NT5E Gene Expression Profiles for Pulmonary Hypertension Diagnosis

Supplementary data from a 2026 bioinformatics study identifies NT5E as a key NAD+ metabolism-related gene in pulmonary hypertension. The file contains results from differential expression, ROC curve, and immune infiltration analyses across two GEO datasets (GSE113439, GSE53408). Researcher Yanan Chu published this work on figshare to support validation of NT5E as a diagnostic biomarker.

Use Cases

• Validate NT5E expression levels as a diagnostic biomarker using provided ROC curve analysis results with AUC values of 0.891 and 0.894.
• Analyze the association between NT5E expression and immune cell infiltration, specifically plasma cells and eosinophils, in the pulmonary hypertension microenvironment.
• Reproduce gene set enrichment analysis (GSEA) findings linking high NT5E expression to enriched PH-related biological functions and pathways.
• Compare differential expression results for NT5E and CD38 genes identified from overlapping DEGs, NMRGs, and weighted gene co-expression network analysis modules.

Strengths

• ROC analysis shows high predictive accuracy for NT5E with AUC values of 0.891 and 0.894 across two independent datasets.
• Analysis integrates multiple data sources: GEO database expression data, KEGG and Reactome pathway genes, and weighted gene co-expression networks.
• Findings are supported by in vitro cellular experiments validating NT5E's functional role in pulmonary arterial smooth muscle cells.

Limitations

• The 192.4 KB file size indicates a limited dataset, likely containing summary results rather than raw expression matrices.
• Specific row counts, column names, and sample-level data for the GEO datasets are not included in this supplementary file.
• Temporal coverage and sample demographics for the source GEO datasets are not specified within this file.

Provenance

Source

Gene Expression Omnibus (GEO) databases GSE113439 and GSE53408, with NMRGs from KEGG and Reactome.

Collection Method

Bioinformatics analysis using Limma R package for DEGs, weighted gene co-expression network analysis, ROC analysis, GSEA, and CIBERSORT algorithm for immune infiltration.

Freshness

Last updated April 2026, representing recent research.