Supplementary File 1: CXCL9/SPP1 Polarity Axis in NSCLC Tumor-Associated Macrophages

A supplementary document for a study introducing the CXCL9/SPP1 polarity axis for tumor-associated macrophages in non-small cell lung cancer. The research integrated single-cell and bulk transcriptomic data to identify four TAM subpopulations and constructed a six-gene prognostic model using machine learning. The file, authored by Houqiang Li, was last updated on 2026-04-17.

Use Cases

• Validate the six-gene prognostic signature for NSCLC patient risk stratification based on the described model.
• Study the dynamic plasticity of tumor-associated macrophage polarity using the pseudotime trajectory analysis framework.
• Correlate CXCL9/SPP1 expression ratios with immune status features in the tumor microenvironment.
• Benchmark new TAM classification methods against the described NSCLC-specific functional framework.

Strengths

• The underlying study employed a combination of 101 machine learning algorithms for model optimization.
• The prognostic model was validated and effectively stratified patients into high-risk and low-risk groups.
• The research integrated both single-cell and bulk transcriptomic data sources.

Limitations

• The dataset is a 16.1 KB DOCX file, which is a very small supplementary document, not the primary research data.
• Column-level documentation for any potential embedded data is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for computational reuse.

Provenance

Source

figshare, authored by Houqiang Li.

Collection Method

Likely contains supplementary text, figures, or tables from the described computational biology study.

Freshness

Last updated 2026-04-17 05:20:10; freshness should be verified.