A review of research on salivary biomarkers for oral cancer detection.
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ABSTRACT:
SUBMITTER: Cheng YS
PROVIDER: S-EPMC3945802 | biostudies-literature | 2014 Feb
REPOSITORIES: biostudies-literature
Publications
A review of research on salivary biomarkers for oral cancer detection.
Cheng Yi-Shing Lisa YS Rees Terry T Wright John J
Clinical and translational medicine 20140224 1
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 car ...[more]
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Project description:Different efforts have been made to find better and less invasive methods for the diagnosis and prediction of oral cancer, such as the study of saliva as a source of biomarkers. The aim of this study was to perform a scoping review about salivary molecules that have been assessed as possible biomarkers for the diagnosis of oral squamous cell carcinoma (OSCC). A search was conducted using EBSCO, PubMed (MEDLINE), Scopus, and Web of Science. The research question was as follows: which molecules present in saliva have utility to be used as biomarkers for the early detection of oral cancer? Sixty-two studies were included. Over 100 molecules were assessed. Most of the markers were oriented towards the early diagnosis of OSCC and were classified based on their ability for detecting OSCC and oral potentially malignant disorders (OPMDs), OSCC outcome prediction, and the prediction of the malignant transformation of OPMDs. TNF-α, IL-1β, IL-6 IL-8, LDH, and MMP-9 were the most studied, with almost all studies reporting high sensitivity and specificity values. TNF-α, IL-1β, IL-6 IL-8, LDH, and MMP-9 are the most promising salivary biomarkers. However, more studies with larger cohorts are needed before translating the use of these biomarkers to clinical settings.
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Project description: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).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.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.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.Salivary proteomic and transcriptomic biomarkers can discriminate oral cancer from control subjects.
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Project description:We evaluated potential biomarkers in human whole saliva for the early diagnosis of oral squamous cell carcinoma (OSCC). We selected 30 candidate genes with relevance to cancer from recent reports in PubMed. Saliva samples were obtained from 34 non-tumor control and 33 OSCC patients. Real-time PCR was performed, and mRNA levels were compared. Normalized mRNA levels of six genes (NGFI-A binding protein 2 (NAB2), cytochrome P450, family 27, subfamily A, polypeptide 1 (CYP27A1), nuclear pore complex interacting protein family, member B4 (NPIPB4), monoamine oxidase B (MAOB), sialic acid acetyltransferase (SIAE), and collagen, type III, alpha 1 (COL3A1)) were significantly lower in saliva of OSCC patients. Receiver operating characteristics (ROC) analysis was used to individually evaluate the predictive power of the potential biomarkers for OSCC diagnosis. The area under the curve (AUC) values were evaluated for the OSCC vs. non-tumor groups via univariate ROC analyses, as well as multivariate ROC analyses of combinations of multiple potential biomarkers. The combination of CYP27A1 + SIAE showed a favorable AUC value of 0.84. When we divided saliva samples into two groups according to age using a 60-year cut-off, with OSCC patients and controls evaluated together, the AUC of MAOB-NAB2 was more predictive of OSCC in the under-60 group (AUC, 0.91; sensitivity, 0.92; and specificity, 0.86) than any other gene combination. These results are expected to aid the early diagnosis of OSCC, especially in patients under 60 years of age. While more studies with larger numbers of patients are necessary, our result suggest that salivary mRNA would be a potent biomarker for early OSCC diagnosis.
