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. 2024 Sep 6:15:1420174.
doi: 10.3389/fphar.2024.1420174. eCollection 2024.

Exploring pharmacokinetic variability of palbociclib in HR+/HER2- metastatic breast cancer: a focus on age, renal function, and drug-gene interactions

Elena Peruzzi  1 , Bianca Posocco  1 , Lorenzo Gerratana  2   3 , Margherita Nuti  1 , Marco Orleni  1   4 , Sara Gagno  1 , Elena De Mattia  1 , Fabio Puglisi  2   3 , Erika Cecchin  1 , Giuseppe Toffoli  1 , Rossana Roncato  1   3
Affiliations

Exploring pharmacokinetic variability of palbociclib in HR+/HER2- metastatic breast cancer: a focus on age, renal function, and drug-gene interactions

Elena Peruzzi et al. Front Pharmacol. .

Abstract

Palbociclib, an oral inhibitor of cyclin-dependent kinase 4 and 6, is approved for the treatment of metastatic breast cancer. This study investigated the influence of diverse clinical and biological factors-age, renal function, genetic variations, and concomitant medications (pharmacokinetic covariates)-on palbociclib pharmacokinetics. Employing a validated LC-MS/MS method, we analyzed the minimum plasma concentrations (Ctrough) of palbociclib in 68 women and determined the percentage deviations from the median Ctrough for each dosage group. Variations in a panel of absorption, distribution, metabolism, and excretion (ADME) genes were assessed using end-point allele-specific fluorescence detection and pyrosequencing. Two distinct patient cohorts were defined based on median values of age, creatinine, and eGFR, which exhibited statistically significant differences in percentage deviations (p = 0.0095, p = 0.0288, and p = 0.0005, respectively). Homozygous carriers of the PPARA variants displayed larger positive percentage deviations than the other group (p = 0.0292). Similarly, patients concurrently taking CYP3A and P-glycoprotein inhibitors alongside anticancer therapy exhibited significant variations (p = 0.0285 and p = 0.0334, respectively). Furthermore, exploring the drug-drug-gene interactions between inhibitors of CYP3A and P-glycoprotein with their respective genetic variants revealed two patient groups with statistically different percentage deviations (p = 0.0075, p = 0.0012, and p = 0.0191, respectively). These results could help address cases where pharmacokinetic covariates or subclinical conditions impair palbociclib adherence or response, aiming to offer tailored dosing strategies or monitoring for individual patients.

Keywords: drug-drug interactions; drug-drug-gene interactions; drug-gene interaction; metastatic breast cancer; minimum plasma concentration; palbociclib; pharmacokinetic covariate; pharmacokinetic variability.

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Conflict of interest statement

LG reports consulting or advisory roles with AstraZeneca, Daiichi Sankyo, Eli Lilly, GlaxoSmithKline, Incyte, Novartis, Pfizer, Menarini Stemmline, and AbbVie; and research funding for Menarini Silicon Biosystems. FP reports consulting or advisory roles with Roche, MSD, AstraZeneca, Novartis, Eli Lilly, Pfizer, Pierre Fabre, Daiichi Sankyo, Eisai, and Amgen, in addition to research funding from Eisai, AstraZeneca, and Roche. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

FIGURE 1
FIGURE 1
Distribution of samples based on the different dosages. The horizontal bar represents the median with the IQR, while the dots represent values of minimum plasma concentrations measured.
FIGURE 2
FIGURE 2
Associations between the clinical–biological factors recorded and the percentage deviations. The box plot depicts the median (horizontal bar) and the IQR. The dots represent the percentage deviations. Abbreviations: ns, not significant; eGFR, estimated glomerular filtration rate.
FIGURE 3
FIGURE 3
Associations between pharmacogenetic data detected and the percentage deviations calculated. Regarding CYP3A, the status of the three metabolizers was evaluated. For ABCB1, the 1236T-3435T-2677T/A haplotype was considered, and the homozygous carriers were compared with all others. Finally, homozygous carriers of both variant polymorphisms of PPARA were compared with others. The box plot depicts the median (horizontal bar) and the IQR. The dots represent the percentage deviations. Abbreviations: ns, not significant;, PM, poor metabolizer; IM, intermediate metabolizer; NM, normal metabolizer.
FIGURE 4
FIGURE 4
Distribution of percentage deviation values based on the number of concomitant medications. The box plot depicts the median (horizontal bar) and the IQR. The dots represent the percentage deviations.
FIGURE 5
FIGURE 5
Associations between inhibitors detected and the percentage deviations. The box plot depicts the median (horizontal bar) and the IQR. The dots represent the percentage deviations.
FIGURE 6
FIGURE 6
Associations between concomitant medications detected and the percentage deviation. The box plot depicts the median (horizontal bar) and the IQR. The dots represent the percentage deviations. Abbreviations: ns, not significant; PPI, proton pump inhibitor.
FIGURE 7
FIGURE 7
Associations between DDGI and the percentage deviations. The box plot depicts the median (horizontal bar) and the IQR. The dots represent the percentage deviations. Abbreviation: DDGI, drug–drug–gene interactions.
FIGURE 8
FIGURE 8
Illustration of the roles of P-gp and CYP3A in the palbociclib ADME processes. Reduced function of P-gp and CYP3A, as assessed through DDGI, can lead to increased concentrations of palbociclib in the bloodstream. Created with BioRender.com.
See this image and copyright information in PMC

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