The Diagnostic Value of Salivary microRNA in Esophageal Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE41268 | GEO | 2012/10/03
SECONDARY ACCESSION(S): PRJNA176426
REPOSITORIES: GEO
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Project description:Tissue microRNAs (miRNAs) can detect cancers and predict prognosis. Several recent studies reported that tissue, plasma, and saliva miRNAs share similar expression profiles. In this study, we investigated the diagnostic value of salivary miRNAs (including whole saliva and saliva supernatant) for detection of esophageal cancer. By Agilent microarray, six deregulated miRNAs from whole saliva samples from seven patients with esophageal cancer and three healthy controls were selected. The six selected miRNAs were subjected to validation of their expression levels by RT-qPCR using both whole saliva and saliva supernatant samples from an independent set of 39 patients with esophageal cancer and 19 healthy controls.
2012-10-03 | E-GEOD-41268 | biostudies-arrayexpress
Project description:Background: The differential abundance of cell-free RNAs in bodily fluids is emerging as a promising tool for the non-invasive molecular diagnosis of cancer. Human saliva is considered a promising source of non-invasive biomarkers of diagnostic value for oral cancer detection. This study aims to identify diagnostic potent salivary RNAs in oral squamous cell carcinoma (OSCC)-patients by RNA-Sequencing. Method: Unstimulated saliva was collected from 5 normal control (NC) individuals and 9 OSCC patients (PS) with prior consent and ethical committee approvals. Total RNA isolated from cell-free saliva (CFS) supernatant was used to prepare small RNA libraries and sequenced on the Ion Torrent S5 platform. The sequencing reads were aligned to the human genome (hg19) using Bowtie 2, and the differential expression analysis was performed using RUVSeq and DESeq2. Mapped reads were screened across miRBase (v22) annotations for miRNAs and Gencode (v19) annotation for other RNAs. Reads were quantified by the Featurecount (v1.4.6) module of the R-package. The microbial-RNA enrichment analysis was determined using the One Codex platform. Result: RNA-sequencing detected protein-coding transcripts (PCTs), long-intergenic RNAs (lincRNAs), microRNAs (miRNAs), small nuclear RNAs (snRNAs), transfer RNAs (tRNAs) and pseudogenes from the saliva of PS and HC samples. Transcriptome analyses revealed 89 PCTs, 18 lincRNAs and 6 miRNAs differentially expressed between PS and HC with a log2fold change ≥ 1 or ≤ -1 and p-value < 0.05. Gene ontology and pathway enrichment analyses indicated a significant correlation of the identified PCTs and miRNAs to various cancer-related pathways that may have implications in the pathogenesis of OSCC. Interestingly, unmapped non-human reads aligned to the microbial reference genomes. Further analyses of these microbial sequence reads revealed a significant microbial dysbiosis differentiating PS from HC. Metabolic pathways and functional analysis of the identified microbial phylotypes showed gene ontologies associated with inflammation, cell proliferation, ROS generation, and a range of metabolic processes. Conclusion: We report novel panels of differentially expressed PCTs, miRNAs and lincRNAs distinguishing PS from HC. Importantly, our results also provide evidence for oral microbial dysbiosis that appears to have pathological implications in OSCC. Summarily, this study provides a comprehensive landscape of salivary RNAs that can be exploited as non-invasive biomarkers for OSCC detection.
2023-01-30 | GSE176077 | GEO
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: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:We have performed gene expression microarray analysis to profile transcriptomic signatures between cancer and noncancerous patients Gastric cancer is currently the second leading cause of cancer deaths. Due to the difficulty of diagnosing patients in the early stages of gastric cancer, it is critical to develop a method that can diagnose the disease at the early stage to allow for better treatment options. In this study, we discovered salivary transcriptomic and miRNA biomarkers for the detection of gastric cancer and identified there are mRNA-miRNA correlations in saliva. RNA was extracted from saliva supernatant and mRNA candidates were identified that can distinguish gastric cancer from non-gastric cancer patients
2015-01-15 | E-GEOD-64951 | biostudies-arrayexpress
Project description:Early surgery is vital in the treatment of highly fatal pancreatic cancer (PC). But there is no valuable and non-invasive biomarker to screen PC currently. Studies showed many salivary molecules can detect several systemic diseases. We aimed to investigate whether salivary microRNAs (miRNAs) can act as a biomarker to detect resectable PC. By Agilent microarray salivary miRNAs were profiled from saliva samples from 8 patients with resectable PC and 8 healthy controls. Candidate biomarkers discovered from the profile were subjected to validation by qPCR.
