Salivary biomarkers in cancer detection and management

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.

Objectives: The high burden of breast cancer in women worldwide underscores the unmet potential of biomarker for early detection. New strategies and biomarkers for early detection of breast cancer are sorely needed. In this study, we have conducted a prospective sample collection and retrospective blinded validation (PRoBE design) to evaluate the performance and translational utilities of salivary biomarkers for the non-invasive detection of breast cancer. Methods: The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatant from patients with invasive ductal carinoma and matched controls respectively. The discovered transcriptomic and proteomic candidate biomarkers were subjected to a clinical validation using an independent sample set of 31 breast cancer (invasive ductal carcinoma, stages I and II) and 62 healthy controls. Transcriptomic biomarkers were validated by qPCR and proteomic biomarkers were validated by quantitative immuno-blot. Results: Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven mRNA biomarker candidates and two protein biomarker candidates were selected for independent validation. Eight mRNA biomarkers and one protein biomarker have been validated for breast cancer detection, yielding ROC-plot AUC values between 0.665 and 0.959. Six biomarkers have known associations with breast cancer. Conclusion: Salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity. This report provides proof of concept of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers' discriminatory power paves the way for a pivotal clinical validation. Supported by NIH grant U01DE016275, U01DE017790 and R21CA126733 (DTW). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2726.

A promising method for non-invasive cancer diagnosis and prognosis is through salivary biomarkers. By utilizing the distinct characteristics of saliva and the progress made in biomarker studies, these markers provide more accurate diagnoses for a wider range of malignancies. An attempt was made to thoroughly investigate the field of salivary biomarkers for tumor prognosis and diagnosis, with an emphasis on their use in various cancer forms. Predetermined search criteria were utilized for a systematic search across numerous databases for peer-reviewed papers from 2009 to 2021. Studies concentrating on the detection, validation, and clinical use of salivary biomarkers for different types of cancers were included in the inclusion criteria. Initially, 238 articles were found, of which 15 relevant articles satisfied the inclusion requirements. Information on study aims, methodology, findings, and conclusions were gathered for data extraction. We identified recurrent themes, patterns, and contradictions by a thematic analysis. We also assessedstate-of-the-art salivary biomarkers for tumor diagnosis and prognosis. One major finding is the identification of biomolecules in saliva linked to several cancer forms, including pancreatic, oral, breast, lung, and stomach cancers. There is an increasing amount of evidence demonstrating the value of saliva-based diagnostics in oncology. This is due to new detection methodsand developments in salivary proteomics and genomics. Identification of exosomes and microvesicles as salivary biomarker profiles offered molecular understandings of the etiology and evolution of cancer, thereby opening new avenues for diagnosis and treatment. Salivary biomarkers are a non-invasive approach for the early detection and prediction of cancer, thanks to the unique properties of saliva and advancements in biomarker research. This potential revolution could enhance patient outcomes and reduce cancer-related deaths.

Using saliva for disease diagnostics and health surveillance is a promising approach as collecting saliva is relatively easy and non-invasive. Over the past two decades, using salivary biomarkers specifically for early cancer detection has attracted much research interest, especially for cancers occurring in the oral cavity and oropharynx, for which the five-year survival rate (62%) is still one of the lowest among all major human cancers. More than 90% of oral cancers are oral squamous cell carcinoma (OSCC) and the standard method for detection is through a comprehensive clinical examination by oral healthcare professionals. Despite the fact that the oral cavity is easily accessible, most OSCCs are not diagnosed until an advanced stage, which is believed to be the major reason for the low survival rate, and points to the urgent need for clinical diagnostic aids for early detection of OSCC. Thus, much research effort has been dedicated to investigating potential salivary biomarkers for OSCC, and more than 100 such biomarkers have been reported in the literature. However, some important issues and challenges have emerged that require solutions and further research in order to find reliable OSCC salivary biomarkers for clinical use. This review article provides an up-to-date list of potential OSCC salivary biomarkers reported as of the fall of 2013, and discusses those emerging issues. By raising the awareness of these issues on the part of both researchers and clinicians, it is hoped that reliable, specific and sensitive salivary biomarkers may be found soon—and not only biomarkers for early OSCC detection but also for detecting other types of cancers or even for monitoring non-cancerous disease activity.

