Novel drug candidate for the treatment of several soft‑tissue sarcoma histologic subtypes: A computational method using survival‑associated gene signatures for drug repurposing

Oncology Reports
Xia YangGang Chen

Abstract

Systemic treatment options for soft tissue sarcomas (STSs) have remained unchanged despite the need for novel drug candidates to improve STS outcomes. Drug repurposing involves the application of clinical drugs to different diseases, reducing development time, and cost. It has also become a fast and effective way to identify drug candidates. The present study used a computational method to screen three drug‑gene interaction databases for novel drug candidates for the treatment of several common STS histologic subtypes through drug repurposing. STS survival‑associated genes were generated by conducting a univariate cox regression analysis using The Cancer Genome Atlas survival data. These genes were then applied to three databases (the Connectivity Map, the Drug Gene Interaction Database and the L1000 Fireworks Display) to identify drug candidates for STS treatment. Additionally, pathway analysis and molecular docking were conducted to evaluate the molecular mechanisms of the candidate drug. Bepridil was identified as a potential candidate for several STS histologic subtype treatments by overlapping the screening results from three drug‑gene interaction databases. The pathway analysis with the Kyoto Encyclopedia of Genes and Gen...Continue Reading

Software Mentioned

R
SystemsDock Systems
SystemsDock
L1000 Fireworks Display
Mol2
Affymetrix
CMap
BioconductoR
edgeR
WebGestalt

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