Paget's Disease Prognostic Genes KLF13 and TIA1 with Risk-Score Model

RNA sequencing of Mammary and Extramammary Paget's disease tissues identified KLF13 and TIA1 as hub genes associated with recurrence. A risk-score model based on these genes stratified patients into high- and low-risk groups, validated in internal and external cohorts. The dataset, authored by Ying Chen and last updated in 2026, includes gene expression data supporting these findings.

Use Cases

• Build a recurrence prediction model based on KLF13 and TIA1 gene expression levels.
• Validate prognostic biomarkers for Paget's disease based on RNA-seq data.
• Stratify cancer patients into risk groups based on a two-gene risk-score model.
• Investigate molecular drivers of recurrence in Mammary versus Extramammary Paget's disease.

Strengths

• Validation in both an internal cohort and an independent external Chinese cohort.
• In vitro and in vivo functional validation for TIA1's oncogenic role is described.
• Specific gene expression values with statistical significance are reported (e.g., KLF13: 22.74 ± 3.41 vs. 15.36 ± 4.91, P < 0.001).

Limitations

• The dataset is a single 11.5 KB DOCX file, suggesting limited raw data 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 and weighted gene co-expression network analysis (WGCNA).

Freshness

Last updated 2026-05-12 22:02:06; freshness should be verified.