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.
Project description:Peritoneal carcinomatosis is a frequent finding in patients with primary gastric cancer, and it is associated with a poor prognosis. A major mechanism in peritoneal carcinomatosis is the dissemination of cancer cells into the abdominal cavity, mainly in diffuse gastric adenocarcinoma. The features that enable diffuse primary gastric tumours to develop peritoneal dissemination have been little investigated and are only incompletely understood. We therefore compared the gene expression profile in patients with diffuse primary gastric cancer with and without peritoneal carcinomatosis. Specimens from consecutive gastric cancer patients with and without peritoneal carcinomatosis were investigated using oligonucleotide microarrays. Keywords: Disease state analysis
Project description:Reliable identification of cancer markers can have substantial implications to early detection of cancer. We report here an integrated computational and experimental study on identification of gastric cancer markers in patients’ tissue and sera based on (i) genome-scale transcriptomic analyses on 80 paired gastric cancer/reference tissues, with the aim of identifying abnormally expressed genes at various subtypes/stages of gastric carcinoma (ii) a computational identification of differentially expressed genes that may have their proteins secreted into blood circulation, followed by experimental validations. 160 Total samples were analyzed on paried tumor and adjacent normal tissues from 80 gastric cancer patients. Differential analysis identified genes with a fold-change over 1.5.
Project description:Gastric cancer is a common tumor of the digestive system. Identification of potential molecules associated with gastric cancer progression and validation of potential biomarkers for gastric cancer diagnosis are very important. Thus, the aim of our study was to determine the serum metabolic characteristics of the serum of patients with chronic gastritis (CG) or gastric cancer (GC) and validate candidate biomarkers for disease diagnosis.
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).
Project description:We identified the molecular subtypes and conserved modules in gastric cancer by unsupervised clustering algorithm. We defined six molecular signatrues of gastric cancer associated with the biological heterogeneity of gastric cancer and clinical outcome of patients.
Project description:We identified the molecular subtypes and conserved modules in gastric cancer by unsupervised clustering algorithm. We defined five molecular subtypes and six molecular signatrues of gastric cancer associated with the biological heterogeneity of gastric cancer and clinical outcome of patients.
Project description:We identified the molecular subtypes and conserved modules in gastric cancer by unsupervised clustering algorithm. We defined five molecular subtypes and six molecular signatrues of gastric cancer associated with the biological heterogeneity of gastric cancer and clinical outcome of patients.