Kinetic Modeling of ABCG2 Transporter Heterogeneity: A Quantitative, Single-Cell Analysis of the Side Population Assay

Systems Biology Approaches to Enzyme Kinetics

Intracellular drug metabolism involves transport, bioactivation, conjugation, and other biochemical steps. The dynamics of these steps are each dependent on a number of other cellular factors that can ultimately lead to unexpected behavior. In this review, we discuss the confounding processes and coupled reactions within bioactivation networks that require a systems-level perspective in order to fully understand the time-varying behavior. When converting known in vitro characteristics of drug-enzyme interactions into descriptions of cellular systems, features such as substrate availability, cell-to-cell variability, and intracellular redox state, deserve special focus. Two examples are provided. First, a model of hydrogen peroxide clearance during chemotherapy treatment serves as a basis to discuss an example of sensitivity analysis. Second, an example of doxorubicin bioactivation is used for discussing points of consideration when constructing and analyzing network models of drug metabolism.

Involvement of the Estrogen and Progesterone Axis in Cancer Stemness: Elucidating Molecular Mechanisms and Clinical Significance

Estrogen and progesterone regulate the growth and development of human tissues, including the reproductive system and breasts, through estrogen and progesterone receptors, respectively. These receptors are also important indicators for the clinical prognosis of breast cancer and various reproductive cancers. Many studies have reported that cancer stem cells (CSCs) play a key role in tumor initiation, progression, metastasis, and recurrence. Although the role of estrogen and progesterone in human organs and various cancers has been studied, the molecular mechanisms underlying the action of these hormones on CSCs remain unclear. Therefore, further elucidation of the effects of estrogen and progesterone on CSCs should provide a new direction for developing pertinent therapies. In this review, we summarize the current knowledge on the estrogen and progesterone axis involved in cancer stemness and discuss potential therapeutic strategies to inhibit CSCs by targeting relevant pathways.

The PI3K/AKT signaling pathway regulates ABCG2 expression and confers resistance to chemotherapy in human multiple myeloma

Side population (SP) cells are involved in the development of multidrug resistance (MDR) in human multiple myeloma (MM), due to their cancer stem cell (CSC)‑like phenotypes. ATP‑binding cassette (ABC) drug transporter proteins have been reported to be closely associated with MDR in leukemia; however, the correlation between ABC proteins and the progression of MM remains unclear. The present study used MM cell lines and clinical samples to determine the role of ABC subfamily G member 2 (ABCG2) in MM via flow cytometry, reverse transcription‑quantitative polymerase chain reaction and western blotting. SP cells sorted from MM cell lines, including NCI‑H929 cells, via fluorescence‑activated cell sorting, exhibited CSC‑like phenotypes and expressed high levels of ABCG2. Expression of ABCG2 and activation of the phosphatidylinositol 3‑kinase (PI3K)/AKT serine/threonine kinase (AKT) signaling pathway was positively associated with the proportion of SP cells in the NCI‑H929 cell line. In addition, suppression of the PI3K/AKT pathway using LY294002 or rapamycin counteracted the protective effects of ABCG2 against chemotherapeutic drug treatment. Mechanistically, PI3K/AKT signaling may regulate ABCG2 expression, and ABCG2 may regulate phosphatase and tensin homolog expression via a potential negative feedback loop. Furthermore, SP cell proportion, ABCG2 expression and PI3K/AKT pathway activation were associated with disease progression in patients with MM. These findings indicated the critical roles of ABCG2 and PI3K/AKT signaling in controlling stemness of MM cells, and suggested a novel strategy for targeting ABCG2 and PI3K/AKT signaling to treat MM with MDR.

Determinants of drug-target interactions at the single cell level

The physiochemical determinants of drug-target interactions in the microenvironment of the cell are complex and generally not defined by simple diffusion and intrinsic chemical reactivity. Non-specific interactions of drugs and macromolecules in cells are rarely considered formally in assessing pharmacodynamics. Here, we demonstrate that non-specific interactions lead to very slow incorporation kinetics of DNA binding drugs. We observe a rate of drug incorporation in cell nuclei three orders of magnitude slower than in vitro due to anomalous drug diffusion within cells. This slow diffusion, however, has an advantageous consequence: it leads to virtually irreversible binding of the drug to specific DNA targets in cells. We show that non-specific interactions drive slow drug diffusion manifesting as slow reaction front propagation. We study the effect of non-specific interactions in different cellular compartments by permeabilization of plasma and nuclear membranes in order to pinpoint differential compartment effects on variability in intracellular drug kinetics. These results provide the basis for a comprehensive model of the determinants of intracellular diffusion of small-molecule drugs, their target-seeking trajectories, and the consequences of these processes on the apparent kinetics of drug-target interactions.

