Modeling oxaliplatin drug delivery to circadian rhythms in drug metabolism and host tolerance

Chronotherapy of Early Colon Cancer: Advantage of Morning Dose Schedules

Colon adenomas with proliferating mutant cells may progress to invasive carcinomas. Proliferation of cells in human colorectal tissue is circadian, greater in the interval 4 to 12 hours after midnight than 16 to 24 hours after midnight. We have tested the hypothesis that chemotherapy administered during the time of greater cell proliferation will be more effective than chemotherapy administered during the time of lesser proliferation. An agent-based computer model of cell proliferation in colon crypts was calibrated with measurements of cell numbers in human biopsy specimens. It was used to simulate cytotoxic chemotherapy of an early stage of colon cancer, adenomas with about 20% of mutant cells. Chemotherapy doses were scheduled at different 4-hour intervals during the 24-hour day, and repeated at weekly intervals. Chemotherapy administered at 4 to 8 hours after midnight cured mutant cells in 100% of 50 trials with an average time to cure of 7.82 days (s.e.m. = 0.99). In contrast, chemotherapy administered at 20 to 24 hours after midnight cured only 18% of 50 trials, with the average time to cure of 23.51 days (s.e.m. = 2.42). These simulation results suggest that clinical chemotherapy of early colon cancer may be more effective when given in the morning than later in the day.

Mapping genes for drug chronotherapy

Genome-wide association studies have been increasingly used to map and characterize genes that contribute to interindividual variation in drug response. Some studies have integrated the pharmacokinetic (PK) and pharmacodynamic (PD) processes of drug reactions into association mapping, gleaning new insight into how genes determine the dynamic relationship of drug effect and drug dose. Here, we present an evolutionary framework by which two distinct concepts, chronopharmacodynamics and heterochrony (describing variation in the timing and rate of developmental events), are married to comprehend the pharmacogenetic architecture of drug response. The resulting new concept, heterochronopharmacodynamics (HCPD), can better interpret how genes influence drug efficacy and drug toxicity according to the circadian rhythm of the body and changes in drug concentration.

Prediction of the partition coefficients using QSPR modeling and simulation of paclitaxel release from the diffusion-controlled drug delivery devices

An in silico approach is proposed to first predict the partition coefficient of the model drug, paclitaxel, in different biocompatible and biodegradable polymer versus the blood plasma using artificial neural networks (ANNs) and semi-empirical quantitative structure property relationships (QSPRs). A simplified molecular-input line-entry system (SMILES) notation is used to represent the structures of the different polymers and the drug. The SMILES notation is then used to calculate the various structure-based descriptors. These descriptors are then used in the ANNs and semi-empirical QSPRs to predict the properties for a given drug-polymer device. A fluid flow model is subsequently solved to simulate the controlled drug release in the blood plasma. The effects of various parameters are also studied on the drug release profiles from these devices. The proposed approach provides a systematic framework to simulate the controlled release of the drug from the diffusion-controlled drug-polymer release systems. The developed models can be used in a reverse engineer framework to design the controlled delivery devices for a target drug release profile in near future.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation

BACKGROUND

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level.

SCOPE OF REVIEW

We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies.

MAJOR CONCLUSIONS

Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies.

GENERAL SIGNIFICANCE

Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Cancer chronotherapeutics: experimental, theoretical, and clinical aspects

The circadian timing system controls cell cycle, apoptosis, drug bioactivation, and transport and detoxification mechanisms in healthy tissues. As a consequence, the tolerability of cancer chemotherapy varies up to several folds as a function of circadian timing of drug administration in experimental models. Best antitumor efficacy of single-agent or combination chemotherapy usually corresponds to the delivery of anticancer drugs near their respective times of best tolerability. Mathematical models reveal that such coincidence between chronotolerance and chronoefficacy is best explained by differences in the circadian and cell cycle dynamics of host and cancer cells, especially with regard circadian entrainment and cell cycle variability. In the clinic, a large improvement in tolerability was shown in international randomized trials where cancer patients received the same sinusoidal chronotherapy schedule over 24h as compared to constant-rate infusion or wrongly timed chronotherapy. However, sex, genetic background, and lifestyle were found to influence optimal chronotherapy scheduling. These findings support systems biology approaches to cancer chronotherapeutics. They involve the systematic experimental mapping and modeling of chronopharmacology pathways in synchronized cell cultures and their adjustment to mouse models of both sexes and distinct genetic background, as recently shown for irinotecan. Model-based personalized circadian drug delivery aims at jointly improving tolerability and efficacy of anticancer drugs based on the circadian timing system of individual patients, using dedicated circadian biomarker and drug delivery technologies.

