ORIGINAL RESEARCH article
Front. Med.
Sec. Obstetrics and Gynecology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1590405
This article is part of the Research TopicRevolutionizing Cancer Care: AI and Technological Advances in Breast and Gynecological OncologyView all 4 articles
Evaluation of Pyroptosis-Associated Genes in Endometrial Cancer Utilizing a 101-Combination Machine Learning Framework and Multi-Omics Data
Provisionally accepted
- 1Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- 2Shanghai Songjiang District Maternal and Child Health Care Hospital, Shanghai, China
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Background: Endometrial cancer (EC) is a common and increasingly prevalent gynecological malignancy. Pyroptosis, a pro-inflammatory form of programmed cell death, plays dual roles in cancer but remains poorly understood in the context of EC and its immune microenvironment. Methods: We identified pyroptosis-associated genes (PAGs) and applied a 101-combination machine learning framework to construct and validate a robust prognostic model using TCGA bulk RNA-seq and single-cell transcriptomic data. Immune infiltration was assessed using CIBERSORT and Tumor Immune Dysfunction and Exclusion (TIDE), while CellChat was employed to investigate pyroptosis-related cell-cell communication. Drug sensitivity was predicted with OncoPredict. Results: A seven-gene prognostic model demonstrated robust predictive performance with concordance index (C-index) values exceeding 0.70 in both training and validation cohorts. The model stratified EC patients into high-and low-risk groups with distinct immune infiltration profiles and differential responses to programmed cell death protein 1 (PD-1) blockade. Drug sensitivity analysis revealed several therapeutic agents with potential efficacy in highrisk and low-risk subgroups. Conclusion: This study highlights the clinical and immunological relevance of pyroptosis in EC and introduces a PAG-based model with strong predictive and therapeutic potential. These findings provide a foundation for developing pyroptosis-guided precision immunotherapy strategies in EC.
Keywords: endometrial cancer, pyroptosis, Prognostic model, immune microenvironment, drug sensitivity
Received: 09 Mar 2025; Accepted: 25 Apr 2025.
Copyright: © 2025 Huang, Chen, Tang, Zhan, Chen, Teng, Sang, Zhou and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Weilin Sang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Lina Zhou, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Ye Yang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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