The present study evaluated the sensitivity and specificity of important proteomic salivary biomarkers; IL-6, IL-8, and sCD44 in the early detection of oral cancer, and any possible associations with risk factors of oral cancer in an Egyptian population. The present investigation was conducted on 100 individuals; 25 healthy controls, 25 patients having oral potentially malignant disorders (OPMDs) with dysplasia; 25 patients having OPMDs without dysplasia, and 25 oral cancer patients. Demographic data modified gingival index, oral hygiene level, and salivary levels of the biomarkers were assessed. Salivary levels of IL-6, IL-8, and sCD44 progressively increased with increased disease severity. Salivary IL-8 and IL-6 levels possess a discriminating potential from normal tissue through different degrees of dysplasia to oral cancer, sCD44 levels had a discriminating power between normal and dysplastic tissues with high sensitivity and specificity. A positive correlation was found between the three biomarkers and the grade of oral squamous cell carcinoma (OSCC) and with different risk factors. This is the first study that evaluated multiple salivary proteomic biomarkers in the Egyptian population, and the results validate the ability of IL-6, IL-8, and sCD44 to be used as sensitive diagnostic and prognostic biomarkers for screening and early detection of oral cancer.

The aim of this paper was to discuss the potency of gut microbiome as a non-invasive predictive biomarker for early detection of pancreatic cancer and hepatocellular carcinoma. We analysed the available up-to-date literature (PubMed, Embase, Google Scholar databases) regarding the link between gut microbiome and early detection of pancreatic cancer, as well as hepatocellular carcinoma. The following search linked to gut microbiome and aforementioned cancers was used: 'gut microbiome', 'gut microbiota', 'pancreatic cancer', 'pancreatic ductal adenocarcinoma', hepatocellular carcinoma', 'microbial biomarkers', 'fungal microbiota', 'mycobiota'. The search was conducted in English. The association between gut microbiota imbalance and development of pancreatic cancer and hepatocellular carcinoma has been recognized during last several years. The most common type of pancreatic cancer is pancreatic ductal adenocarcinoma, whose carcinogenesis is strongly related to oral microbial dysbiosis, H. pylori infection, bactibilia, hepatotropic viruses, and intrapancreatic microbiota. It is known that gut-liver axis exists and may affect hepatocarcinogenesis. Currently, the treatment strategies of these cancers are strongly limited and there are not well-recognized screening tools to early diagnose them. The growing attention towards the use of gut microbiome as a predictive non-invasive biomarker to detect pancreatic cancer and hepatocellular carcinoma in early stage has been observed. To conclude, the field regarding the link between gut microbiome as a non-invasive biomarkers and early detection of pancreatic cancer and hepatocellular carcinoma exists, however, it is not well-investigated. Additionally, many of the studies were conducted with small sample sizes, whereas biomarkers are ethnicity-dependent and should be validated in wide range of populations. Nevertheless, these aspects are promising and open up new diagnostic options.

Identifying novel biomarkers for early detection of lung cancer is crucial. Non-invasively available saliva is an ideal biofluid for biomarker exploration; however, the rationale underlying biomarker detection from organs distal to the oral cavity in saliva requires clarification. Therefore, we analyzed metabolomic profiles of cancer tissues compared with those of adjacent non-cancerous tissues, as well as plasma and saliva samples collected from patients with lung cancer (n = 109 pairs). Additionally, we analyzed plasma and saliva samples collected from control participants (n = 83 and 71, respectively). Capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry were performed to comprehensively quantify hydrophilic metabolites. Paired tissues were compared, revealing 53 significantly different metabolites. Plasma and saliva showed 44 and 40 significantly different metabolites, respectively, between patients and controls. Of these, 12 metabolites exhibited significant differences in all three comparisons and primarily belonged to the polyamine and amino acid pathways; N1-acetylspermidine exhibited the highest discrimination ability. A combination of 12 salivary metabolites was evaluated using a machine learning method to differentiate patients with lung cancer from controls. Salivary data were randomly split into training and validation datasets. Areas under the receiver operating characteristic curve were 0.744 for cross-validation using training data and 0.792 for validation data. This model exhibited a higher discrimination ability for N1-acetylspermidine than that for other metabolites. The probability of lung cancer calculated using this model was independent of most patient characteristics. These results suggest that consistently different salivary biomarkers in both plasma and lung tissues might facilitate non-invasive lung cancer screening.

