Pilot Study on the Impact of Polymorphisms Linked to Multi-Kinase Inhibitor Metabolism on Lenvatinib Side Effects in Patients with Advanced Thyroid Cancer

Author:

Cantara Silvia12ORCID,Dalmiglio Cristina1,Marzocchi Carlotta1ORCID,Sagnella Alfonso1ORCID,Brilli Lucia1,Trimarchi Andrea1ORCID,Maino Fabio1,Valerio Laura1ORCID,Castagna Maria Grazia1

Affiliation:

1. Department of Medical, Surgical and Neurological Sciences, University of Siena, 53100 Siena, Italy

2. Laboratory of Clinical and Translational Research, AOU Siena, 53100 Siena, Italy

Abstract

Multi-kinase inhibitors (MKIs) represent the best therapeutic option in advanced thyroid cancer patients. The therapeutic efficacy and toxicity of MKIs are very heterogeneous and are difficult to predict before starting treatment. Moreover, due to the development of severe adverse events, it is necessary to interrupt the therapy some patients. Using a pharmacogenetic approach, we evaluated polymorphisms in genes coding for proteins involved with the absorption and elimination of the drug in 18 advanced thyroid cancer patients treated with lenvatinib, and correlated the genetic background with (1) diarrhea, nausea, vomiting and epigastric pain; (2) oral mucositis and xerostomia; (3) hypertension and proteinuria; (4) asthenia; (5) anorexia and weight loss; (6) hand foot syndrome. Analyzed variants belong to cytochrome P450 (CYP3A4 rs2242480 and rs2687116 and CYP3A5 rs776746) genes and to ATP-binding cassette transporters (ABCB1 rs1045642, rs2032582 and rs2235048 and ABCG2 rs2231142). Our results suggest that the GG genotype for rs2242480 in CYP3A4 and CC genotype in rs776746 for CYP3A5 were both associated with the presence of hypertension. Being heterozygous for SNPs in the ABCB1 gene (rs1045642 and 2235048) implicated a higher grade of weight loss. The ABCG2 rs2231142 statistically correlated with a higher extent of mucositis and xerostomia (CC genotype). Heterozygous and rare homozygous genotypes for rs2242480 in CYP3A4 and for rs776746 for CYP3A5 were found to be statistically linked to a worse outcome. Evaluating the genetic profile before starting lenvatinib treatment may help to predict the occurrence and grade of some side effects, and may contribute to improving patient management.

Funder

PRIN

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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