TNF signaling pathway upregulation as a potential pharmaceutical target for cocaine-addicted individuals

(1) Plymouth High School, Canton, Michigan, (2) Cranbrook Kingswood High School, Bloomfield Hills, Michigan, (3) Huron High School, Ann Arbor, Michigan, (4) University of Michigan, Ann Arbor, Michigan, (5) miRcore, Ann Arbor, Michigan

https://doi.org/10.59720/21-062
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Cocaine is a highly addictive stimulant that induces the buildup of dopamine in the brain, which over-stimulates the body’s reward system. Overdose deaths related to cocaine have been steadily increasing since 2014, with existing addiction treatments having limited capabilities. Therefore, the purpose of this investigation was to analyze the differentially expressed genes related to cocaine addiction and the cellular pathways they are associated with to expand potential targets for pharmacological therapies.
We used the dataset GSE54839 from the National Center for Biotechnology Information (NCBI) database to investigate the RNA expression differences between groups of chronic cocaine abusers and drug-free subjects. In our analysis, we split 60 samples into 2 test groups of 30 from an originally triplicated dataset. We identified about 370 significantly expressed genes (p-value < 5 x 10-4). We categorized these genes as upregulated or downregulated genes using String-dB. We performed further enrichment testing using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) analyses.
In this dataset, we identified the Tumor Necrosis Factor (TNF) KEGG pathway as the most prominently upregulated pathway in cocaine-addicted individuals. Because of this, we believe that TNF pathway proteins have the potential to be pharmaceutical targets for treating cocaine addiction. However, the existing medications that mediate TNF activity mainly target autoimmune diseases, thus not guaranteeing that a protein could directly address cocaine addiction. Future research should further characterize the TNF pathway’s efficacy as a pharmaceutical target.

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