Ontology highlight
ABSTRACT:
PROVIDER: PRJNA999038 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Extracellular RNA (exRNA) is an emerging paradigm as endocrine signals in cellular communication, biomarker development, therapeutic applications and systemic physiology. This project is to test the hypothesis that salivary extracellular RNA (exRNA) can be developed for the clinical detection of human diseases. Our laboratory first reported the existence of a transcriptome and microRNA profile in cell free saliva followed by its scientific characterizations and clinical utilities including biomarker development for molecular oncology applications. Most recently we have performed RNA-sequencing in cell free saliva and reported three major types of RNA in saliva (mRNA, miRNA and snoRNA). This study is to test the hypothesis that salivary exRNA can be developed to detect gastric cancer by performing a biomarker development study to definitively validate salivary exRNA biomarkers for the detection of gastric cancer.
2018-10-27 | GSE121870 | GEO
Project description:Liver cancer is one of the most lethal cancers worldwide. Liquid biopsy provides a noninvasive approach in detecting and monitoring cancer biomarkers to overcome current limitations associated with tissue biopsies, comprising the analysis of circulating tumor-derived material. In this study, we profiled plasma cell-free RNA-seq to identify recurrently dysregulated RNA biomarkers for the liquid biopsy of cancer.
2020-09-30 | GSE142987 | GEO
Project description:Extracellular vesicles are structures surrounded by a lipid bilayer that facilitate intercellular communication by transporting biomolecules. These vesicles are now commonly referred to as part of liquid biopsy. In this study, we examine the characterization of miRNAs found in extracellular vesicles from patients with both benign gastric diseases and gastric cancer. By studying these miRNAs, we aim to identify potential biomarkers for gastric cancer.
2023-10-11 | GSE227778 | GEO
Project description:Multi-parametric liquid biopsy approach
| PRJEB39331 | ENA
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:Discovered salivary transcriptomic biomarkers for the detection of gastric cancer
| PRJNA272615 | ENA
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
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.
2015-01-15 | GSE64951 | 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:Multiple Salivary Biomarkers for Early Detection of Pancreatic Cancer
2015-08-06 | E-GEOD-14245 | ExpressionAtlas