Epigenetic instability may alter cell state transitions and anticancer drug resistance.

Drug resistance is a significant obstacle to successful and durable anti-cancer therapy. Targeted therapy is often effective during early phases of treatment; however, eventually cancer cells adapt and transition to drug-resistant cells states rendering the treatment ineffective. It is proposed that cell state can be a determinant of drug efficacy and manipulated to affect the development of anticancer drug resistance. In this work, we developed two stochastic cell state models and an integrated stochastic-deterministic model referenced to brain tumors. The stochastic cell state models included transcriptionally-permissive and -restrictive states based on the underlying hypothesis that epigenetic instability mitigates lock-in of drug-resistant states. When moderate epigenetic instability was implemented the drug-resistant cell populations were reduced, on average, by 60%, whereas a high level of epigenetic disruption reduced them by about 90%. The stochastic-deterministic model utilized the stochastic cell state model to drive the dynamics of the DNA repair enzyme, methylguanine-methyltransferase (MGMT), that repairs temozolomide (TMZ)-induced O6-methylguanine (O6mG) adducts. In the presence of epigenetic instability, the production of MGMT decreased that coincided with an increase of O6mG adducts following a multiple-dose regimen of TMZ. Generation of epigenetic instability via epigenetic modifier therapy could be a viable strategy to mitigate anticancer drug resistance.

Inhibition of HIPK2 Alleviates Thoracic Aortic Disease in Mice With Progressively Severe Marfan Syndrome.

Objective: Despite considerable research, the goal of finding nonsurgical remedies against thoracic aortic aneurysm and acute aortic dissection remains elusive. We sought to identify a novel aortic PK (protein kinase) that can be pharmacologically targeted to mitigate aneurysmal disease in a well-established mouse model of early-onset progressively severe Marfan syndrome (MFS). Approach and Results: Computational analyses of transcriptomic data derived from the ascending aorta of MFS mice predicted a probable association between thoracic aortic aneurysm and acute aortic dissection development and the multifunctional, stress-activated HIPK2 (homeodomain-interacting protein kinase 2). Consistent with this prediction, Hipk2 gene inactivation significantly extended the survival of MFS mice by slowing aneurysm growth and delaying transmural rupture. HIPK2 also ranked among the top predicted PKs in computational analyses of DEGs (differentially expressed genes) in the dilated aorta of 3 MFS patients, which strengthened the clinical relevance of the experimental finding. Additional in silico analyses of the human and mouse data sets identified the TGF (transforming growth factor)-ß/Smad3 signaling pathway as a potential target of HIPK2 in the MFS aorta. Chronic treatment of MFS mice with an allosteric inhibitor of HIPK2-mediated stimulation of Smad3 signaling validated this prediction by mitigating thoracic aortic aneurysm and acute aortic dissection pathology and partially improving aortic material stiffness. Conclusions: HIPK2 is a previously unrecognized determinant of aneurysmal disease and an attractive new target for antithoracic aortic aneurysm and acute aortic dissection multidrug therapy.

The effect of ABCG2 and ABCC4 on the pharmacokinetics of methotrexate in the brain.

