LUAD Multi-omics Data: Efferocytosis Gene Signatures and ADAM9 Analysis

Guofu Lin's research dataset underpins a study on lung adenocarcinoma (LUAD) progression. It includes multi-omics data from 517 tumor and 59 normal tissue samples from TCGA-LUAD, used to construct an 11-gene prognostic model. The dataset was last updated on 2026-05-25 and is shared under a CC-BY-4.0 license.

Use Cases

• Constructing prognostic models for lung adenocarcinoma based on efferocytosis-related gene signatures.
• Analyzing immune cell infiltration and immunosuppressive microenvironments correlated with ADAM9 expression.
• Validating gene signatures via survival analysis and nomogram construction.
• Investigating cell-cell interaction signaling hubs within the tumor microenvironment using single-cell sequencing insights.

Strengths

• Includes data from 517 tumor and 59 normal tissue samples, providing a case-control basis for analysis.
• The prognostic model is based on 11 specific efferocytosis-related gene signatures, including ADAM9.
• Analysis integrates multi-dimensional methods including consensus clustering, LASSO regression, and single-cell sequencing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying analytical datasets is unknown, which may limit suitability assessment.
• The primary file is a 1.1 MB PDF, suggesting the raw data may not be directly included and may require extraction from the publication.

Provenance

Source

The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) project, with analysis by author Guofu Lin.

Collection Method

Data analysis involved consensus clustering, LASSO regression, immune infiltration algorithms, and in vitro experiments.

Freshness

Last updated 2026-05-25 06:03:33; freshness should be verified.