Computational drug repurposing based on the RNA sequencing data analysis for colorectal cancer
Computational drug repurposing based on the RNA sequencing data analysis for colorectal cancer
Atena Vaghf,1,*Nayere Abdali,2Shahram Tahmasebian,3
1. Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran 2. Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran 3. Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran
Introduction: Colorectal cancer (CRC) is the third most common diagnosis malignancy and the second leading cause of mortality worldwide. Given the prevalence of CRC, its high heterogeneity, and the limitations of its treatments, exploring novel therapeutic options is a pressing issue that needs to be addressed. Drug repurposing offers an affordable solution by identifying new indications of approved or investigational drugs to develop new treatments for a different disease. RNA sequencing (RNA-seq) is one effective approach that helps discover new functional genes. Besides, RNA-Seq has an immense application in cancer research and development of cancer therapeutics. Therefore, this study aimed to reveal the drug-repurposing candidates for CRC by applied a computational drug repurposing pipeline using the RNA-seq data.
Methods: The RNA sequencing of 20 colorectal tumor samples with matched adjacent normal colorectal tissue under the accession code GSE142279 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). The differentially expressed genes (DEGs) between CRC and normal tissues were obtained by using GEO2R. Next, the Library of Integrated Network-based Signatures (LINCS) database was used to identify potential candidate drugs which can reversed the expression of DEGs. Then, through considerable literature review and drugbank (https://go.drugbank.com) studies, the top-ranked drugs with the highest p-value were selected. Besides, all DEGs were subjected to GO and KEGG pathway enrichment analysis on the Enrichr online platform (https://maayanlab.cloud/Enrichr/). GO analysis categorizes genes function into three parts: biological processes, cellular components, and molecular functions.
Results: This study identified 4713 genes with |log2FC|>1 and P-value <0.01 as DEGs: 2526 upregulated and 2187 downregulated genes. In drug list, we selected cancer and non-cancer drugs, among which Pentobarbital and Canertinib can be mentioned. Pentobarbital is used to induce sleep, cause sedation, and control certain types of seizures. Canertinib is a pan-erbB tyrosine kinase inhibitor which work against esophageal squamous carcinoma. GO ontology analysis demonstrated that for biological processes analysis, DEGs were mainly enriched in extracellular structure organization, cellular component were significantly enriched in collagen-containing extracellular matrix, and molecular function was enriched in frizzled binding. The results of KEGG pathway enrichment indicated that the DEGs were mainly enriched in cell adhesion molecules and Wnt signaling pathway.
Conclusion: This study proposed Pentobarbital and Canertinib drugs as promosing repurposable candidate for the treatment of CRC progression that it’s probably can used to different stages of disease progression.
Keywords: Colorectal cancer; Drug repurposing; RNA sequencing