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Project description:Proteases are important molecules that are involved in many physiological and pathological processes of the human body, such as growth, apoptosis and metastasis cancer cells. They are potential targets in cancer diagnosis and biotherapy. In this study, we analyzed the salivary protease spectrum of patients with oral squamous cell carcinoma (OSCC), oral benign masses and chronic periodontitis, as well as that of health, using human protease array kits, enzyme-linked immunosorbent assay, western blot and immunofluorescence. The salivary protease spectrum was found to be associated with oral diseases. For example, the saliva of patients with OSCC contained increased numbers of proteases than those of other oral diseases and health. The levels of matrix metalloproteinase (MMP)-1, MMP-2, MMP-10, MMP-12, A disintegrin and metalloprotease (ADAM)9, A disintegrin and metalloprotease with thrombospondin type 13 motifs (ADAMST13), cathepsin V and kallikrein 5 in the saliva of patients with OSCC were significantly increased compared with those of other groups. Taking MMP-1, cathepsin V, kallikrein 5 and ADAM9 as biomarkers of OSCC, cutoff values were199, 11.34, 9.29 and 202.55 pg·mL-1, respectively. From the area under the curve, sensitivity and specificity, the combination of cathepsin V/kallikrein5/ADAM9 was an optimal biomarker for diagnosing OSCC. Thus, analysis of the salivary protease spectrum may be an innovative and cost-efficient approach to evaluating the health status of the oral cavity. Specifically, increases in cathepsin V, kallikrein 5 and ADAM9 may be useful biomarkers in the screening and diagnosis of OSCC.
| S-EPMC6315043 | biostudies-literature
Project description:Oral cavity squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. In Taiwan, OSCC is the fifth leading cause of cancer-related mortality and leads to 2800 deaths per year. The poor outcome of OSCC patients is principally ascribed to the fact that this disease is often advanced at the time of diagnosis, suggesting that early detection of OSCC is urgently needed. Analysis of cancer-related body fluids is one promising approach to identify biomarker candidates of cancers. To identify OSCC biomarkers, salivary proteomes of OSCC patients, individuals with oral potentially malignant disorders (OPMDs), and healthy volunteers were comparatively profiled with isobaric tags for relative and absolute quantitation (iTRAQ)-based mass spectrometry (MS). The salivary levels of 67 and 18 proteins in the OSCC group are elevated and decreased compared with that in the noncancerous group (OPMD and healthy groups), respectively. The candidate biomarkers were further selected using the multiple reaction monitoring (MRM)-MS and validated with the immunoassays. More importantly, the higher salivary level of three proteins, complement factor H (CFH), fibrinogen alpha chain (FGA), and alpha-1-antitrypsin (SERPINA1) was correlated with advanced stages of OSCC. Our results indicate that analysis of salivary proteome is a feasible strategy for biomarker discovery, and the three proteins are potential salivary markers for OSCC diagnosis.
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Project description:A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. 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 transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatants respectively. Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven transcriptomic biomarker candidates and two proteomic biomarker candidates were selected for a preclinical validation using an independent sample set. Transcriptomic biomarkers were validated by RT-qPCR and proteomic biomarkers were validated by quantitative protein immunoblot. 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. This report provides proof of concept of salivary biomarkers for the non-invasive detection of breast cancer. The salivary biomarkersâ discriminatory power paves the way for a PRoBE-design definitive validation study. Keywords: Salivary biomarker, Breast cancer, Early detection, Salivary transcriptome, Salivary proteome This study, which was approved by the UCLA and Cedars-Sinai Medical Center Institutional Review Boards (#06-07-043 and #3870, respectively), started sample collection in February 2007. The sample collection followed the PRoBE principle (prospective specimen collection). The saliva bank for breast cancer project at the UCLA Dental Research Institute in collaboration with Cedars Sinai Medical Center has collected 200 saliva samples since 2007 with all subjects recruited from the Saul and Joyce Brandman Breast Cancer Center. Of these, 113 samples, including 41 breast cancer patients and 72 healthy control individuals, were selected for the discovery and validation phase of this study. Inclusion criteria of cancer patients consisted of a confirmed diagnosis of breast cancer. Exclusion criteria of cancer patients included therapy/surgery and/or a diagnosis of other malignancies within 5 years prior to saliva collection. Exclusion criteria of control patients included a diagnosis of any malignancies within 5 years prior to saliva collection. Written informed consents and questionnaire data sheets were obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were consistently collected, stabilized, and preserved as previously described. The sample supernatants were reserved at -80 C prior to assay. This study consisted of a discovery phase, followed by an independent preclinical validation phase. Of the 113 samples, 10 breast cancer samples and 10 healthy control samples were chosen for the discovery phase. All breast cancer cases are invasive ductal carcinoma (IDC), the most common type of breast cancer. Biomarkers identified from the discovery studies were first verified using the discovery sample set. An independent sample set, including 31 breast cancer patients and 62 healthy control subjects, was used for the biomarker validation phase.
