Paget's Disease Gene Expression Data for Recurrence Prediction Model

RNA sequencing data from Mammary and Extramammary Paget's disease tissues identifies KLF13 and TIA1 as hub genes associated with recurrence. The dataset includes internal and external validation cohorts, with a risk-score model developed by author Ying Chen. The data was last updated on May 12, 2026.

Use Cases

• Training a predictive model for Paget's disease recurrence based on KLF13 and TIA1 gene expression levels.
• Validating gene expression biomarkers for cancer prognosis using internal and external patient cohorts.
• Analyzing functional pathway differences between Mammary and Extramammary Paget's disease subtypes.

Strengths

• Includes internal and external validation cohorts, as mentioned in the description.
• Specific gene expression values (e.g., KLF13: 22.74 ± 3.41 vs. 15.36 ± 4.91) are provided for key prognostic genes.
• Data is associated with a published study that performed RNA-seq, WGCNA, and in vitro/in vivo validation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific patient cohorts studied.

Provenance

Source

figshare

Collection Method

RNA sequencing performed on MPD and EMPD tissues, with analysis via weighted gene co-expression network analysis (WGCNA).

Freshness

Last updated 2026-05-12 22:02:08; freshness should be verified.