MRPL3 Prognostic Biomarker Data for Lung Adenocarcinoma

A gene expression dataset from TCGA and GEO cohorts used to identify prognostic biomarkers for lung adenocarcinoma. The dataset, created by Lan Yin and last updated in May 2026, likely contains results from differential expression, correlation, and survival analyses. It supports a prognostic model built via LASSO regression and includes experimental validation data for the MRPL3 gene.

Use Cases

• Building prognostic models for lung adenocarcinoma based on lactylation and disulfidptosis gene signatures.
• Validating MRPL3 as a therapeutic target based on its correlation with poor prognosis and tumor stage.
• Analyzing the link between gene expression and the immunosuppressive tumor microenvironment.
• Studying the role of glycolytic-lactate metabolism in cancer progression using gene expression data.

Strengths

• The dataset is derived from authoritative gene expression sources like The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).
• The model was validated across testing, validation, and external cohorts, suggesting reliability.
• Findings were supported by in vivo and in vitro experimental validation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small (41.2 KB), indicating limited scope or summary-level data.

Provenance

Source

Gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts.

Collection Method

Differential expression analysis, correlation analysis, univariate survival analysis, and LASSO regression.

Freshness

Last updated 2026-05-19 05:40:23; freshness should be verified.