ArticleJournal of the Chinese Medical Association : JCMA2020
Identification of key genes and pathways associated with topotecan treatment using multiple bioinformatics tools.
Article in Journal of the Chinese Medical Association : JCMA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Transcriptomic Analysis of CRISPR/Cas9-Mediated PARP1-Knockout Cells under the Influence of Topotecan and TDP1 Inhibitor.International journal of molecular sciences · 2023Article
- LncTx: A network-based method to repurpose drugs acting on the survival-related lncRNAs in lung cancer.Computational and structural biotechnology journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe goal of this study is to determine critical genes and pathways associated with topotecan using publicly accessible bioinformatics tools.
methodsTopotecan 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.
resultsEleven 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.
conclusionUsing 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.