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Updated: Sep 16, 2025
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Published on: May 30, 2025
PANoptosis-driven molecular stratification in esophageal squamous cell carcinoma: A multi-omics prognostic model and
Zhiqiang Yi1, Ting Tao2, Qiqi Zhang3
1The Second Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, 830011, China; Chongqing University Fuling Hospital, Chongqing, 408000, China.
Background:
Esophageal squamous cell carcinoma (ESCC), accounting for approximately 90 % of esophageal cancer (EC) cases globally, is characterized by aggressive metastasis and poor prognosis. PANoptosis, an integrated form of pyroptosis, apoptosis, and necroptosis, has emerged as a potential predictor of cancer survival and therapy response. However, its role in ESCC remains unclear.
Methods:
Using univariate and LASSO Cox regression analyses, we identified prognostic PANoptosis-related genes (PRGs) to construct a risk model that stratified patients into high- and low-risk groups. The model's accuracy was validated using Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and nomograms. Differential pathways were investigated using gene set enrichment analysis (GSEA), while the significance of genes was highlighted through single-cell RNA sequencing (scRNA-seq) analysis. In vitro experiments validated the tumor-suppressive effects of AZD4547, an FGFR inhibitor. This study elucidates the PANoptosis-driven mechanisms underlying the prognosis and therapeutic strategies for ESCC.
Results:
Thirteen PRGs (CCNE1, CEACAM1, CR2, CRYAB, ERBB3, GAST, HELLS, IFT57, KLF5, MAPK13, PLAU, SAP18, SPATA4) associated with survival were identified and formed the foundation of a robust prognostic model. The model was validated in one external microarray cohort and an independent RNA-seq cohort. Immune microenvironment analysis revealed distinct differences in immune infiltration patterns and checkpoint expression levels between high-risk and low-risk groups. GSEA indicated that the activation of EMT, MYC signaling, E2F targets, and G2M checkpoints might contribute to adverse clinical outcomes in high-risk patients. Furthermore, AZD4547 demonstrated significant suppression of tumor proliferation and inhibition of EMT progression in cells with high-risk scores.
Conclusion:
This study developed and validated the first prognostic model for ESCC based on PANoptosis, highlighting FGFR inhibitors as potential therapeutic strategies for targeting specific subtypes through the suppression of EMT and modulation of the MYC/E2F pathways.
