ABCB1 Single Nucleotide Polymorphism Genotypes as Predictors of Paclitaxel-Induced Peripheral Neuropathy in Breast Cancer

Abstract

Background:

Paclitaxel is a key antineoplastic agent in the treatment of breast cancer and many other malignancies. However, paclitaxel-induced peripheral neuropathy (PIPN) is a common adverse event that occurs with paclitaxel therapy and frequently causes considerable pain and a decline in patients' quality of life. Single nucleotide polymorphisms (SNPs) in the ABCB1 gene have been frequently associated with increased severity of PIPN. However, the validity of ABCB1 SNP markers to predict the incidence of PIPN has not been confirmed.

Methods:

We extracted genomic DNA from samples collected from 92 Egyptian female breast cancer patients receiving weekly paclitaxel and used them to genotype ABCB1 G1236A (rs1128503) and ABCB1 G3435A (rs1045642). Markers that correlated with PIPN, together with baseline clinical factors, were used to fit additive, dominant, overdominant, and recessive genetic models. We applied a repeated k-fold cross-validation algorithm to select the model with the highest predictive accuracy. We finally performed model diagnostics and receiver operating characteristics (ROCs) analysis for the model with the highest classification accuracy.

Results:

The additive model achieved the highest classification accuracy. The G1236A homozygous AA variant correlated with grade ≥2 PIPN (p = 0.018). PIPN also correlated with body surface area (BSA) (p = 0.003) and history of diabetes before treatment (p = 0.015). ROCs analysis showed a sensitivity of 76.9%, a specificity of 86.8%, a positive predictive value of 83.64%, and a negative predictive value of 81.08% for the additive model.

Conclusion:

The ABCB1 G1236A, BSA, and history of diabetes are valid predictors of PIPN, which can enable the personalization of paclitaxel dosing to prevent PIPN.