ArticleOpen medicine (Warsaw, Poland)2020
Bioinformatics Analysis of the Expression of ATP Binding Cassette Subfamily C Member 3 (ABCC3) in Human Glioma.
Article in Open medicine (Warsaw, Poland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.BMC cancer · 2024Pooled it
- Stochastic LASSO for extremely high-dimensional genomic data.Scientific reports · 2026Article
- Blood transcriptomic signatures link β-amyloid deposition to molecular pathways across SCD, MCI, and dementia.Frontiers in aging neuroscience · 2026Article
- Recognition of a Novel Gene Signature for Human Glioblastoma.International journal of molecular sciences · 2022Article
- Clinicopathological and Prognostic Significance of ABCC3 in Human Glioma.Journal of oncology · 2021Article
- Cannabinoid Receptor Interacting Protein 1a (CRIP1a) in Health and Disease.Biomolecules · 2020Review
- In silico identification of the prognostic biomarkers and therapeutic targets associated with cancer stem cell characteristics of glioma.Bioscience reports · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the expression of the ABCC3 gene in human glioma and its correlation with the patient's prognosis.
methodsThe cancer genome atlas (TCGA) database was used to analyze the differential expression of the ABCC3 gene in human glioma. The STRING database was used to construct the protein-protein interaction (PPI) network of the ABCC3 gene coding protein. The co-expression genes relevant to the ABCC3 gene were analyzed by the Pearson correlation test. A log-rank test was used to analyze the difference of overall survival (OS) and disease-free survival (DFS) between the high and low ABCC3 gene expression groups.
resultsThe expression level of the ABCC3 gene in glioma tissues was lower than that of corresponding normal brain tissues. The PPI network contains 51 nodes with the average node degree of 13.3 and the local clustering coefficient of 0.72 which indicated that the PPI enrichment was significant (p<0.001). Ten hub genes (ABCC3,NR1I2,NR1H4,-CYP7A1,SLC10A1,CYP3A4,UGT1A1,UGT1A8,UGT1A6 and ALB) were identified by the cytoscape software. The KEGG analysis was enriched in drug metabolism - cytochrome P450 and PPAR signaling pathway. CFI gene expression level was positive correlated with the ABCC3 expression level (r=0.71, p<0.05). And the CNRIP1 gene expressed was negative correlated with ABCC3 expression (r=-0.43, p<0.05). The overall survival (HR=2.8, P<0.05) and disease-free survival rates (HR=2.0, P<0.05) of patients with ABCC3 low expression glioma were significantly higher than those of patients with high expression of ABCC3. Conclusion The expression level of the ABCC3 gene in glioma was decreased compared to normal brain tissue. The overall survival and disease-free survival of in the ABCC3 low-expression group was significant decreased.
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