ArticleFrontiers in oncology2026
Prognostic biomarkers related to PANoptosis in esophageal cancer and their immune microenvironment: multi-omics analysis and therapeutic significance.
Article in Frontiers in 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
Introduction: Esophageal squamous cell carcinoma (ESCA) is one of the most common cancers worldwide. PANoptosis is an inflammatory programmed cell death pathway event regulated by the PANoptosome complex. Currently, there is limited research on the PANoptosis-related genes (PORGs) in ESCA. We aim to explore the prognostic biomarkers of PANoptosis in ESCA and their underlying mechanisms through comprehensive bioinformatics analysis. Methods: In this study, we analyzed transcriptome and single-cell RNA sequencing (scRNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were used to identify PANoptosis-related differentially expressed genes (POR-DEGs) in esophageal cancer. Hub genes were screened by univariate and multivariate Cox regression combined with machine learning models to construct diagnostic and prognostic models. The potential mechanisms of hub genes in esophageal cancer were preliminarily explored through gene immune infiltration and functional enrichment analysis. The differences and driving factors between high- and low-risk subgroups, as well as the regulation of PANoptosis by hub genes related to macrophages, were further revealed by immune assessment, drug sensitivity analysis, single-cell analysis, and molecular docking. Finally, the accuracy of model genes was verified by immunohistochemistry in clinical samples. Results: Firstly, 74 PANoptosis-related differentially expressed genes (POR-DEGs) were identified for further analysis. Among the 74 genes, CCT6A, GMNN, and HSPB6 were identified as hub genes, and the constructed diagnostic and prognostic models were valuable. The high-risk subgroup showed poor prognosis, immune exhaustion, significant activation of pDC-LILRA4 cells, poor response to immunotherapy, and moderate sensitivity to chemotherapy. Further exploration of the immune regulatory mechanism of prognostic biomarkers revealed that the three hub genes, CCT6A, GMNN, and HSPB6, were closely related to the ESCA immune microenvironment. The CCT6A targeted by the traditional Chinese medicine component quercetin may inhibit PANoptosis by promoting the differentiation of Mono-CD14 cells into TAM-SPP1 macrophages. Discussion: We constructed prognostic and diagnostic models using PANoptosis-related prognostic biomarkers, analyzed the differences and treatments between high-risk and low-risk groups, and revealed a new mechanism by which CCT6A may inhibit PANoptosis by promoting TAM-SPP1 differentiation, providing new targets and biomarkers for ESCA treatment.
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