Comprehensive analysis of the potential effect and mechanism of pyroptosis-related genes in treatment-related myeloid tumors - Jing Cheng; Weiyue Fang; Hongxia Tan; Xiaoxia Zhan; Xiaohui Zhu (PLoS ONE, 2026)
Treatment-related myeloid neoplasms (t-MN) represent a severe complication of cancer therapy, characterized by poor prognosis and limited treatment options. This study presents a preliminary, exploratory bioinformatic analysis aimed at characterizing the expression landscape and potential regulatory roles of pyroptosis-related genes (PRGs) in a murine model of t-MN. Utilizing RNA-seq data (GEO: GSE135866), differential expression analysis identified 1286 DEGs. Cross-referencing 367 curated mouse PRGs revealed 46 pyroptosis-related DEGs (PRDEGs). Functional enrichment analysis (GO, KEGG) showed these PRDEGs are significantly involved in autophagy, inflammatory regulation, apoptosis, NOD-like receptor signaling, and the AMPK pathway. GSEA associated the broader gene set with PI3K-Akt and Notch signaling. Protein-protein interaction network analysis identified five critical hub genes: Trp53 , Mtor , Gpx3 , Foxo3 , and Cybb . ROC curve analysis confirmed these hub genes exhibit significant differential expression and high diagnostic accuracy (AUC > 0.9) in distinguishing t-MN from controls. Furthermore, immunoinfiltration analysis (CIBERSORT) revealed significant differences in immune cell composition between t-MN and control samples and identified notable correlations between hub gene expression and specific immune cell abundances. Importantly, given the limited sample size and the use of murine bone marrow data, the statistical findings should be interpreted strictly at the exploratory and hypothesis-generating level. This study does not support definitive biological conclusions or causal inferences but rather aims to delineate the pyroptosis-related molecular profile in a preclinical t-MN model. The results are intended to inform and guide future investigations—including validation in larger cohorts, independent experimental models, and human clinical samples—to assess the translational potential of these candidate biomarkers and therapeutic targets.