Abstract
BACKGROUND: Wilms tumor (WT) lacks precise molecular subtyping tools, which limits the development of personalized therapies. To address this issue, we investigated whether NK cell-related genes (NKGs) could refine the molecular subtyping of WT, aiming to identify novel therapeutic strategies. METHODS: Consensus clustering was employed for the molecular subtyping of WT. The immune microenvironment of different WT subtypes was assessed using immune profiling algorithms. Potential therapeutic compounds targeting the identified subtypes were screened using the CMap database, and their mechanisms of action were elucidated through molecular docking and molecular dynamics simulations. Subsequently, in vitro cell experiments, including CCK8, flow cytometry, and Transwell assays, were performed to assess the biological behavior of tumor cells. A prognostic signatures was constructed using machine learning algorithms, with its performance evaluated by ROC curves, calibration curves, and the concordance index. Additionally, cellular localization and expression of marker genes were investigated through single-cell analysis and validated using RT-qPCR. RESULTS: We developed novel molecular subtyping tools that classified WT into prognostically distinct subtypes: "immune-rich" and "immune-desert". Screening the CMap database identified the small-molecule drug TGX-221 as a candidate modulator. TGX-221 significantly inhibited the malignant progression of WT through a dual-action mechanism: blocking the key oncogenic Wnt/β-catenin signaling pathway and sensitizing tumor cells to NK cell-mediated cytotoxicity. Furthermore, a prognostic signatures based on HS2ST1, EPI3M, and PPP3CA effectively predicted patient outcomes. Notably, HS2ST1 emerged as a novel biomarker, potentially promoting cancer stem cell-like properties via heparan sulfate-mediated enhancement of Wnt/β-catenin signaling, highlighting its dual value as both a prognostic indicator and a therapeutic target. CONCLUSION: Molecular subtyping and prognostic signatures based on NKGs enable the precise identification of high-risk WT patients. Moreover, TGX-221 represents a promising novel therapeutic candidate, while HS2ST1 serves as a potential prognostic biomarker. These findings collectively provide tools for risk stratification and targeted therapy, advancing precision oncology for WT.