Over the last years, epigenetic changes, including DNA methylation and histone modifications detected in early tumorigenesis and cancer progression, have been proposed as biomarkers for cancer detection, tumor prognosis, and prediction to treatment response. Importantly for the clinical use of DNA methylation biomarkers, specific methylation signatures can be detected in many body fluids including serum/plasma samples. Several of these potential epigenetic biomarkers detected in women's cancers, colorectal cancers, prostate, pancreatic, gastric, and lung cancers are discussed. Studies conducted in breast cancer, for example, found that aberrant methylation detection of several genes in serum DNA and genome-wide epigenetic change could be used for early breast cancer diagnosis and prediction of breast cancer risk. In colorectal cancers, numerous studies have been conducted to identify specific methylation markers important for CRC detection and in fact clinical assays evaluating the methylation status of SEPT19 gene and vimentin, became commercially available. Furthermore, some epigenetic changes detected in gastric washes have been suggested as potential circulating noninvasive biomarkers for the early detection of gastric cancers. For the early detection of prostate cancer, few epigenetic markers have shown a better sensitivity and specificity than serum PSA, indicating that the inclusion of these markers together with current screening tools, could improve early diagnosis and may reduce unnecessary repeat biopsies. Similarly, in pancreatic cancers, abnormal DNA methylation of several genes including NPTX2, have been suggested as a diagnostic biomarker. Epigenetic dysregulation was also observed in several tumor suppressor genes and miRNAs in lung cancer patients, suggesting the important role of these changes in cancer initiation and progression. In conclusion, epigenetic changes detected in biological fluids could play an essential role in the early detection of several cancer types and this may have a great impact for the cancer precision medicine field.

More than 100 salivary constituents have been found to show levels significantly different in patients with oral squamous cell carcinoma (OSCC) from those found in healthy controls, and therefore have been suggested to be potential salivary biomarkers for OSCC detection. However, many of these potential OSCC salivary biomarkers are also involved in chronic inflammation, and whether the levels of these biomarkers could be affected by the presence of chronic periodontitis was not known. The objective of this pilot study was therefore to measure the levels of seven previously reported potential OSCC salivary mRNA biomarkers in patients with chronic periodontitis and compare them to levels found in patients with OSCC and healthy controls. The seven salivary mRNAs were interleukin (IL)-8, IL-1β, dual specificity phosphatase 1, H3 histone family 3A, ornithine decarboxylase antizyme 1, S100 calcium-binding protein P (S100P) and spermidine/spermine N1-acetyltransferase 1. Unstimulated whole saliva samples were collected from a total of 105 human subjects from the following four study groups: OSCC; CPNS (chronic periodontitis, moderate to severe degree, non-smokers); CPS (chronic periodontitis, moderate to severe degree, smokers); and healthy controls. Levels of each mRNA in patient groups (OSCC or chronic periodontitis) relative to the healthy controls were determined by a pre-amplification reverse transcription-quantitative polymerase chain reaction approach with nested gene-specific primers. Results were recorded and analyzed by the Bio-Rad CFX96 Real-Time System. Mean fold changes between each pair of patient vs. control groups were analyzed by the Mann-Whitney U-test with Bonferroni corrections. Only S100P showed significantly higher levels in patients with OSCC compared to both patients with CPNS (p = 0.003) and CPS (p = 0.007). The difference in S100P levels between patients with OSCC and healthy controls was also marginally significant (p = 0.009). There was no significant difference in the levels of salivary IL-8, IL-1β and dual specificity phosphatase 1 mRNAs between patients with OSCC and patients with CPNS (p = 0.510, 0.058 and 0.078, respectively); no significant difference in levels of salivary ornithine decarboxylase antizyme 1 and spermine N1-acetyltransferase mRNAs between patients with OSCC and patients with CPS (p = 0.318 and 0.764, respectively); and no significant difference in levels of the H3 histone family 3A mRNA between patients with OSCC and either CPS (p = 0.449) or healthy controls (p = 0.107). Salivary S100P mRNA could be a reliable biomarker for OSCC detection, regardless of the presence of chronic periodontitis. The presence of chronic periodontitis could significantly affect the levels of the other six mRNAs, and negatively influence reliability for using them as biomarkers for oral cancer detection.

BackgroundA sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.Methodology/Principal FindingsSalivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.ConclusionsOur findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.

Oral cancer is a significant global health concern, with a high mortality rate mainly due to late-stage diagnosis. Early detection plays a critical role in improving patient outcomes, highlighting the need for non-invasive and accessible screening methods. Salivary biomarkers have emerged as a promising avenue for oral cancer detection, leveraging advancements in human DNA and RNA analysis. Several DNA-based biomarkers, such as genetic mutations, chromosomal aberrations, and epigenetic alterations, have shown promise in detecting oral cancer at various stages. Likewise, RNA-based biomarkers, including microRNAs, long non-coding RNAs, and messenger RNAs, have demonstrated potential for diagnosing oral cancer and predicting treatment outcomes. The integration of high-throughput sequencing technologies, such as next-generation sequencing and transcriptomic profiling, has enabled the identification of novel biomarkers and provided deeper insights into the molecular mechanisms underlying oral cancer development and progression. Despite the promising results, challenges remain in standardizing sample collection, establishing robust biomarker panels, and validating their clinical utility. Nevertheless, salivary biomarkers hold great promise as a non-invasive, cost-effective, and accessible approach for oral cancer detection, ultimately leading to improved patient outcomes through early diagnosis and intervention. The analysis of genetic material obtained from saliva offers several advantages, including ease of collection, non-invasiveness, and the potential for repeated sampling. Furthermore, saliva reflects the physiological and pathological status of the oral cavity, making it an ideal source for biomarker discovery and validation. This article presents a comprehensive review of the current research on salivary biomarkers for oral cancer detection, focusing on insights gained from human DNA and RNA analysis.

