Glioma Prognostic Signature Based on Chromatin Remodeling Genes

A prognostic signature for glioma developed from RNA-seq profiles from the CGGA, GTEx, and TCGA cohorts. The dataset likely contains results from consensus clustering and a SuperPC-based model identifying 28 differentially expressed genes. It was authored by Kun Wang and last updated on May 8, 2026.

Use Cases

• Risk stratification of glioma patients based on the chromatin remodeling-related gene signature.
• Identifying potential therapeutic targets, such as LMNA, for glioma treatment.
• Cross-validation of gene expression patterns using single-cell RNA sequencing, spatial transcriptomics, and proteomic data.
• Virtual screening for candidate LMNA-targeting compounds based on molecular docking analyses.

Strengths

• Derived from multiple cohorts (CGGA, GTEx, TCGA), suggesting cross-validation.
• Signature built from systematic screening of 117 machine-learning algorithm combinations.
• Experimental validation includes in vitro and in vivo assays for core gene LMNA.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is 13.8 KB, indicating a very limited scope, likely containing summary results rather than raw data.

Provenance

Source

figshare

Collection Method

Analysis of RNA-seq profiles from CGGA, GTEx, and TCGA cohorts.

Freshness

Last updated 2026-05-08 06:15:54; freshness should be verified.