Integrating multi-omics and machine learning to decipher the molecular pathways of bisphenol a-associated lactylation-related genes driving bladder cancer.

PPI enrichment analysis was highly significant (P < 1.0e-16; Fig 5B ), indicating that the observed interaction density was greater than expected by chance and suggesting coordinated involvement of these genes in bladder cancer–related pathways.

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Further survival analysis showed that only high ENO1 expression was significantly associated with poorer overall survival in the TCGA-BLCA cohort (HR = 1.367, 95% CI: 1.019–1.834, P = 0.037), whereas the other three genes did not reach statistical significance in Cox regression ( Fig 9K ).

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Most intersecting genes showed a trend toward higher expression in tumor tissues, and several genes, including EAF1, UPF1, KHDRBS1, and SP3L, were markedly upregulated in the tumor group ( Fig 5A ), indicating preferential upregulation of these genes in bladder cancer tissues.

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