Prognostic Biomarker Identification for Pancreatic Cancer by Analyzing Multiple mRNA Microarray and microRNA Expression Datasets

Having the five-year survival rate of approximately 5%, currently, the fourth leading reason for cancer-related deaths is pancreatic cancer. Previously, various works have concluded that early diagnosis plays a significant role in improving the survival rate and different online tools have been used to identify prognostic biomarker which is a long process. We think that the statistical feature selection method can provide a better and faster result here. To establish our statement, we selected three different mRNA microarray (GSE15471, GSE28735 and GSE16515) and a microRNA (GSE41372) dataset for identification of differentially expressed genes (DEGs) and differentially expressed microRNAs (DEMs). By using a parametric test (Student's t-test), 178 DEGs and 16 DEMs were selected. After identifying target genes of DEMs, we selected two DEGs (ECT2 and NRP2) which were also identified among DEMs target genes. Furthermore, overall survival analysis confirmed that ECT2 and NRP2 were correlated with inadequate overall survival. Hence, we concluded that for pancreatic cancer, a parametric test like Student's t-test can perform better for biomarker identification, and here, ECT2 and NRP2 can act as possible biomarkers. All the resources, programs and snippets of our literature can be discovered at https://github.com/Srizon143005/PancreaticCancerBiomarkers.