Ovarian Cancer Prognostic Model Based on Five Palmitoylation-Related Genes

A five-gene prognostic model for epithelial ovarian cancer constructed from transcriptome and clinical data from TCGA, GTEx, and GEO databases. The model's validity was confirmed using patient samples from TCGA and GEO, and it demonstrated predictive accuracy superior to traditional clinical factors alone. Author Tingting Yu published this research document under a CC-BY-4.0 license on figshare in April 2026.

Use Cases

• Predicting patient survival risk based on the five-gene palmitoylation signature described in the study
• Analyzing correlations between palmitoylation-related gene expression and immune cell infiltration in ovarian cancer
• Investigating potential drug sensitivity and treatment strategies for ovarian cancer based on the model's risk groups
• Validating prognostic biomarkers for epithelial ovarian cancer using independent datasets

Strengths

• Model construction and validation used data from multiple authoritative sources: TCGA, GTEx, and GEO
• Predictive performance was assessed via Kaplan-Meier survival analysis and ROC curve evaluation
• The model is based on a specific biological mechanism: palmitoylation-related genes

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• The primary file is a 6.3 MB DOCX document, which may require extraction of underlying data

Provenance

Source

Transcriptome and clinical data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases.

Collection Method

Data was obtained from public databases; a prognostic model was constructed using univariate Cox and Lasso-Cox regression.

Freshness

Last updated 2026-04-21 22:01:28; freshness should be verified