Quantitative modeling of tumor dynamics and development of drug resistance in non-small cell lung cancer patients treated with erlotinib

Abstract

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.

FIGURE 1

Graphical structure of the tumor dynamics model.

FIGURE 2

VPC of the developed population PK model. The blue dashed lines represent 95th and 5th percentiles of the observations, the red dashed line represents the 50th percentile of the observations, the blue shaded areas represent 95% confidence interval of the 95th and 5th percentiles based on the simulations respectively, and the red shaded area represents 95% confidence interval of the 50th percentile based on the simulations. VPC, visual predictive check; PK, pharmacokinetic.

FIGURE 3

VPC considering dropout of the developed tumor dynamics model. The blue dashed lines represent 95th and 5th percentiles of the observations, the red dashed line represents the 50th percentile of the observations, the blue shaded areas represent 95% confidence interval of the 95th and 5th percentiles based on the simulations respectively, and the red shaded area represents 95% confidence interval of the 50th percentile based on the simulations. VPC, visual predictive check.

FIGURE 4

Parameter estimates from the tumor dynamics model versus baseline plasma circulating tumor DNA (ctDNA) measurements on primary mutant EGFR variant allele frequency and TP53 mutation. VAF, variant allele frequency.