Paget's Disease Gene Expression Data for Recurrence Prediction

RNA sequencing data from Mammary and Extramammary Paget's disease tissues identifies KLF13 and TIA1 as prognostic genes. The dataset supports a risk-score model validated in internal and external patient cohorts. Author Ying Chen published the data under a CC-BY-4.0 license on figshare in 2026.

Use Cases

• Validate prognostic biomarkers for Paget's disease based on KLF13 and TIA1 gene expression levels.
• Build risk stratification models for patient recurrence based on the described RNA-seq profiles.
• Compare molecular pathways between Mammary and Extramammary Paget's disease subtypes as suggested by the analysis.
• Benchmark new gene expression analysis methods against the WGCNA and survival analysis results described.

Strengths

• Includes internal validation with specific gene expression statistics (e.g., KLF13: 22.74 ± 3.41 vs. 15.36 ± 4.91).
• Model validated in an independent external cohort, suggesting generalizability.
• Experimental validation includes both in vitro and in vivo knockdown studies for TIA1.

Limitations

• Dataset scale is very small at 7.4 KB; row and column counts are unknown.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect bias inherent to the specific patient cohorts studied.

Provenance

Source

figshare, author Ying Chen.

Collection Method

RNA sequencing performed on Paget's disease tissues, with analysis via WGCNA and survival modeling.

Freshness

Last updated 2026-05-12 22:02:07; freshness should be verified.