2010-02-21 | E-GEOD-20266 | biostudies-arrayexpress
Project description:Pancreatic cancer is the fourth 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. Oral fluid (saliva) meets the demand for non-invasive, accessible, and highly efficient diagnostic medium. The level of salivary analytes, such as mRNA and microflora, vary upon disease onset; thus possess valuable signatures for early detection and screening. In this study, we evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for non-invasive detection of early pancreatic cancer. Two biomarker discovery technologies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133 Plus 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 early 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. 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 study comprehensively compared the salivary transcriptome and microflora between pancreatic cancer and control subjects. We have discovered and validated eleven mRNA biomarkers and two microbial biomarkers for early detection of pancreatic cancer in saliva. The logistic regression model with four salivary biomarkers can detect pancreatic cancer specifically without the complication of chronic pancreatitis. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer. Keywords: Salivary biomarker, pancreatic cancer, early detection, salivary transcriptome, salivary microflora This study, which was approved by the UCLA Institutional Review Board, started sample collection in February 2006 and ended in April 2008. It had a discovery and verification phase, followed by an independent validation phase. All patients with clinically diagnosed early or locally advanced pancreatic cancer, chronic pancreatitis and matched healthy control were recruited from the UCLA Medical Center. The controls were matched for gender, age, ethnicity and smoking history. We chose early and locally advanced pancreatic cancers because they were considered early stage diseases. All patients were recently diagnosed with primary disease, and had not received any prior treatment in the form of chemotherapy, radiotherapy, surgery, or alternative remedies. No subjects had a history of prior malignancy, immunodeficiency, autoimmune disorders, hepatitis, or HIV infection. Written informed consent was obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were collected and processed as previously described. The saliva bank of pancreatic disease at the UCLA Dental Research Institute has collected 283 saliva samples since 2006. Of these, 114 samples, from 42 pancreatic cancer patients, 30 chronic pancreatitis patients and 42 healthy control subjects, met the following eligibility criteria: the disease subjectsâ?? samples were obtained immediately after primary diagnosis from patients without evidence of metastasis; the saliva sample was free of blood (Table 1 in accompanying manuscript). Of the 114 samples, 12 pancreatic cancer samples and 12 healthy control samples were chosen for the discovery and verification phase. The transcriptomic approach profiled the saliva supernatant samples from 12 pancreatic cancer patients and 12 healthy control subjects using the Affymetrix Human Genome U133 Plus 2.0 Array platform.
2008-12-30 | E-GEOD-14245 | biostudies-arrayexpress
Project description:Pancreatic cancer is the fourth 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. Oral fluid (saliva) meets the demand for non-invasive, accessible, and highly efficient diagnostic medium. The level of salivary analytes, such as mRNA and microflora, vary upon disease onset; thus possess valuable signatures for early detection and screening. In this study, we evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for non-invasive detection of early pancreatic cancer. Two biomarker discovery technologies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133 Plus 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 early 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. 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 study comprehensively compared the salivary transcriptome and microflora between pancreatic cancer and control subjects. We have discovered and validated eleven mRNA biomarkers and two microbial biomarkers for early detection of pancreatic cancer in saliva. The logistic regression model with four salivary biomarkers can detect pancreatic cancer specifically without the complication of chronic pancreatitis. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer. Keywords: Salivary biomarker, pancreatic cancer, early detection, salivary transcriptome, salivary microflora
2008-12-31 | GSE14245 | GEO
Project description:A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. 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 transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatants respectively. Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven transcriptomic biomarker candidates and two proteomic biomarker candidates were selected for a preclinical validation using an independent sample set. Transcriptomic biomarkers were validated by RT-qPCR and proteomic biomarkers were validated by quantitative protein immunoblot. 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. This report provides proof of concept of salivary biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers’ discriminatory power paves the way for a PRoBE-design definitive validation study. Keywords: Salivary biomarker, Breast cancer, Early detection, Salivary transcriptome, Salivary proteome
2010-02-11 | GSE20266 | GEO