4630 Pancreatic cancer is the 4th leading cause of cancer death. Lack of early detection technology for pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. We evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for pancreatic cancer detection. Biomarker discovery strategies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133+2.0 array was used to discover altered gene expression in saliva supernatant. The Human Oral Microbe Identification Microarray (HOMIM) was used to investigate microflora shift in saliva pellet. Biomarkers selected from both studies were subjected to an independent clinical validation using a cohort of 30 pancreatic cancer, 30 chronic pancreatitis and 30 healthy matched-control saliva samples. Two panels of salivary biomarkers, including eleven mRNA biomarkers and two microbial biomarkers were discovered and validated for pancreatic cancer detection. The logistic regression model with the combination of three mRNA biomarkers (ACRV1, DMXL2 and DPM1) yielded a ROC-plot AUC value of 0.974 (95% CI, 0.896 to 0.997; P < 0.0001) with 93.3% sensitivity and 90% specificity in distinguishing pancreatic cancer patients from healthy subjects. The logistic regression model with the combination of two bacterial biomarkers (Neisseria elongata and Streptococcus mitis) yielded a ROC-plot AUC value of 0.895 (95% CI, 0.784 to 0.961; P < 0.0001) with 96.4% sensitivity and 82.1% specificity in distinguishing pancreatic cancer patients from healthy subjects. More importantly, the logistic regression model with the combination of four biomarkers (mRNA biomarkers, ACRV1, DMXL2 and DPM1; bacterial biomarker, S. mitis) could differentiate pancreatic cancer patients from all non-cancer subjects (chronic pancreatitis and healthy control), yielding a ROC-plot AUC value of 0.949 (95% CI, 0.877 to 0.985; P < 0.0001) with 92.9% sensitivity and 85.5% specificity. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer. No significant financial relationships to disclose.

Background: DNA methylation significantly contributes to all hallmarks of cancer. In particular, promoter hypermethylation has been identified as a potential marker for early detection of cancer, therapy monitoring, assessment of prognosis or prediction of therapy response. Here, we identified and validated breast cancer-specific methylation markers for diagnosis of the disease with high sensitivity and specificity. Methods: 151 bio-banked samples were obtained for a randomized blind study; 65 subjects diagnosed with breast cancer (Stage I to IV), 15 subjects with benign breast disease, 32 subjects diagnosed with other cancer types (11 colorectal, 9 liver and 12 lung cancer), and 39 healthy donor samples. Cell-free DNA was then extracted from the samples, bisulfite converted, and DNA methylation was quantified by using the IvyGene Platform. Finally, the raw data were collected and analyzed to evaluate the test performance. Results: A total of 53 of the 65 breast cancer samples were correctly identified for an overall calculated sensitivity of 89% with little difference between the sensitivity of detecting Stage I to Stage IV breast cancer (range 88% to 94%). The breast cancer subjects were correctly identified with 96% specificity. Additionally, 28 of 32 samples drawn from healthy donor subjects (specificity 95%) and all 15 samples drawn from subjects diagnosed with benign breast disease (specificity 100%) were also correctly identified. Of the samples drawn from subjects with cancer other than breast cancer, over 96% of lung cancer, colorectal cancer and liver cancer samples were correctly identified as not breast cancer. Conclusion: The results demonstrate the high diagnostic potential of ctDNA methylation markers in the blood for the detection of breast cancer. In addition, a quantitative analysis of ctDNA provides an opportunity for non-invasive detection of cancer and it's benefits can be anticipated to improve patient management and healthcare quality.

Cancer is the second most common cause of death in the USA. Its symptoms are often not specific and absent, until the tumors have already metastasized. Therefore, there is an urgent demand for developing rapid, highly accurate and noninvasive tools for cancer screening, early detection, diagnostics, staging and prognostics. Saliva as a multi-constituent oral fluid comprises secretions from the major and minor salivary glands, extensively supplied by blood. Molecules such as DNAs, RNAs, proteins, metabolites, and microbiota, present in blood, could be also found in saliva. Recently, salivary diagnostics has drawn significant attention for the detection of specific biomarkers, since the sample collection and processing are simple, cost-effective, and precise and do not cause patient discomfort. Here, we review recent salivary candidate biomarkers for systemic cancers by dividing them according to their origin into: genomic, transcriptomic, proteomic, metabolomic and microbial types.

Salivary Transcriptomic Biomarkers for Detection of Resectable Pancreatic Cancer