Methotrexate (MTX) is the cornerstone of chemotherapy for primary central nervous system lymphoma, yet how the blood-brain barrier (BBB) efflux transporters ABCG2 and ABCC4 influence the required high-dose therapy is unknown. To evaluate their role, we used four mouse strains, C57BL/6 (wild-type; WT), Abcg2(-/-), Abcc4(-/-), and Abcg2(-/-);Abcc4(-/-) (double knockout; DKO) to conduct brain microdialysis studies after single intravenous MTX doses of 50 mg/kg. When the area under the concentration-time curve for plasma (AUC(plasma)) was used to assess systemic exposure to MTX, the rank order was Abcc4(-/-) < WT < Abcg2(-/-) < Abcg2(-/-)Abcc4(-/-). Only the DKO exposure was significantly higher than that of the WT group (P < 0.01), a reflection of the role of Abcg2 in biliary excretion and Abcc4 in renal excretion. MTX brain interstitial fluid concentrations obtained by microdialysis were used to calculate the area under the concentration-time curve for the brain (AUC(brain)), which found the rank order of exposure to be WT < Abcc4(-/-) < Abcg2(-/-) < Abcg2(-/-)Abcc4(-/-) with the largest difference being 4-fold: 286.13 ± 130 µg*min/ml (DKO) versus 66.85 ± 26 (WT). Because the transporters affected the systemic disposition of MTX, particularly in the DKO group, the ratio of the AUC(brain)/AUC(plasma) or the brain/plasma partition coefficient Kp was calculated, revealing that the DKO strain had a significantly higher value (0.23 ± 0.09) than the WT strain (0.11 ± 0.05). Both Abcg2 and Abcc4 limited BBB penetration of MTX; however, only when both drug efflux pumps were negated did the brain accumulation of MTX significantly increase. These findings indicate a contributory role of both ABCG2 and ABCC4 to limiting MTX distribution in patients.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions.

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions.

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte- like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

Multiscale mapping of transcriptomic signatures for cardiotoxic drugs.

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focus on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced-pluripotent-stem-cell-derived cardiomyocytes, using bulk transcriptomic profiles. We use singular value decomposition to identify drug-selective patterns across cell lines obtained from multiple healthy human subjects. Cellular pathways affected by cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to published single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Integration of transcriptomic outlier analysis with whole genomic sequencing of our six cell lines enables us to correctly reidentify a genomic variant causally linked to anthracycline-induced cardiotoxicity and predict genomic variants potentially associated with TKI-induced cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale signatures for cardiotoxicity that could be used for drug development and patient stratification.

Cell state-directed therapy - epigenetic modulation of gene transcription demonstrated with a quantitative systems pharmacology model of temozolomide.

Cancer therapy continues to be plagued by modest therapeutic advances. This is particularly evident in glioblastoma multiforme (GBM) wherein treatment failures are attributed to intratumoral heterogeneity (ITH), a dynamic process of cell state transitions or plasticity. To address ITH, we introduce the concept of cell state-directed (CSD) therapy through a quantitative systems pharmacology model of temozolomide (TMZ), a cornerstone of GBM drug therapy. The model consisting of multiple modules incorporated an epigenetic-based gene transcription-translation module that enabled CSD therapy. Numerous model simulations were conducted to demonstrate the potential impact of CSD therapy on TMZ activity. The simulations included those based on global sensitivity analyses to identify fragile nodes - MDM2 and XIAP - in the network, and also how an epigenetic modifier (birabresib) could overcome a mechanism of TMZ resistance. The positive results of CSD therapy on TMZ activity supports continued efforts to develop CSD therapy as a new anticancer approach.

Activation of alternate prosurvival pathways accounts for acquired sunitinib resistance in U87MG glioma xenografts.

Acquired drug resistance represents a major obstacle to using sunitinib for the treatment of solid tumors. Here, we examined the cellular and molecular alterations in tumors that are associated with acquired brain tumor resistance to sunitinib by using an in vivo model. U87MG tumors obtained from nude mice that received sunitinib (40 mg/kg/day) for 30 days were classified into sunitinib-sensitive and -resistant groups based on tumor volume and underwent targeted gene microarray and protein array analyses. The expression of several angiogenesis-associated genes was significantly modulated in sunitinib-treated tumors compared with those in control tumors (p<0.05), whereas no significant differences were observed between sunitinib-sensitive and -resistant tumors (p>0.05). Tumor vasculature based on microvessel density, neurogenin 2 chondroitin sulfate proteoglycan density, and α-smooth muscle actin density was also similar in sunitinib-treatment groups (p>0.05). The moderate increase in unbound sunitinib tumor-to-plasma area-under-the-curve ratio in sunitinib-resistant mice was accompanied by up-regulated ATP-binding cassette G2 expression in tumor. The most profound difference between the sunitinib-sensitive and -resistant groups was found in the expression of several phosphorylated proteins involved in intracellular signaling. In particular, phospholipase C-γ1 phosphorylation in sunitinib-resistant tumors was up-regulated by 2.6-fold compared with that in sunitinib-sensitive tumors (p<0.05). In conclusion, acquired sunitinib resistance in U87MG tumors is not associated with revascularization in tumors, but rather with the activation of alternate prosurvival pathways involved in an escape mechanism facilitating tumor growth and possibly insufficient drug uptake in tumor cells caused by an up-regulated membrane efflux transporter.

