Evolution of resistance to anti-cancer therapy during general dosing schedules

Anti-cancer drugs targeted to specific oncogenic pathways have shown promising therapeutic results in the past few years; however, drug resistance remains an important obstacle for these therapies. Resistance to these drugs can emerge due to a variety of reasons including genetic or epigenetic changes which alter the binding site of the drug target, cellular metabolism or export mechanisms. Obtaining a better understanding of the evolution of resistant populations during therapy may enable the design of more effective therapeutic regimens which prevent or delay progression of disease due to resistance. In this paper, we use stochastic mathematical models to study the evolutionary dynamics of resistance under time-varying dosing schedules and pharmacokinetic effects. The populations of sensitive and resistant cells are modeled as multi-type non-homogeneous birth-death processes in which the drug concentration affects the birth and death rates of both the sensitive and resistant cell populations in continuous time. This flexible model allows us to consider the effects of generalized treatment strategies as well as detailed pharmacokinetic phenomena such as drug elimination and accumulation over multiple doses. We develop estimates for the probability of developing resistance and moments of the size of the resistant cell population. With these estimates, we optimize treatment schedules over a subspace of tolerated schedules to minimize the risk of disease progression due to resistance as well as locate ideal schedules for controlling the population size of resistant clones in situations where resistance is inevitable. Our methodology can be used to describe dynamics of resistance arising due to a single (epi)genetic alteration in any tumor type.     

Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients

Background

The advent of targeted therapy for cancer treatment has brought about a paradigm shift in the clinical management of human malignancies. Agents such as erlotinib used for EGFR-mutant non-small cell lung cancer or imatinib for chronic myeloid leukemia, for instance, lead to rapid tumor responses. Unfortunately, however, resistance often emerges and renders these agents ineffective after a variable amount of time. The FDA-approved dosing schedules for these drugs were not designed to optimally prevent the emergence of resistance. To this end, we have previously utilized evolutionary mathematical modeling of treatment responses to elucidate the dosing schedules best able to prevent or delay the onset of resistance. Here we expand on our approaches by taking into account dose-dependent mutation rates at which resistant cells emerge. The relationship between the serum drug concentration and the rate at which resistance mutations arise can lead to non-intuitive results about the best dose administration strategies to prevent or delay the emergence of resistance.

Methods

We used mathematical modeling, available clinical trial data, and different considerations of the relationship between mutation rate and drug concentration to predict the effectiveness of different dosing strategies.

Results

We designed several distinct measures to interrogate the effects of different treatment dosing strategies and found that a low-dose continuous strategy coupled with high-dose pulses leads to the maximal delay until clinically observable resistance. Furthermore, the response to treatment is robust against different assumptions of the mutation rate as a function of drug concentration.

Conclusions

For new and existing targeted drugs, our methodology can be employed to compare the effectiveness of different dose administration schedules and investigate the influence of changing mutation rates on outcomes.     

HIV drug resistance and optimization of antiviral treatment in resource-poor countries

HIV drug resistance has been associated with treatment failure in Western countries but the lessons learned can be useful in optimization of highly active antiretroviral treatment (HAART) in resource-poor settings. There is a need to improve access to HAART in such regions, but appropriate strategies must be rapidly implemented, such as adapted programs to facilitate adherence to therapy, rational use of genotypic drug resistance monitoring in specific situations, and use of alternative treatment regimens. The implications of HIV genetic diversity must also be considered in management of drug resistance.     

Three-dimensional culture models to study drug resistance in breast cancer

Despite recent advances in breast cancer treatment, drug resistance frequently presents as a challenge, contributing to a higher risk of relapse and decreased overall survival rate. It is now generally recognized that the extracellular matrix and cellular heterogeneity of the tumor microenvironment influences the cancer cells' ultimate fate. Therefore, strategies employed to examine mechanisms of drug resistance must take microenvironmental influences, as well as genetic mutations, into account. This review discusses three-dimensional (3D) in vitro model systems which incorporate microenvironmental influences to study mechanisms of drug resistance in breast cancer. These bioengineered models include spheroid-based models, biomaterial-based models such as polymeric scaffolds and hydrogels, and microfluidic chip-based models. The advantages of these model systems over traditionally studied two-dimensional tissue culture polystyrene are examined. Additionally, the applicability of such 3D models for studying the impact of tumor microenvironment signals on drug response and/or resistance is discussed. Finally, the potential of such models for use in the development of strategies to combat drug resistance and determine the most promising treatment regimen is explored.     

