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Computational prioritization of candidate TCDD-associated targets in retinoblastoma using network toxicology and
Yingluan Wang1, Qiang Hu1, Zhan Cao2
1Department of Ophthalmology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Background:
Retinoblastoma (RB) is the most common ocular malignancy in children, but the relationship between environmental pollutants and RB-related molecular alterations remains unclear. This study aimed to identify candidate targets and pathways potentially linking 2.3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) with RB.
Methods:
Network toxicology, computational toxicology, and integrated RB transcriptomic analyses were used to identify candidate TCDD-RB targets. WGCNA, eight machine-learning algorithms, and SHAP analysis were applied to screen hub genes and evaluate their contributions to model prediction. Functional enrichment analysis, GSEA/GSVA, immune microenvironment analysis, molecular docking, and expression validation in RB cell lines were subsequently performed to assess the potential biological relevance of the hub genes.
Results:
A total of 18 candidate TCDD-RB targets were identified and were mainly enriched in cell-cycle regulation, G2/M transition, DNA replication, and the p53 signaling pathway. Machine learning further identified five hub genes, namely, CA14, PIP5K1B, GRIA2, KDR, and CDK1. Among them, CDK1 was significantly upregulated in RB and was associated with proliferation-related pathways, including the cell cycle, DNA replication, and mismatch repair. The other four genes were significantly downregulated and may be involved in metabolic homeostasis and immune microenvironment regulation. Molecular docking predicted potential structural compatibility between TCDD and all five hub proteins, with CDK1 showing the most favorable predicted docking energy. qRT-PCR analysis in RB cell lines supported the differential expression patterns of the five hub genes, and qRT-PCR and Western blotting confirmed the efficiency of CDK1 overexpression and knockdown.
Conclusion:
This study delineated a candidate molecular network at the intersection of TCDD-associated toxic This study delineated a candidate molecular network at the intersection of TCDD-associated toxicological targets and RB-related transcriptomic alterations. CDK1 emerged as a candidate hub associated with cell-cycle dysregulation, whereas CA14, PIP5K1B, GRIA2, and KDR were linked to broader disturbances in cellular homeostasis and microenvironmental regulation. Because these findings are based primarily on computational analyses and preliminary expression validation, they should be regarded as hypothesis-generating. Direct TCDD exposure and functional studies are required to determine whether TCDD functionally affects these genes or RB-related cellular phenotypes.