AUTHOR=Tan Jiang-Shan , Hu Song , Guo Ting-Ting , Hua Lu , Wang Xiao-Jian 

TITLE=Text Mining-Based Drug Discovery for Connective Tissue Disease–Associated Pulmonary Arterial Hypertension

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.743210

DOI=10.3389/fphar.2022.743210

ISSN=1663-9812

ABSTRACT=Abstract
Background: The current medical therapy in connective tissue disease-associated pulmonary arterial hypertension (CTD-PAH) does not show favored efficiency for all patients, the exploration of novel drugs is desired.
Methods: Text mining was performed to obtain CTD- and PAH-related gene sets, and the intersection of the two gene sets were analyzed for functional enrichment through DAVID. Protein-protein interaction network of the overlapping genes and the significant gene modules were determined using STRING. The enriched candidate genes were further analyzed by Drug Gene Interaction database to find the drugs with potentially therapeutic effect on CTD-PAH. 
Results: Based on text mining analysis, 179 genes related to CTD and PAH were identified. Through enrichment analysis of the genes, 20 genes representing 6 pathways were obtained. To further narrow the scope of potential existing drugs, we selected the targeted drugs with the conditions of Query Score ≥ 5 and Interaction Score ≥ 1. Finally, thirteen drugs targeting the 6 genes were selected to be candidate drugs, which have been divided into 4 drug-gene interaction types, and 12 of them have their initial drug indications approved by FDA. Potential gene targets of the drugs on this list are IL-6 (1 drug) and IL-1β (2 drugs), MMP9 (1 drug), VEGFA (3 drugs), TGFB1 (1 drug) and EGFR (5 drugs). These drugs might be used to treat CTD-PAH.
Conclusion: We identified thirteen drugs targeting 6 genes which may have potentially therapeutic effect on CTD-PAH.