ArticleCurrent medicinal chemistry2025
Identification and Characterization of Prognostic Macrophage Subpopulations for Human Esophageal Carcinoma.
Article in Current medicinal chemistry, 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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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy.Journal of translational medicine · 2025Article
- Exploring research trends in cancer immunotherapy via single-cell technologies: a scientometric perspective.Frontiers in immunology · 2025Review
- Integrative analyses of bulk and single-cell RNA-seq reveals the correlation between SPP1Cancer immunology, immunotherapy : CII · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsThe aim of the present study was to investigate the relationship between the cellular ecosystem and the progression of esophageal carcinoma (ESCA) based on the evolution of macrophages and to analyze the potential of using macrophages as a new therapeutic approach in ESCA treatment.
backgroundMacrophage-based immunotherapy could be used for treating ESCA patients, but its clinical application is limited by the intra-tumor heterogeneity of macrophages.
objectiveThe objective of this study was to analyze the diversity, differentiation trajectory, and intercellular communication of macrophages in ESCA and its prognostic significance.
methodsSingle-cell RNA sequencing (scRNA-seq) data in the GSE154763 dataset were downloaded from Gene Expression Omnibus (GEO) to identify cell clusters and annotate cell types using the Seurat R package. The scRNA-seq profiles of macrophages were extracted, and cluster analysis was performed to identify macrophage subsets. The differentiation trajectories of macrophage subgroups were visualized employing Monocle2. Finally, ligand-receptor pairs and communication intensity among the classified subgroups were analyzed using Cell Chat.
resultsA total of 8 cell types were identified between ESCA tissues and paracancer tissues. The most abundant macrophages in ESCA tissues were further divided into 5 cell clusters. Compared with the normal tissues, the proportion of HSPA6+ macrophages in ESCA tissues increased the most, and the number of ligand-receptor pairs that mediated the communication of HSPA6+ macrophages with mast cells and monocytes also increased significantly. More importantly, a high proportion of HSPA6+ macrophages was inversely correlated with the survival outcomes for ESCA patients.
conclusionsThis study analyzed the diversity, distribution and differentiation trajectory of macrophages in ESCA tissues at single-cell level and classified a prognostic macrophage subtype (HSPA6+ macrophages) of ESCA, providing a theoretical basis for macrophage-targeted therapy in ESCA.
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