TSPAN32 Biomarker Study in Lung Adenocarcinoma: Gene Expression and Radiotherapy Response

A 2026 study by Guomin Huang analyzes genomic data from The Cancer Genome Atlas (TCGA) to identify a 12-gene risk score model for lung adenocarcinoma prognosis. The research focuses on the key gene TSPAN32, assessing its role as a predictive biomarker for radiotherapy effectiveness and immune infiltration. The dataset is a 1.2 MB document containing the full study methodology and results.

Use Cases

• Developing prognostic models for lung adenocarcinoma based on the described 12-gene risk score.
• Investigating the relationship between TSPAN32 expression and immune cell infiltration in tumors.
• Studying gene expression patterns associated with radiotherapy sensitivity in cancer cell lines.
• Validating in silico findings from TCGA data through experimental design analysis.

Strengths

• Includes a validated 12-gene risk score model for prognosis prediction.
• Contains experimental validation results from in vitro and in vivo studies on A549 and H1299 cell lines.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The primary data file is a DOCX document, which may require parsing to extract structured information.

Provenance

Source

figshare

Collection Method

Analysis of genomic datasets from The Cancer Genome Atlas (TCGA), supplemented with in vitro and in vivo experiments.

Time Range

The study was published in 2026, but the underlying TCGA data likely covers an earlier period.

Freshness

Last updated 2026-04-14 05:11:53; freshness should be verified.

Geography

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