Exploiting the Synergy between Carboplatin and ABT-737 in the Treatment of Ovarian Carcinomas

Platinum drug-resistance in ovarian cancers mediated by anti-apoptotic proteins such as Bcl-xL is a major factor contributing to the chemotherapeutic resistance of recurrent disease. Consequently, concurrent inhibition of Bcl-xL in combination with chemotherapy may improve treatment outcomes for patients. Here, we develop a mathematical model to investigate the potential of combination therapy with ABT-737, a small molecule inhibitor of Bcl-xL, and carboplatin, a platinum-based drug, on a simulated tumor xenograft. The model is calibrated against in vivo experimental data, wherein xenografts established in mice were treated with ABT-737 and/or carboplatin on a fixed periodic schedule. The validated model is used to predict the minimum drug load that will achieve a predetermined level of tumor growth inhibition, thereby maximizing the synergy between the two drugs. Our simulations suggest that the infusion-duration of each carboplatin dose is a critical parameter, with an 8-hour infusion of carboplatin given weekly combined with a daily bolus dose of ABT-737 predicted to minimize residual disease. The potential of combination therapy to prevent or delay the onset of carboplatin-resistance is also investigated. When resistance is acquired as a result of aberrant DNA-damage repair in cells treated with carboplatin, drug delivery schedules that induce tumor remission with even low doses of combination therapy can be identified. Intrinsic resistance due to pre-existing cohorts of resistant cells precludes tumor regression, but dosing strategies that extend disease-free survival periods can still be identified. These results highlight the potential of our model to accelerate the development of novel therapeutics such as BH3 mimetics.     

Resistance to Protease Inhibitors in a Model of HIV-1 Infection with Impulsive Drug Effects

Background

The emergence of drug resistance is one of the most prevalent reasons for treatment failure in HIV therapy. This has severe implications for the cost of treatment, survival and quality of life.

Methods

We use mathematical modelling to describe the interaction between T cells, HIV-1 and protease inhibitors. We use impulsive differential equations to examine the effects of different levels of protease inhibitors in a T cell. We classify three different regimes according to whether the drug efficacy is low, intermediate or high. The model includes two strains: the wild-type strain, which initially dominates in the absence of drugs, and the mutant strain, which is the less efficient competitor, but has more resistance to the drugs.

Results

Drug regimes may take trajectories through one, two or all three regimes, depending on the dosage and the dosing schedule. Stability analysis shows that resistance does not emerge at low drug levels. At intermediate drug levels, drug resistance is guaranteed to emerge. At high drug levels, either the drug-resistant strain will dominate or, in the absence of longer-lived reservoirs of infected cells, a region exists where viral elimination could theoretically occur. We provide estimates of a range of dosages and dosing schedules where the trajectories lie either solely within a region or cross multiple regions.

Conclusion

Under specific circumstances, if the drug level is physiologically tolerable, elimination of free virus is theoretically possible. This forms the basis for theoretical control using combination therapy and for understanding the effects of partial adherence.     

A Novel Method of Drug Administration to Multiple Zebrafish (Danio rerio) and the Quantification of Withdrawal

Anxiety testing in zebrafish is often studied in combination with the application of pharmacological substances. In these studies, fish are routinely netted and transported between home aquaria and dosing tanks. In order to enhance the ease of compound administration, a novel method for transferring fish between tanks for drug administration was developed. Inserts that are designed for spawning were used to transfer groups of fish into the drug solution, allowing accurate dosing of all fish in the group. This increases the precision and efficiency of dosing, which becomes very important in long schedules of repeated drug administration. We implemented this procedure for use in a study examining the behavior of zebrafish in the light/dark test after administering ethanol with differing 21 day schedules. In fish exposed to daily-moderate amounts of alcohol there was a significant difference in location preference after 2 days of withdrawal when compared to the control group. However, a significant difference in location preference in a group exposed to weekly-binge administration was not observed. This protocol can be generalized for use with all types of compounds that are water-soluble and may be used in any situation when the behavior of fish during or after long schedules of drug administration is being examined. The light/dark test is also a valuable method of assessing withdrawal-induced changes in anxiety.     

