LGMN Gene Signature and Cell Interaction Data for Idiopathic Pulmonary Fibrosis

A 401.5 KB PDF research article published on figshare by Yuechong Xia in April 2026. The study analyzes single-cell transcriptomic and microarray data from the GEO database to identify a macrophage-related gene signature for predicting IPF patient prognosis. In vivo and in vitro experiments investigate the role of the LGMN gene in promoting crosstalk between macrophages and fibroblasts.

Use Cases

• Validate a prognostic gene signature for IPF patients based on monocyte-derived macrophage (MDM) genes.
• Analyze cell-cell interaction patterns, particularly between macrophages and fibroblasts, using CellChat-derived data.
• Investigate the activation of the TGF-β1 signaling pathway in MDMs and myofibroblasts within fibrotic lung tissue.
• Assess the therapeutic potential of LGMN inhibition for reducing TGF-β1 secretion and alleviating pulmonary fibrosis.

Strengths

• Data is derived from single-cell transcriptomic and microarray sources, allowing for cellular-level analysis.
• Findings are validated using ROC curves and an external dataset, suggesting methodological rigor.
• Includes in vivo and in vitro experimental validation of the identified target, LGMN.

Limitations

• The dataset is a 401.5 KB PDF research article; the underlying raw data files are not directly provided.
• Column-level documentation and sample data are unavailable, requiring manual extraction from the paper.
• Row count and specific data formats for the analyzed transcriptomic data are unknown.

Provenance

Source

figshare, author Yuechong Xia.

Collection Method

Analysis of single-cell transcriptomic and microarray data from the GEO database, combined with bioinformatics and experimental validation.

Time Range

Study period not specified; data likely reflects contemporary research up to 2026.

Freshness

Last updated 2026-04-13 04:35:52.

Geography

Geographic coverage of patient data is not specified.