Integrating bulk RNA-seq and scRNA-seq data to explore diverse cell death patterns and develop a programmed cell death-related relapse prediction model in pediatric B-ALL

Acute B-lymphoblastic leukemia (B-ALL) is a hematologic malignancy with diverse mechanisms of PCD influencing its progression. This study aimed to identify PCD-related biomarkers and develop a predictive model for relapse in pediatric B-ALL patients. Initially, we examined the activity of 16 PCD patterns in B-ALL patients using scRNA-seq. Following this, we employed both univariate and multivariate Cox regression analyses to identify relapse-related PCD patterns and constructed a relapse prediction model comprising seven key PCD-related genes: Bcl-2-interacting killer (BIK), translocator protein (TSPO), BCL2L2, PIP4K2C, mixed-lineage kinase-like (MLKL), STAT2, and WW domain-containing oxidoreductase (WWOX). Based on the optimal cut-off value derived from the cell death index(CDI) model, patients were categorized into high-CDI and low-CDI groups. Additionally, we evaluated the association between CDI scores and immune cell infiltration, tumor microenvironment (TME) characteristics, and drug sensitivity. Nine PCD patterns, encompassing ferroptosis, autophagy, necroptosis, entotic cell death, alkaliptosis, apoptosis, netotic cell death, oxeiptosis, and NETosis, exhibited strong associations with relapse in B-cell acute lymphoblastic leukemia (B-ALL). The CDI model, validated across multiple cohorts, demonstrated substantial predictive power for relapse-free survival (RFS) and was identified as an independent risk factor. This study offers a comprehensive analysis of PCD patterns in pediatric B-ALL, yielding valuable insights into potential novel therapeutic strategies and opportunities for personalized treatment approaches.