Screening candidate anticancer drugs for brain tumor chemotherapy: pharmacokinetic-driven approach for a series of (E)-N-(substituted aryl)-3-(substituted phenyl)propenamide analogues.

A pharmacokinetic [PK]-driven screening process was implemented to select new agents for brain tumor chemotherapy from a series of low molecular weight anticancer agents [ON27x] that consisted of 141 compounds. The screening procedures involved a combination of in silico, in vitro and in vivo mouse studies that were cast into a pipeline of tier 1 and tier 2 failures that resulted in a final investigation of 2 analogues in brain tumor-bearing mice. Tier 1 failures included agents with a molecular weight of > 450 Da, a predicted log P (log P) of either <2 or > 3.5, and a cytotoxicity IC(50) value of > 2 uM. Next, 18 compounds underwent cassette dosing studies in normal mice that identified compounds with high systemic clearance, and low blood-brain barrier [BBB] penetration. These indices along with a derived parameter, referred to as the brain exposure index, comprised tier 2 failures that led to the administration of 2 compounds [ON27570, ON27740] as single agents [discrete dosing] to mice bearing intracerebral tumors. Comparison of ON27570's resultant PK parameters to those obtained in the cassette dosing format suggested a drug-drug interaction most likely at the level of BBB transport, and prompted the use of the in vitro MDCK-MDR1 transport model to help assess the nature of the discrepancy. Overall, the approach was able to identify candidate compounds with suitable PK characteristics yet further revisions to the method, such as the use of in vitro metabolism and transport assays, may improve the PK-directed approach to identify efficacious agents for brain tumor chemotherapy.

Preclinical pharmacokinetic and pharmacodynamic evaluation of novel anticancer agents, ON01910.Na (Rigosertib, Estybon™) and ON013105, for brain tumor chemotherapy.

PURPOSE: To evaluate a mitotic inhibitor, ON01910.Na, as a potential chemotherapeutic agent for brain tumors using a series of PK/PD studies, which led to the evaluation of its structural analog, ON013105, a prodrug of the more lipophilic product, ON013100. METHODS: Systemic PK characterization of ON01910 and ON013105 was completed in healthy mice. Using an orthotopic U87 glioma mouse model, brain and brain tumor distribution under steady-state conditions were evaluated for ON01910.Na and ON013105/ON013100; anticancer potential following a multiple-dose schedule of 250 mg/kg/day IP for 7 days was evaluated for ON01910.Na. RESULTS: ON01910 exhibited low brain and brain tumor distribution with quasi-steady-state brain/plasma (Css(brain)/Css(plasma)) and brain tumor/plasma (Css(brain tumor)/Css(plasma)) concentration ratios of 0.03 ± 0.02 and 0.14 ± 0.08, respectively. Significant antiangiogenic potential and antiproliferative capacity of ON01910 in the intracerebral model was absent. ON013100 showed high brain and brain tumor penetration with Css(brain)/Css(plasma) and Css(brain tumor)/Css(plasma) ratios of 0.92 ± 0.26 and 1.35 ± 0.40, respectively; its prodrug ON013105 showed negligible brain and brain tumor penetration. CONCLUSIONS: ON013105, not ON01910.Na, was identified as a potential anticancer drug candidate for further investigation in brain tumor chemotherapy based on the properties of ON013100.

