Multidrug resistance (MDR) is considered a multifactorial event that favors cancer cells becoming resistant to several chemotherapeutic agents. Numerous mechanisms contribute to MDR, such as P-glycoprotein (Pgp/ABCB1) activity that promotes drug efflux, overexpression of inhibitors of apoptosis proteins (IAP) that contribute to evasion of apoptosis, and oncogenic pathway activation that favors cancer cell survival. MDR molecules have been identified in membrane microparticles (MP) and can be transferred to sensitive cancer cells. By co-culturing MP derived from MDR-positive cells with recipient cells, we showed that sensitive cells accumulated Pgp, IAP proteins and mRNA. In addition, MP promoted microRNA transfer and NFκB and Yb-1 activation. Therefore, our results indicate that MP can induce a multifactorial phenotype in sensitive cancer cells.

The involvement of the multidrug resistance (MDR) mediated by ABC transporter proteins P-glycoprotein (Pgp) and multidrug resistance-associated protein-1 (MRP1) overexpressions in patients with chronic myeloid leukemia (CML) are not completely understood. Pgp and MRP1 expressions and activity were analyzed in samples from 158 patients with chronic myeloid leukemia (CML). Using flow cytometry, Pgp expression was more frequently observed in early chronic (P 5 0.00) and in advanced (P 5 0.02) CML phases when it was compared to MRP1 expression. Variation of MDR expression and activity were observed during the CML evolution in patients previously treated with interferon and imatinib. In the K562-Lucena cell line, Pgp positive, imatinib caused an enhancing in Pgp expression at protein and mRNA levels, whereas in the Pgp negative cell line, this drug was capable of decreasing MDR1/Pgp mRNA levels. Our result emphasizes the importance of understanding the different aspects of MDR status in patients with CML when they are under investigation in determining imatinib resistance. V C 2010 International Clinical Cytometry Society

Intratumoral heterogeneity has been found to be a major cause of drug resistance. Cell-to-cell variation increases as a result of cancer-related alterations, which are acquired by stochastic events and further induced by environmental signals. However, most cellular mechanisms include natural fluctuations that are closely regulated, and thus lead to asynchronization of the cells, which causes intrinsic heterogeneity in a given population. Here, we derive two novel mathematical models, a stochastic agent-based model and an integro-differential equation model, each of which describes the growth of cancer cells as a dynamic transition between proliferative and quiescent states. These models are designed to predict variations in growth as a function of the intrinsic heterogeneity emerging from the durations of the cell-cycle and apoptosis, and also include cellular density dependencies. By examining the role all parameters play in the evolution of intrinsic tumor heterogeneity, and the sensitivity of the population growth to parameter values, we show that the cell-cycle length has the most significant effect on the growth dynamics. In addition, we demonstrate that the agent-based model can be approximated well by the more computationally efficient integro-differential equations when the number of cells is large. This essential step in cancer growth modeling will allow us to revisit the mechanisms of multi-drug resistance by examining spatiotemporal differences of cell growth while administering a drug among the different sub-populations in a single tumor, as well as the evolution of those mechanisms as a function of the resistance level.