Pharmacokinetic-pharmacodynamic modeling of the anticancer effect of erlotinib in a human non-small cell lung cancer xenograft mouse model

Wu, Qiong; Li, Mengyao; Li, Hanqing; Deng, Chonghai; Liang, Li; Zhou, Tianyan; Lu, Wei

doi:10.1038/aps.2013.101

Cited by 17 publications

(19 citation statements)

References 30 publications

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“…Among the model parameters that were identified, k TM208 is an important index of drug action being directly linked to the inhibition of tumor growth. TM208 demonstrated a similar efficacy (k TM208 of 0.349 cm 3 /week) to the published estimates of the antitumor effects of other EGFR inhibitors, such as erlotinib (0.507 cm 3 /week) [13] . The transit compartment model has often been used to characterize the delayed effects of pharmacodynamic responses in the signal transduction process [10,39] .…”

Section: Discussionsupporting

confidence: 70%

“…In current pharmaceutical research, particularly oncology investigation and anticancer drug development, a number of validated biomarkers are commonly used as efficacy endpoints to establish PD models www.nature.com/aps Ji XW et al Acta Pharmacologica Sinica npg to clarify the relationship between drug exposure and its combined effects with PK models [11,12] . Several models of EGFR as an important PD biomarker have been developed [13,14] , but few describe the time course of EGFR levels after continuous treatment and the EGFR-TKI resistance phenomenon.…”

Section: Introductionmentioning

confidence: 99%

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Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice

et al. 2016

Acta Pharmacol Sin

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Aim:The novel anticancer compound TM208 is an EGFR tyrosine kinase inhibitor (EGFR-TKI). Since the development of resistance to EGFR-TKIs is a major challenge in their clinical usage, we investigated the profiles of resistance following continuous treatment with TM208 in human breast cancer xenograft mice, and identified the relationship between the tumor pEGFR levels and tumor growth inhibition. Methods: Female BALB/c nude mice were implanted with human breast cancer MCF-7 cells, and the xenograft mice received TM208 (50 or 150 mg·kg -1 ·d -1 , ig) or vehicle for 18 d. The pharmacokinetics (PK) and pharmacodynamics (PD) of TM208 were evaluated. Results: The PK properties of TM208 were described by a one-compartment model with first-order absorption kinetics. Our study showed the inhibitory effects of TM208 on tumor pEGFR levels gradually reached a maximum effect, after which it became weaker over time, which was characterized by a combined tolerance/indirect response PD model with an estimated EC 50 (55.9 μg/L), as well as three parameters ('a' of 27.2%, 'b' of 2730%, 'c' of 0.58 h -1 ) denoting the maximum, extent and rate of resistance, respectively. The relationship between the tumor pEGFR levels and tumor growth inhibition was characterized by a combined logistic tumor growth/ transit compartment model with estimated parameters associated with tumor growth characteristics k ng (0.282 day -1 ), drug potency k TM208 (0.0499 cm 3 /day) and the kinetics of tumor cell death k 1 (0.141 day -1 ), which provided insight into drug mechanisms and behaviors. Conclusion: The proposed PK/PD model provides a better understanding of the pharmacological properties of TM208 in the treatment of breast cancer. Furthermore, simulation based on a tolerance model allows prediction of the occurrence of resistance.

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Section: Discussionsupporting

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice

et al. 2016

Acta Pharmacol Sin

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“…As demonstrated in previous works using IMS [1,2,13,[21][22][23][24], xenografts are highly heterogeneous samples, containing cells in different physiological stages. This is highlighted in the left column of Figure 1, where a representative section stained with acridine orange of each type of xenograft analyzed in the present work is shown.…”

Section: Resultsmentioning

confidence: 99%

Identification of Biomarkers of Necrosis in Xenografts Using Imaging Mass Spectrometry