Educational Needs for Quantitative Systems Pharmacology Scientists.

There is a demand for scientists trained in quantitative systems pharmacology (QSP) that has yet to be met by changes in graduate education. The multidisciplinary nature of QSP is not unlike its predecessor, pharmacokinetics (PKs) and pharmacodynamics (PDs) that have now become firmly established in many educational programs. A hindrance to the evolution of educational programs for QSP is explored and suggestions to move QSP into its proper position as a unique discipline are presented.

Dose-dependent disposition of methotrexate in Abcc2 and Abcc3 gene knockout murine models.

Methotrexate (MTX) is a substrate for numerous human ATP-binding cassette (ABC) efflux transporters, yet the impact of these transporters on MTX pharmacokinetics (PK) over a large dose range has not been examined. To investigate the effects of two transporters-ABC subfamily C member 2 (Abcc2; multidrug resistance protein 2) and ABC subfamily C member 3 (Abcc3; multidrug resistance protein 3)-involved in MTX hepatobiliary disposition in vivo, MTX plasma, urine, and feces concentrations were analyzed after 10, 50, and 200 mg/kg i.v. doses to groups of wild type (WT), Abcc2(-/-), and Abcc3(-/-) mice. The absence of Abcc2 caused a decrease in total clearance of MTX relative to WT mice at all dose levels yet was accompanied by compensatory increases in renal excretion and metabolism to 7-hydroxymethotrexate (7OH-MTX). In Abcc3(-/-) mice, total clearance was elevated at the two lower dose levels and was attributed to stimulation of biliary excretion and confirmed by elevated fecal excretion; however, at the high 200 mg/kg dose, clearance was severely retarded and could be attributed to hepatotoxicity because conversion to 7OH-MTX was diminished. The findings confirmed that both Abcc2 and Abcc3 significantly influenced the PK properties of MTX, and depending on the MTX dose and strain, alternate elimination pathways were elicited and saturable.

Hybrid physiologically-based pharmacokinetic model for remdesivir: Application to SARS-CoV-2.

A novel coronavirus, severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) or coronavirus disease 2019 (COVID-19), has caused a pandemic that continues to cause catastrophic health and economic carnage and has escalated the identification and development of antiviral agents. Remdesivir (RDV), a prodrug and requires intracellular conversions to the active triphosphate nucleoside (TN) has surfaced as an active anti-SARS-CoV-2 drug. To properly design therapeutic treatment regimens, it is imperative to determine if adequate intracellular TN concentrations are achieved in target tissues, such as the lungs. Because measurement of such concentrations is unrealistic in patients, a physiologically-based pharmacokinetic (PBPK) model was developed to characterize RDV and TN disposition. Specifically, a hybrid PBPK model was developed based on previously reported data in humans. The model represented each tissue as a two-compartment model-both extracellular and intracellular compartment wherein each intracellular compartment contained a comprehensive metabolic model to the ultimate active metabolite TN. Global sensitivity analyses and Monte-Carlo simulations were conducted to assess which parameters and how highly sensitive ones impacted peripheral blood mononuclear cells and intracellular lung TN profiles. Finally, clinical multiple-dose regimens indicated that minimum lung intracellular TN concentrations ranged from ~ 9 uM to 4 uM, which suggest current regimens are effective based on in vitro half-maximal effective concentration values. The model can be used to explore tissue drug disposition under various conditions and regimens, and expanded to pharmacodynamic models.

Translocator protein (TSPO) ligand-Ara-C (cytarabine) conjugates as a strategy to deliver antineoplastic drugs and to enhance drug clinical potential.