Standing genetic variation and the evolution of drug resistance in HIV

Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. Resistance can also be transmitted between patients, but this process is not considered in the current study. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between 0 and 39%. For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation. We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-arameters which determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.     

Therapeutic strategies of dual-target small molecules to overcome drug resistance in cancer therapy

Despite some advances in targeted therapeutics of human cancers, curative cancer treatment still remains a tremendous challenge due to the occurrence of drug resistance. A variety of underlying resistance mechanisms to targeted cancer drugs have recently revealed that the dual-target therapeutic strategy would be an attractive avenue. Compared to drug combination strategies, one agent simultaneously modulating two druggable targets generally shows fewer adverse reactions and lower toxicity. As a consequence, the dual-target small molecule has been extensively explored to overcome drug resistance in cancer therapy. Thus, in this review, we focus on summarizing drug resistance mechanisms of cancer cells, such as enhanced drug efflux, deregulated cell death, DNA damage repair, and epigenetic alterations. Based upon the resistance mechanisms, we further discuss the current therapeutic strategies of dual-target small molecules to overcome drug resistance, which will shed new light on exploiting more intricate mechanisms and relevant dual-target drugs for future cancer therapeutics.     

Dosing schedule-dependent change in the disruptive effects of interferon-alpha on the circadian clock function

Altered homeostatic regulation, including the disturbance of circadian rhythms, is often observed in patients undergoing interferon (IFN) therapy. We reported previously that IFN-alpha has the ability to modulate the circadian clock function at the molecular level and that the alteration of clock function could be overcome by changing the dosing schedule. In this study, we investigated the influence of IFN-alpha on the intrinsic biological rhythms in mice by comparing two dosing schedules, continuous administration and repetitive injection. Continuous administration of IFN-alpha to mice decreased the rhythm amplitude of locomotor activity, body temperature, leukocyte counts, and plasma corticosterone levels. The treatment also suppressed the oscillation in the expression of clock genes in the liver. On the other hand, modulation effects were scarcely observed in mice treated with repetitive injection of IFN-alpha. These results indicate that treatment with IFN-alpha does not always modulate the circadian clock function. This notion was also supported by in vitro findings that the inhibitory action of IFN-alpha on the expression of clock genes was dependent on its exposure time to cells. The alteration of clock function induced by IFN-alpha could be avoided by optimizing the dosing schedule.     

生物相容透皮给药微针治疗浅表肿瘤

复杂的肿瘤微环境导致抗肿瘤药物在肿瘤组织内递送效率低下，严重阻碍了药物对浅表肿瘤的治疗效果。生物相容透皮给药微针凭借较高的机械强度，刺穿皮肤角质层，将微针内的药物递送至浅表肿瘤组织内，提高生物利用度，改善静脉注射、口服给药的肝肾毒性等问题。本文介绍了生物相容透皮给药微针的设计及其在癌症化疗、光动力治疗、光热治疗、免疫治疗、基因治疗等领域的研究进展，对浅表肿瘤的微创、局部递药和精准、高效治疗具有重要指导意义。     

Meta analysis of bioactive compounds,miRNA, siRNA and cell death regulators as sensitizers to doxorubicin induced chemoresistance

Cancer has presented to be the most challenging disease, contributing to one in six mortalities worldwide. The current treatment regimen involves multiple rounds of chemotherapy administration, alone or in combination. The treatment has adverse effects including cardiomyopathy, hepatotoxicity, and nephrotoxicity. In addition, the development of resistance to chemo has been attributed to cancer relapse and low patient overall survivability. Multiple drug resistance development may be through numerous factors such as up-regulation of drug transporters, drug inactivation, alteration of drug targets and drug degradation. Doxorubicin is a widely used first line chemotherapeutic drug for a myriad of cancers. It has multiple intracellular targets, DNA intercalation, adduct formation, topoisomerase inhibition, iron chelation, reactive oxygen species generation and promotes immune mediated clearance of the tumor. Agents that can sensitize the resistant cancer cells to the chemotherapeutic drug are currently the focus to improve the clinical efficiency of cancer therapy. This review summarizes the recent 10-year research on the use of natural phytochemicals, inhibitors of apoptosis and autophagy, miRNAs, siRNAs and nanoformulations being investigated for doxorubicin chemosensitization.

