive body fluid, has been shown to harbor exRNA biomarkers for several human diseases. However, the entire spectrum of exRNA from saliva has not been fully characterized. METHODS: Using high-throughput RNA sequencing (RNA-Seq), we conducted an in-depth bioinformatic analysis of noncoding RNAs (ncRNAs) in human cell-free saliva (CFS) from healthy individuals, with a focus on microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and circular RNAs (circRNAs). RESULTS: Our data demonstrated robust reproducibility of miRNA and piRNA profiles across individuals. Furthermore, individual variability of these salivary RNA species was highly similar to those in other body fluids or cellular samples, despite the direct exposure of saliva to environmental impacts. By comparative analysis of >90 RNA-Seq data sets of different origins, we observed that piRNAs were surprisingly abundant in CFS compared with other body fluid or intracellular samples, with expression levels in CFS comparable to those found in embryonic stem cells and skin cells. Conversely, miRNA expression profiles in CFS were highly similar to those in serum and cerebrospinal fluid. Using a customized bioinformatics method, we identified >400 circRNAs in CFS. These data represent the first global characterization and experimental validation of circRNAs in any type of extracellular body fluid. CONCLUSIONS: Our study provides a comprehensive landscape of ncRNA species in human saliva that will facilitate further biomarker discoveries and lay a foundation for future studies related to ncRNAs in human saliva.

Noninvasive saliva-based EGFR gene mutation detection in patients with lung cancer.

RATIONALE: Constitutive activation of the epidermal growth factor receptor (EGFR) is prevalent in epithelial cancers, particularly in non-small cell lung carcinoma (NSCLC). Mutations identified in EGFR predict the sensitivity to EGFR-targeted therapy. Detection of these mutations is mainly based on tissue biopsy, which is invasive, expensive, and time consuming. OBJECTIVES: Noninvasive, real-time, inexpensive detection and monitoring of EGFR mutations in patients with NSCLC is highly desirable. METHODS: We developed a novel core technology, electric field-induced release and measurement (EFIRM), which relies on a multiplexible electrochemical sensor that can detect EGFR mutations directly in bodily fluids. MEASUREMENTS AND MAIN RESULTS: We established EFIRM for the detection of the EGFR mutations in vitro and correlated the results with tumor size from xenografted mice. In clinical application, we demonstrated that EFIRM could detect EGFR mutations in the saliva and plasma of 22 patients with NSCLC. Finally, a blinded test was performed on saliva samples from 40 patients with NSCLC. The receiver operating characteristic analysis indicated that EFIRM detected the exon 19 deletion with an area under the curve of 0.94 and the L858R mutation with an area under the curve of 0.96. CONCLUSIONS: Our data indicate that EFIRM is effective, accurate, rapid, user-friendly, and cost effective for the detection of EGFR mutations in the saliva of patients with NSCLC. We termed this saliva-based EGFR mutation detection (SABER).

Salivary biomarkers: toward future clinical and diagnostic utilities.

The pursuit of timely, cost-effective, accurate, and noninvasive diagnostic methodologies is an endeavor of urgency among clinicians and scientists alike. Detecting pathologies at their earliest stages can significantly affect patient discomfort, prognosis, therapeutic intervention, survival rates, and recurrence. Diagnosis and monitoring often require painful invasive procedures such as biopsies and repeated blood draws, adding undue stress to an already unpleasant experience. The discovery of saliva-based microbial, immunologic, and molecular biomarkers offers unique opportunities to bypass these measures by utilizing oral fluids to evaluate the condition of both healthy and diseased individuals. Here we discuss saliva and its significance as a source of indicators for local, systemic, and infectious disorders. We highlight contemporary innovations and explore recent discoveries that deem saliva a mediator of the body's physiological condition. Additionally, we examine the current state of salivary diagnostics and its associated technologies, future aspirations, and potential as the preferred route of disease detection, monitoring, and prognosis.

Role of pancreatic cancer-derived exosomes in salivary biomarker development.

Recent studies have demonstrated that discriminatory salivary biomarkers can be readily detected upon the development of systemic diseases such as pancreatic cancer, breast cancer, lung cancer, and ovarian cancer. However, the utility of salivary biomarkers for the detection of systemic diseases has been undermined due to the absence of the biological and mechanistic rationale as to why distal diseases from the oral cavity would lead to the development of discriminatory biomarkers in saliva. Here, we examine the hypothesis that pancreatic tumor-derived exosomes are mechanistically involved in the development of pancreatic cancer-discriminatory salivary transcriptomic biomarkers. We first developed a pancreatic cancer mouse model that yielded discriminatory salivary biomarkers by implanting the mouse pancreatic cancer cell line Panc02 into the pancreas of the syngeneic host C57BL/6. The role of pancreatic cancer-derived exosomes in the development of discriminatory salivary biomarkers was then tested by engineering a Panc02 cell line that is suppressed for exosome biogenesis, implanting into the C56BL/6 mouse, and examining whether the discriminatory salivary biomarker profile was ablated or disrupted. Suppression of exosome biogenesis results in the ablation of discriminatory salivary biomarker development. This study supports that tumor-derived exosomes provide a mechanism in the development of discriminatory biomarkers in saliva and distal systemic diseases.