The aim of this work was to evaluate TSPO ligand-Ara-C conjugation as an approach for the selective delivery of the antineoplastic agent to brain tumors as well as for overcome P-gp resistance induction observed for the majority of cytotoxic agents, enhancing the drug clinical potential. To this end, the novel N-imidazopyridinacetyl-Ara-C conjugates 3a-c, 10 and 15 have been prepared and evaluated for their cytotoxicity against glioma cell lines. In contrast to that observed for 3a-c and 10, the conjugate 15 resulted stable in both phosphate buffer and physiological medium. In all cases, the release of free Ara-C from hydrolyzed conjugates was checked by HPLC and ESI-MS analysis. Conjugates 10 and 15 displayed very high in vitro TSPO affinity and selectivity, and, hence, they may possess potential for targeted brain delivery. Due to the favorable features displayed by the conjugate 15, it was further evaluated on glioma cell lines, expressing high levels of TSPO, in the presence and in the absence of specific nucleoside transport (NT) inhibitors. In contrast to that observed for the free Ara-C, the presence of NT inhibitors did not reduce the cytotoxic activity of 15. Moreover, conjugate 15, as N(4)-acyl derivative of Ara-C, should be resistant to inactivation by cytidine deaminase, and it may possess enhanced propensity to target brain tumor cells characterized by a reduced expression of NTs. In addition, this conjugate behaves as a clear P-gp modulator and thereby may be useful to reverse MDR. Transport studies across the MDCKII-MDR1 monolayer indicated that conjugate 15 should overcome the BBB by transcellular pathway. All these features may be useful for enhancing the clinical potential of the nucleoside drug Ara-C.

Predicting In Vivo Efficacy from In Vitro Data: Quantitative Systems Pharmacology Modeling for an Epigenetic Modifier Drug in Cancer.

Reliably predicting in vivo efficacy from in vitro data would facilitate drug development by reducing animal usage and guiding drug dosing in human clinical trials. However, such prediction remains challenging. Here, we built a quantitative pharmacokinetic/pharmacodynamic (PK/PD) mathematical model capable of predicting in vivo efficacy in animal xenograft models of tumor growth while trained almost exclusively on in vitro cell culture data sets. We studied a chemical inhibitor of LSD1 (ORY-1001), a lysine-specific histone demethylase enzyme with epigenetic function, and drug-induced regulation of target engagement, biomarker levels, and tumor cell growth across multiple doses administered in a pulsed and continuous fashion. A PK model of unbound plasma drug concentration was linked to the in vitro PD model, which enabled the prediction of in vivo tumor growth dynamics across a range of drug doses and regimens. Remarkably, only a change in a single parameter-the one controlling intrinsic cell/tumor growth in the absence of drug-was needed to scale the PD model from the in vitro to in vivo setting. These findings create a framework for using in vitro data to predict in vivo drug efficacy with clear benefits to reducing animal usage while enabling the collection of dense time course and dose response data in a highly controlled in vitro environment.

Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity.

Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood, and its prediction remains challenging. We obtain transcriptional profiles of human heart-derived primary cardiomyocyte like cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with the cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.

Differential effect of sunitinib on the distribution of temozolomide in an orthotopic glioma model.

Normalization of tumor vasculature by antiangiogenic agents may improve the delivery of cytotoxic drugs to the tumor, leading to more effective therapy. In this study, we used pharmacokinetic and pharmacodynamic approaches to investigate how sunitinib at different dose levels affects brain distribution of temozolomide (TMZ), and to ascertain the relationship between intratumoral TMZ concentrations and tumor vascularity in an orthotopic human glioma model. Three groups of intracerebral U87MG tumor-bearing mice were given either vehicle or sunitinib at 20 mg/kg or 60 mg/kg per day for 7 days before receiving a steady-state regimen of TMZ that consisted of an intravenous bolus and a 3-h intraarterial infusion. TMZ concentrations in plasma, normal brain, and brain tumor were determined, and several biomarkers related to the antiangiogenic activity of sunitinib were examined. TMZ distribution in the normal brain as indicated by the brain-to-plasma steady-state TMZ concentration ratios was analogous across the three treatment groups. The brain tumor-to-plasma steady-state TMZ concentration (ss C(t)/C(p)) ratio was significantly increased in the 20 mg/kg sunitinib group (0.98 +/- 0.17) compared with the control (0.76 +/- 0.17) and 60 mg/kg sunitinib (0.68 +/- 0.09) groups. The ss C(t)/C(p) ratios were significantly correlated with the vascular normalization index (VNI), derived from the expression of CD31, collagen IV, and alpha-smooth muscle actin, which represents the fraction of functioning vessels out of the total tumor vessels. In conclusion, the effect of sunitinib on the brain tumor distribution of TMZ was dose dependent and indicated that optimal tumor exposure was achieved at a lower dose and was associated with the VNI.

