Paget's Disease Gene Expression Data for Recurrence Prediction Model

RNA sequencing data from Mammary Paget’s disease and extramammary Paget’s disease tissues, used to identify prognostic genes. The dataset, created by Ying Chen and last updated in May 2026, includes expression levels for hub genes KLF13 and TIA1, validated in internal and external patient cohorts. A risk-score model based on these genes was constructed to stratify patients by recurrence risk.

Use Cases

• Validate prognostic biomarkers for Paget's disease based on KLF13 and TIA1 gene expression levels.
• Train a risk-score model for patient stratification using the identified hub genes.
• Compare molecular profiles between Mammary Paget’s disease and extramammary Paget’s disease.
• Investigate the oncogenic role of TIA1 using associated in vitro and in vivo experimental results.

Strengths

• Includes internal validation cohort with statistically significant gene expression differences (e.g., KLF13: 22.74 ± 3.41 vs. 15.36 ± 4.91, P < 0.001).
• Prognostic value of genes was validated in an independent external cohort of Chinese patients.
• Model construction involved multiple analytical methods including WGCNA, ROC curves, Kaplan-Meier analysis, and Decision curve analysis.

Limitations

• Dataset size is 17.1 KB, indicating a very limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

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

Freshness

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

Geography

Includes an independent Chinese patient cohort.