Proteomic analysis of human saliva from lung cancer patients using two-dimensional difference gel electrophoresis and mass spectrometry.

Lung cancer is often asymptomatic or causes only nonspecific symptoms in its early stages. Early detection represents one of the most promising approaches to reduce the growing lung cancer burden. Human saliva is an attractive diagnostic fluid because its collection is less invasive than that of tissue or blood. Profiling of proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of oral or systematic diseases, which may be used extensively in future medical diagnostics. There were 72 subjects enrolled in this study for saliva sample collection according to the approved protocol. Two-dimensional difference gel electrophoresis combined with MS was the platform for salivary proteome separation, quantification, and identification from two pooled samples. Candidate proteomic biomarkers were verified and prevalidated by using immunoassay methods. There were 16 candidate protein biomarkers discovered by two-dimensional difference gel electrophoresis and MS. Three proteins were further verified in the discovery sample set, prevalidation sample set, and lung cancer cell lines. The discriminatory power of these candidate biomarkers in lung cancer patients and healthy control subjects can reach 88.5% sensitivity and 92.3% specificity with AUC = 0.90. This preliminary data report demonstrates that proteomic biomarkers are present in human saliva when people develop lung cancer. The discriminatory power of these candidate biomarkers indicate that a simple saliva test might be established for lung cancer clinical screening and detection.

Seronegative patients with primary Sjögren's syndrome and non-pSS sicca test positive for anti-SSA/Ro52 and -Ro60 in saliva.

OBJECTIVES: Testing for anti-SSA/Ro antibodies in serum is essential in the diagnostic work-up for primary Sjögren's syndrome (pSS). In this study, we aimed to validate our previous assay for detection of salivary anti-SSA/Ro52, and to develop assays for detection of salivary anti-SSA/Ro60 and for detection of anti-Ro52 and -Ro60 in plasma using the electric field-induced release and measurement (EFIRM) platform. METHODS: Whole saliva samples from two independent Danish cohorts (DN1 and DN2) including 49 patients with pSS, 73 patients with sicca symptoms, but not fulfilling the classification criteria for pSS (non-pSS sicca), and 51 healthy controls (HC), as well as plasma samples from the DN1 cohort were analyzed using EFIRM to detect anti-SSA/Ro52 and -Ro60. RESULTS: In the DN1 cohort, 100 % in the pSS group and 16 % in the non-pSS sicca group were serum anti-SSA/Ro positive by ELISA. EFIRM detected anti-SSA (Ro52 and/or -Ro60) in plasma and saliva in 100 % and 96 % patients with pSS, and 16 % and 29 % with non-pSS sicca. In the DN2 cohort, 80 % patients with pSS and 26 % with non-pSS sicca were serum anti-SSA/Ro positive. Salivary anti-SSA discriminated patients with pSS from HC and non-pSS sicca with an AUC range of 0.74-0.96 in the DN1 and DN2 cohorts. EFIRM discriminated pSS from non-pSS sicca with an AUC of 0.98 in plasma. CONCLUSION: Our findings suggest that salivary anti-SSA/Ro antibodies are potential discriminatory biomarkers for pSS, which may also identify seronegative patients, addressing the unmet clinical need of early detection and stratification of pSS.

Distinctive profile of monomeric and polymeric anti-SSA/Ro52 immunoglobulin A1 isoforms in saliva of patients with primary Sjögren's syndrome and Sicca.

OBJECTIVE: Primary Sjögren's syndrome (pSS) is the second most common chronic autoimmune connective tissue disease. Autoantibodies, immunoglobulin (IgG) anti-SSA/Ro, in serum is a key diagnostic feature of pSS. Since pSS is a disease of the salivary gland, we investigated anti-SSA/Ro52 in saliva. METHODS: Using a novel electrochemical detection platform, Electric Field-Induced Release and Measurement, we measured IgG/M/A, IgG, IgA, IgA isotypes (IgA1 and IgA2) and IgA1 subclasses (polymeric and monomeric IgA1) to anti-SSA/Ro52 in saliva supernatant of 34 pSS, 35 dry eyes and dry mouth (patients with Sicca) and 41 health controls. RESULTS: Saliva IgG/M/A, IgG, IgA, IgA isotypes and IgA1 subclasses to anti-SSA/Ro52 differed significantly between pSS, non-pSS Sicca and healthy subjects. Elevated monomeric IgA1 was observed in patients with non-pSS Sicca while elevated polymeric IgA1 (pIgA1) was observed in patients with pSS. Salivary polymeric but not monomeric IgA1 (mIgA1) isoform correlated with focus score (r2=0.467, p=0.001) CONCLUSIONS: Salivary anti-Ro52 polymeric IgA1 isoform is associated with glandular inflammation in pSS, while salivary monomeric IgA1 is associated with Sicca. Whether IgA1 isotope switching plays a role in the progression of the Sicca to pSS warrants further investigation.

