ArticleScientific reports2025
A signature based on efferocytosis-related genes for the evaluation of prognosis and the tumour microenvironment in gastric cancer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Spatial and Temporal Heterogeneity of Macrophage Efferocytosis in Tumors: Emerging Implications for Immunotherapy Biomarkers and Therapeutic Timing.Cancer medicine · 2026Review
- Review
- A novel efferocytosis-related gene signature for predicting prognosis and therapeutic response in bladder cancer.Scientific reports · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
Gastric cancer (GC) is a highly malignant tumor of the digestive system. The process of efferocytosis has been confirmed to be closely associated with tumor progression and microenvironment remodeling. Nevertheless, the mechanism of efferocytosis in GC remains unclear. This study integrates single-cell RNA sequencing (scRNA-seq) datasets with the TCGA transcriptome data for GC, focusing on the expression and distribution of efferocytosis-related genes (ERGs) at the single-cell level in GC. The prognostic features of ERGs are determined by Cox and LASSO analysis. And we analyzed and evaluated the differences between the two groups of patients in terms of long-term prognosis, immune infiltration, expression of immune checkpoints, and response to chemotherapeutic drugs. Seven cell types were identified from 10 GC samples. ERGs were mainly concentrated in macrophages, dividing macrophages into 5 cell subtypes. LASSO combined with Cox ultimately confirmed 4 independent prognostic genes, and a prognostic nomogram was constructed based on gene risk scores and clinical features, which was validated in an independent dataset. Further studies revealed that ERGs were closely related to the patient's immune cell infiltration (especially M2 macrophages), immunotherapy response, and drug sensitivity. We developed an ERG-based predictive model that could serve as a valuable tool for prognosis assessment and decision support in the context of immunotherapy and chemotherapy.
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Registered trials
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