Administration of temozolomide: Comparison of conventional and metronomic chemotherapy regimens

Dose-dependent bidirectional pharmacological effects of vinorelbine-based metronomic combination chemotherapy on tumor growth and metastasis and mechanisms in melanoma mouse model

BACKGROUND

There is evidence that the empirical setting of doses and schedules of antineoplastic agents in metronomic chemotherapy (MC) might lead to undesirable outcomes, such as promoting tumor growth or metastasis at certain low doses. However, details about the dose effect of antineoplastic agents in MC have not been fully known yet.

OBJECTIVES

Vinorelbine combined with cisplatin or fluorouracil (VNR/CDDP or VNR/FU) was selected to investigate its effects on tumor growth or metastasis as well as mechanisms.

METHODS

Experimental techniques, including immunohistochemistry, western blot, immunofluorescence, and flow cytometry, were used to explore the mechanisms, along with cell proliferation, apoptosis, migration, and invasion.

RESULTS

The results showed that VNR/CDDP or VNR/FU promoted tumor growth and metastasis at low doses and inhibited them at high ones. Except that expressions of apoptotic proteins were elevated at both low and high doses, low-dose treatments enhanced angiogenesis and promoted the mobilization and recruitment of myeloid-derived suppressor cells (MDSCs), while high-dose treatments reversed these effects. Additionally, low concentrations of VNR/CDDP or VNR/FU stimulated tumor cell functions such as anti-apoptosis, migration, and invasion, but high concentrations only suppressed cell proliferation and increased apoptosis.

CONCLUSION

This study elucidated a bidirectional action mode regulated by multiple mechanisms at different doses in MC and also highlighted the risks of low-dose metronomic administration of antineoplastic agents in the clinic. More preclinical and clinical studies focusing on the dose-effect of metronomic regimens are urgently needed because an effective therapeutic regimen should be an optimal setting of drugs, doses, schedules, or combinations.

Evaluation of the pharmacological activity of hybrid organotin compounds in a B16 melanoma model in the classical and metronomic administration modes

Introduction: In modern medical chemistry, much attention is paid to the search for new antimetastatic agents based on metal compounds. Organotin compounds promise to be good candidates as the treatment of malignant neoplasms. In order to reduce a possible nonspecific toxic effect of tin compounds and to expand the intended therapeutic use, the paper presents hybrid tin (IV) complexes with Sn-S bond containing a fragment of 2,6-di-tert-butylphenol. The aim of the study was to evaluate the antitumor and antimetastatic effects of bis (3,5-di-tert-butyl-4-hydroxyphenylthiolate) dimethylolol (Me3) and (3,5-di-tert-butyl-4-hydroxyphenylthiolate) triphenylolol (Me5) in a model of transplanted melanoma tumor in B16 mice in classical and metronomic administration mode.

Materials and methods: The efficacy of organotin compounds was studied in a model of a transplanted tumor with spontaneous metastasis of C57Bl/6 (female) melanoma B16 mice using the following indicators: average life expectancy, inhibition of tumor growth by weight, tumor mass, and metastasis inhibition index.

Results and discussion: The most pronounced antimetastatic effect (54% and 36%) is achieved with a five-fold intraperitoneal injection of Me3 and Me5 at the total doses of 375 mg/kg and 250 mg/kg. The comparable results of the efficacy were obtained in the classical and metronomic modes of the injection of hybrid organotin compounds. With an increase in the injected dose, there is an effect of activating the tumor process with the generalized metastasis.

Conclusion: Bis dimethylolol (Me3) and triphenylolol (Me5) compounds demonstrate both a pronounced antimetastatic activity and a multidirectional effect on the growth of the primary focus and the metastasis in lungs, depending on an injected dose.

Evaluation of solid tumor response to sequential treatment cycles via a new computational hybrid approach

The development of an in silico approach that evaluates and identifies appropriate treatment protocols for individuals could help grow personalized treatment and increase cancer patient lifespans. With this motivation, the present study introduces a novel approach for sequential treatment cycles based on simultaneously examining drug delivery, tumor growth, and chemotherapy efficacy. This model incorporates the physical conditions of tumor geometry, including tumor, capillary network, and normal tissue assuming real circumstances, as well as the intravascular and interstitial fluid flow, drug concentration, chemotherapy efficacy, and tumor recurrence. Three treatment approaches-maximum tolerated dose (MTD), metronomic chemotherapy (MC), and chemo-switching (CS)-as well as different chemotherapy schedules are investigated on a real tumor geometry extracted from image. Additionally, a sensitivity analysis of effective parameters of drug is carried out to evaluate the potential of using different other drugs in cancer treatment. The main findings are: (i) CS, MC, and MTD have the best performance in reducing tumor cells, respectively; (ii) multiple doses raise the efficacy of drugs that have slower clearance, higher diffusivity, and lower to medium binding affinities; (iii) the suggested approach to eradicating tumors is to reduce their cells to a predetermined rate through chemotherapy and then apply adjunct therapy.

