LUAD CAF Subgroup and NR2F2 Analysis: Single-Cell and Bulk RNA-Seq Data

A 394.9 KB PDF document published on figshare by Song Zhou on April 13, 2026. It describes integrated single-cell and bulk RNA sequencing data from GEO and TCGA databases, used to analyze cancer-associated fibroblasts in lung adenocarcinoma. The study identifies a key CAF subgroup, constructs a 16-gene prognostic model, and validates the role of NR2F2 in tumor progression through in vitro experiments.

Use Cases

• Constructing prognostic risk models for lung adenocarcinoma patients based on identified CAF subgroup marker genes.
• Analyzing cellular interaction networks and functional states within the tumor immune microenvironment using single-cell RNA-seq data.
• Investigating the role of NR2F2 in promoting matrix remodeling and metabolic reprogramming in cancer-associated fibroblasts.
• Validating associations between prognostic risk scores and immunosuppressive microenvironment features like PD-L1 expression.

Strengths

• Data is integrated from multiple authoritative sources, including GEO and TCGA databases.
• Analysis includes validation through an independent cohort (GSE72094) and in vitro functional experiments.
• The prognostic model is constructed using a specific method (LASSO-Cox regression) and consists of 16 genes.

Limitations

• The primary file is a 394.9 KB PDF; the underlying raw datasets are not directly provided, requiring separate sourcing.
• Column-level documentation for the integrated datasets is absent; field semantics must be inferred from the paper.
• Row count and granularity of the source sequencing data are unknown, which may limit suitability assessment.

Provenance

Source

Integrated from GEO and TCGA databases.

Collection Method

Single-cell and bulk RNA sequencing data analysis, validated with in vitro experiments.

Time Range

Temporal coverage of the source sequencing data is not specified.

Freshness

Last updated 2026-04-13 04:36:05.

Geography

Spatial coverage is not specified.