Identification of key genes and pathways associated with topotecan treatment using multiple bioinformatics tools

The goal of this study is to determine critical genes and pathways associated with topotecan using publicly accessible bioinformatics tools.

Topotecan signatures were downloaded from the Library of Integrated Network-Based Cellular Signatures (LINCS) database (http://www.ilincs.org/ilincs/). Differentially expressed genes (DEGs) were defined as genes that appeared at least three times with p values <0.05 and a fold change of ≥50% (|log2FC| ≥ 0.58). Hub genes were identified by evaluating the following parameters using a protein-protein interaction network: node degrees, betweenness, and eigenfactor scores. Hub genes and the top-40 DEGs by |log2FC| were used to generate a Venn diagram, and key genes were identified. Functional and pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Information on ovarian cancer patients derived from The Cancer Genome Atlas (TCGA) database was analyzed, and the effect of topotecan on the protein expression was examined by Western blotting.

Eleven topotecan signatures were downloaded, and 65 upregulated and 87 downregulated DEGs were identified. Twenty-one hub genes were identified. We identified eight key genes as upregulated genes, including NFKBIA, IKBKB, GADD45A, CDKN1A, and HIST2H2BE, while EZH2, CDC20, and CDK7 were identified as downregulated genes, which play critical roles in the cell cycle and carcinogenesis in KEGG analysis. In the TCGA analysis, the CDKN1A+/EZH2- group had the longest median survival, while the CDKN1A-/EZH2+ group had the shortest median survival. Topotecan-treated murine ovarian (MOSEC), colorectal (CT26), and lung (LLC) cancer cell lines displayed upregulated CDKN1A encoding p21 and downregulated Ezh2.

Using publicly accessible bioinformatics tools, we evaluated key genes and pathways related to topotecan and examined the key genes using the TCGA database and in vitro studies.