Fig 2: The KEGG pathway overrepresentation among the PPI networks for CYP4B1.

Fig 3: CYP4B1 gene expression in breast cancer tissues compared to that in normal breast tissues. ***: p-value <0.001.

Fig 4: Exploratory correlation analysis between CYP4B1 expression and drug sensitivity across cancer cell lines in the GDSC dataset. Bubble plot summarizing the top 30 gene–drug correlations, where each bubble represents the association between CYP4B1 mRNA expression and the half-maximal inhibitory concentration (IC50) of a drug in 860 cancer cell lines. Bubble color indicates correlation direction (red = positive correlation; blue = negative correlation), and bubble size reflects statistical significance after false discovery rate adjustment. These correlations are weak and are presented for hypothesis generation and systems-level context only, without implying therapeutic prediction or clinically relevant drug resistance. Bubble size reflects the significance of the association after false discovery rate adjustment, and bubbles outlined in black indicate statistically significant correlations (FDR ≤ 0.05).

Fig 5: CYP4B1 expression in different experimental controls. (A) Breast cancer tissue incubated with normal goat serum (negative control) displayed no immunoreactivity; (B) Breast cancer tissue incubated with CYP4B1 primary antibody developed cytoplasmic immunoreactivity; (C) Breast cancer tissue incubated with neutralized CYP4B1 primary antibody developed minimal CYP4B1 immunoreactivity; (D) Colon cancer tissue incubated with CYP4B1 primary antibody developed strong CYP4B1 immunoreactivity (positive control); and (E) Colon cancer tissue incubated with neutralized CYP4B1 primary antibody developed minimal CYP4B1 immunoreactivity. Arrows indicate representative CYP4B1-positive cells. All images were captured at ×400 magnification, Scale bar = 50 μm.