A coupled drug kinetics-cell cycle model to analyse the response of human cells to intervention by topotecan

Nuclear cytometry and chromatin organization

The nuclear-targeting chemical probe, for the detection and quantification of DNA within cells, has been a mainstay of cytometry-from the colorimetric Feulgen stain to smart fluorescent agents with tuned functionality. The level of nuclear structure and function at which the probe aims to readout, or indeed at which a DNA-targeted drug acts, is shadowed by a wide range of detection modalities and analytical methods. These methods are invariably limited in terms of the resolution attainable versus the volume occupied by targeted chromatin structures. The scalar challenge arises from the need to understand the extent and different levels of compaction of genomic DNA and how such structures can be re-modeled, reported, or even perturbed by both probes and drugs. Nuclear cytometry can report on the complex levels of chromatin order, disorder, disassembly, and even active disruption by probes and drugs. Nuclear probes can report defining features of clinical and therapeutic interest as in NETosis and other cell death processes. New cytometric approaches continue to bridge the scalar challenges of analyzing chromatin organization. Advances in super-resolution microscopy address the resolution and depth of analysis issues in cellular systems. Typical of recent insights into chromatin organization enabled by exploiting a DNA interacting probe is ChromEM tomography (ChromEMT). ChromEMT uses the unique properties of the anthraquinone-based cytometric dye DRAQ5™ to reveal that local and global 3D chromatin structures effect differences in compaction. The focus of this review is nuclear and chromatin cytometry, with linked reference to DNA targeting probes and drugs as exemplified by the anthracenediones.

Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

PURPOSE

Cancer is a manifestation of aberrant cellular proliferation, and the cell cycle is one of the most successfully drugged targets in oncology. No prior study has been reported that simultaneously targets the 3 principal cell cycle phases populated by proliferating cells--G1, S, and G2/M.

METHODS

Temsirolimus (G1 inhibitor), topotecan (S inhibitor), and bortezomib (G2/M inhibitor) were administered in combination to patients with advanced malignancies using a 3+3 dose escalation schedule to assess the safety and establish the maximum tolerated dose (primary endpoints) of this cell cycle targeting approach. An in silico pharmacodynamic model using established effects of each of these agents on the cell cycle was used to validate the regimen and to guide the dosing regimen.

RESULTS

Sixty-two subjects were enrolled. The most common adverse events and dose-limiting toxicities were cytopenias, consistent with the cell cycle targeting approach employed. All cytopenias resolved to baseline values upon holding study drug administration. The maximum tolerated dose was temsirolimus 15 mg/kg IV D1, 8, 15; topotecan 2.8 mg/m(2) IV D1, 8; and bortezomib 0.6 mg/m2 IV D1, 4, 8, 11 [DOSAGE ERROR CORRECTED] of a 21-day cycle. In silico modeling suggests the regimen induces cell population shifts from G2/M and S phases to G1 phase and the quiescent G0 phase. Eighteen percent of subjects (11/62) achieved partial response (n = 2, serous ovarian and papillary thyroid) or stable disease for > 6 months (n = 9).

CONCLUSION

Combining drugs with inhibitory activity of G1 phase, S phase, and G2/M phase is safe and warrants further evaluation.

Towards an integrated systems-based modelling framework for drug transport and its effect on tumour cells

Background

A systematic understanding of chemotherapeutic influence on solid tumours is highly challenging and complex as it encompasses the interplay of phenomena occurring at multiple scales. It is desirable to have a multiscale systems framework capable of disentangling the individual roles of multiple contributing factors, such as transport and extracellular factors, and purely intracellular factors, as well as the interactions among these factors. Based on a recently developed systems-based modelling framework, we have developed a coupled system in order to further elucidate the role of drug transport, and its interplay with cellular signalling by incorporating intra- and extra-vascular drug transport in tumour, dynamic descriptions of intracellular signalling and tumour cell density dynamics.

Results

Different aspects of the interaction between transport and cell signalling and the effects of transport parameters have been investigated in silico. Limited drug penetration is found to be a major constraint in inducing drug effect; many aspects of the interaction of transport with cell signalling are independent of the details of cell signalling. A sensitivity analysis indicates that the effect of drug diffusivity depends on the balance between interstitial drug transport and the specific requirement for triggering apoptosis (governed by highly nonlinear signalling networks), suggesting that the effect of drug diffusivity in such cases must be considered in conjunction with descriptions of cellular dynamics.

Conclusions

The modelling framework developed in this study provides qualitative and mechanistic insights into the effect of drug on tumour cells. It provides an in silico experimental platform to investigate the interplay between extracellular factors (e.g. transport) and intracellular factors. Such a platform is essential to understanding the individual and combined effects of transport and cellular factors in solid tumour.

Use of mathematical models to understand anticancer drug delivery and its effect on solid tumors

The transport of anticancer drugs and their effect on tumor cells involve a number of physical and biochemical processes. Mathematical modeling provides a tool to help us understand the interaction of these complex processes, thereby contributing to the improvement and optimization of drug delivery. This article starts with a discussion of the biological and physiological properties of tumors, which are often found as barriers to anticancer drug transport and effect. A broad spectrum of mathematical models is reviewed to give an overview of the current state of modeling approaches and different categories of models are outlined. These include pharmacokinetic and transport-based models for the prediction of temporal and temporal-spatial profiles of antidrug concentrations, as well as empirical or deterministic models to describe the effect of drug. We conclude that the systematic elucidation and integration of cellular signal transduction with the biophysical aspects of drug transport will lead to a better understanding of the entire drug-delivery process.

Mathematical modeling as a tool for planning anticancer therapy

We review a large volume of literature concerning mathematical models of cancer therapy, oriented towards optimization of treatment protocols. The review, although partly idiosyncratic, covers such major areas of therapy optimization as phase-specific chemotherapy, antiangiogenic therapy and therapy under drug resistance. We start from early cell cycle progression models, very simple but admitting explicit mathematical solutions, based on methods of control theory. We continue with more complex models involving evolution of drug resistance and pharmacokinetic and pharmacodynamic effects. Then, we consider two more recent areas: angiogenesis of tumors and molecular signaling within and among cells. We discuss biological background and mathematical techniques of this field, which has a large although only partly realized potential for contributing to cancer treatment.