Development of transcriptomic biomarker signature in human saliva to detect lung cancer.

Lung cancer is the leading cause of cancer death for both men and women worldwide. Since most of the symptoms found for lung cancer are nonspecific, diagnosis is mostly done at late and progressed stage with the consecutive poor therapy outcome. Effective early detection techniques are sorely needed. The emerging field of salivary diagnostics could provide scientifically credible, easy-to-use, non-invasive and cost-effective detection methods. Recent advances have allowed us to develop discriminatory salivary biomarkers for a variety of diseases from oral to systematic diseases. In this study, salivary transcriptomes of lung cancer patients were profiled and led to the discovery and pre-validation of seven highly discriminatory transcriptomic salivary biomarkers (BRAF, CCNI, EGRF, FGF19, FRS2, GREB1, and LZTS1). The logistic regression model combining five of the mRNA biomarkers (CCNI, EGFR, FGF19, FRS2, and GREB1) could differentiate lung cancer patients from normal control subjects, yielding AUC value of 0.925 with 93.75 % sensitivity and 82.81 % specificity in the pre-validation sample set. These salivary mRNA biomarkers possess the discriminatory power for the detection of lung cancer. This report provides the proof of concept of salivary biomarkers for the non-invasive detection of the systematic disease. These results poised the salivary biomarkers for the initiation of a multi-center validation in a definitive clinical context.

Variations of oral microbiota are associated with pancreatic diseases including pancreatic cancer.

OBJECTIVE: The associations between oral diseases and increased risk of pancreatic cancer have been reported in several prospective cohort studies. In this study, we measured variations of salivary microbiota and evaluated their potential associations with pancreatic cancer and chronic pancreatitis. METHODS: This study was divided into three phases: (1) microbial profiling using the Human Oral Microbe Identification Microarray to investigate salivary microbiota variation between 10 resectable patients with pancreatic cancer and 10 matched healthy controls, (2) identification and verification of bacterial candidates by real-time quantitative PCR (qPCR) and (3) validation of bacterial candidates by qPCR on an independent cohort of 28 resectable pancreatic cancer, 28 matched healthy control and 27 chronic pancreatitis samples. RESULTS: Comprehensive comparison of the salivary microbiota between patients with pancreatic cancer and healthy control subjects revealed a significant variation of salivary microflora. Thirty-one bacterial species/clusters were increased in the saliva of patients with pancreatic cancer (n=10) in comparison to those of the healthy controls (n=10), whereas 25 bacterial species/clusters were decreased. Two out of six bacterial candidates (Neisseria elongata and Streptococcus mitis) were validated using the independent samples, showing significant variation (p<0.05, qPCR) between patients with pancreatic cancer and controls (n=56). Additionally, two bacteria (Granulicatella adiacens and S mitis) showed significant variation (p<0.05, qPCR) between chronic pancreatitis samples and controls (n=55). The combination of two bacterial biomarkers (N elongata and S mitis) yielded a receiver operating characteristic plot area under the curve value of 0.90 (95% CI 0.78 to 0.96, p<0.0001) with a 96.4% sensitivity and 82.1% specificity in distinguishing patients with pancreatic cancer from healthy subjects. CONCLUSIONS: The authors observed associations between variations of patients' salivary microbiota with pancreatic cancer and chronic pancreatitis. This report also provides proof of salivary microbiota as an informative source for discovering non-invasive biomarkers of systemic diseases.

Saliva diagnostics: Salivaomics, saliva exosomics, and saliva liquid biopsy.

BACKGROUND: Each day, humans produce approximately 0.5 through 1.5 liters of saliva, a biofluid that is rich in biological omic constituents. Our lack of understanding how omic biomarkers migrate from diseased tissue to the saliva has impeded the clinical translation of saliva testing. Although such biomarkers must be conveyed via the vascular and lymphatic systems to the salivary glands, the molecular mechanisms that underlie this transport remain unclear. Although COVID-19 highlighted the need for rapid and reliable testing for infectious diseases, it represents only one of the many health conditions that potentially can be diagnosed using a saliva sample. TYPES OF STUDIES REVIEWED: The authors discuss salivaomics, saliva exosomics, and the mechanisms on which saliva diagnostics are based and introduce a novel electrochemical sensing technology that may be exploited for saliva liquid biopsy. RESULTS: The utility of saliva for screening for lung cancer is under investigation. Saliva testing may be used to stratify patients, monitor treatment response, and detect disease recurrence. The authors also highlight the landscapes of saliva-based SARS-CoV-2 testing and ultrashort cell-free DNA and outline how these fields are likely to evolve in the near future. PRACTICAL IMPLICATIONS: Breakthroughs in the study of saliva research, therefore, will facilitate clinical deployment of saliva-based testing.