Succinylation-Related Genes in Bladder Cancer: Single-Cell and Transcriptomic Integration

15 paired bladder cancer and adjacent normal tissue samples form the Soochow-BLCA cohort. The dataset integrates transcriptomic data from The Cancer Genome Atlas and Gene Expression Omnibus to identify prognostic succinylation-related genes. Author Jiajian Yang published the dataset under a CC-BY-4.0 license on figshare in May 2026.

Use Cases

• Building a prognostic risk model based on the identified succinylation-related genes KCTD16, CD3D, and GSDMB.
• Analyzing immune evasion and tumor microenvironment states using the described TIDE scores and cell subpopulation data.
• Validating gene expression patterns in bladder cancer subtypes, such as non-muscle-invasive versus muscle-invasive.
• Investigating cell-cell communication and pseudotime-dependent expression patterns in epithelial, T cell, and fibroblast subpopulations.

Strengths

• Integrates data from multiple sources, including a 15-sample cohort, TCGA, and GEO datasets.
• Includes validation via RT-qPCR and functional assays, suggesting experimental grounding.
• The derived prognostic model reportedly achieved an AUC greater than 0.7.

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 small in scale at 831.4 KB, indicating limited raw data.

Provenance

Source

figshare

Collection Method

Integration of transcriptomic sequencing from a Soochow-BLCA cohort with public TCGA and GEO datasets, analyzed via LASSO and Cox regression.

Freshness

Last updated 2026-05-15 04:27:45; freshness should be verified.