Stemness Signature Prognostic Model for Esophageal Carcinoma

A 10.0 KB Excel file contains a stemness gene prognostic model for esophageal carcinoma, developed by Yubing Liu and last updated on May 19, 2026. The model was constructed using bulk and single-cell RNA-seq data, Cox regression, and LASSO analysis. It predicts patient prognosis and drug response, with its 1-, 2-, and 3-year survival predictions reportedly outperforming TNM staging.

Use Cases

• Predicting patient prognosis based on the constructed stemness gene model.
• Analyzing drug response predictions based on the model's reported capabilities.
• Investigating the role of the model gene RBBP7 in tumor cell stemness and immune microenvironment reshaping.
• Exploring crosstalk between prognostic genes and the tumor microenvironment using inferred CellChat analysis results.

Strengths

• The model's 1-, 2-, and 3-year survival predictions are reported to outperform TNM staging.
• The model gene RBBP7 is identified as the most influential prognostic factor.
• Analysis integrates bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and functional experiments.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset's small size (10.0 KB) suggests it likely contains model coefficients or summary results, not raw genomic data.

Provenance

Source

figshare

Collection Method

Integrated multi-omics research using bulk RNA-seq, single-cell RNA-seq (scRNA-seq), WGCNA, Cox regression, LASSO analysis, CellChat, and functional experiments.

Freshness

Last updated 2026-05-19 05:44:39; freshness should be verified.