Dual Targeting of Prostate Cancer Cells and Tumor-Associated Macrophages for Mitigating Tumorigenesis and Metastasis: Hyaluronic Acid Functionalized Polymeric Nanospheres for CD44-Mediated Active Targeting

doi:10.21203/rs.3.rs-3335630/v1

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Dual Targeting of Prostate Cancer Cells and Tumor-Associated Macrophages for Mitigating Tumorigenesis and Metastasis: Hyaluronic Acid Functionalized Polymeric Nanospheres for CD44-Mediated Active Targeting

https://doi.org/10.21203/rs.3.rs-3335630/v1

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Prostate cancer (PC) is the second leading cause of cancer-related fatalities in men due to enormous ability of progression, metastasis, and development of multidrug resistance (MDR). The existing conventional therapies are producing reasonable clinical response in PC patients; however, they are associated with substantial limitations. The advent of nanotechnology has resolved several key issues associated with conventional therapies; however, undesired pharmacokinetics, non-selective targeting, and evasion of tumor-associated macrophages (TAMs) yet persist as paramount challenge to current nano-therapies. Herein, we proposed dual targeting strategy for concurrent action against PC cells and TAMs hosted by tumor microenvironment. Henceforth, chitosan (CS)-based polymeric nanospheres (PNSPs) were fabricated via ionic-gelation method and functionalized with hyaluronic acid (polyanionic biological macromolecule) via electrostatic adsorption. HA was employed as a targeting ligand for CD44 receptors that are overexpressed on PC cells and TAMs. The optimized PNSPs were extensively pondered for physicochemical properties (particle size ⁓160 nm, PDI 0.453, zeta potential ⁓30 mV), morphology (smooth spherical), stability, release kinetics (biphasic and pH-responsive), cytotoxicity (lowest IC₅₀), cell uptake efficiency, mechanism of cell internalization (CD44-mediated endocytosis), and anti-metastatic efficacy. Conclusively, our findings warranted that HA-functionalized PNSPs act as a double edge sword for dual targeting of PC cells and TAMs to mitigate cancer progression and metastasis.

Dual targeting strategy

Hyaluronic acid

Electrostatic functionalization

Chitosan nanospheres

Active targeting

CD44-mediated endocytosis

Having immense metastatic potential, prostate cancer is the second leading cause of cancer-related fatalities in men.
Dual targeting is a smart strategy for concurrent action against both prostate cancer and tumor-associated macrophages.
Hyaluronic acid-mediated functionalization of polymeric nanospheres revealed promising potential for CD44-mediated active targeting.
Optimized (Design Expert^®) nanospheres exhibited paramount potential for intracellular uptake and cytotoxicity against prostate cancer.
Superior anti-metastatic efficacy was evident by downregulating cancer cell proliferation and migration in confluent cell monolayer.

Cancer is among the most devastating diseases triggered by genetic mutation or due to complex intercellular, intracellular, and/or non-cellular cross-talks in the body [1, 2]. It is characterized by an abnormal growth of cells having overwhelming potential of invasion and metastasis to other tissues/organs of the body. In contrast to benign tumors that restrict to the primary sites, cancers are characterized by massive potential to spread to other parts of the body. Over 100 different types of cancer have been diagnosed in human, among them, prostate cancer (PC) is the second most aggressive and prevalent type of cancer in men with highest mortality rates after the lung cancer [1, 2]. According to the recent Cancer Statistics, percentage of population diagnosed with PC at advanced stages has alarmingly increased from 3.9–8.2% over the past decade. Owing to its enormous ability of tumorigenesis, metastasis (local or distant), multi-drug resistance (MDR), and poor disease-free survival (DFS) and overall survival (OS) rates, PC is the second leading cause of cancer-related mortalities in men (more than 370,000 deaths globally) [1, 2].

A wide variety of FDA-approved chemotherapeutics are being clinically prescribed for treatment of PC, alone or in conjunction with other viable treatments such as radiotherapy, surgery, hormonal replacement therapy, bone marrow transplant, immunotherapy, and/or personalized medicines [3, 4]. The conventional therapies produce reasonable clinical response in PC patients; however, their therapeutic significance is inadequate due to various drug-related factors such as low aqueous solubility, undesirable pharmacokinetics, narrow therapeutic index, non-specific biodistribution, and off-target adverse events [3–5]. In addition, several biological factors including, genetic mutation, altered epigenetics, enhanced drug efflux, activation of specific signaling pathways, and MDR also contribute to failure of existing conventional therapies and poor DFS and OS rates in PC patients [6, 7]. MDR is not solely related to ability of cancer cells to survive against the existing chemotherapeutics, but it is also associated with TME which play a crucial pro-oncogenic role in promoting the progression of cancer, metastasis to other body tissues, and chemoresistance.

TME consists of extracellular matrix (ECM), stromal cells (e.g., MSCs, fibroblasts, adipocytes, vasculature, etc.), red blood cells, pericytes, various immune players (e.g., macrophages, natural killer cells, dendritic cells, and lymphocytes), and cancer cells (Fig. 1B). Among various immune players, tumor-associated macrophages (TAMs) are the most abundant cells within TME that play a crucial role in the development and progression of TME via the dysregulation of various cytokines, chemokines, growth factors, angiogenesis, and immune functioning [6, 7]. Within the TME, TAMs can be polarized into two different phenotypes such as M1 (anti-inflammatory and anti-tumor) and M2 (inflammatory and pro-tumor) which are unique and distinct in functioning. M2-subtype of TAMs are of crucial concern because they promote tumor growth, metastasis, invasion, TME remodelling, and immunosuppression [6, 7]. Therefore, while designing a newer anti-neoplastic therapy, M2-subtype of TAMs should be considered as an important chemo-target in addition to cancer cells for tumbling the cancer-related fatalities.

With the advent of versatile nanotechnology-based nanocarriers such as polymeric nanoparticles, liposomes, niosomes, micelles, dendrimers, solid lipid nanoparticles, nanostructured lipid carriers, and inorganic nanoparticles, majority of challenges associated with conventional chemotherapeutics have been reasonably addressed [8–11]. However, it is worth mentioning that despite relative success of nanotechnology-based nanocarriers for treatment of PC in in vitro and in vivo models, nano-therapies are still below the expectation to provide rational therapeutic outcomes along with adequate pharmacokinetics, pharmacodynamics, and safety in humans [8–11].

To counter these challenges, various specialized strategies have been adapted in the design of nanocarriers including the passive and active targeting approaches. The passive targeting is achieved through Enhanced Permeation and Retention (EPR) effect which enables preferential diffusion of systematically available nanocarriers into TME due to poor lymphatic drainage and leaky vasculature in the tumor tissues [12, 13]. Notably, size of nanocarriers play a crucial role to attain an adequate EPR effect, and optimum size range for passive distribution of nanocarriers to TME is < 200 nm [12, 13]. On the other hand, nanocarriers have been uniquely functionalized with various targeting ligands (i.e., targeting peptides, aptamers, antibodies, and small molecules) for selective targeting of tumor cells having distinct biology (e.g., overexpressed CD44, folic acid, P-glycoprotein, transferrin receptors, etc.) [14–17]. Plethora of studies have reported that targetable NPs (passive and active) have shown better results in terms of precise site-specific targeting via recognizing specific biomarkers overexpressed on cancer cells, improving pharmacokinetics, and mitigating off-target effects compared to non-targetable NPs [14–17]. Undoubtedly, passive and active targeting strategies have shown obvious improvement in anticancer response of NPs in in vitro and in vivo models; however, literature survey of past two decades indicated that, on average, < 1% of injected NPs (targeted and non-targeted) had shown uptake into TME of solid malignant tumors [18], and these findings were really disappointment in human models.

To deal with this, cleverly designed nanocarriers are an obvious need of the current time to maximize the biodistribution of chemotherapeutics into solid malignant tumors. Dual-targeting strategy is a smart approach to resolve majority of issues related to nanocarriers [19, 20]. Dual-targeting strategy defines as anchoring of two targeting ligands on NPs corona to recognize and competitively bind to two different receptors overexpressed on cancer cells, or conjugation of one targeting ligand on NPs corona to recognize and competitively bind to two different receptors or two different target cells. Dual-targeting strategy could provide better selectivity, efficient internalization via multiple endocytosis mechanisms, inhibition of MDR, and treatment of multiple types of cancers concurrently [19, 20].

Herein, we aimed to construct polymeric nanospheres (PNSPs) as a double-edge sword for dual action against PC cells and M2-subtype of TAMs residing in the TME (Fig. 1). These PNSPs were made up of chitosan (CS) matrix encapsulated with two chemotherapeutic agents, methotrexate (MTX) and zoledronic acid (ZA) for synergistic action against PC. The ZA is a highly potent third-generation bisphosphonate with proven anticancer efficacy against PC via induction of apoptosis, inhibition of tumor invasion, downregulation of angiogenesis, and regression of tumor proliferation [21]. Likewise, MTX is a well-recognized antineoplastic agent with potent anti-oncogenic efficacy against a wide variety of cancers [22]. Owing to its folic acid-like structure, MTX has also been used as a targeting ligand for folate receptors that are heavily expressed on different types of cancer, including the PC [23]. To install dual targeting feature, engineered MTX/ZA co-loaded PNSPs were functionalized with hyaluronic acid (HA) as a targeting ligand. HA is a natural carbohydrate polymer consisting of D-glucuronic acid and N-acetyl-d-glucosamine units and it exhibits great specificity towards integral membrane glycoprotein known as cluster differentiation-44 (CD44) [24]. CD44 is a cell surface receptor heavily expressed on many types of cells, including the PC cells and TAMs, and hence has been chosen as a biological target for dual action against both PC cells and TAMs. The developed HA-decorated nanospheres (HA-PNSPs) were extensively optimized and characterized for particle size, polydispersity index (PDI), zeta potential, encapsulation efficiency (%EE), loading capacity (%LC), morphology, colloidal stability, crystallographic structure, molecular docking with CD44 receptors, in vitro release kinetics, cell uptake efficiency, cytotoxicity (IC₅₀) against PC cells and TAMs, specific cell internalization via CD44-mediated endocytosis, and anti-metastatic potential.

2.1. Materials

Low molecular weight chitosan (CS) (M.W. 70 kDa, deacetylated chitin, poly(D-glucosamine)), sodium tripolyphosphate (TPP) (technical grade, 85%), zoledronic acid (ZA) (pharmaceutical standard), methotrexate (MTX) (pharmaceutical standard), hyaluronic acid sodium salt from Streptococcus equi (HA) (bacterial glycosaminoglycan polysaccharide), acetic acid (glacial), dimethyl sulfoxide, ethanol, sodium acetate and phosphate buffered saline were purchased from Sigma-Aldrich (USA). Coumarin-6, anti-CD44 Alexa Fluor™ 647 antibodies, Dulbecco's Modified Eagle Medium (DMEM) medium, Roswell Park Memorial Institute (RPMI) medium, mounting media with DAPI, RAW 264.7 cells (model M2-subtype of macrophages), and human prostate adenocarcinoma cells (PC-3 cells) were purchased from Biomedical Scientific Services, Al Ain, UAE. All other chemicals used were of analytical grade and resourced from Pharmaceutics and Pharmaceutical Technology laboratories at SIMHR, UOS.

2.2. Quality by Design (QbD) for optimization of HA-PNSPs

While designing a new formulation or optimizing an existing formulation, it is paramount to recognize critical material attributes (CMAs) and critical process parameters (CPPs) and understand their effect on critical quality attributes (CQAs) of the product. For this purpose, D-optimal response surface design was employed to optimize the HA-PNSPs (HA-MTX-ZA-CS-NPs) using the Design-Expert® software (Version 13.0, Stat-Ease Inc., Minneapolis, MN, USA).

In this experimental design, two discrete numerical factors and one categorical factor were set as CMAs and their effect was investigated on the chosen CQAs. The under-investigation factors include, 1) CS concentration (X₁), 2) HA concentration (X₂), and 3) homogenization after ionic gelation (X₃). The levels of independent variables were set to ensure a maximal design space as well as a plausible processing of PNSPs (Table 1). The effect of chosen CMAs (independent variables) was studied on three responses (dependent variables) which include, 1) particle size (PS, Y₁), 2) PDI (Y₂), and 3) zeta potential (ZP, Y₃). To attain overall highest desirability value, the optimization goals for studied responses were set as smallest PS, narrowest PDI, and highest ZP. The optimal independent variables were then fixed to prepare optimized HA-PNSPs for further testing and analysis.

The Design-Expert® software generated 19 experimental runs, including the five replications (Table 2). All experimental runs were conducted in triplicate (n = 3) in a random order to disregard bias and improve the predictability of the model. The resulting responses were concurrently fitted to linear, two-factor interaction (2FI), and quadratic response surface models and the consequential polynomial equations were statistically validated by analysis of variance (ANOVA). To simply the model, three and higher order interactions were abandoned. To ensure the significance of the model, several statistical parameters such as p-value, lack-of-fit p-value, adjusted multiple correlation coefficient (Adjusted-R²), predicted multiple correlation coefficient (Predicted-R²) and multiple correlation coefficient (R²) were determined. Notably, the model with maximal Adjusted-R² and Predicted-R² with an insignificant lack-of fit was chosen.

Table 1

The independent (factors) and dependent (responses) variables for optimization of HA- PNSPs.
	Numerical Factor (discrete)	Applied Levels
X₁	Chitosan concentration (% w/v)	0.1	0.3		0.5
X₂	HA concentration (% w/v)	0.001	0.0255		0.05
	Categorical Factor	Applied Levels
X₃	Homogenization after ionic gelation	Yes		No
	Responses	Optimization Goal
Y₁	PS	Minimize
Y₂	PDI	Minimize
Y₃	ZP	Maximize

Table 2

Experimental design and measured responses for optimization of HA-PNSPs. X₁: CS concentration (% w/v), X₂: HA concentration (% w/v), X₃: homogenization (yes/no).
Formulation	X₁ (% w/v)	X₂ (% w/v)	X₃ (Yes/No)	Y₁: PS (nm)	Y₂: PDI	Y₃: ZP (mV)
F1	0.5	0.05	No	2232	0.983	14
F2	0.5	0.0255	Yes	883	0.874	17
F3	0.3	0.0255	Yes	323	0.943	25
F4	0.5	0.05	Yes	2223	0.989	12
F5	0.3	0.05	No	1962	0.984	17
F6	0.5	0.05	Yes	2237	0.978	11
F7	0.1	0.001	Yes	161.13	0.523	31.1
F8	0.3	0.001	No	213	0.744	23
F9	0.5	0.0255	No	898	0.912	13
F10	0.3	0.0255	No	332	0.923	24
F11	0.1	0.0255	No	199.8	0.469	23
F12	0.5	0.001	Yes	624	0.92	17
F13	0.1	0.05	Yes	987	0.696	18.6
F14	0.1	0.001	Yes	165.13	0.423	28.9
F15	0.1	0.0255	Yes	190	0.433	24
F16	0.5	0.001	Yes	628	0.921	16
F17	0.1	0.05	Yes	975	0.632	17.5
F18	0.1	0.05	No	998	0.632	16.5
F19	0.3	0.001	No	217	0.687	16

2.3. Selection of optimal nanosystem

After the assessment of significance of the chosen model for response prediction, 3D response surface plots were generated by the Design-Expert® software for each selected response to estimate the degree of interaction between different factors. By careful visual examination, the optimal value for each response was determined based on the optimization goals which were set as smallest PS, narrowest PDI, and highest ZP. For optimization, both the numerical and graphical analyses were performed using the desirability function. Notably, the desirability value ranges from 0.0 to 1.0 and the value closest to 1.0 corresponds to the desired response [25].

2.4. Method validation

For validation purpose, blank PNSPs (CS-NPs) were first prepared using the previously established ionic-gelation method [26–28] with minor modifications. For optimization, several parameters such as chitosan (CS) concentration, TPP concentration, homogenization time and stirring speed were varied during the preparation process. Briefly, CS solution (0.1–0.5% w/v) was prepared in acetic acid (2% v/v) using the magnetic stirrer at 700 rpm at room temperature (20 ± 3°C) for 2 h. The prepared CS solution was then homogenized for additional 30 min using the T23 digital ULTRA TURRAX stirrer homogenizer (IKA, Germany) at 15,000 rpm followed by filtration through membrane filter (0.22 µm). On the other hand, TPP solution (0.1% w/v) was prepared in purified distilled water via magnetic stirring (10 min). Finally, 10 mL of TTP solution was added dropwise into 25 mL of prepared CS solution while constantly stirring the mixture at 700 rpm on magnetic stirrer. Following the dropwise addition of TPP, mixture was kept on magnetic stirrer for additional 30 min to maximize the ionic gelation process between CS (polycation) and TPP (polyanion). The resulting CS-NPs dispersion was then ultracentrifuged using the Sorvall evolution RC superspeed centrifuge (Thermo Fischer Scientific, USA) at 20,000 rpm for 30 min and blank PNSPs pellets were collected and redispersed in distilled water and stored at -20°C for further testing.

2.5. Preparation of MTX/ZA co-loaded PNSPs (MTX-ZA-CS-NPs)

Following the experimental design, MTX-ZA-CS-NPs were prepared according to our previously optimized ionic gelation method [26–28]. Briefly, MTX solution (0.1% w/v) was prepared by mixing 10 mg of MTX powder into 10 mL of co-solvent (8 mL ethanol:2 mL DMSO) under constant magnetic stirring at 500 rpm for 1 h. Similarly, ZA solution (0.1% w/v) was prepared by mixing 10 mg of ZA powder into 10 mL of purified distilled water under constant magnetic stirring at 500 rpm for 1 h. To fabricate MTX-ZA-CS-NPs, 25 mL of pre-formed CS solution (0.1, 0.3, 0.5% w/v) was incubated with 1 mL of MTX (0.1% w/v) and ZA (0.1% w/v) solutions by keeping the mixture on magnetic stirrer (700 rpm) for 30 min and afterward 10 mL of TPP solution was added dropwise in the mixture while constant stirring at 700 rpm. To optimize the loading efficiency of both drugs, MTX-ZA-CS-NPs dispersion was kept on magnetic stirrer for additional 30 min. Subsequently, the fabricated MTX-ZA-CS-NPs dispersion was subjected to ultracentrifugation at 20,000 rpm for 30 min. The supernatants were collected for estimation of encapsulation efficiency (%EE) and loading capacity (%LC) while MTX-ZA-CS-NPs pellets were collected and re-dispersed in purified distilled water for further testing of physicochemical characteristics.

2.6. Functionalization of MTX-ZA-CS-NPs with HA

To install CD44-mediated dual targeting feature, the fabricated MTX-ZA-CS-NPs were functionalized with HA [26–28] in accordance with the experimental design generated by Design-Expert® software. The surface functionalization of MTX-ZA-CS-NPs was carried out with three different HA concentrations (0.001, 0.0255, 0.05% w/v) for the purpose of optimization of physicochemical characteristics. Briefly, HA solution (0.001, 0.0255, 0.05% w/v) was prepared in sodium acetate buffer (pH 5.5) by magnetically stirring the mixture at 1200 rpm for 30 min. Finally, MTX-ZA-CS-NPs dispersions were added into HA solutions dropwise at a volume-ratio of 1:1 of CS-NP: HA and the mixture was kept on magnetic stirring for 3 h for efficient surface decoration. The HA-functionalized PNSPs (HA-MTX-ZA-CS-NPs) were then harvested by ultracentrifugation (20,000 rpm for 30 min) and stored at -20°C for further testing.

2.7. Physicochemical characterization

The average particle size, polydispersity index (PDI) and zeta potential of fabricated PNSPs and HA-PNSPs were measured using the Malvern Nano-ZS Zetasizer (Malvern Instruments, UK) principled at dynamic laser light scattering (DLS) technique. Each measurement was performed in triplicate and results were reported as mean ± standard deviation (S.D).

2.8. Measurements of %EE and %LC

The %EE and %LC of MTX and ZA were estimated using the high-performance liquid chromatography (HPLC). For that, freshly prepared HA-PNSPs dispersions were ultracentrifuged at 20,000 rpm for 30 min and supernatants were harvested and subjected to HPLC to indirectly analyze the amount of both encapsulated drugs into HA-PNSPs. The λ_max for MTX and ZA were 303 and 230 nm, respectively. For accuracy, standard curves for both drugs were established using the serial dilutions. The %EE and %LC of both drugs were calculated using the following formulae [26–28]:

$$EE \left(\%\right) = Initial amount of drug – free drug in supernatant) / (initial amount of drug) x 100$$

$$\text{L}\text{C} \left(\text{\%}\right) = \text{I}\text{n}\text{i}\text{t}\text{i}\text{a}\text{l} \text{a}\text{m}\text{o}\text{u}\text{n}\text{t} \text{o}\text{f} \text{d}\text{r}\text{u}\text{g} – \text{f}\text{r}\text{e}\text{e} \text{d}\text{r}\text{u}\text{g} \text{i}\text{n} \text{s}\text{u}\text{p}\text{e}\text{r}\text{n}\text{a}\text{t}\text{a}\text{n}\text{t}) / \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{f}\text{r}\text{e}\text{e}\text{z}\text{e}-\text{d}\text{r}\text{i}\text{e}\text{d} \text{C}\text{S}\text{N}\text{P}\text{s}) \text{x} 100$$

2.9. Fourier transform infra-red (FT-IR) spectrophotometric analysis

For qualitative validation of successful loading of MTX and ZA on PNSPs and functionalization with HA, FT-IR analysis was conducted. Briefly, 2.0 mg of lyophilized powder of HA-MTX-ZA-CS-NPs was thoroughly ground with KBr (98 mg) using the mortar and pestle. Prior to grinding, all the test samples were placed in oven overnight for complete drying. The well-ground dried samples were then put under hydraulic press to prepare scannable pellets. The prepared scannable pellets were then fixed in a sample holder and placed in the instrument for scanning at 4000 − 400 cm^− 1 with resolution of 2 cm^− 1. Results were evaluated by comparing the fingerprint peaks as well as shifts in peaks of various functional groups which indicate molecular changes due to specific molecular interactions. Same protocol was followed for scanning of unfunctionalized MTX-ZA-CS-NPs as well as the raw material such as pure CS, MTX, ZA, and HA.

2.10. X-ray diffraction (XRD) analysis

XRD analysis was executed to determine crystallographic structure and to estimate structural and molecular changes that might happen during encapsulation of drugs within the core or adsorption on the shell of polymeric matrix of PNSPs. This technique is also widely used to evaluate the crystallinity or amorphousness of a test material or to identify possible transitions between crystalline and amorphous forms. The crystallography of fabricated HA-MTX-ZA-CS-NPs was performed by using the X-Ray Diffractometer (RIGAKU ULTIMA IV, TYPE II, and HE-2001Q). The scanning rate of diffractogram of samples was 2°/min and was recorded in the range of 2θ = 1–100°. Same protocol was followed for scanning of unfunctionalized MTX-ZA-CS-NPs as well as the raw material such as pure CS, MTX, ZA, and HA.

2.11. Nuclear magnetic resonance (NMR) spectroscopic analysis

All test samples were dissolved in deuterated DMSO and subjected to NMR spectroscopic analysis. NMR experiments were performed using Bruker Ascend 600 spectrophotometer. ¹H NMR signals were recorded at 600 MHz and ¹³C NMR at 150 MHz in DMSO-d6 using Bruker Avance III Ascend spectrophotometer equipped with Z-gradient 5 mm BBO probe using the standard pulse sequences and pulse cycling. Each sample was calibrated at 90° high-power pulse for ¹H. The sample temperature was set at 300 K. A 2D NOESY spectrum was recorded with 440 increments (64 scans each) in t₁ time domain and 2,000 complex points in t₂ time domain using a spectral width of 8,500 Hz in both dimensions with ¹H carrier on solvent. NMR spectra were processed and plotted using MestRenova suite version 11.0. Mnova provides an interface for processing and plotting NMR data.

2.12. Morphological examination

The scanning electron microscopy (SEM) was employed to analyze surface morphology of unfunctionalized PNSPs (MTX-ZA-CS-NPs) and HA-functionalized PNSPs (HA-MTX-ZA-CS-NPs). For that, prepared PNSPs dispersions were subjected to ultracentrifugation (20,000 rpm for 30 min) and pellets were collected and stored in the freezer (-20°C). The frozen PNSPs dispersions were then subjected to lyophilization for 24 to 48 h. To minimize dehydration effects during lyophilization, the fabricated PNSPs were pre-treated with mannitol as a lyoprotectant. The lyophilized PNSPs were then redispersed in phosphate buffered saline (PBS) (pH 7.4). To ensure complete redispersion in PBS, PNSPs dispersions were subjected to sonication for 5–10 min using Branson 2510 Ultrasonic Cleaner (Marshall Scientific, USA). Afterward, one drop of PNSPs dispersion was spread over the slide and carefully covered with coverslip and left to dry under vacuum. The test sample was then fixed on a carbon tape and a gold sputter module in a high vacuum was used to sputter coated the dried PNSPs. The gold coated PNSPs were scanned, and images were captured at an acceleration voltage of 3.0 kV using a Thermo Scientific Apreo SEM.

2.13. Storage colloidal stability

To find suitable storage medium and conditions for HA-PNSPs (HA-MTX-ZA-CS-NPs), a series of experiments were carried out while storing the fabricated PNSPs and HA-PNSPs in the refrigerator (2–8°C) for 8 weeks. Briefly, MTX-ZA-CS-NPs and HA-MTX-ZA-CS-NPs were prepared and ultracentrifuged (20,000 rpm for 20 min) followed by their redispersion in PBS (pH 7.4) and storage in the refrigerator (2–8°C) [26–28]. At different time points, 1 mL sample of PNSPs and HA-PNSPs dispersions were withdrawn and analyzed using the Malvern Nano-ZS Zetasizer (Malvern Instruments, UK) to evaluate any significant changes in the particle size, PDI and zeta potential of PNSPs.

2.14. In vitro drug release kinetics

Drug release mechanism is a crucial feature of any formulation which predict its behavior, stability, performance, pharmacokinetics, dosage frequency, and therapeutic efficacy [27, 28]. To estimate the release pattern of encapsulated/adsorbed drugs (MTX and ZA), freshly prepared PNSPs and HA-PNSPs were harvested by ultracentrifugation and uniformly redispersed into PBS at two different pHs (pHs 5.0 and 7.4). The PNSPs dispersion was then transferred to a dialysis bag which was then tied up from both ends. The dialysis bag was then submerged in 10 mL of release media (PBS at pH 5.0 and 7.4) and placed in water bath at 37°C at 200 rpm. At different time points, 1 mL of dialysate was taken and replaced with same volume of fresh PBS. The amount of MTX and ZA released from the core or shells of the PNSPs into the dialysate was measured using the UV-Visible spectroscopy [26–28].

2.15. Molecular docking

Molecular docking is a unique tool in structural molecular biology and computer-assisted drug design. This technique provides useful information to predict predominant mode(s) of interaction between the small molecule (e.g., drug or ligand) and the protein molecule (e.g., binding site of target receptor) to form a stable 3D structure. Hence, to comprehend possible interactions between HA (ligand) and CD44 receptors (binding site), we performed molecular docking by employing the program Autodock Vina [29]. A high resolution (1.08 Å) X-ray crystal structure of the human cell surface receptor CD44 hyaluronan binding domain was extracted from the RSCB protein data bank (http://www.rcsb.org) under the entry code PDB ID: 4PZ3. The complexed peptide was extracted from the initial X-ray structure followed by removal of water molecules. Polar hydrogens and Gastieger charges were added and the corresponding charge files were generated using the MGL Tools. A short hexamer of hyaluronic acid (GlcUA-GlcNAc-GlcUA-GlcNAc-GlcUA-GlcNAc) was drawn using the software ChemDraw Ultra 15.0 (Cambridge Soft Corporation, USA) and the lowest energy conformation was obtained by means of MOPAC2012 program [30] embedded within VEGA-ZZ® [31, 32]. The accurate energy minimization was achieved by Austin Model-1 (AM1) semiemperical force-field within MOPAC. Later, a grid box of the size (24 Å³) was established to cover the hyaluronan binding domain, with a spacing of 1.0 Å between the grid points. The box was centered toward the coordinates of (4.71×3.71×16.61). The exhaustiveness and the number of poses were set to 12 and 10 respectively. The 3D-best docked poses were visualized via Discovery Studio® visualizer (Dassault Systèmes Biovia Corporation, France).

2.16. Cell culture studies

A series of experiments were conducted to investigate the cytotoxicity, IC₅₀, cell morphology, cell uptake efficiency, and mechanism of intracellular trafficking of optimized HA-PNSPs (HA-MTX-ZA-CS-NPs) in comparison with unfunctionalized PNSPs (MTX-ZA-CS-NPs), blank CS-NPs (with no drugs), HA-coated blank CS-NPs, free drugs (MTX + ZA), and untreated (control). Two different cell lines such as human prostate adenocarcinoma cells (PC-3 cells) and M2-phenotype of TAMs (RAW 264.7) were employed in these experiments. PC-3 cells were cultured in Roswell Park Memorial Institute (RPMI-1640) medium supplemented with 10% fetal bovine serum (FBS) and 1% streptomycin/penicillin, and RAW 264.7 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) containing 10% FBS and 1% streptomycin/penicillin. The cultured cell lines were maintained at 37°C in an incubator with a controlled humidified atmosphere composed of 5% CO₂.

