DLBCL Fatty Acid Metabolism Gene Signature for Prognostic Prediction

Shuai Wang published a prognostic gene signature on figshare in April 2026. The dataset likely contains gene expression data and derived scores related to fatty acid metabolism in diffuse large B-cell lymphoma (DLBCL). It includes a FAMscore developed via machine learning to predict patient risk and survival.

Use Cases

• Predicting overall survival in DLBCL patients based on the FAMscore prognostic signature.
• Characterizing the immune microenvironment in tumors based on the association between FAMscore and immune infiltration.
• Investigating the role of specific fatty acid metabolism genes like CPT1A in cell proliferation and apoptosis.
• Building a nomogram for personalized treatment strategies based on the integration of FAMscore, COO subtype, and IPI score.

Strengths

• The dataset includes a validated prognostic signature (FAMscore) developed through an integrative machine learning pipeline.
• The findings were validated using quantitative real-time PCR and single-cell RNA sequencing data.
• The dataset is licensed under CC-BY-4.0, allowing for open reuse.

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 26.9 KB, indicating a very limited scope likely containing summary results rather than raw transcriptomic data.

Provenance

Source

figshare

Collection Method

Transcriptomic data was analyzed from the Gene Expression Omnibus (GEO) database.

Freshness

Last updated 2026-04-10 06:02:46