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Multiscale design of cell-type-specific pharmacokinetic/pharmacodynamic models for personalized medicine: application to temozolomide in brain tumors.

ABSTRACT: Optimizing anticancer therapeutics needs to account for variable drug responses in heterogeneous cell populations within the tumor as well as in organs of toxicity. To address cell heterogeneity, we propose a multiscale modeling approach-from in vitro to preclinical and clinical studies-to develop cell-type-specific pharmacokinetic-pharmacodynamic (PK-PD) models. A physiologically based mechanistic modeling approach integrating data from aqueous solutions, U87 glioma cells, mice, and cancer patients was utilized to characterize the brain disposition of temozolomide (TMZ), the cornerstone of chemotherapy against glioblastoma multiforme. The final model represented intracellular normal brain and brain tumor compartments in which TMZ pH-dependent conversion to the DNA-alkylating species leads to the formation of DNA adducts that serve as an entry point for a PD model. This multiscale protocol can be extended to account for TMZ PK-PD in different cell populations, thus providing a critical tool to personalize TMZ-based chemotherapy on a cell-type-specific basis.

SUBMITTER: Ballesta A

PROVIDER: S-EPMC4017092 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Multiscale design of cell-type-specific pharmacokinetic/pharmacodynamic models for personalized medicine: application to temozolomide in brain tumors.

Ballesta A A Zhou Q Q Zhang X X Lv H H Gallo J M JM

CPT: pharmacometrics & systems pharmacology 20140430

Optimizing anticancer therapeutics needs to account for variable drug responses in heterogeneous cell populations within the tumor as well as in organs of toxicity. To address cell heterogeneity, we propose a multiscale modeling approach-from in vitro to preclinical and clinical studies-to develop cell-type-specific pharmacokinetic-pharmacodynamic (PK-PD) models. A physiologically based mechanistic modeling approach integrating data from aqueous solutions, U87 glioma cells, mice, and cancer pati ...[more]

PMID: 24785551

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Project description:BackgroundIntrahepatic cholangiocarcinoma (ICC) remains one of the most intractable malignancies. The development of effective drug treatments for ICC is seriously hampered by the lack of reliable tumor models. At present, patient derived xenograft (PDX) models prove to accurately reflect the genetic and biological diversity required to decipher tumor biology and therapeutic vulnerabilities. This study was designed to investigate the establishment and potential application of PDX models for guiding personalized medicine and identifying potential biomarker for lenvatinib resistance.MethodsWe generated PDX models from 89 patients with ICC and compared the morphological and molecular similarities of parental tumors and passaged PDXs. The clinicopathologic features affecting PDX engraftment and the prognostic significance of PDX engraftment were analyzed. Drug treatment responses were analyzed in IMF-138, IMF-114 PDX models and corresponding patients. Finally, lenvatinib treatment response was examined in PDX models and potential drug resistance mechanism was revealed.ResultsForty-nine PDX models were established (take rate: 55.1%). Successful PDX engraftment was associated with negative HbsAg (P = 0.031), presence of mVI (P = 0.001), poorer tumor differentiation (P = 0.023), multiple tumor number (P = 0.003), presence of lymph node metastasis (P = 0.001), and later TNM stage (P = 0.039). Moreover, patients with tumor engraftment had significantly shorter time to recurrence (TTR) (P < 0.001) and worse overall survival (OS) (P < 0.001). Multivariate analysis indicated that PDX engraftment was an independent risk factor for shortened TTR (HR = 1.84; 95% CI, 1.05-3.23; P = 0.034) and OS (HR = 2.13; 95% CI, 1.11-4.11; P = 0.024). PDXs were histologically and genetically similar to their parental tumors. We also applied IMF-138 and IMF-114 PDX drug testing results to guide clinical treatment for patients with ICC and found similar treatment responses. PDX models also facilitated personalized medicine for patients with ICC based on drug screening results using whole exome sequencing data. Additionally, PDX models reflected the heterogeneous sensitivity to lenvatinib treatment and CDH1 might be vital to lenvatinib-resistance.ConclusionPDX models provide a powerful platform for preclinical drug discovery, and potentially facilitate the implementation of personalized medicine and improvement of survival of ICC cancer patient.

Project description:Malignant peripheral nerve sheath tumors (MPNSTs) are soft-tissue sarcomas that can arise either sporadically or in association with neurofibromatosis type 1 (NF1). These aggressive malignancies confer poor survival, with no effective therapy available. We present the generation and characterization of five distinct MPNST orthoxenograft models for preclinical testing and personalized medicine. Four of the models are patient-derived tumor xenografts (PDTX), two independent MPNSTs from the same NF1 patient and two from different sporadic patients. The fifth model is an orthoxenograft derived from an NF1-related MPNST cell line. All MPNST orthoxenografts were generated by tumor implantation, or cell line injection, next to the sciatic nerve of nude mice, and were perpetuated by 7-10 mouse-to-mouse passages. The models reliably recapitulate the histopathological properties of their parental primary tumors. They also mimic distal dissemination properties in mice. Human stroma was rapidly lost after MPNST engraftment and replaced by murine stroma, which facilitated genomic tumor characterization. Compatible with an origin in a catastrophic event and subsequent genome stabilization, MPNST contained highly altered genomes that remained remarkably stable in orthoxenograft establishment and along passages. Mutational frequency and type of somatic point mutations were highly variable among the different MPNSTs modeled, but very consistent when comparing primary tumors with matched orthoxenografts generated. Unsupervised cluster analysis and principal component analysis (PCA) using an MPNST expression signature of ~1,000 genes grouped together all primary tumor-orthoxenograft pairs. Our work points to differences in the engraftment process of primary tumors compared with the engraftment of established cell lines. Following standardization and extensive characterization and validation, the orthoxenograft models were used for initial preclinical drug testing. Sorafenib (a BRAF inhibitor), in combination with doxorubicin or rapamycin, was found to be the most effective treatment for reducing MPNST growth. The development of genomically well-characterized preclinical models for MPNST allowed the evaluation of novel therapeutic strategies for personalized medicine.

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Multiscale design of cell-type-specific pharmacokinetic/pharmacodynamic models for personalized medicine: application to temozolomide in brain tumors.

Publications

Multiscale design of cell-type-specific pharmacokinetic/pharmacodynamic models for personalized medicine: application to temozolomide in brain tumors.

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