MicroRNA expression profiling in gastric cancers plasmas
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE86822 | GEO | 2016/09/13
SECONDARY ACCESSION(S): PRJNA342626
REPOSITORIES: GEO
Similar Datasets
Project description:The study was undertaken to identify microRNAs differently expressed by intestinal type of gastric cancer using miRNA microarray. The miRNA expression in the intestinal type of gastric cancer depending on H. pylori infection suggest that different gastric cancer pathogenesis could be exist between H. pylori-positive and -negative gastric cancer.
2014-01-25 | GSE54397 | GEO
Project description:The study was undertaken to identify microRNAs differently expressed by intestinal type of gastric cancer using miRNA microarray. The miRNA expression in the intestinal type of gastric cancer depending on H. pylori infection suggest that different gastric cancer pathogenesis could be exist between H. pylori-positive and -negative gastric cancer. Total RNA was extracted from cancerous region and non-cancerous regions in formalin fixed paraffin embedded tissues of intestinal type gastric cancer patients who were H. pylori-positive (n=8) or -negative (n=8). Corresponding author: Nayoung Kim, M.D., Department of Internal Medicine, Seoul National University Bundang Hospital (Tel., +82-31-787-7008; e-mail, nayoungkim49@empas.com).
2014-01-25 | E-GEOD-54397 | biostudies-arrayexpress
Project description:Using the highly sensitive miRCURY LNA™ microRNA array, we screened 3100 microRNAs abundant in the human gastric cancer and Adjacent normal gastric mucosa tissues, and the function of differentially expressed microRNAs were analyzed by bioinformatics. The enrichment results indicated that these microRNAs perhaps participated in the occurrence and development process of gastric cancer.
2016-02-20 | GSE78091 | GEO
Project description:Circulating microRNAs (miRNAs) in serum may serve as promising diagnostic biomarkers for patients with gastric cancer (GC). Using quantitative reverse transcription polymerase chain reaction (qRT-PCR) based Exiqon panel, we identified 58 differentially expressed miRNAs from 3 GC pool samples and 1 normal control (NC) pool in the initial screening phase. Identified miRNAs were further validated in the training (49 GC VS. 47 NCs) and validation phases (154 GC VS. 120 NCs) using qRT-PCR. Consequently, six serum miRNAs (miR-10b-5p, miR-132-3p, miR-185-5p, miR-195-5p, miR-20a-3p and miR-296-5p) were significantly overexpressed in GC compared with NCs. The areas under the receiver operating characteristic (ROC) curve of the six-miRNA panel were 0.764 and 0.702 for the training and validation phases, respectively. In conclusion, we identified a six-miRNA panel in serum for the detection of GC.
2016-08-31 | GSE86226 | GEO
Project description:The paper "Metabolomic Machine Learning Predictor for Diagnosis and Prognosis of Gastric Cancer" addresses the need for non-invasive diagnostic tools for gastric cancer (GC). Traditional methods like endoscopy are invasive and expensive. The authors conducted a targeted metabolomics analysis of 702 plasma samples to develop machine learning models for GC diagnosis and prognosis. The diagnostic model, using 10 metabolites, achieved a sensitivity of 0.905, outperforming conventional protein marker-based methods. The prognostic model effectively stratified patients into risk groups, surpassing traditional clinical models.
I have successfully reproduced the diagnosis model from the paper. This machine learning-based system differentiates GC patients from non-GC controls using metabolomics data from plasma samples analyzed by liquid chromatography-mass spectrometry (LC-MS). The model focuses on 10 metabolites, including succinate, uridine, lactate, and serotonin. Employing LASSO regression and a random forest classifier, the model achieved an AUROC of 0.967, with a sensitivity of 0.854 and specificity of 0.926. This model significantly outperforms traditional diagnostic methods and underscores the potential of integrating machine learning with metabolomics for early GC detection and treatment.
2024-07-23 | MODEL2407230001 | BioModels
Project description:Acute pulmonary embolism (APE) remains among the most formidable challenges facing public health practice in the 21st century. Accurate diagnosis of APE is severely hindered by the lack of biomarkers with both high sensitivity and specificity. MicroRNAs (miRNAs) involve various pathophysiologic processes underlying multitudinous diseases. Accmulating evidences point to the fact that miRNAs may serve as ideal biomarkers.The aim of the present study was to explore the potential of plasma miRNAs as biomarkers for diagnosis of APE. Two TaqMan miRNA arrays were performed on plasma of 10 APE patients and 10 healthy controls.
2013-08-08 | E-GEOD-24149 | biostudies-arrayexpress
Project description:The aim of this study was to determine differences in microRNA expression profiles of gastric cancer and adjacent healthy gastric mucosa. Both types of tissue samples were collected during operative procedures of 20 patients. microRNA expression was determined by miRNA microarrays.
2017-01-12 | GSE93415 | GEO
Project description:Gastric cancer is one of the most lethal malignancies with high mortality and gastric cancer-specific biomarker is need due to the lack of specific method for early screening, diagnosis, and prognosis of the patients with gastric cancer. Ascites is known for an important source for conducing biomarker discovery because it contains the secreted proteins from malignant cells, growth factors, and cytokines. In this study, we have conducted a comprehensive proteome study using ascites of patients with inflammatory diseases and gastric cancer. In the discovery stage, we have identified 2761 ascites-specific proteins, where 234 proteins were quantitated using the label free quantitation method, the normalized spectral abundance factor (NSAF); 152 and 82 proteins showed up and down-regulated pattern, respectively. Our ascites proteome can be used as baseline data for the discovery of novel biomarkers of the gastric cancer.
2018-04-16 | PXD002213 | Pride
Project description:To further investigate of microRNA expression profile of gastric cancer, we have employed whole microRNA gene chip as a discovery platform to identify gene differential expression between gastric cancer tissues with mormal gastric tissues.Expression of four microRNAs (miR-125b,miR-451,miR-192b,miR-200b) from this signature was quantified and verified in the same RNA samples by real-time PCR.
2011-01-15 | GSE26645 | GEO
Project description:Examine methylation changes in gene promoters in gastric cancers and matched normal control gastric epithelium, using Nimblegen arrays. Direct comparison of gastric cancers and matched normal control gastric epithelium
2013-06-14 | E-GEOD-40919 | biostudies-arrayexpress