Disulfidptosis-Related Gene Expression and Prognostic Signature for Ewing's Sarcoma

A 5-gene risk model (NDUFS1, LRPPRC, NDUFA11, OXSM, NUBPL) derived from transcriptomic analysis of four GEO datasets stratifies Ewing's sarcoma patients by survival outcome. The dataset includes drug sensitivity predictions from GDSC and immune infiltration scores, validated experimentally in RD-ES cells. Author Zhenyang Wang published the data on figshare in April 2026.

Use Cases

• Developing prognostic risk scores based on the five disulfidptosis-related genes (NDUFS1, LRPPRC, NDUFA11, OXSM, NUBPL)
• Predicting drug sensitivity to microtubule inhibitors based on the risk signature
• Analyzing immune infiltration in tumor microenvironment using ssGSEA scores
• Investigating gene expression heterogeneity in malignant cells using single-cell RNA sequencing data
• Evaluating protein-drug interactions via molecular docking simulations of DRGs and chemotherapeutic agents

Strengths

• Includes experimental validation of gene dysregulation via PCR and Western blotting in RD-ES cells
• Integrates multiple analysis types: differential expression, co-expression networks, functional enrichment, and single-cell RNA sequencing
• Risk model was validated as an independent prognostic indicator

Limitations

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

Provenance

Source

figshare

Collection Method

Analysis of four GEO datasets, GDSC database, and single-cell RNA sequencing data, with experimental validation.

Freshness

Last updated 2026-04-15 05:44:39; freshness should be verified