Search: WFRF:(Guchelaar Henk Jan) >
Quantitative modeli...
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Yin, AnyueLeiden Univ, Med Ctr, Dept Clin Pharm & Toxicol, Leiden, Netherlands.
(author)
Quantitative modeling of tumor dynamics and development of drug resistance in non-small cell lung cancer patients treated with erlotinib
- Article/chapterEnglish2024
Publisher, publication year, extent ...
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John Wiley & Sons,2024
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electronicrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:uu-531579
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https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-531579URI
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https://doi.org/10.1002/psp4.13105DOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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Insight into the development of treatment resistance can support the optimization of anticancer treatments. This study aims to characterize the tumor dynamics and development of drug resistance in patients with non-small cell lung cancer treated with erlotinib, and investigate the relationship between baseline circulating tumor DNA (ctDNA) data and tumor dynamics. Data obtained for the analysis included (1) intensively sampled erlotinib concentrations from 29 patients from two previous pharmacokinetic (PK) studies, and (2) tumor sizes, ctDNA measurements, and sparsely sampled erlotinib concentrations from 18 patients from the START-TKI study. A two-compartment population PK model was first developed which well-described the PK data. The PK model was subsequently applied to investigate the exposure-tumor dynamics relationship. To characterize the tumor dynamics, models accounting for intra-tumor heterogeneity and acquired resistance with or without primary resistance were investigated. Eventually, the model assumed acquired resistance only resulted in an adequate fit. Additionally, models with or without exposure-dependent treatment effect were explored, and no significant exposure-response relationship for erlotinib was identified within the observed exposure range. Subsequently, the correlation of baseline ctDNA data on EGFR and TP53 variants with tumor dynamics' parameters was explored. The analysis indicated that higher baseline plasma EGFR mutation levels correlated with increased tumor growth rates, and the inclusion of ctDNA measurements improved model fit. This result suggests that quantitative ctDNA measurements at baseline have the potential to be a predictor of anticancer treatment response. The developed model can potentially be applied to design optimal treatment regimens that better overcome resistance.
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Veerman, G. D. MarijnErasmus MC Canc Inst, Dept Med Oncol, Rotterdam, Netherlands.
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van Hasselt, Johan G. C.Leiden Univ, Leiden Acad Ctr Drug Res LACDR, Div Syst Pharmacol & Pharm, Leiden, Netherlands.
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Steendam, Christi M. J.Erasmus MC Canc Inst, Dept Pulm Dis, Rotterdam, Netherlands.;Catharina Hosp, Dept Pulm Dis, Eindhoven, Netherlands.
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Dubbink, Hendrikus JanErasmus MC Canc Inst, Dept Pathol, Rotterdam, Netherlands.
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Guchelaar, Henk-JanLeiden Univ, Med Ctr, Dept Clin Pharm & Toxicol, Leiden, Netherlands.
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Friberg, Lena E.Uppsala universitet,Institutionen för farmaci(Swepub:uu)lenasimo
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Dingemans, Anne-Marie C.Erasmus MC Canc Inst, Dept Pulm Dis, Rotterdam, Netherlands.
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Mathijssen, Ron H. J.Erasmus MC Canc Inst, Dept Med Oncol, Rotterdam, Netherlands.
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Moes, Dirk Jan A. R.Leiden Univ, Med Ctr, Dept Clin Pharm & Toxicol, Leiden, Netherlands.;Albinusdreef 2, NL-2333 ZA Leiden, Netherlands.
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Leiden Univ, Med Ctr, Dept Clin Pharm & Toxicol, Leiden, Netherlands.Erasmus MC Canc Inst, Dept Med Oncol, Rotterdam, Netherlands.
(creator_code:org_t)
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In:CPT: John Wiley & Sons13:4, s. 612-6232163-8306
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