LUAD Prognostic Genes: Single-Cell Transcriptome and Mendelian Randomization Analysis

A 30.4 KB Excel file by Jiaxin Li, last updated March 25, 2026, presents results from a study integrating single-cell transcriptome analysis and Mendelian randomization to identify prognostic genes in lung adenocarcinoma. The study identified seven genes associated with endoplasmic reticulum stress and butyrate metabolism and validated their expression in non-small cell lung cancer cell lines. A risk model and nomogram were constructed to predict patient survival outcomes.

Use Cases

• Validate prognostic gene signatures based on the seven identified genes (VDAC1, TXNRD1, GDF15, TRIB3, LPL, KCNQ1, PKP2).
• Build survival prediction models based on the described risk model and nomogram for 1-, 3-, and 5-year survival.
• Analyze immune microenvironment composition based on the 13 differentially abundant immune cell types mentioned, including M1 macrophages.
• Investigate pathway enrichment in patient subgroups based on described pathways like olfactory transduction, ribosome, and complement-coagulation cascades.

Strengths

• Identifies seven specific prognostic genes (VDAC1, TXNRD1, GDF15, TRIB3, LPL, KCNQ1, PKP2) with expression validated by RT-qPCR.
• Risk model and nomogram were constructed and demonstrated predictive accuracy for 1-, 3-, and 5-year survival.
• Analysis includes results from single-cell transcriptomics, Mendelian randomization, and immune profiling of 13 cell types.

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 (30.4 KB), suggesting it contains summary results rather than primary sequencing data.

Provenance

Source

Author Jiaxin Li via figshare.

Collection Method

Integrated analysis of public datasets using weighted gene co-expression network analysis, differential expression analysis, and Mendelian randomization.

Freshness

Last updated 2026-03-25 22:03:05