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Background: Although post-traumatic stress disorder (PTSD) and depression screening are recommended for traumatic injury patients, routine screening is still uncommon. Salivary inflammatory biomarkers have biological plausibility and potential feasibility and acceptability for screening. This study tested prospective associations between several salivary inflammatory biomarkers (proinflammatory cytokines interleukin-1β, interleukin-6, tumor necrosis factor-α; and C-reactive protein), collected during hospitalization and PTSD and depressive symptoms at 5-month follow-up., Methods: Adult traumatic injury patients (N = 696) at a major urban Level 1 trauma center provided salivary samples and completed PTSD and depressive symptom measures during days 0-13 of inpatient hospitalization. At 5-month follow-up, 368 patients (77 % male, 23 % female) completed the Clinician-Administered PTSD Scale for DSM-IV and the Self-rated Inventory of Depressive Symptomatology. Analyses focused on a latent inflammatory cytokine factor and C-reactive protein at baseline predicting 5-month PTSD and depression symptom outcomes and included baseline symptom levels as covariates., Results: A latent factor representing proinflammatory cytokines was not related to 5-month PTSD or depressive symptom severity. Higher salivary CRP was related to greater PTSD symptom severity (β = .10, p = .03) at 5-month follow-up and more severity in the following depressive symptoms: changes in weight and appetite, bodily complaints, and constipation/diarrhea (β's from .14 to .16, p's from .004 -.03)., Conclusion: In a primarily Latine and Black trauma patient sample, salivary CRP measured after traumatic injury was related to greater PTSD symptom severity and severity in several depressive symptom clusters. Our preliminary findings suggest that salivary or systemic CRP may be useful to include in models predicting post-trauma psychopathology., (Copyright © 2024 Elsevier Inc. All rights reserved.)

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., (© 2018 American Association for Clinical Chemistry.)

Aims: Insulin resistance (IR) detection is challenging and no test is currently used in clinical practice. We developed salivary biomarkers that could be used for IR detection., Methods: We collected saliva from 186 healthy and 276 pre-diabetic participants, divided them into high and low IR groups based on a HOMA cutoff of 2.5. We profiled extracellular transcriptome by microarray in saliva supernatant from 23 high IR and 15 low IR participants, and pre-validated the top ten extracellular mRNA (exRNA) markers in a new cohort of 40 high and 40 low IR participants. A prediction panel was then built and validated in an independent cohort of 149 high and 195 low IR participants., Results: Transcriptomic analyses identified 42 exRNA candidates differentially present in saliva of high and low IR participants. From the top ten candidates, six were individually validated (PRKCB, S100A12, IL1R2, CAMP, VPS4B, CAP1) (p<0.01) and yielded AUC values ranging from 0.66 to 0.76. Body mass index (BMI) was significant higher in high compared to low IR group with AUC of 0.66, and showed no correlation with any of candidate biomarkers. The combination of four exRNA markers (IL1R2, VPS4B, CAP1, LUZP6) with BMI achieved excellent results in the prediction panel building dataset (AUC=0.79, sensitivity=79%, specificity=64%). The prediction model was validated in an independent cohort (AUC=0.82, sensitivity=63%, specificity=92%)., Conclusions: A panel of four salivary exRNA biomarkers (IL1R2, VPS4B, CAP1, LUZP6) and BMI was validated that can distinguish high and low IR participants, overall and in subgroups of healthy and pre-diabetic participants., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The stabilization and processing of salivary transcriptome and proteome biomarkers is a critical challenge due to the ubiquitous nature of nucleases and proteases as well as the inherent instability of these biomarkers. Furthermore, extension of salivary transcriptome and proteome analysis to point-of-care and remote sites requires the availability of self-administered ambient temperature collection and storage tools. To address these challenges, a self-contained whole saliva collection and extraction system, RNAPro•SAL, has been developed that provides rapid ambient temperature collection along with concurrent processing and stabilization of extracellular RNA (exRNA) and proteins. The system was compared to the University of California, Los Angeles (UCLA) standard clinical collection process (standard operating procedure, SOP). Both systems measured total RNA and protein, and exRNA IL-8, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β-actin and ribosomal protein S9 (RPS9) by qPCR. Proteome analysis was measured by EIA analysis of interleukin-8 (IL-8), and β-actin, as well as total protein. Over 97% of viable cells were removed by both methods. The system compared favorably to the labor-intensive clinical SOP, which requires low-temperature collection and isolation, yielding samples with similar protein and exRNA recovery and stability.

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.

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.

