Principal Investigator; Associate Dean for Innovation and Entrepreneurship Cornell University, United States
Introduction: Multidrug resistance remains a primary challenge facing cancer treatment, contributing to up to ninety percent of cancer-related deaths (Bukowski+ 2020). One important mechanism of multidrug resistance is overexpression of P-glycoprotein (P-gp), a transmembrane efflux pump that confers resistance to many structurally diverse chemotherapeutics. While early efforts to circumvent P-gp-mediated multidrug resistance focused on administration of small molecule inhibitors that block the ability of P-gp to efflux therapeutic substrates from the cell, more recent work has sought to reverse the resistant phenotype by reducing P-gp expression, often through administration of siRNA. However, while several studies demonstrate partial restoration of the drug sensitive phenotype following siRNA-mediated P-gp knockdown, P-gp expression levels are reported as ratios relative to the initial expression level and, as such, are limited in scope. A quantitative model relating absolute P-gp expression to drug sensitivity is required to contextualize the ability of P-gp knockdown to mediate drug efflux across studies. In this study, we use siRNA to modulate P-gp expression in a multidrug resistant melanoma line and correlate quantitative receptor density to drug sensitivity for three common P-gp substrate chemotherapeutics. This work demonstrates a linear correlation between drug sensitivity and P-gp receptor density and provides a model to quantify drug sensitivity as a function of P-gp expression.
Materials and
Methods: All studies were performed using the MDA435/LCC6 melanoma line. Wild-type MDA435/LCC6 (P-gp negative) and MDA435/LCC6-MDR1 (P-gp positive) cells were cultured in modified improved minimum essential medium (IMEM) supplemented with 10% fetal bovine serum and maintained at 37 °C and 5% CO2. To modulate P-gp expression, MDA435/LCC6-MDR1 cells were transfected with varying concentrations of siRNA targeted against P-gp (IDT Technologies) using Lipofectamine RNAiMAX (ThermoFisher). A nontargeting siRNA sequence was used as a negative control. To determine drug sensitivity, cells were cultured with transfection medium for 24 hours. The cells were washed with PBS and treated with varying concentrations of doxorubicin hydrochloride, vinblastine sulfate, or paclitaxel in IMEM for an additional 72 hours. Following drug treatment, cell viability was determined by performing an MTS assay (Promega), and drug sensitivity was quantified by calculating IC50 using a standard dose-response curve. To quantify P-gp expression, cells were cultured with transfection medium for 24 hours. Culture media was then replaced, and cells were cultured for an additional 72 hours. Cells were trypsinized, seeded in V-bottom plates, and stained with live/dead stain and an AlexaFluor 647-labeled anti-P-gp antibody (Abcam). Following fixation in 2% paraformaldehyde, cells were analyzed via flow cytometry to quantify fluorescence. To quantify P-gp receptor density, a standard curve to correlate fluorescence to AlexaFluor 647 concentration was generated using AlexaFluor 647-labeled beads (Bangs Laboratories). Additionally, P-gp expression was measured using western blot to quantify relative changes in P-gp expression as a function of siRNA concentration. Data analysis was performed using GraphPad Prism 10.
Results, Conclusions, and Discussions: In this study, P-gp expression by MDA435/LCC6-MDR1 cells was successfully modulated using varying concentrations of siRNA. Using flow cytometry, native P-gp expression of MDA435/LCC6-MDR1 was quantified as 4.06x10^4 + 0.6x10^4 receptors per cell. P-gp expression levels measured by flow cytometry following transfection with varying concentrations of siRNA is shown in Figure 1a. Western blot was used to confirm these fold-change trends in P-gp expression. To correlate P-gp expression levels to drug sensitivity, MDA435/LCC6-MDR1 cells transfected with the siRNA concentration gradient were treated with doxorubicin hydrochloride, vinblastine sulfate, and paclitaxel for 72 hours. Wild-type MDA435/LCC6 and MDA435/LCC6-MDR1 cells transfected with nontargeting siRNA were used as controls. Following quantification of cell viability, IC50 values were calculated for each drug and siRNA concentration and plotted against P-gp expression, shown in Figure 1b-d. Linear regression was performed to determine the relationship between P-gp expression and drug sensitivity. For paclitaxel, the correlation is modeled via the equation paclitaxel IC50 (nM) = 0.003784 x P-gp expression + 1.969 (R^2 = 0.9011). Similarly, vinblastine sulfate follows a linear relationship modeled by the equation vinblastine IC50 (nM) = 1.472x10^-4 x P-gp expression – 0.1275 (R^2 = 0.8926). Finally, doxorubicin hydrochloride can be modeled using the equation doxorubicin IC50 = 0.04424 x P-gp expression – 2031 (R^2 = 0.4320).
In this work, we have developed quantitative models to correlate absolute P-glycoprotein expression with drug sensitivity for three common chemotherapeutics. These models follow a linear correlation between drug IC50 and P-gp cell density at steady state. The variable slopes observed across P-gp substrates may be due to differences in the rate of passive transport of each drug across the cell membrane. Diffusion into the lipid bilayer enables substrates to be bound by the inward-facing binding pocket of P-gp and is an essential first step to P-gp-mediated drug efflux. The models we have reported can be used to contextualize quantitative changes in P-gp expression in terms of resultant impact on drug sensitivity for doxorubicin, vinblastine, and paclitaxel in a multidrug resistant melanoma line. Future work will expand the model to describe two additional multidrug-resistant cancer lines to further validate these observations.
Acknowledgements (Optional): MDA435/LCC6 and MDA435/LCC6-MDR1 cells were a generous gift from Dr. Robert Clarke (Georgetown University, Washington, DC) and MD Anderson Cancer Center (Houston, TX). Flow cytometry experiments were conducted at the Cornell Biotechnology Resource Center Flow Cytometry Facility (RRID:SCR_021740). This work was supported in part by The National Science Foundation Graduate Research Fellowship grant DGE-1650441 (to C.R.).