Optimizing cancer pharmacotherapeutics using mathematical modeling and a systems biology approach

Research in mathematics and in mathematical biology on cancer and its treatments has been soaring in the past 10 years at an unprecedented speed. Such thriving is likely due as much to new findings in fundamental biology as to an emerging general interest from mathematicians and engineers towards applications in biology and medicine and to their subsequently designed representations and predictions of tumor processes that are now allowed by modern means of computation and simulation. This article, which does not claim the status of an extended review paper on mathematical models of cancer and its treatment, is focused on modeling in a systems biology perspective. I will list here the most necessary mathematical methods, in my opinion, which, while enforcing already existing methods, should be further developed towards designing and applying optimized individualized treatments of cancer in the clinic.

Functional mapping of drug response with pharmacodynamic-pharmacokinetic principles

Recent research in pharmacogenomics has inspired our hope to predict drug response by linking it with DNA information extracted from the human genome. However, many genetic models of drug response do not incorporate biochemical principles of host-drug interactions, limiting the effectiveness of the predictive models. We argue that functional mapping, a computational tool aimed at identifying genes and genetic networks that control dynamic traits, can help explain the detailed genetic architecture of drug response by incorporating pharmacokinetic and pharmacodynamic processes. Functional mapping is particularly powerful in determining the genetic commonality and differences of drug efficacy vs. drug toxicity and drug sensitivity vs. drug resistance. We pinpoint several future directions in which functional mapping can be coupled with systems biology to unravel the genetic and metabolic machinery of drug response.

Modelling the genesis and treatment of cancer: the potential role of physiologically based pharmacodynamics

Physiologically based modelling of pharmacodynamics/toxicodynamics requires an a priori knowledge on the underlying mechanisms causing toxicity or causing the disease. In the context of cancer, the objective of the expert meeting was to discuss the molecular understanding of the disease, modelling approaches used so far to describe the process, preclinical models of cancer treatment and to evaluate modelling approaches developed based on improved knowledge. Molecular events in cancerogenesis can be detected using 'omics' technology, a tool applied in experimental carcinogenesis, but also for diagnostics and prognosis. The molecular understanding forms the basis for new drugs, for example targeting protein kinases specifically expressed in cancer. At present, empirical preclinical models of tumour growth are in great use as the development of physiological models is cost and resource intensive. Although a major challenge in PKPD modelling in oncology patients is the complexity of the system, based in part on preclinical models, successful models have been constructed describing the mechanism of action and providing a tool to establish levels of biomarker associated with efficacy and assisting in defining biologically effective dose range selection for first dose in man. To follow the concentration in the tumour compartment enables to link kinetics and dynamics. In order to obtain a reliable model of tumour growth dynamics and drug effects, specific aspects of the modelling of the concentration-effect relationship in cancer treatment that need to be accounted for include: the physiological/circadian rhythms of the cell cycle; the treatment with combinations and the need to optimally choose appropriate combinations of the multiple agents to study; and the schedule dependence of the response in the clinical situation.

Circadian Timing in Cancer Treatments

The circadian timing system is composed of molecular clocks, which drive 24-h changes in xenobiotic metabolism and detoxification, cell cycle events, DNA repair, apoptosis, and angiogenesis. The cellular circadian clocks are coordinated by endogenous physiological rhythms, so that they tick in synchrony in the host tissues that can be damaged by anticancer agents. As a result, circadian timing can modify 2- to 10-fold the tolerability of anticancer medications in experimental models and in cancer patients. Improved efficacy is also seen when drugs are given near their respective times of best tolerability, due to (a) inherently poor circadian entrainment of tumors and (b) persistent circadian entrainment of healthy tissues. Conversely, host clocks are disrupted whenever anticancer drugs are administered at their most toxic time. On the other hand, circadian disruption accelerates experimental and clinical cancer processes. Gender, circadian physiology, clock genes, and cell cycle critically affect outcome on cancer chronotherapeutics. Mathematical and systems biology approaches currently develop and integrate theoretical, experimental, and technological tools in order to further optimize and personalize the circadian administration of cancer treatments.

