Abstract 129P
Background
Adrenocortical carcinoma (ACC) is a rare and aggressive cancer originating in the adrenal glands. The overall survival rate for ACC remains low, with only about 30% of patients surviving beyond five years, highlighting the urgent need for improved treatment options. To address this, a differential gene expression-based drug repurposing framework was purposed to obtain the most potential FDA-approved drugs for adrenocortical carcinoma.
Methods
This study used the gene expression signature of ACC, collected from the Gene Expression Omnibus (GEO) database followed by differential gene expression (DEG) analysis using the on-site GEO2R tool. The hub genes were identified through the protein-protein interaction (PPI) network and STRING-Cytoscape. Moreover, these hub genes were further analyzed using a cloud-based software, clue.io, to identify potential small molecule drugs followed by an intensive literature survey to exclude experimental, investigational, withdrawn, and FDA-unapproved drugs/small molecules.
Results
The purposed approach successfully predicted 24 FDA-approved drugs with potential to target ACC. Out of which five drugs had previously been tested for adrenocortical cancer. Molecular docking was performed for the remaining drugs, uncovering six small molecule drugs with high binding affinity to host target proteins.
Conclusions
The purposed computational drug repurposing framework can accelerate drug discovery, saving time and cost due to the leveraged established safety profiles. The high binding affinity of the identified drugs to target proteins suggests potential therapeutic efficacy, but need further in vitro and in vivo validation. Broadly, the study enlightens a promising direction for the future of cancer treatment and drug discovery, offering the potential for more effective treatments for rare cancers.
Editorial acknowledgement
Clinical trial identification
Legal entity responsible for the study
The authors.
Funding
This work was supported by the National Research Foundation (NRF), Korea, under project BK21 FOUR.
Disclosure
All authors have declared no conflicts of interest.
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