ArticleMedicine2020
Conjoint analysis for hepatic carcinoma with hub genes and multi-slice spiral CT.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma.PloS one · 2025Article
- CENPs in hepatocellular carcinoma: a comprehensive review of expression patterns, clinical correlations, and functional mechanisms.American journal of cancer research · 2025Review
- Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning.Scientific reports · 2023Article
- ASPM promotes ATR-CHK1 activation and stabilizes stalled replication forks in response to replication stress.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatic carcinoma (HCC) is a common malignant tumor, with insidious onset and poor prognosis. However, more hub genes associated with hepatocellular carcinoma are unknown. And there are few researches about the conjoint analysis with the hub genes and multi-slice spiral computerized tomography (CT).A total of 100 HCC participates were recruited, who all received the examination of multi-slice spiral CT. Two expression profile data sets (GSE101728 and GSE101685) were downloaded from the Gene Expression Omnibus (GEO) database. GEO2R can perform a command to compare gene expression profiles between groups in order to identify differently expressed genes (DEGs). Functional annotation of DEGs via Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was made with Database for Annotation, Visualization, and Integrated Discovery (DAVID). Construction and analysis of protein-protein interaction network were performed. Furthermore, the study could mine of hub genes and explore the correlation with the multi-slice CT. Real-time quantitative polymerase chain reaction (RT-qPCR) assay was used the exam the expression of hub genes.A total of 10 genes were identified as hub genes with degrees ≥10. The hub genes (NIMA Related Kinase 2 [NEK2], Anillin Actin Binding Protein [ANLN], DNA Topoisomerase II Alpha [TOP2A], Centromere Protein F [CENPF], Assembly Factor For Spindle Microtubules [ASPM], Cell Division Cycle 20 [CDC20], Cyclin Dependent Kinase 1 [CDK1], Cyclin B1 [CCNB1], Epithelial Cell Transforming 2 [ECT2], Cyclin B2 [CCNB2]) were identified from the Molecular Complex Detection (MCODE) network. These hub genes were highly expressed in HCC tissues, and when these genes were highly expressed, the survival prognosis of HCC patients was poor. The type of CT enhancement was significantly related with the expression of NEK2 (P < .001), ANLN (P < .001), and TOP2A (P = .006).The combination between the gene expression (NEK2, ANLN, and TOP2A) and type of CT enhancement might provide a new idea for future basic research and targeted therapy of HCC.
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