Development of a prognostic model incorporating a cuproptosis-related signature and CNN3 as a predictor in childhood acute myelocytic leukemia

Background: Childhood acute myeloid leukemia (cAML) is the second most common pediatric blood cancer, with high heterogeneity and poor prognosis. Recent studies have highlighted cuproptosis, a newly discovered form of programmed cell death triggered by the accumulation of intracellular copper ions, as a critical mechanism influencing cancer survival and resistance. Given its emerging role in cancer biology, we investigated cuproptosis-related genes (CRGs) in cAML to explore their potential in prognostic prediction and therapeutic targeting.

Methods: Gene expression data from publicly available sources were analyzed to identify differentially expressed CRGs. Samples were categorized based on their expression profiles, followed by the development of a prognostic risk model using multivariable Cox regression, LASSO, and univariable analyses. The model's performance was evaluated through Kaplan-Meier survival analysis and ROC analysis. Immune infiltration in the tumor microenvironment was assessed using ssGSEA, validated by CIBERSORT. Drug sensitivity correlations were analyzed, and functional validation experiments were conducted on THP-1 and MOLM13 cell lines to assess the role of CNN3.

Results: A set of 12 differential CRGs was used to build a robust prognostic risk model, with high accuracy in predicting patient outcomes (P < 0.001). Significant differences in immune cell composition were identified between risk groups, particularly in T cells, B cells, monocytes, and dendritic cells. Drug sensitivity analysis revealed altered IC50 values for drugs like 5-fluorouracil and bortezomib. Knockdown of CNN3 in leukemia cell lines led to reduced cell proliferation.

Conclusion: Our CRGs-based prognostic model shows potential for guiding personalized treatment strategies in cAML. The differences in immune cell infiltration between risk groups suggest that immune modulation is key in cAML progression. CNN3 and LGR4 were identified as modulators of cAML progression, making them potential therapeutic targets. Future studies with larger cohorts are essential to validate these findings and further explore CRGs-targeted therapies.