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

Zhenyang Wang's research dataset, last updated April 15, 2026, contains transcriptomic analysis results for Ewing's sarcoma. The data includes differential expression of nine disulfidptosis-related genes, a five-gene prognostic risk model, and associated drug sensitivity and single-cell RNA sequencing analyses. The 3.3 MB dataset is available under a CC-BY-4.0 license.

Use Cases

• Developing prognostic risk models based on the five-gene signature (NDUFS1, LRPPRC, NDUFA11, OXSM, NUBPL).
• Predicting drug sensitivity to microtubule inhibitors based on the described risk score stratification.
• Analyzing single-cell RNA sequencing data to explore functional heterogeneity and tumor microenvironment interactions.
• Performing molecular docking simulations to evaluate interactions between disulfidptosis-related gene proteins and chemotherapeutic agents.

Strengths

• Includes experimental validation of five key genes at RNA and protein levels in RD-ES cells.
• Risk model was validated as an independent prognostic indicator with significantly different survival outcomes for high- and low-risk groups.
• Analysis incorporates data from four GEO datasets and the GDSC database for drug sensitivity.

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 cell lines and GEO datasets used.

Provenance

Source

figshare

Collection Method

Transcriptomic analysis of four GEO datasets, single-cell RNA sequencing analysis, and experimental validation in RD-ES cells.

Time Range

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Freshness

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

Geography

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