Identifying mechanisms of chronotolerance and chronoefficacy for the anticancer drugs 5-fluorouracil and oxaliplatin by computational modeling

We use an automaton model for the cell cycle to assess the toxicity of various circadian patterns of anticancer drug delivery so as to enhance the efficiency of cancer chronotherapy. Based on the sequential transitions between the successive phases G1, S (DNA replication), G2, and M (mitosis) of the cell cycle, the model allows us to simulate the distribution of cell cycle phases as well as entrainment by the circadian clock. We use the model to evaluate circadian patterns of administration of two anticancer drugs, 5-fluorouracil (5-FU) and oxaliplatin (l-OHP). We first consider the case of 5-FU, which exerts its cytotoxic effects on cells in S phase. We compare various circadian patterns of drug administration differing by the time of maximum drug delivery. The model explains why minimum cytotoxicity is obtained when the time of peak delivery is close to 4a.m., which temporal pattern of drug administration is used clinically for 5-FU. We also determine how cytotoxicity is affected by the variability in duration of cell cycle phases and by cell cycle length in the presence or absence of entrainment by the circadian clock. The results indicate that the same temporal pattern of drug administration can have minimum cytotoxicity toward one cell population, e.g. of normal cells, and at the same time can display high cytotoxicity toward a second cell population, e.g. of tumour cells. Thus the model allows us to uncover factors that may contribute to improve simultaneously chronotolerance and chronoefficacy of anticancer drugs. We next consider the case of oxaliplatin, which, in contrast to 5-FU, kills cells in different phases of the cell cycle. We incorporate into the model the pharmacokinetics of plasma thiols and intracellular glutathione, which interfere with the action of the drug by forming with it inactive complexes. The model shows how circadian changes in l-OHP cytotoxicity may arise from circadian variations in the levels of plasma thiols and glutathione. Corroborating experimental and clinical results, the simulations of the model account for the observation that the temporal profiles minimizing l-OHP cytotoxicity are in antiphase with those minimizing cytotoxicity for 5-FU.

Implications of circadian clocks for the rhythmic delivery of cancer therapeutics

The circadian timing system (CTS) controls drug metabolism and cellular proliferation over the 24 hour day through molecular clocks in each cell. These cellular clocks are coordinated by a hypothalamic pacemaker, the suprachiasmatic nuclei, that generates or controls circadian physiology. The CTS plays a role in cancer processes and their treatments through the downregulation of malignant growth and the generation of large and predictable 24 hour changes in toxicity and efficacy of anti-cancer drugs. The tight interactions between circadian clocks, cell division cycle and pharmacology pathways have supported sinusoidal circadian-based delivery of cancer treatments. Such chronotherapeutics have been mostly implemented in patients with metastatic colorectal cancer, the second most common cause of death from cancer. Stochastic and deterministic models of the interactions between circadian clock, cell cycle and pharmacology confirmed the poor therapeutic value of both constant-rate and wrongly timed chronomodulated infusions. An automaton model for the cell cycle revealed the critical roles of variability in circadian entrainment and cell cycle phase durations in healthy tissues and tumours for the success of properly timed circadian delivery schedules. The models showed that additional therapeutic strategy further sets the constraints for the identification of the most effective chronomodulated schedules.

Implications of circadian clocks for the rhythmic delivery of cancer therapeutics

