A Multi-Method Approach to Investigate the Toxicity of Aristolochic Acid on Upper Tract Urothelial Carcinoma

Exposure to aristolochic acid (AA) has been strongly linked to the development of upper tract urothelial carcinoma (UTUC), but the precise molecular mechanisms driving AA-associated carcinogenesis remain unclear, limiting effective prevention and treatment strategies. This study aimed to identify core target genes and explore the associated toxic mechanisms by integrating network toxicology, microarray analysis, machine learning, and experimental validation.

Potential AA targets were identified from multiple databases. Differential expression and weighted gene co-expression network analyses were performed on microarray data from AA-related UTUC samples and matched normal urothelium samples to identify hub genes. Overlapping genes between AA-related targets and UTUC hub genes were considered potential pathogenic targets of AA-induced UTUC toxicity. To enhance the accuracy and predictive power, various machine learning algorithms were employed for gene selection. Molecular docking was performed to assess the binding affinity of AA to the core targets. Functional analysis was performed to elucidate potential toxic mechanisms. Gene expression was validated using quantitative real-time PCR in clinical samples from patients with AA-related UTUC and controls.

In total, 379 AA target genes and 793 hub genes of UTUC were identified, leading to the identification of 20 shared genes that were considered potential pathogenic targets of AA-induced UTUC toxicity. Machine learning algorithms extracted five core target genes: AVPR1A, CFD, F10, SCN3A, and NPY1R. Molecular docking confirmed the stable binding of AA to these core targets. Functional analysis suggested that AA-induced UTUC may involve disruption of vascular homeostasis, calcium signaling, and immune modulation. The expression of core genes was successfully validated in clinical samples.

This study integrated network toxicology, microarray analysis, machine learning, and experimental validation to comprehensively elucidate the molecular mechanisms underlying AA-induced UTUC. The combined approach used in this study extends beyond the exploration of individual targets or pathways. Instead, it provides a comprehensive view of the toxic effects of AA through multiple targets and pathways, thereby offering a robust framework for understanding the complex toxicological processes of various harmful compounds. The findings of this study provide crucial insights into the toxicological mechanisms of AA with implications for therapeutic development and regulatory strategies. These insights offer guidance for improving the clinical applications and safety regulations of traditional medicines.

We identified and validated five novel core target genes associated with AA-induced UTUC: AVPR1A, CFD, F10, SCN3A, and NPY1R. Functional investigations revealed that AA-induced UTUC may involve the disruption of vascular homeostasis, calcium signaling, and immune system modulation. Thes.