Table 4_Identification of a prognostic signature based on ammonia metabolism-related genes

A prognostic model for clear cell renal cell carcinoma (ccRCC) based on six ammonia metabolism-related genes. The dataset was created by Yao Jiang and last updated on April 23, 2026. It integrates bulk and single-cell transcriptomic data from public resources to explore potential therapeutic strategies.

Use Cases

• Validating the prognostic power of the six identified genes (RGS20, ADA, AICDA, SLC12A5, RUFY4, CDK5RAP3) in ccRCC.
• Investigating immune cell infiltration differences between high-risk and low-risk patient groups.
• Analyzing cell communication networks between malignant cells and T cells in ccRCC tumor microenvironments.
• Conducting functional enrichment analysis on pathways like 'olfactory transduction' linked to patient risk groups.

Strengths

• Model is based on an integrated analysis of both bulk and single-cell transcriptomic data.
• Identifies six specific prognostic genes with RT-qPCR validation results (p < 0.05).
• Includes analysis of 16 immune cell types with differential abundance between risk groups.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (15.4 KB), indicating limited raw data, likely containing summary results or model parameters.

Provenance

Source

figshare

Collection Method

Transcriptomic data and ammonia death-related genes were retrieved from public resources, followed by differential expression analysis, machine learning filtering, and single-cell level analyses.

Freshness

Last updated 2026-04-23 05:36:03; freshness should be verified.