Fernández

Garate

Lage

et al. 2015

J. Am. Soc. Mass Spectrom.

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Abstract. Xenografts are commonly used to test the effect of new drugs on human cancer. However, because of their heterogeneity, analysis of the results is often controversial. Part of the problem originates in the existence of tumor cells at different metabolic stages: from metastatic to necrotic cells, as it happens in real tumors. Imaging mass spectrometry is an excellent solution for the analysis of the results as it yields detailed information not only on the composition of the tissue but also on the distribution of the biomolecules within the tissue. Here, we use imaging mass spectrometry to determine the distribution of phosphatidylcholine (PC), phosphatidylethanolamine (PE), and their plasmanyl-and plasmenylether derivatives (PC-P/O and PE-P/O) in xenografts of five different tumor cell lines: A-549, NCI-H1975, BX-PC3, HT29, and U-87 MG. The results demonstrate that the necrotic areas showed a higher abundance of Na + adducts and of PC-P/O species, whereas a large abundance of PE-P/O species was found in all the xenografts. Thus, the PC/PC-ether and Na + /K + ratios may highlight the necrotic areas while an increase on the number of PEether species may be pointing to the existence of viable tumor tissues. Furthermore, the existence of important changes in the concentration of Na + and K + adducts between different tissues has to be taken into account while interpreting the imaging mass spectrometry results.

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“…For simplicity, in this work we assume that it is directly proportional to the applied drug concentration. However, pharmacodynamic/pharmacokinetic considerations could be incorporated to more accurately describe the uptake/evolution of the drug in vivo or in vitro; for example, as in [2,79,21]. …”

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confidence: 99%

A mathematical approach to differentiate spontaneous and induced evolution to drug resistance during cancer treatment

Greene

Gevertz

Sontag

2017

Preprint

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Resistance to chemotherapy is a major impediment to the successful treatment of cancer. Classically, resistance has been thought to arise primarily through random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that the progression to drug resistance need not occur randomly, but instead may be induced by the therapeutic agent itself. This process of resistance induction can be a result of genetic changes, or can occur through epigenetic alterations that cause otherwise drug-sensitive cancer cells to undergo phenotype switching. This relatively novel notion of resistance further complicates the already challenging task of designing treatment protocols that minimize the risk of developing drug resistance. In an effort to better understand resistance to treatment, we have developed a mathematical modeling framework that incorporates both random and drug-induced resistance. Our model demonstrates that the ability (or lack thereof) of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. The importance of induced resistance in treatment response led us to ask if, in our model, one can determine the resistance induction rate of a drug for a given treatment protocol. Not only could we prove that the induction parameter in our model is theoretically identifiable, we have also proposed a possible in vitro protocol which could potentially be used to determine a treatment's propensity to induce resistance. (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/235150 doi: bioRxiv preprint first posted online Dec. 15, 2017; Tumor resistance to chemotherapy and targeted drugs is a major cause of treatment failure. Both molecular and microenvironmental factors have been implicated in the development of drug resistance [34]. As an example of molecular resistance, the upregulation of drug efflux transporters can prevent sufficiently high intracellular drug accumulation, limiting treatment efficacy [31]. Other molecular causes of drug resistance include modification of drug targets, enhanced DNA damage repair mechanisms, dysregulation of apoptotic pathways, and the presence of cancer stem cells [31,17,34,78,81]. The irregular tumor vasculature which results in inconsistent drug distribution and hypoxia is an example of a microenvironmental factor that impacts drug resistance [76]. Other characteristics of the tumor microenvironment that influence drug resistance include regions of acidity, immune cell infiltration and activation, and the tumor stroma [27,76,56,15,34,55].Research continues to shed light on the multitude of factors that contribute to cancer drug resistance. Mathematical modeling studies in particular have been used to explore both broad and detailed aspects of cancer drug resistance, as reviewed in [43,7,25]. The fundamental ques...

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Pharmacokinetic-pharmacodynamic modeling of the anticancer effect of erlotinib in a human non-small cell lung cancer xenograft mouse model

Cited by 17 publications

References 30 publications

Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice

Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice

Identification of Biomarkers of Necrosis in Xenografts Using Imaging Mass Spectrometry

A mathematical approach to differentiate spontaneous and induced evolution to drug resistance during cancer treatment

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