2013-12-15 | E-GEOD-53325 | biostudies-arrayexpress
Project description:Saliva (oral fluids) is an emerging biofluid poised for clinical diseases detection. Although the rationale for oral diseases applications (e.g. oral cancer) is clear, the rationale and relationship between systemic diseases and saliva biomarkers are unknown. In this study, we used mouse models of melanoma and non-small cell lung cancer and compared the transcriptome biomarker profiles of tumor-bearing mice to those of control mice. Microarray analysis showed that salivary transcriptomes were significantly altered in tumor-bearing mice vs. controls. Analysis of the transcriptomes in the mouse tumors, serum, salivary glands and saliva revealed that salivary biomarkers have multiple origins. Furthermore, we identified that the expression of two groups of significantly altered transcription factors Runx1, Mlxipl, Trim30 and Egr1, Tbx1, Nr1d1 in melanoma-bearing mice that can potentially be responsible for 82.6% of the up-regulated genes expression and 62.5% of the down-regulated gene expression in the mice saliva, respectively. We also confirmed that the ectopic production of nerve growth factor (NGF) in the melanoma tumor tissue as a tumor-released mediator that can induce expression of the transcription factor Egr-1 in the salivary gland. Taken together, our data support the conclusion that upon systemic disease development, a disease-specific change occurs in the salivary biomarker profile. Although the origins of the disease-specific salivary biomarkers are both systemic and local, stimulation of salivary gland by mediators released from remote tumors play an important role in regulating the salivary surrogate biomarker profiles.
2008-11-11 | GSE13443 | GEO
Project description:Saliva aids in the predigestion of food and perception of taste. It helps to maintain the integrity of the mineralized tooth and epithelial surfaces in the mouth, and shields the oro-digestive tract from environmental hazards and invading pathogens. Although salivary glands and saliva fluid are biologically and functionally inseparable, they have thus far been investigated as separate entities. To bridge this gap, we performed an integrative analysis of the transcriptome of 27 samples collected from the major human adult and fetal major salivary glands - submandibular, sublingual, and parotid - along with mass-spectrometry-based saliva proteome data and immunohistochemical localization in glandular tissue. Our results suggest that functional maturation at the transcriptome level occurs late in gland development, and is driven mainly by the transcription of genes that code for secreted saliva proteins. We further provide evidence that protein dosage of the most abundant salivary proteins secreted by the salivary glands is predominantly regulated at the transcriptome level. Finally, we demonstrate distinct transcriptomic profiles of each major salivary gland type that reveal functional specialization and will aid in future clinical analyses. Our study provides the hitherto most comprehensive RNAseq dataset of healthy salivary glands in humans, thus establishing a robust framework for deeper studies of saliva and salivary gland biology, development, and evolution, ultimately paving the way for better understanding the importance of these craniofacial secretory organs in health and their malfunctions in disease.
2020-07-10 | GSE143702 | GEO
Project description:During blood feeding haematophagous arthropods inject into their hosts a cocktail of salivary proteins whose main role is to counteract host haemostasis, inflammation and immunity. However, animal body fluids are known to also carry miRNAs. To get insights into saliva and salivary gland miRNA repertoires of the African malaria vector Anopheles coluzzii we used small RNA-Seq and identified 214 miRNAs, including tissue-enriched, sex-biased and putative novel anopheline miRNAs. Noteworthy, miRNAs were asymmetrically distributed between saliva and salivary glands, suggesting that selected miRNAs may be preferentially directed toward mosquito saliva. The evolutionary conservation of a subset of saliva miRNAs in Anopheles and Aedes mosquitoes, and in the tick Ixodes ricinus, supports the idea of a non-random occurrence pointing to their possible physiological role in blood feeding by arthropods. Strikingly, eleven of the most abundant An. coluzzi saliva miRNAs mimicked human miRNAs. Prediction analysis and search for experimentally validated targets indicated that miRNAs from An. coluzzii saliva may act on host mRNAs involved in immune and inflammatory responses. Overall, this study raises the intriguing hypothesis that miRNAs injected into vertebrates with vector saliva may contribute to host manipulation with possible implication for vector-host interaction and pathogen transmission.
2019-02-22 | GSE120658 | GEO
Project description:Mosquito saliva facilitates blood feeding through the anti-haemostatic, anti-inflammatory and immunomodulatory properties of its proteins. However, the potential contribution of non-coding RNAs to host manipulation is still poorly understood. We analysed small RNAs from Aedes aegypti saliva and salivary glands and show here that chikungunya virus-infection triggers both the siRNA and piRNA antiviral pathways with limited effects on miRNA expression profiles. Saliva appears enriched in specific miRNA subsets and its miRNA content is well conserved among mosquitoes and ticks, clearly pointing to a non-random sorting and occurrence. Finally, we provide evidence that miRNAs from Ae. aegypti saliva may target human immune and inflammatory pathways, as indicated by prediction analysis and searching for experimentally validated targets of identical human miRNAs. Overall, we believe these observations convincingly support a scenario where both proteins and miRNAs from mosquito saliva are injected into vertebrates during blood feeding and contribute to the complex vector-host-pathogen interactions.
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