Background: Oral cancer is the sixth most common cancer with a 5-year survival rate of approximately 60%. Presently, there are no scientifically credible early detection techniques beyond conventional clinical oral examination. The goal of this study is to validate whether the seven mRNAs and three proteins previously reported as biomarkers are capable of discriminating patients with oral squamous cell carcinomas (OSCC) from healthy subjects in independent cohorts and by a National Cancer Institute (NCI)-Early Detection Research Network (EDRN)-Biomarker Reference Laboratory (BRL)., Methods: Three hundred and ninety-five subjects from five independent cohorts based on case controlled design were investigated by two independent laboratories, University of California, Los Angeles (Los Angeles, CA) discovery laboratory and NCI-EDRN-BRL., Results: Expression of all seven mRNA and three protein markers was increased in OSCC versus controls in all five cohorts. With respect to individual marker performance across the five cohorts, the increase in interleukin (IL)-8 and subcutaneous adipose tissue (SAT) was statistically significant and they remained top performers across different cohorts in terms of sensitivity and specificity. A previously identified multiple marker model showed an area under the receiver operating characteristic (ROC) curve for prediction of OSCC status ranging from 0.74 to 0.86 across the cohorts., Conclusions: The validation of these biomarkers showed their feasibility in the discrimination of OSCCs from healthy controls. Established assay technologies are robust enough to perform independently. Individual cutoff values for each of these markers and for the combined predictive model need to be further defined in large clinical studies., Impact: Salivary proteomic and transcriptomic biomarkers can discriminate oral cancer from control subjects., (©2012 AACR.)

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.

The translation of salivary alpha-amylase (sAA) to the ambulatory assessment of stress hinges on the development of technologies capable of speedy and accurate reporting of sAA levels. Here, we describe the developmental validation and usability testing of a point-of-care, colorimetric, sAA biosensor. A disposable test strip allows for streamlined sample collection and a corresponding hand-held reader with integrated analytic capabilities permits rapid analysis and reporting of sAA levels. Bioanalytical validation utilizing saliva samples from 20 normal subjects indicates that, within the biosensor's linear range (10-230 U/ml), its accuracy (R(2)=0.989), precision (CV<9%), and measurement repeatability (range -3.1% to +3.1%) approach more elaborate laboratory-based, clinical analyzers. The truncated sampling-reporting cycle (<1 min) and the excellent performance characteristics of the biosensor has the potential to take sAA analysis out of the realm of dedicated, centralized laboratories and facilitate future sAA biomarker qualification studies., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Recent developments in biosensor technology allow point-of-use reporting of salivary alpha amylase (sAA) levels while approaching the precision and accuracy of conventional laboratory-based testing. We deployed a portable prototype sAA biosensor in 54 healthy, male dental students during a low stress baseline and during final exams. At baseline, participants completed the Brief Symptom Inventory (BSI). At baseline and the exam week, participants provided saliva samples at 10 AM, 1 PM, and 5 PM, and rated concurrent subjective distress. Although subjective distress was higher during exams compared to baseline, sAA levels did not differ between baseline and exams. Higher sAA levels were related to higher concurrent subjective distress, and higher depressive and social isolation symptoms on the BSI were related to lower sAA during exams. Results from this study, in combination with previous validation data, suggest that the sAA biosensor is a promising tool for point-of-use measures of exposure to stress., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Objective: Sjögren’s syndrome (SS) is a systemic autoimmune disease with a variety of presenting symptoms that may delay its diagnosis. We previously discovered a number of candidate salivary biomarkers for primary SS using both mass spectrometry and expression microarray analysis. In the current study, we aimed to verify these candidate biomarkers in independent patient populations and to evaluate their predictive values for primary SS detection., Methods: In total, 34 patients with primary SS, 34 patients with systemic lupus erythematosus (SLE), and 34 healthy individuals were enrolled for the validation studies. Salivary protein biomarkers were measured using either Western blotting or enzyme-linked immunosorbent assay, and the messenger RNA (mRNA) biomarkers were measured using quantitative polymerase chain reaction. Statistical analysis was performed using R software, version 2.9., Results: Three protein biomarkers (cathepsin D [CPD], α-enolase, and ß₂-microglobulin [ß₂m]) and 3 mRNA biomarkers (myeloid cell nuclear differentiation antigen [MNDA], guanylate binding protein 2 [GBP-2], and low-affinity IIIb receptor for the Fc fragment of IgG) were significantly elevated in patients with primary SS compared with both SLE patients and healthy controls. The combination of 3 protein biomarkers, CPD, α-enolase, and ß₂m, yielded a receiver operating characteristic (ROC) value of 0.99 in distinguishing primary SS from healthy controls. The combination of protein biomarkers ß₂m and 2 mRNA biomarkers, MNDA and GBP-2, reached an ROC of 0.95 in discriminating primary SS from SLE., Conclusion: We have successfully verified a panel of protein and mRNA biomarkers that can discriminate primary SS from both SLE and healthy controls. If further validated in patients with primary SS and those with sicca symptoms but no autoimmune disease, these biomarkers may lead to a simple yet highly discriminatory clinical tool for diagnosis of primary SS.

