Employing network toxicology, molecular docking, machine learning, and single-cell analysis to analyze BPA...

Area of Science:

• Environmental Health
• Oncology
• Molecular Biology

Background:

• Bisphenol A (BPA) is an endocrine-disrupting chemical with suspected links to various cancers.
• Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, and its environmental risk factors are not fully understood.

Purpose of the Study:

• To elucidate the molecular mechanisms by which BPA induces ccRCC.
• To identify novel candidate genes and pathways associated with BPA-induced ccRCC.
• To explore the potential of identified genes as biomarkers for ccRCC risk assessment.

Main Methods:

• Integration of multiple Gene Expression Omnibus (GEO) transcriptomic datasets.
• Differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA).
• Machine learning algorithms for core gene identification, molecular docking, single-cell RNA sequencing analysis, and in vitro validation.

Main Results:

• Four core genes (ITGB2, TBXAS1, LIPA, CLEC7A) were identified as significantly upregulated in ccRCC and associated with BPA exposure.
• Enrichment analyses revealed involvement of cell adhesion, lipid metabolism, arachidonic acid signaling, and innate immune response pathways.
• LIPA expression was elevated in kidney cancer tissues and correlated with clinical outcomes; BPA exposure promoted ccRCC progression in vitro.

Conclusions:

• BPA exposure drives ccRCC progression through specific molecular pathways and gene expression alterations.
• The identified core genes (ITGB2, TBXAS1, LIPA, CLEC7A) represent potential diagnostic and prognostic biomarkers for BPA-induced ccRCC.
• This study provides critical insights into the environmental etiology of ccRCC and highlights the need for monitoring BPA exposure.