Prognostic characterization and immune landscape of PANoptosis-based molecular subtypes in breast cancer
Abstract Background PANoptosis is a unique form of inflammatory cell death that integrates a complex interaction between pyroptosis, apoptosis and necroptosis, but the expression properties and prognostic effects in breast cancer are still unclear. Methods In this study, 31 PANoptosis related genes were screened through the breast cancer data sets of TCGA and GEO, then the PANoptosis subtypes of breast cancer were identified, potential prognostic markers were found through the differences between molecular subtypes, prognostic models were established, prognostic genes were inferred, and finally the diagnostic and prognostic value of model genes are verified by clinical samples. Results Two types of PANoptosis molecular subtypes with survival differences were identified based on the differentially expressed PRGs in tumors. a 7-gene prognostic model was constructed based on 24 PRDEGs to evaluate the prognosis of breast cancer. Univariate Cox analysis confirmed that the model score was an independent prognostic factor, and confirmed that the risk score was significantly correlated with the clinical features of breast cancer, the proportion of immunoinfiltrating cells, genomic mutations, and the expression of immune modulators. We verified that the expressions of GSDMC and GSDMD were significantly increased, while the expressions of GSDMB, GSDME and 4 prognostic genes ( IL33 , PARP3 , BCL2 , IFI35 ) were significantly decreased in clinical breast cancer patient samples, and confirmed that the differential expression of IL-33 was correlated with clinical and prognostic indicators of breast cancer. Conclusions We demonstrated the potential of molecular clustering and prognostic features of PANoptosis in predicting breast cancer survival and immunotherapy. In addition, we verified the expression and prognostic value of breast cancer prognostic genes through clinical samples, providing new strategies for the diagnosis and treatment of breast cancer.
Authors
- 邵国安
- Jianya Mao
- Shu Chen (ORCID: https://orcid.org/0009-0003-7567-2434)
- Zhongli Geng (ORCID: https://orcid.org/0000-0002-6670-9763)
- Shengbin Bai
- Xin Yang
- Zhenghao ZHANG
- Xinyi Zhang
- Adilijiang Aierken
- Hong Wang
- Hui Chen
Institutions
- Xinjiang Medical University (CN)
- Fifth Affiliated Hospital of Xinjiang Medical University (CN)
- People's Hospital of Xinjiang Uygur Autonomous Region (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2026-10-26
- DOI
- https://doi.org/10.1007/s12672-026-06187-3
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00