     

Effect of Duration and Intermittency of Rifampin on Tuberculosis Treatment Outcomes: A Systematic Review and Meta-Analysis

Background

Treatment regimens for active tuberculosis (TB) that are intermittent, or use rifampin during only the initial phase, offer practical advantages, but their efficacy has been questioned. We conducted a systematic review of treatment regimens for active TB, to assess the effect of duration and intermittency of rifampin use on TB treatment outcomes.

Methods and Findings

PubMed, Embase, and the Cochrane CENTRAL database for clinical trials were searched for randomized controlled trials, published in English, French, or Spanish, between 1965 and June 2008. Selected studies utilized standardized treatment with rifampin-containing regimens. Studies reported bacteriologically confirmed failure and/or relapse in previously untreated patients with bacteriologically confirmed pulmonary TB. Pooled cumulative incidences of treatment outcomes and association with risk factors were computed with stratified random effects meta-analyses. Meta-regression was performed using a negative binomial regression model. A total of 57 trials with 312 arms and 21,472 participants were included in the analysis. Regimens utilizing rifampin only for the first 1–2 mo had significantly higher rates of failure, relapse, and acquired drug resistance, as compared to regimens that used rifampin for 6 mo. This was particularly evident when there was initial drug resistance to isoniazid, streptomycin, or both. On the other hand, there was little evidence of difference in failure or relapse with daily or intermittent schedules of treatment administration, although there was insufficient published evidence of the efficacy of twice-weekly rifampin administration throughout therapy.

Conclusions

TB treatment outcomes were significantly worse with shorter duration of rifampin, or with initial drug resistance to isoniazid and/or streptomycin. Treatment outcomes were similar with all intermittent schedules evaluated, but there is insufficient evidence to support administration of treatment twice weekly throughout therapy. Please see later in the article for the Editors'' Summary     

低剂量化疗联合中药抗血管生成作用的研究进展

自从八十年代初Folkman提出肿瘤生长依赖于新血管生成的理论,抗血管生成治疗已逐渐成为肿瘤研究的热点和肿瘤治疗的新策略。对抗血管生成治疗的深入研究也使人们对许多细胞毒化疗药物的功能活性有了新的审视,近期一些国外研究表明降低化疗药物的剂量可特异地杀伤新生肿瘤血管内皮细胞,利用化疗药物的这一新靶点,采取合理的给药方式和计划,可能帮助解决常规高剂量化疗引起的毒副作用和耐药性的难题。我国传统的中医药在肿瘤诊治上已经积累了许多宝贵的经验,对这些初步筛选出采的抗肿瘤中药借助现代技术进行精细分析、模拟修饰和药理机制研究,发现我国传统中药提取物中许多有效成分显示出了抗血管生成作用,将其与低剂量化疗联合应用也显示出良好抑瘤效果,同时毒副作用小,患者生存质量提高,因此这种联合疗法为晚期肿瘤患者提供了一种新的安全有效的治疗途径,本文对目前低剂量化疗与中药联合应用的抗肿瘤血管生成机制及应用前景作一综述。     

Nonlinear system identification for prostate cancer and optimality of intermittent androgen suppression therapy

These days prostate cancer is one of the most common types of malignant neoplasm in men. Androgen ablation therapy (hormone therapy) has been shown to be effective for advanced prostate cancer. However, continuous hormone therapy often causes recurrence. This results from the progression of androgen-dependent cancer cells to androgen-independent cancer cells during the continuous hormone therapy. One possible method to prevent the progression to the androgen-independent state is intermittent androgen suppression (IAS) therapy, which ceases dosing intermittently. In this paper, we propose two methods to estimate the dynamics of prostate cancer, and investigate the IAS therapy from the viewpoint of optimality. The two methods that we propose for dynamics estimation are a variational Bayesian method for a piecewise affine (PWA) system and a Gaussian process regression method. We apply the proposed methods to real clinical data and compare their predictive performances. Then, using the estimated dynamics of prostate cancer, we observe how prostate cancer behaves for various dosing schedules. It can be seen that the conventional IAS therapy is a way of imposing high cost for dosing while keeping the prostate cancer in a safe state. We would like to dedicate this paper to the memory of Professor Luigi M. Ricciardi.     