Small-molecule drug design assumes target binding of high affinity. Most small molecules can interact with other macromolecules in the cell ‘nonspecifically,’ i.e., with significantly lower affinity. The extent to which these nonspecific interactions influence the availability and action of the drug for its specific target depends upon the relative concentrations of drug, the specific target, and nonspecific targets. The structure of the cell is quite crowded with a highly non-uniform distribution of macromolecules that can interact with the drug of interest both specifically and nonspecifically. Thus, some compartments or micro-domains within the cell may have a comparatively high concentration of nonspecific targets, sufficient to trap the drug and retard its diffusion toward the specific target. Here, using small-molecule binding to DNA and single cell monitoring, we demonstrate that this effect results in apparently anomalous small molecule-DNA binding kinetics in cells at rates that are 1000-fold slower than in a homogeneous, dilute, aqueous environment. This slow intracellular diffusion, however, has an advantageous consequence: it leads to virtually irreversible binding of the small molecule (drug) to specific DNA targets in cells. We study and quantify the effect of nonspecific interactions between small DNA-binding molecules, including known DNA-binding drugs, in different cellular compartments in order to identify factors that account for the variability in binding kinetics among individual cells.

Estrogen induces cell proliferation by promoting ABCG2-mediated efflux in endometrial cancer cells

Recently, it has reported that overeating of lipid-food has led to increase the amount of estrogen in vivo and the incidence of endometrial carcinomas. It is well-known that ATP-binding cassette transporter sub-family G2 (ABCG2) is highly expressed in cancer stem cells (CSCs). CSCs possess the ability for differentiation, tumorigenesis, stem cell self-renewal, and the efflux of anti-cancer drug and these abilities affect malignancy of cancer cells. However, little is known about the relationship between the expression of ABCG2 and malignancy of cancer cells. The present study aimed at understanding the regulatory mechanism underlying 17-β-estradiol (E2)-induced cell proliferation under the control of ABCG2. E2 increased cell viability with a peak at 1 μM and facilitated ABCG2 mRNA expression followed by the increase of ABCG2 expression level at plasma membrane. E2-induced cell proliferation was inhibited by reserpine, an inhibitor of ABCG2, and the ABCG2 siRNA treatment. Thus, these results imply that ABCG2 plays an important role in the promotion of E2-induced cell proliferation in Ishikawa cells.

Oscillatory IL-2 stimulus reveals pertinent signaling timescales of T cell responsiveness

Cell response to extracellular ligand is affected not only by ligand availability, but also by pre-existing cell-to-cell variability that enables a range of responses within a cell population. We developed a computational model that incorporates cell heterogeneity in order to investigate Jurkat T cell response to time dependent extracellular IL-2 stimulation. Our model predicted preferred timing of IL-2 oscillatory input for maximizing downstream intracellular STAT5 nuclear translocation. The modeled cytokine exposure was replicated experimentally through the use of a microfluidic platform that enabled the parallelized capture of dynamic single cell response to precisely delivered pulses of IL-2 stimulus. The in vitro results demonstrate that single cell response profiles vary with pulsatile IL-2 input at pre-equilibrium levels. These observations confirmed our model predictions that Jurkat cells have a preferred range of extracellular IL-2 fluctuations, in which downstream response is rapidly initiated. Further investigation into this filtering behavior could increase our understanding of how pre-existing cellular states within immune cell populations enable a systems response within a preferred range of ligand fluctuations, and whether the observed cytokine range corresponds to in vivo conditions.

Variable Cell Line Pharmacokinetics Contribute to Non-Linear Treatment Response in Heterogeneous Cell Populations

We develop a combined experimental-mathematical framework to investigate heterogeneity in the context of breast cancer treated with doxorubicin. We engineer a cell line to over-express the multi-drug resistance 1 protein (MDR1), an ATP-dependent pump that effluxes intracellular drug. Co-culture experiments mixing the MDR1-overexpressing line with its parental line are evaluated via fluorescence microscopy. To quantify the impact of population heterogeneity on therapy response, these data are analyzed with a coupled pharmacokinetics/pharmacodynamics model. The proliferation and death rates of each line vary with co-culture condition (the relative fraction of each cell line at the time of seeding). For example, the death rate in the parental line under low-dose doxorubicin treatment is increased from 0.64 (± 0.22) × 10^-2 to 1.46 (± 0.58) × 10^-2 h^-1 with increasing fractions of MDR1-overexpressing cells. The growth rate of the MDR1-overexpressing line increases 29% as its relative fraction is decreased. Simulations of the pharmacokinetics/pharmacodynamics model suggest increased efflux from MDR1-overexpressing cells contributes to the increased death rate in the parental cells. Experimentally, the death rate of parental cells is constant across co-culture conditions under co-treatment with an MDR1 inhibitor. These data indicate that intercellular pharmacokinetic variability should be considered in analyzing treatment response in heterogeneous populations.