Impact of angiogenesis inhibition by sunitinib on tumor distribution of temozolomide.

PURPOSE: As combination chemotherapy of antiangiogenic agents with conventional chemotherapeutic drugs continues to evolve, an understanding of the pharmacokinetic and pharmacodynamic variables associated with optimal treatment is needed. Thus, the effect of the multitargeted tyrosine kinase inhibitor sunitinib on tumor distribution of temozolomide was investigated to evaluate conditions for optimal combination chemotherapy. EXPERIMENTAL DESIGN: In mice bearing SF188V+ human glioma xenografts, measurements of temozolomide pharmacokinetic properties and sunitinib pharmacodynamic activities were evaluated, the latter including determinants for vascular normalization, including CD31, collagen IV, and alpha-SMA. RESULTS: Sunitinib given in a daily dose of either 10 or 40 mg/kg orally over 14 days increased temozolomide tumor distribution, as indicated by the tumor-to-plasma AUC ratio compared with control; however, only the 10 mg/kg group reached statistical significance (P < 0.05). From the pharmacodynamic analysis, a "vascular normalization index" incorporating the microvessel density (MVD) and protein expression of alpha-SMA and collagen IV was proposed as an indication of the number of tumor vessels with relatively good quality, which was found to be significantly correlated with the unbound temozolomide AUC in tumor interstitial fluid (P = 0.05). Furthermore, both sunitinib-treated groups maintained the molecular balance between angiopoietins Ang-1 and Ang-2, suggesting a critical role of angiopoietins in vascular normalization. CONCLUSIONS: Several important factors relevant to the antiangiogenic agent-induced tumor vascular normalization have been identified and incorporated into a vascular normalization index that may serve to correlate the angiogenic phenotype to the distribution of cytotoxic drugs in solid tumors.

Multidrug resistance protein 4 protects bone marrow, thymus, spleen, and intestine from nucleotide analogue-induced damage.

Nucleoside-based analogues are mainstays in the treatment of cancer, viral infections, and inflammatory diseases. Recent studies showing that the ATP-binding cassette transporter, multidrug resistance protein 4, is able to efflux nucleoside and nucleotide analogues from transfected cells suggests that the pump may affect the efficacy of this class of agents. However, the in vivo pharmacologic functions of the pump are largely unexplored. Here, using Mrp4(-/-) mice as a model system, and the nucleotide analogue, 9'-(2'-phosphonylmethoxyethyl)-adenine (PMEA) as a probe, we investigate the ability of Mrp4 to function in vivo as an endogenous resistance factor. In the absence of alterations in plasma PMEA levels, Mrp4-null mice treated with PMEA exhibit increased lethality associated with marked toxicity in several tissues. Affected tissues include the bone marrow, spleen, thymus, and gastrointestinal tract. In addition, PMEA penetration into the brain is increased in Mrp4(-/-) mice. These findings indicate that Mrp4 is an endogenous resistance factor, and that the pump may be a component of the blood-brain barrier for nucleoside-based analogues. This is the first demonstration that an ATP-binding cassette transporter can affect in vivo tissue sensitivity towards this class of agents.