Cancer genetic predisposition: current events and perspectives 2005

Studies performed during these last twenty years have had a major impact on the understanding of carcinogenesis. They have opened a new field : cancer genetic predisposition. At the present time, most of the cancer predispositions linked to the alteration of one gene, associated with a high risk of cancer and with a specific phenotype have been identified. About 40 genes have been identified and have led to genetic testing. The indication of genetic testing, the management of at risk patients need the establishment of guidelines. The next challenge is the identification of cancer predisposing genes associated with low risk or modifying the effect of treatment.     

The Worst Drug Rule Revisited: Mathematical Modeling of Cyclic Cancer Treatments

In drug treatments of cancer, cyclic treatment strategies are characterized by alternating applications of two (or more) different drugs, given one at a time. One of the main problems of drug treatment in cancer is associated with the generation of drug resistance by mutations of cancerous cells. We use mathematical methods to develop general guidelines on optimal cyclic treatment scheduling, with the aim of minimizing the resistance generation. We define a condition on the drugs’ potencies which allows for a relatively successful application of cyclic therapies. We find that the best strategy is to start with the stronger drug, but use longer cycle durations for the weaker drug. We further investigate the situation where a degree of cross-resistance is present, such that certain mutations cause cells to become resistant to both drugs simultaneously. We show that the general rule (best-drug-first, worst-drug-longer) is unchanged by the presence of cross-resistance. We design a systematic method to test all strategies and come up with the optimal timing and drug order. The role of various constraints in the optimal therapy design, and in particular, suboptimal treatment durations and drug toxicity, is considered. The connection with the “worst drug rule” of Day (Cancer Res. 46:3876, 1986b) is discussed.     

Correlation of in vitro and in vivo resistance development to antimicrobial agents

Preclinical in vitro and in vivo determinations of the likelihood of an antibiotic to develop resistance can and has proven predictive of their likelihood of resistance development in patients. Problematic antibiotic/bacterial species combinations are often associated with high frequencies of single-step resistance development in that species. Thus, treatment of organisms with rapid in vitro emergence of drug resistance should be monitored carefully. In vitro studies, however, are limited in predicting resistance mediated through acquisition of a resistance plasmid.The frequency of resistance development to a drug is dependent on factors such as the drug used for selections, the concentration (i.e., dosing) of the drug, the bacterium, and the site of infection. Organisms intrinsically less susceptible to an antibiotic develop resistance rapidly due to their low therapeutic ratios. Since cross-resistance often occurs within an antibiotic class, it may be desirable to initiate therapy with a drug with low resistance-selecting potential. Optimal dosing regimens are especially critical when treating bacterial species likely to develop drug resistance. Though combination drug therapies have proven affective in experimental animal infections and in man, they do not prevent resistant variants from emerging. Understanding of drug-resistance development will contribute to our management of infectious diseases.     

MicroRNAs in cancer drug resistance: Basic evidence and clinical applications

Development of drug resistance has considerably limited the efficacy of cancer treatments, including chemotherapy and targeted therapies. Hence, understanding the molecular mechanisms underpinning the innate or the acquired resistance to these therapies is critical to improve drug efficiency and clinical outcomes. Several studies have implicated microRNAs (miRNA) in this process. MiRNAs repress gene expression by specific binding to complementary sequences in the 3' region of target messenger RNAs (mRNAs), followed by target mRNA degradation or blocked translation. By targeting molecules specific to a particular pathway within tumor cells, the new generation of cancer treatment strategies has shown significant advantages over conventional chemotherapy. However, the long-term efficacy of targeted therapies often remains poor, because tumor cells develop resistance to such therapeutics. Targeted therapies often involve monoclonal antibodies (mAbs), such as those blocking the ErB/HER tyrosine kinases, epidermal growth factor receptor (cetuximab) and HER2 (trastuzumab), and those inhibiting vascular endothelial growth factor receptor signaling (e.g., bevacizumab). Even though these are among the most used agents in tumor medicine, clinical response to these drugs is reduced due to the emergence of drug resistance as a result of toxic effects in the tumor microenvironment. Research on different types of human cancers has revealed that aberrant expression of miRNAs promotes resistance to the aforementioned drugs. In this study, we review the mechanisms of tumor cell resistance to mAb therapies and the role of miRNAs therein. Emerging treatment strategies combine therapies using innovative miRNA mimics or antagonizers with conventional approaches to maximize outcomes of patients with cancer.