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.
Project description:<p>The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented.</p> <p>Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30097497">30097497</a> DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States). </p>
Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis. Using the extracted genomic DNA from 56 primary gastric cancers, array CGH was done to elucidate the prognostic biomarkers.
Project description:Genome-wide mRNA expression profiles of 37 unique gastric cancer cell lines (GCCLs). Keywords: gastric cancer, cell culture Profiling of 37 unique Gastric Cancer Cell Lines on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A total of 37 arrays. 21 of these Samples represent a re-analysis of CEL files initially submitted under Series GSE15455.
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