KDM5C-SIX5-UBE2C Axis in Glioblastoma Progression and Warburg Effect

This dataset supports a study investigating the role of the SIX5 transcription factor in glioblastoma progression. It integrates analyses from public datasets GSE4290 and GSE50161, TCGA, and UALCAN, with in vitro and in vivo experimental validation. The research identifies a KDM5C–SIX5–UBE2C regulatory axis promoting tumor growth via AKT/mTOR signaling and glycolytic reprogramming.

Use Cases

• Validate the prognostic association of SIX5 expression levels with poor survival using TCGA and UALCAN database analyses.
• Investigate co-expression patterns of SIX5 with glycolytic genes like GLUT1, HK2, PGK1, and LDHA to model the Warburg effect.
• Build a regulatory network model linking KDM5C, SIX5, and UBE2C based on transcriptional activation and knockdown/overexpression experiments.
• Analyze spatial enrichment of SIX5 in tumor core and invasion front subsets using single-cell RNA sequencing and spatial transcriptomics data.

Strengths

• Integrates multiple public genomic datasets (GSE4290, GSE50161, TCGA, UALCAN) for cross-validation.
• Includes functional validation from in vitro assays (U87, U251 cells) and in vivo xenograft studies.
• Focuses on a specific regulatory axis (KDM5C–SIX5–UBE2C) with mechanistic links to AKT/mTOR signaling and glycolysis.

Limitations

• Dataset is a 15.8 KB DOCX file containing a research article, not a structured tabular dataset for direct analysis.
• No raw data tables, column definitions, or sample data are provided within the document.
• Scope is limited to the specific genes and pathways studied; not a broad omics resource.

Provenance

Source

figshare

Collection Method

Bioinformatics analysis of public datasets combined with original wet-lab experiments.

Time Range

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Freshness

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Geography

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