The scrambled story between hyaluronan and glioblastoma

Advances in cancer biology are revealing the importance of the cancer cell microenvironment on tumorigenesis and cancer progression. Hyaluronan (HA), the main glycosaminoglycan in the extracellular matrix, has been associated with the progression of glioblastoma (GBM), the most frequent and lethal primary tumor in the central nervous system, for several decades. However, the mechanisms by which HA impacts GBM properties and processes have been difficult to elucidate. In this review, we provide a comprehensive assessment of the current knowledge on HA's effects on GBM biology, introducing its primary receptors CD44 and RHAMM and the plethora of relevant downstream signaling pathways that can scramble efforts to directly link HA activity to biological outcomes. We consider the complexities of studying an extracellular polymer and the different strategies used to try to capture its function, including 2D and 3D in vitro studies, patient samples, and in vivo models. Given that HA affects not only migration and invasion, but also cell proliferation, adherence, and chemoresistance, we highlight the potential role of HA as a therapeutic target. Finally, we review the different existing approaches to diminish its protumor effects, such as the use of 4-methylumbelliferone, HA oligomers, and hyaluronidases and encourage further research along these lines in order to improve the survival and quality of life of GBM patients.

4-Methylumbelliferone as a potent and selective antitumor drug on a glioblastoma model

Glioblastoma (GBM), the most frequent primary tumor of the central nervous system, has a median survival of 14.6 months. 4-Methylumbelliferone (4MU) is a coumarin derivative widely used as a hyaluronan synthesis inhibitor with proven antitumor activity and without toxic effects reported. We aim to evaluate the antitumor effect of 4MU alone or combined with temozolomide (TMZ) on a GBM cell line, its absence of toxicity on brain cells and its selectivity for tumor cells. The antitumor effect of 4MU alone or combined with TMZ was evaluated on GL26 cells by assessing the metabolic activity through the XTT assay, cell proliferation by BrdU incorporation assay, migration by the wound healing assay, cell death by fluorescein diacetate/propidium iodide (FDA/PI) staining, apoptosis by membrane asymmetry and DNA fragmentation and metalloproteinase activity by zymography. The levels of hyaluronan and its capacity to counteract the effects of 4MU and the expression of RHAMM and CD44 were also determined. The toxicity and selectivity of 4MU were determined by XTT assay and PI staining on normal brain primary cell culture (NBPC-GFP) and GL26/NBPC-GFP cocultures. The GL26 cells expressed RHAMM but not CD44 while synthetized hyaluronan. 4MU decreased hyaluronan synthesis, diminished proliferation and induced apoptosis while reducing cell migration and the activity of metalloproteinases, which was restored by addition of hyaluronic acid. Furthermore, 4MU sensitized GL26 cells to the TMZ effect and showed selective toxicity on tumor cells without exhibiting neurotoxic effects. We demonstrated for the first time the cytotoxic effect of 4MU on GBM cells, highlighting its potential usefulness to improve GBM treatment.

Optimization of Cancer Treatment in the Frequency Domain

Thorough exploration of alternative dosing frequencies is often not performed in conventional pharmacometrics approaches. Quantitative systems pharmacology (QSP) can provide novel insights into optimal dosing regimen and drug behaviors which could add a new dimension to the design of novel treatments. However, methods for such an approach are currently lacking. Recently, we illustrated the utility of frequency-domain response analysis (FdRA), an analytical method used in control engineering, using several generic pharmacokinetic-pharmacodynamic case studies. While FdRA is not applicable to models harboring ever increasing variables such as those describing tumor growth, studying such models in the frequency domain provides valuable insight into optimal dosing frequencies. Through the analysis of three distinct tumor growth models (cell cycle-specific, metronomic, and acquired resistance), we demonstrate the application of a simulation-based analysis in the frequency domain to optimize cancer treatments. We study the response of tumor growth to dosing frequencies while simultaneously examining treatment safety, and found for all three models that above a certain dosing frequency, tumor size is insensitive to an increase in dosing frequency, e.g., for the cell cycle-specific model, one dose per 3 days, and an hourly dose yield the same reduction of tumor size to 3% of the initial size after 1 year of treatment. Additionally, we explore the effect of drug elimination rate changes on the tumor growth response. In summary, we show that the frequency-domain view of three models of tumor growth dynamics can help in optimizing drug dosing regimen to improve treatment success.

Optimal dynamic regimens with artificial intelligence: The case of temozolomide

We determine an optimal protocol for temozolomide using population variability and dynamic optimization techniques inspired by artificial intelligence. We use a Pharmacokinetics/Pharmacodynamics (PK/PD) model based on Faivre and coauthors (Faivre, et al., 2013) for the pharmacokinetics of temozolomide, as well as the pharmacodynamics of its efficacy. For toxicity, which is measured by the nadir of the normalized absolute neutrophil count, we formalize the myelosuppression effect of temozolomide with the physiological model of Panetta and coauthors (Panetta, et al., 2003). We apply the model to a population with variability as given in Panetta and coauthors (Panetta, et al., 2003). Our optimization algorithm is a variant in the class of Monte-Carlo tree search algorithms. We do not impose periodicity constraint on our solution. We set the objective of tumor size minimization while not allowing more severe toxicity levels than the standard Maximum Tolerated Dose (MTD) regimen. The protocol we propose achieves higher efficacy in the sense that –compared to the usual MTD regimen– it divides the tumor size by approximately 7.66 after 336 days –the 95% confidence interval being [7.36–7.97]. The toxicity is similar to MTD. Overall, our protocol, obtained with a very flexible method, gives significant results for the present case of temozolomide and calls for further research mixing operational research or artificial intelligence and clinical research in oncology.