The potential drug for treatment in pancreatic adenocarcinoma: a bioinformatical study based on distinct drug databases.

ABSTRACT:

Background

The prediction of drug-target interaction from chemical and biological data can advance our search for potential drug, contributing to a therapeutic strategy for pancreatic adenocarcinoma (PAAD). We aim to identify hub genes of PAAD and search for potential drugs from distinct databases. The docking simulation is adopted to validate our findings from computable perspective.

Methods

Differently expressed genes (DEGs) of PAAD were performed based on TCGA. With two Cytoscape plugins of CentiScaPe and MCODE, hub genes were analyzed and visualized by STRING analysis of Protein-protein Interaction (PPI). The hub genes were further selected with significant prognostic values. In addition, we examined the correlation between hub genes and immune infiltration in PAAD. Subs

SUBMITTER: Liu H 

PROVIDER: S-EPMC7079489 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature