Macrophage Targeting pH Responsive Polymersomes for Glucocorticoid Therapy

Glucocorticoid (GC) drugs are the cornerstone therapy used in the treatment of inflammatory diseases. Here, we report pH responsive poly(2-methacryloyloxyethyl phosphorylcholine)–poly(2-(diisopropylamino)ethyl methacrylate) (PMPC–PDPA) polymersomes as a suitable nanoscopic carrier to precisely and controllably deliver GCs within inflamed target cells. The in vitro cellular studies revealed that polymersomes ensure the stability, selectivity and bioavailability of the loaded drug within macrophages. At molecular level, we tested key inflammation-related markers, such as the nuclear factor-κB, tumour necrosis factor-α, interleukin-1β, and interleukin-6. With this, we demonstrated that pH responsive polymersomes are able to enhance the anti-inflammatory effect of loaded GC drug. Overall, we prove the potential of PMPC–PDPA polymersomes to efficiently promote the inflammation shutdown, while reducing the well-known therapeutic limitations in GC-based therapy.

Cy5-labelled PMPC-b-PDPA was prepared as above but using bis [2 -(2bromoisobutyryloxy)ethyl] disulfide as initiator [1]. After purification and isolation, an aliquote of the obtained polymer was reacted with Cyanine5 maleimide (1.1 eq.) and PPh3 (2 eq.) in degassed chloroform/methanol [2:1 (v/v)]. The final polymer concentration was 1.6 mM, and the reaction was kept stirring under N2 and in the dark at room temperature for 48 h. After this time, the reaction solution was opened to the air, filtered onto a silica column and dialysed using a 3.5 kDa MWCO dialysis membrane (Spectrum Labs, Netherland) against chloroform/methanol 2:1 (v/v) (2 -3 × 500 mL), methanol (4 -6 × 500 mL), and double-distilled water (4 -6 × 2 L). After dialysis the copolymer was isolated by freeze-drying.  Regarding the characterization study, HPLC analyses resulted in the drug encapsulation and loading efficiencies within PMPC-PDPA polymersomes. The drug encapsulation efficiency (EE) was calculated as the ratio between the final and initial mass of loaded prednisolone disodium 21phosphate (PDP). The drug loading efficiency (LE) was determined according to a previously reported method [2] represented as the number of PDP molecules loaded within the total lumen volume of PMPC-PDPA polymersomes (which is related with the size of the vesicle and the actual amount of loaded drug).

Drug Release study
To examine the kinetics and mechanism of PDP release from the PMPC-PDPA polymersomes, the data obtained from the in vitro drug release studies of each pH profile was analyzed using various models, including the zero and first order, Higuchi, Hixson-Crowell and Korsmeyer-Peppas models [4,5]. Table S1. Mathematical models for drug-release kinetics.

Equation 1 Information
Zero-Order Q = Q0 + K0t refers to the process of constant drug release from a drug delivery device

First-Order
Log C = Log C0 -k1t / 2.303 represents a system where the release rate of the drug depends on the concentration of the drug in the system

Hixson-Crowell
describes the release from systems where there is a change in surface area and diameter of particles Higuchi Qt = kH (t) 0.5 assumes that the drug's release is caused primarily by a diffusion mechanism

Korsmeyer-Peppas
F=Mt/M N = Kt n provides insight into the type of drug release mechanism taking place from swellable devices 1 Q is the amount of drug released or dissolved; Q0 is initial amount of drug in solution; C0 is the initial concentration of drug; t is the time in hours; F is the fraction of drug release at time t; Mt/M is the fraction of drug released at time t; K are the rate constants for each models. Table S2. Correlation coefficient (r 2 ) from various drug release mathematical models for each pH profile. For the RT-qPCR experiments, the ribosomal protein L13A (RPL13A) was used as reference gene, because it was stably expressed in THP-1, both in stimulated and unstimulated cells (data not shown). RT-qPCR data was analysed using the comparative cycle threshold (Ct) method, also known as the ΔΔCt method. The Ct value of each target gene (TNFα, IL1β, IL6 and IL8) was normalized to the reference gene (RPL13A), obtaining the ΔCt value (Equation 1) of treatment and control (i.e., nontreated). Then, the change in Ct is compared against the control to obtain the ΔΔCt value (Equation 2) using the following equations: ΔCt = Ct (target gene) -Ct (RPL13A) (1) ΔΔCt = ΔCt (treated) -ΔCt (non-treated) (2) Then, the -ΔΔCt values corresponds to the folds in gene expression change of the treated compared to the non-treated group.