ArticleComputational and structural biotechnology journal2024
ECGA: A web server to explore and analyze extrachromosomal gene in cancer.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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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.
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Who cites it
2 citing papers in PubMed.
- FerrDb V3: expanding the manually curated resource for regulators and disease associations from ferroptosis to regulated cell death.Nucleic acids research · 2026Article
- An EcDNA gene-based risk model and functional verification of a key ec-lncRNA AC016394.2 for prostate cancer.Cancer cell international · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Circular extrachromosomal DNA (ecDNA) plays a crucial role in the onset, progression, and evolution of many types of cancers, with dysregulated gene expression driven by ecDNA as a key mechanism. Although database resources for ecDNA are now available, a sophisticated web application dedicated to ecDNA gene analysis remains absent. Therefore, we developed ecDNA gene analyzer (ECGA). ECGA catalogues 23,274 unique ecDNA genes of 27 cancers across 27 tissues. ECGA also offers five specialized analysis tools: (1) 'Venn analysis' looks for overlaps between a given gene list and ecDNA genes; (2) 'Enrichment analysis' performs over-representation analysis and gene set enrichment analysis of input gene list within predefined ecDNA gene sets; (3) 'Target discovery' identifies upregulated ecDNA genes as targets by comparing with reference expression in normal samples; (4) 'DE analysis' finds differentially expressed ecDNA genes; (5) 'Signature discovery' discerns ecDNA gene signatures capable of classifying samples into phenotypic groups, and it is accompanied by 'Signature validation' for model test on unseen data. In summary, ECGA emerges as an indispensable platform in cancer genetics, bridging gaps in basic research, medical reporting, and pharmaceutical development, and propelling ecDNA research forward. ECGA is freely available at https://www.zhounan.org/ecga/.
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Registered trials
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