SAMRS: Scissor-Associated Macrophage Risk Score for Lung Adenocarcinoma Prognosis

A machine learning model integrating single-cell RNA-seq data from GEO with bulk transcriptomic profiles from TCGA-LUAD to create a macrophage-derived risk score. The Scissor-Associated Macrophage Risk Score (SAMRS) was developed by Yueyue Shi and last updated on 2026-05-14. It is designed for prognostic stratification and immunotherapy response assessment in lung adenocarcinoma.

Use Cases

• Prognostic patient stratification in lung adenocarcinoma based on the SAMRS risk score.
• Predicting immunotherapy response likelihood based on the link between SAMRS scores and immune evasion signals.
• Investigating macrophage subpopulation roles in tumor progression using the identified phenotype-associated subsets.
• Validating candidate genes like TIMP1 across bulk, single-cell, and spatial transcriptomic analyses.

Strengths

• Model integrates data from two major public repositories, GEO and TCGA.
• The dataset is openly licensed under CC-BY-4.0.
• Validation included genomic features, cell-cell communication analysis, and functional experiments.

Limitations

• The dataset is very small at 2.9 KB, suggesting it contains model outputs or summary scores rather than raw data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analyses.

Provenance

Source

Integrated single-cell data from GEO and bulk transcriptomic data from TCGA-LUAD.

Collection Method

Scissor algorithm applied to map clinical phenotypes onto single cells, followed by machine learning model construction.

Freshness

Last updated 2026-05-14 04:29:51; freshness should be verified.