Frontiers in cell and developmental biology · 2026
Integrative PANoptosis-focused omics analysis uncovers GSDMC as a candidate biomarker in breast cancer.
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Hong Jinghui, Wei Zhihao, Li Mengxin, Gao Xiaochuan, Wu Yuheng, Wang Xuyutian, Wang Xin, Zhang Tianxing, Song Dong
Аннотация
BACKGROUND: PANoptosis, a form of programmed cell death involving crosstalk among pyroptosis, apoptosis, and necroptosis, has recently emerged as a key player in tumor progression and therapy resistance. Despite growing evidence linking PANoptosis to various cancers, the prognostic significance of PANoptosis-related genes (PANRGs) and their roles in breast cancer is not well defined. Investigating their relevance could reveal novel biomarkers for patient stratification and identify new therapeutic targets to overcome resistance to existing treatments.
METHODS: Multi-omics data from TCGA and GEO were analyzed to identify differentially expressed PANRGs. A prognostic signature was constructed via LASSO and multivariate Cox regression and validated in independent cohorts. Functional, microenvironmental, mutational, and drug sensitivity analyses were performed, with key findings validated experimentally.
RESULTS: A five-gene PANRG signature (AIFM1, GSDMC, IRF1, IL18, GZMB) effectively stratified patients into high- and low-risk groups. High-risk patients showed poorer overall survival, advanced TNM stages, immunosuppressive "cold tumor" microenvironments, metabolic reprogramming, higher TP53 mutation frequency, and increased resistance to chemotherapy but greater sensitivity to HER2/mTOR/EGFR-targeted therapies. Single-cell analysis revealed enhanced stromal communication and macrophage dynamics in high-risk patients. Experimental validation confirmed GSDMC upregulation in breast cancer tissues and its association with poor prognosis.
CONCLUSION: This study developed and validated a novel PANoptosis-related prognostic signature for breast cancer, which predicts patient survival, immune landscape, metabolic features, and therapy response. The findings highlight the potential of PANRGs as biomarkers and therapeutic targets, providing a foundation for precision medicine in breast cancer treatment.
METHODS: Multi-omics data from TCGA and GEO were analyzed to identify differentially expressed PANRGs. A prognostic signature was constructed via LASSO and multivariate Cox regression and validated in independent cohorts. Functional, microenvironmental, mutational, and drug sensitivity analyses were performed, with key findings validated experimentally.
RESULTS: A five-gene PANRG signature (AIFM1, GSDMC, IRF1, IL18, GZMB) effectively stratified patients into high- and low-risk groups. High-risk patients showed poorer overall survival, advanced TNM stages, immunosuppressive "cold tumor" microenvironments, metabolic reprogramming, higher TP53 mutation frequency, and increased resistance to chemotherapy but greater sensitivity to HER2/mTOR/EGFR-targeted therapies. Single-cell analysis revealed enhanced stromal communication and macrophage dynamics in high-risk patients. Experimental validation confirmed GSDMC upregulation in breast cancer tissues and its association with poor prognosis.
CONCLUSION: This study developed and validated a novel PANoptosis-related prognostic signature for breast cancer, which predicts patient survival, immune landscape, metabolic features, and therapy response. The findings highlight the potential of PANRGs as biomarkers and therapeutic targets, providing a foundation for precision medicine in breast cancer treatment.