Table 4_Integrated transcriptomic profiling of programmed cell death patterns unveils macr

Manling Xie published a dataset on 2026-05-19 containing integrated transcriptomic analysis of programmed cell death patterns in hepatic ischemia-reperfusion injury. The data, derived from four public GEO datasets, includes bulk and single-cell RNA-seq results used to identify hub genes and construct a risk prediction model. The study focuses on the THBS1-CD47 axis mediating macrophage-hepatocyte crosstalk.

Use Cases

• Training machine learning models for HIRI risk prediction based on the five identified hub genes (THBS1, MAP1LC3B, PPP1R15A, CXCL8, ZC3H12A).
• Analyzing heterogeneous programmed cell death patterns (e.g., anoikis, pyroptosis) in liver tissue from transcriptomic data.
• Investigating macrophage-hepatocyte crosstalk mechanisms via the THBS1-CD47 signaling axis described in the study.
• Validating single-cell RNA-seq findings against bulk transcriptomic data for HIRI pathology.

Strengths

• Integrates data from four distinct public GEO datasets (GSE151648, GSE14951, GSE12720, GSE171539).
• Identifies 25 differentially expressed programmed cell death-related genes and 5 hub genes for modeling.
• Analysis spans both bulk and single-cell transcriptomic levels, covering 19 PCD patterns.
• Published under a permissive CC-BY-4.0 license.

Limitations

• Dataset size is 41.8 KB, indicating a very limited scope, likely containing summary results rather than raw expression matrices.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analysis.

Provenance

Source

Gene Expression Omnibus (GEO) databases GSE151648, GSE14951, GSE12720, and GSE171539.

Collection Method

Bulk and single-cell transcriptomic analysis, machine learning algorithms, and in vivo/in vitro experimental validation.

Freshness

Last updated 2026-05-19 04:22:43; freshness should be verified.