Early-Stage Lung Adenocarcinoma Gene Expression Data for Recurrence Risk Stratification

292 patient gene expression profiles from NCBI GEO datasets were reanalyzed to identify transcriptional programs linked to recurrence risk in early-stage lung adenocarcinoma. The study, authored by Jyothi Thyagabhavan Mony and last updated in April 2026, identifies a prognostic dichotomy between protective immune-related programs and risk-associated extracellular matrix remodeling. An independent validation was performed using 90 treatment-naive, early-stage patients from the TCGA-LUAD cohort.

Use Cases

• Identify gene expression modules associated with recurrence risk based on immune and stromal transcriptional programs.
• Validate prognostic signatures for lung adenocarcinoma survival in an independent cohort.
• Analyze the relationship between extracellular matrix remodeling and impaired lymphocyte responses in early-stage disease.
• Perform pathway-level enrichment analysis on differentially expressed genes linked to recurrence.

Strengths

• Analysis integrates data from 292 patients across NCBI GEO datasets.
• Independent validation was performed on a cohort of 90 patients from TCGA-LUAD.
• Data is openly shared under a CC-BY-4.0 license.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 27.6 MB file size suggests a small to medium-scale dataset.

Provenance

Source

figshare, authored by Jyothi Thyagabhavan Mony.

Collection Method

Reanalysis of gene expression data from public NCBI GEO datasets and TCGA-LUAD.

Time Range

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Freshness

Last updated 2026-04-16 05:25:56; freshness should be verified.

Geography

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