AFAP1L1: An Immune-Related Prognostic Biomarker in Clear Cell Renal Cell Carcinoma

This dataset supports a study identifying the gene AFAP1L1 as a potential immune-related prognostic biomarker for clear cell renal cell carcinoma (ccRCC). Analyses include univariate and multivariate Cox regression, differential gene expression, functional enrichment, immunoassays, and single-cell expression profiling. The study validated findings across training, E-MTAB-1980, and CPTAC cohorts and identified five potential therapeutic agents.

Use Cases

• Prognostic modeling based on AFAP1L1 expression levels and overall survival data
• Functional enrichment analysis of differentially expressed genes related to signaling pathways and nephron development
• Immune cell correlation analysis investigating relationships between AFAP1L1 and neutrophils or macrophages
• Single-cell expression analysis to evaluate AFAP1L1 levels in specific cell types like endothelial cells
• Drug discovery screening using Connectivity Map results to identify potential small-molecule therapeutics

Strengths

• Includes validation across multiple independent cohorts (E-MTAB-1980 and CPTAC), supporting result robustness
• Applies multiple analytical methods, including Cox regression, differential expression, and single-cell trajectory analysis
• Dataset is openly licensed under CC-BY-4.0, facilitating reuse
• Cross-platform presence on figshare suggests established sharing and potential for visibility

Limitations

• Column names and a precise row count are not provided, limiting assessment of data structure and scale
• The dataset size is given as 954070 bytes, but the nature of the contained files (e.g., PDFs, raw data) is unspecified
• The last update date is projected to 2026-03-23, which is inconsistent with standard dating and may indicate a metadata error

Provenance

Source

Author is Qiaoping Yan; originating institution is not specified.

Collection Method

Data likely generated from gene expression analysis (e.g., qRT-PCR), public cohort data (E-MTAB-1980, CPTAC), and computational bioinformatics workflows.

Freshness

2026-03-23 11:45:35