Background & Aims: Lack of detection technology for early pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. New strategies and biomarkers for early detection are sorely needed. In this study, we have conducted a prospective sample collection and retrospective blinded validation to evaluate the performance and translational utilities of salivary transcriptomic biomarkers for the noninvasive detection of resectable pancreatic cancer., Methods: The Affymetrix HG U133 Plus 2.0 Array (Affymetrix, Santa Clara, CA) was used to profile transcriptomes and discover altered gene expression in saliva supernatant. Biomarkers discovered from the microarray study were subjected to clinical validation using an independent sample set of 30 pancreatic cancer patients, 30 chronic pancreatitis patients, and 30 healthy controls., Results: Twelve messenger RNA biomarkers were discovered and validated. The logistic regression model with the combination of 4 messenger RNA biomarkers (KRAS, MBD3L2, ACRV1, and DPM1) could differentiate pancreatic cancer patients from noncancer subjects (chronic pancreatitis and healthy control), yielding a receiver operating characteristic plot, area under the curve value of 0.971 with 90.0% sensitivity and 95.0% specificity., Conclusions: The salivary biomarkers possess discriminatory power for the detection of resectable pancreatic cancer, with high specificity and sensitivity. This report provides the proof of concept of salivary biomarkers for the noninvasive detection of a systemic cancer and paves the way for prediction model validation study followed by pivotal clinical validation., (Copyright 2010 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Purpose: We have previously shown that a transcriptome is found in saliva and subpanels of these mRNAs can be used as oral cancer biomarkers. In this study, we measured the presence of microRNAs (miRNA) in saliva and determined their potential as an additional set of oral cancer biomarkers., Experimental Design: A total of 314 miRNAs were measured using reverse transcriptase-preamplification-quantitative PCR in 12 healthy controls. Degradation pattern of endogenous and exogenous saliva miRNAs were measured at room temperature over time. Selected miRNAs were validated in saliva of 50 oral squamous cell carcinoma patients and 50 healthy matched control subjects., Results: We detected approximately 50 miRNAs in both the whole and supernatant saliva. Endogenous saliva miRNA degraded much slower compared with exogenous miRNA. Two miRNAs, miR-125a and miR-200a, were present in significantly lower levels (P < 0.05) in the saliva of oral squamous cell carcinoma patients than in control subjects., Conclusions: Both whole and supernatant saliva of healthy controls contained dozens of miRNAs, and similar to saliva mRNAs, these miRNAs are stable. Saliva miRNAs can be used for oral cancer detection.

Purpose: This study aims to explore the presence of informative protein biomarkers in the human saliva proteome and to evaluate their potential for detection of oral squamous cell carcinoma (OSCC)., Experimental Design: Whole saliva samples were collected from patients (n = 64) with OSCC and matched healthy subjects (n = 64). The proteins in pooled whole saliva samples of patients with OSCC (n = 16) and matched healthy subjects (n = 16) were profiled using shotgun proteomics based on C4 reversed-phase liquid chromatography for prefractionation, capillary reversed-phase liquid chromatography with quadruple time-of-flight mass spectrometry, and Mascot sequence database searching. Immunoassays were used for validation of the candidate biomarkers on a new group of OSCC (n = 48) and matched healthy subjects (n = 48). Receiver operating characteristic analysis was exploited to evaluate the diagnostic value of discovered candidate biomarkers for OSCC., Results: Subtractive proteomics revealed several salivary proteins at differential levels between the OSCC patients and matched control subjects. Five candidate biomarkers were successfully validated using immunoassays on an independent set of OSCC patients and matched healthy subjects. The combination of these candidate biomarkers yielded a receiver operating characteristic value of 93%, sensitivity of 90%, and specificity of 83% in detecting OSCC., Conclusion: Patient-based saliva proteomics is a promising approach to searching for OSCC biomarkers. The discovery of these new targets may lead to a simple clinical tool for the noninvasive diagnosis of oral cancer. Long-term longitudinal studies with large populations of individuals with oral cancer and those who are at high risk of developing oral cancer are needed to validate these potential biomarkers.