The circadian timing system controls drug metabolism and cellular proliferation over the 24 h through molecular clocks in each cell, circadian physiology, and the suprachiasmatic nuclei--a hypothalamic pacemaker clock that coordinates circadian rhythms. As a result, both the toxicity and efficacy of over 30 anticancer agents vary by more than 50% as a function of dosing time in experimental models. The circadian timing system also down-regulates malignant growth in experimental models and possibly in cancer patients. Programmable-in-time infusion pumps and rhythmic physiology monitoring devices have made possible the application of chronotherapeutics to more than 2000 cancer patients without hospitalization. This strategy first revealed the antitumor efficacy of oxaliplatin against colorectal cancer. In this disease, international clinical trials have shown a five-fold improvement in patient tolerability and near doubling of antitumor activity through the chronomodulated, in comparison to constant-rate, delivery of oxaliplatin and 5-fluorouracil-leucovorin. Here, the relevance of the peak time, with reference to circadian rhythms, of the chemotherapeutic delivery of these cancer medications for achieving best tolerability was investigated in 114 patients with metastatic colorectal cancer and in 45 patients with non-small cell lung cancer. The incidence of severe adverse events varied up to five-fold as a function of the choice of when during the 24 h the peak dose of the medications was timed. The optimal chronomodulated schedules corresponded to peak delivery rates at 1 a.m. or 4 a.m. for 5-fluorouracil-leucovorin, at 1 p.m. or 4 p.m. for oxaliplatin, and at 4 p.m. for carboplatin. Sex of patient was an important determinant of drug schedule tolerability. This finding is consistent with recent results from a chronotherapy trial involving 554 patients with metastatic colorectal cancer, where sex also predicted survival outcome from chronotherapy, but not conventional drug delivery. Ongoing translational studies, mathematical modeling, and technology developments are further paving the way for tailoring cancer chronotherapeutics to the main rhythmic characteristics of the individual patient. Targeting therapeutic delivery to the dynamics of the cross-talk between the circadian clock, the cell division cycle, and pharmacology pathways represents a new challenge to concurrently improve the quality of life and survival of cancer patients through personalized cancer chronotherapeutics.

Chronobiology, drug delivery, and chronotherapeutics

Biological processes and functions are organized in space, as a physical anatomy, and time, as a biological time structure. The latter is expressed by short-, intermediate-, and long-period oscillations, i.e., biological rhythms. The circadian (24-h) time structure has been most studied and shows great importance to the practice of medicine and pharmacotherapy of patients. The phase and amplitude of key physiological and biochemical circadian rhythms contribute to the known predictable-in-time patterns in the occurrence of serious and life-threatening medical events, like myocardial infraction and stroke, and the manifestation and severity of symptoms of chronic diseases, like allergic rhinitis, asthma, and arthritis. Moreover, body rhythms can significantly affect responses of patients to diagnostic tests and, most important to the theme of this special issue, medications. Rhythmicity in the pathophysiology of disease is one basis for chronotherapeutics--purposeful variation in time of the concentration of medicines in synchrony with biological rhythm determinants of disease activity--to optimize treatment outcomes. A second basis is the control of undesired effects of medications, especially when the therapeutic range is narrow and the potential for adverse effects high, which is the case for cancer drugs. A third basis is to meet the biological requirements for frequency-modulated drug delivery, which is the case for certain neuroendocrine peptide analogues. Great progress has been realized with hydrogels, and they offer many advantages and opportunities in the design of chronotherapeutic systems for drug delivery via the oral, buccal, nasal, subcutaneous, transdermal, rectal, and vaginal routes. Nonetheless, innovative delivery systems will be necessary to ensure optimal application of chronotherapeutic interventions. Next generation drug-delivery systems must be configurable so they (i) require minimal volitional adherence, (ii) respond to sensitive biomarkers of disease activity that often vary in time as periodic (circadian rhythmic) and non-periodic (random) patterns to release medication to targeted tissue(s) on a real time as needed basis, and (iii) are cost-effective.

Cross-talks between circadian timing system and cell division cycle determine cancer biology and therapeutics

The circadian clock orchestrates cellular functions over 24 hours, including cell divisions, a process that results from the cell cycle. The circadian clock and cell cycle interact at the level of genes, proteins, and biochemical signals. The disruption or the reinforcement of the host circadian timing system, respectively, accelerates or slows down cancer growth through modifications of host and tumor circadian clocks. Thus, cancer cells not only display mutations of cell cycle genes but also exhibit severe defects in clock gene expression levels or 24-hour patterns, which can in turn favor abnormal proliferation. Most of the experimental research actively ongoing in this field has been driven by the original demonstration that cancer patients with poor circadian rhythms had poor quality of life and poor survival outcome independently of known prognostic factors. Further basic research on the gender dependencies in circadian properties is now warranted, because a large clinical trial has revealed that gender can largely affect the survival outcome of cancer patients on chronotherapeutic delivery. Mathematical models further show that the therapeutic index of chemotherapeutic drugs can be optimized through distinct delivery profiles, depending on the initial host/tumor status and variability in circadian entrainment and/or cell cycle length. Clinical trials and systems-biology approaches in cancer chronotherapeutics raise novel issues to be addressed experimentally in the field of biological clocks. The challenge ahead is to therapeutically harness the circadian timing system to concurrently improve quality of life and down-regulate malignant growth.