1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Finding the cross-tissue biomarkers gastric cancer diagnosis by transcriptome high throughput data analysis
Paper ID : 1464-ICB10
Authors:
Kiarash Zare *1, Hossein Pourmontaseri1, Mohammad Mehdi Naghizadeh Jahromi2, Pardis Mohammadi3
1کمیته تحقیقات دانشجویی، دانشگاه علوم پزشکی فسا، فسا، ایران
2گروه پزشکی اجتماعی دانشکده پزشکی، دانشگاه علوم پزشکی فسا، فسا، ایران
3مرکز تحقیقات فیتوشیمی، دانشگاه علوم ، پزشکی شهید بهشتی، تهران، ایران
Abstract:
Gastric cancer (GC) is one of the most common gastrointestinal malignancies. Although several approaches have been developed to diagnose GC in recent years, still, there is a long distance to provide rapid, non-invasive, and inexpensive detections. The present study aimed to detect cross-tissue biomarkers in tissue, blood, and salivary samples of GC patients [1,2]. The GC-related terms were searched in array express and Gene Expression omnibus to collect and analyze appropriate datasets. Each dataset was analyzed with GEO2R tools to calculate differentially expressed genes. Then, a defined formula [-log(p.value)×|log(fold change)|] was applied to select the 2000 top significant probs [3,4]. In the end, we selected the intersection genes which were repeated at least in four out of eight tissue datasets. At last, we integrated two GC blood and salivary datasets and found the common genes in all datasets. The analysis showed 190 and 144 common genes in GC tissue and blood datasets. The evaluation of VENN diagram results demonstrated that common gene expression between tissue and blood, salivary and blood, tissue and salivary, was 6, 17, and 17. Also, the common genes between tissue, salivary, and blood were 4 genes, including AKR1C1, SORBS2, CKM, and PDLIM3. Our finding indicated that explored genes would manipulate oxidoreductase activity, production of structural proteins, and transferase activity in favor of GC pathogenesis. We concluded that four candidate common genes which have been explored in the present study between salivary, tissue, and blood samples of GC patients would develop promising diagnostic approaches in the future. If laboratory investigations confirm the results of the present study in the future, it is possible to obtain rapid and inexpensive tests to accurately diagnose GC patients.
Keywords:
gastric cancer, biomarkers, transcriptome, data analysis, diagnostic approach
Status : Paper Accepted (Poster Presentation)