Background: The application of global gene expression profiling to saliva samples is hampered by the presence of partially fragmented and degraded RNAs that are difficult to amplify and detect with the prevailing technologies. Moreover, the often limited volume of saliva samples is a challenge to quantitative PCR (qPCR) validation of multiple candidates. The aim of this study was to provide proof-of-concept data on the combination of a universal mRNA-amplification method with exon arrays for candidate selection and a multiplex preamplification method for easy validation., Methods: We used a universal mRNA-specific linear-amplification strategy in combination with Affymetrix Exon Arrays to amplify salivary RNA from 18 healthy individuals on the nanogram scale. Multiple selected candidates were preamplified in one multiplex reverse transcription PCR reaction, cleaned up enzymatically, and validated by qPCR., Results: We defined a salivary exon core transcriptome (SECT) containing 851 transcripts of genes that have highly similar expression profiles in healthy individuals. A subset of the SECT transcripts was verified by qPCR analysis. Informatics analysis of the SECT revealed several functional clusters and sequence motifs. Sex-specific salivary exon biomarkers were identified and validated in tests with samples from healthy individuals., Conclusions: It is feasible to use samples containing fragmented RNAs to conduct high-resolution expression profiling with coverage of the entire transcriptome and to validate multiple targets from limited amounts of sample.

Objective: To identify a panel of protein and messenger RNA (mRNA) biomarkers in human whole saliva (WS) that may be used in the detection of primary Sjögren's syndrome (SS)., Methods: Mass spectrometry and expression microarray profiling were used to identify candidate protein and mRNA biomarkers of primary SS in WS samples. Validation of the discovered mRNA and protein biomarkers was also demonstrated using real-time quantitative polymerase chain reaction and immunoblotting techniques., Results: Sixteen WS proteins were found to be down-regulated and 25 WS proteins were found to be up-regulated in primary SS patients compared with matched healthy control subjects. These proteins reflected the damage of glandular cells and inflammation of the oral cavity system in patients with primary SS. In addition, 16 WS peptides (10 up-regulated and 6 down-regulated in primary SS) were found at significantly different levels (P < 0.05) in primary SS patients and controls. Using stringent criteria (3-fold change; P < 0.0005), 27 mRNA in saliva samples were found to be significantly up-regulated in the primary SS patients. Strikingly, 19 of 27 genes that were found to be overexpressed were interferon-inducible or were related to lymphocyte filtration and antigen presentation known to be involved in the pathogenesis of primary SS., Conclusion: Our preliminary study has indicated that WS from patients with primary SS contains molecular signatures that reflect damaged glandular cells and an activated immune response in this autoimmune disease. These candidate proteomic and genomic biomarkers may improve the clinical detection of primary SS once they have been further validated. We also found that WS contains more informative proteins, peptides, and mRNA, as compared with gland-specific saliva, that can be used in generating candidate biomarkers for the detection of primary SS.

Purpose: Oral fluid (saliva) meets the demand for noninvasive, accessible, and highly efficient diagnostic medium. Recent discovery that a large panel of human RNA can be reliably detected in saliva gives rise to a novel clinical approach, salivary transcriptome diagnostics. The purpose of this study is to evaluate the diagnostic value of this new approach by using oral squamous cell carcinoma (OSCC) as the proof-of-principle disease., Experimental Design: Unstimulated saliva was collected from patients (n = 32) with primary T1/T2 OSCC and normal subjects (n = 32) with matched age, gender, and smoking history. RNA isolation was done from the saliva supernatant, followed by two-round linear amplification with T7 RNA polymerase. Human Genome U133A microarrays were applied for profiling human salivary transcriptome. The different gene expression patterns were analyzed by combining a t test comparison and a fold-change analysis on 10 matched cancer patients and controls. Quantitative polymerase chain reaction (qPCR) was used to validate the selected genes that showed significant difference (P < 0.01) by microarray. The predictive power of these salivary mRNA biomarkers was analyzed by receiver operating characteristic curve and classification models., Results: Microarray analysis showed there are 1,679 genes exhibited significantly different expression level in saliva between cancer patients and controls (P < 0.05). Seven cancer-related mRNA biomarkers that exhibited at least a 3.5-fold elevation in OSCC saliva (P < 0.01) were consistently validated by qPCR on saliva samples from OSCC patients (n = 32) and controls (n = 32). These potential salivary RNA biomarkers are transcripts of IL8, IL1B, DUSP1, HA3, OAZ1, S100P, and SAT. The combinations of these biomarkers yielded sensitivity (91%) and specificity (91%) in distinguishing OSCC from the controls., Conclusions: The utility of salivary transcriptome diagnostics is successfully demonstrated in this study for oral cancer detection. This novel clinical approach could be exploited to a robust, high-throughput, and reproducible tool for early cancer detection. Salivary transcriptome profiling can be applied to evaluate its usefulness for other major disease applications as well as for normal health surveillance.