
==== Front
Res Sq
ResearchSquare
Research Square
2693-5015
American Journal Experts

10.21203/rs.3.rs-4765282/v1
10.21203/rs.3.rs-4765282
preprint
1
Article
Reversal Gene Expression Assessment for Drug Repurposing, a Case Study of Glioblastoma
Sun Shixue https://orcid.org/0000-0002-0929-977X

Shyr Zeenat
McDaniel Kathleen
Fang Yuhong
Tao Dingyin
Chen Catherine Z.
Zheng Wei
Zhu Qian https://orcid.org/0000-0002-4858-6333

09 9 2024
rs.3.rs-4765282https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
https://www.researchsquare.com/article/rs-4765282/v1
nihpp-rs4765282v1.pdf
Abstract

Glioblastoma (GBM) is a rare brain cancer with an exceptionally high mortality rate, which illustrates the pressing demand for more effective therapeutic options. Despite considerable research efforts on GBM, its underlying biological mechanisms remain unclear. Furthermore, none of the United States Food and Drug Administration (FDA) approved drugs used for GBM deliver satisfactory survival improvement. This study presents a novel computational pipeline by utilizing gene expression data analysis for GBM for drug repurposing to address the challenges in rare disease drug development, particularly focusing on GBM. The GBM Gene Expression Profile (GGEP) was constructed with multi-omics data to identify drugs with reversal gene expression to GGEP from the Integrated Network-Based Cellular Signatures (iLINCS) database. We prioritized the candidates via hierarchical clustering of their expression signatures and quantification of their reversal strength by calculating two self-defined indices based on the GGEP genes’ log 2 foldchange (LFCs) that the drug candidates could induce. Among eight prioritized candidates, in-vitro experiments validated Clofarabine and Ciclopirox as highly efficacious in selectively targeting GBM cancer cells. The success of this study illustrated a promising avenue for accelerating drug development by uncovering underlying gene expression effect between drugs and diseases, which can be extended to other rare diseases and non-rare diseases.
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