Modeling UGT2B7 and NR1I3 genes through multilayer network to highlight hidden link with taxane neurotoxicity

Breast cancer (BC) remains a leading global malignancy, with taxane-based treatment (TBT), including paclitaxel and docetaxel, significantly enhancing outcomes across earlystage, locally advanced, and metastatic BC. Despite its efficacy, TBT can cause severe taxane-related peripheral neurotoxicity (TrPN), which limits dosing and affects patient quality of life. TrPN is cumulative, primarily sensory, and unpredictable, with genetic predisposition playing a key role in its development. Previous pharmacogenomic (PGx) study identified five single nucleotide polymorphisms (SNPs) in the NR1I3 and UGT2B7 genes, linked to protection against severe TrPN in BC patients. ROC analysis validated these findings in an independent BC dataset. Neuroprotective effects were in patients homozygous for allele variants 2 with ultrametabolizer phenotype, which accelerates taxane inactivation and reduces treatment efficacy, potentially worsening prognosis. NR1I3 and UGT2B7 genes could serve as predictive biomarkers for TrPN and taxane bioavailability. Further network and pathway enrichment analyses (PEA) provided insights into the molecular pathways involved in TrPN and BC progression. Network analysis, a powerful tool in computational biology, integrates genomic and proteomic data to uncover drug-response mechanisms. This approach advances personalized medicine by identifying key genes and biomarkers for predicting treatment response and adverse effects, offering new therapeutic opportunities.