m6A-Autophagy lncRNA Signature for Esophageal Cancer Prognosis and Immune Profiling

Transcriptomic data from The Cancer Genome Atlas and Gene Expression Omnibus were used to develop a prognostic model for esophageal squamous cell carcinoma. The model is based on five m6A- and autophagy-related long non-coding RNAs and includes analyses of survival, immune cell infiltration, and drug sensitivity. Author Mingyi Yang published the dataset under a CC-BY-4.0 license on figshare in May 2026.

Use Cases

• Predicting overall survival in esophageal squamous cell carcinoma patients based on a five-lncRNA signature.
• Analyzing the correlation between prognostic risk scores and immune cell infiltration profiles, such as mast cells and B cells.
• Identifying potential therapeutic compounds, like Shikonin or VX-680, tailored to distinct risk subgroups.
• Investigating the expression of immune checkpoint molecules TNFRSF18 and LAIR1 in relation to cancer risk stratification.

Strengths

• Model was validated using an independent cohort from the Gene Expression Omnibus.
• Analysis includes multiple validation methods: survival analysis, ROC curves, and independent prognostic analysis.
• Integrates single-cell sequencing data to corroborate immune microenvironment findings.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect the specific biases inherent to the TCGA and GEO source repositories.

Provenance

Source

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).

Collection Method

Transcriptomic data analysis integrating co-expression, differential expression, and regression modeling.

Freshness

Last updated 2026-05-28 06:20:39; freshness should be verified.