Finding the cross-tissue biomarkers gastric cancer diagnosis by transcriptome high throughput data analysis

Gastric cancer (GC) is one of the most common gastrointestinal malignancies. Although several approacheshave been developed to diagnose GC in recent years, still, there is a long distance to provide rapid, noninvasive,and inexpensive detections. The present study aimed to detect cross-tissue biomarkers in tissue,blood, and salivary samples of GC patients. The GC-related terms were searched in array express and GeneExpression omnibus to collect and analyze appropriate datasets. Each dataset was analyzed with GEO۲Rtools to calculate differentially expressed genes. Then, a defined formula [-log(p.value)×|log(fold change)|]was applied to select the ۲۰۰۰ top significant probs. In the end, we selected the intersection genes which wererepeated at least in four out of eight tissue datasets. At last, we integrated two GC blood and salivary datasetsand found the common genes in all datasets. The analysis showed ۱۹۰ and ۱۴۴ common genes in GC tissueand blood datasets. The evaluation of VENN diagram results demonstrated that common gene expressionbetween tissue and blood, salivary and blood, tissue and salivary, was ۶, ۱۷, and ۱۷. Also, the common genesbetween tissue, salivary, and blood were ۴ genes, including AKR۱C۱, SORBS۲, CKM, and PDLIM۳. Ourfinding indicated that explored genes would manipulate oxidoreductase activity, production of structuralproteins, and transferase activity in favor of GC pathogenesis. We concluded that four candidate commongenes which have been explored in the present study between salivary, tissue, and blood samples of GCpatients would develop promising diagnostic approaches in the future. If laboratory investigations confirmthe results of the present study in the future, it is possible to obtain rapid and inexpensive tests to accuratelydiagnose GC patients.

Keywords:

gastric cancer , biomarkers , transcriptome , data analysis , diagnostic approach