ArticleDiscover oncology2026
Integrative analysis of polyamine-associated genes reveals a prognostic and immunological signature in esophageal squamous cell carcinoma.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Esophageal squamous cell carcinoma (ESCA) is a highly aggressive malignancy with substantial heterogeneity and poor prognosis. Polyamine metabolism has been implicated in tumor progression and immune regulation, yet its specific role in ESCA remains unclear. Here, we performed integrative single-cell and bulk transcriptomic analyses to explore the significance of polyamine metabolism in ESCA. Using single-cell RNA-seq data from four ESCA patients (GSE188900), we identified seven major cell populations and evaluated polyamine activity via gene set scoring. B lymphocytes and myeloid cells exhibited the highest polyamine scores. Differential expression and enrichment analyses between Polyamine-High and -Low groups revealed associations with immune-related pathways, including T cell activation and cell adhesion. From these genes, we developed a prognostic model consisting of eight polyamine-associated genes (LYPD3, DHPS, MUC5B, CXCL14, SQSTM1, RUNX3, PTPRC, and KRT14) using Cox and LASSO regression. The model effectively stratified patients into high- and low-risk groups in both the GSE53624 training and GSE53622 validation cohorts, with the high-risk group showing significantly worse survival. Immune infiltration analysis using MCPcounter, xCell, and ssGSEA showed distinct immune landscapes across risk groups, with low-risk patients exhibiting higher neutrophil and type 2 helper T cell infiltration. Drug sensitivity analysis based on oncoPredict revealed compounds with differential efficacy between risk groups, and the model also predicted response to PD-1 blockade in an external immunotherapy cohort. In summary, polyamine metabolism is closely linked to the immune microenvironment and prognosis of ESCA, providing a potential biomarker for patient stratification and treatment optimization.
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