2.16.1. Cytotoxicity and IC₅₀

The half-maximal inhibitory concentration (IC₅₀) is a widely used pharmacological parameter to estimate the efficacy of a drug formulation. Therefore, we estimated IC₅₀ value of HA-functionalized PNSPs (HA-MTX-ZA-CS-NPs) in comparison with unfunctionalized PNSPs (MTX-ZA-CS-NPs), blank CS-NPs, HA-functionalized blank CS-NPs, free drugs (MTX + ZA), and control (untreated) using the MTT (3-(4, 5-dimethyldiazol-2-yl)-2, 5-diphenyltetrazolium bromide) assay. Briefly, 5×10³ cells were seeded into each well of a 96-well plate and were treated with different concentrations of test samples or remained untreated. After 24 h, 10 µL of 5 mg/mL MTT solution was added into each well and the plate was incubated at 37⁰C for 4 h. At the end of incubation time, medium was removed from each well and 100 µL of DMSO was added to dissolve formazan crystals and the optical density (OD) of each well was measured at 570 nm using a Synergy H1 (BioTek) ultraviolet spectrophotometer. The percentage of viable cells was calculated using the following equation:

$$\text{C}\text{e}\text{l}\text{l} \text{v}\text{i}\text{a}\text{b}\text{i}\text{l}\text{i}\text{t}\text{y} \left(\text{\%}\right)=\left(\text{O}\text{D} \text{o}\text{f} \text{t}\text{e}\text{s}\text{t} \text{w}\text{e}\text{l}\text{l}\right)/\left(\text{O}\text{D} \text{o}\text{f} \text{r}\text{e}\text{f}\text{e}\text{r}\text{e}\text{n}\text{c}\text{e} \text{w}\text{e}\text{l}\text{l}\right) \times 100$$

2.16.2. Cell uptake efficiency

The cell uptake efficiency of HA-PNSPs into PC cells (PC-3) and M2-macrophages (RAW 264.7 cells) was evaluated using the confocal microscopy and flow cytometry. Briefly, 1×10³ cells were seeded into each well of 6-well plate followed by placing the coverslip over the plate and stored at 37°C for 24 h to allow cells to adhere. Next day, cells were treated with HA-functionalized coumarin (CMR)-loaded CS-NPs (HA-CMR-CS-NPs) for 24 h at 37°C. Same protocol was used for treating the cells with unfunctionalized CMR-loaded CS-NPs (CMR-CS-NPs), free CMR, and control (untreated). After 24 h, cells were washed thrice with PBS (pH 7.4) and then fixed using the 5% paraformaldehyde (PFA) solution for 30 min. The fixed cells were washed again with PBS twice and cell nuclei were then stained with a mounting solution containing DAPI for 20 min at room temperature. Finally, fluorescent images of cells treated with different formulations were taken using the confocal microscope (Nikon eclipse Ti Melville, NY 11747 − 3064, USA) with a violet laser (405 nm) and blue laser (488 nm) at a magnification of 60×.

Taken together, flow cytometry was used to quantify the cell uptake efficiency of HA-CMR-CS-NPs into PC-3 and RAW 264.7 cells and results were compared with CMR-CS-NPs, free CMR, and control (untreated). After 24 h of treatment with testing nanoformulations, cells were collected by trypsinization and washed three times with PBS. Finally, collected cells were analyzed to evaluate the intensity of CMR within both cells using the BD FACSAria III flow cytometer. Standard fluidics, optical and electronic configuration was used to acquire the resulting data by BD FACSDiva software and resulting data was further analyzed using the FlowJo software (FlowJo LLC., Ashland, Oregon, USA).

2.17. Specific CD44-mediated cell internalization

This experiment was performed to qualitatively evaluate the CD44-mediated internalization of HA-functionalized CMR-CS-NPs into PC-3 and RAW 264.7 cells in comparison with unfunctionalized CMR-CS-NPs, free CMR, and control (untreated). Briefly, PC-3 and RAW 264.7 cells were seeded and allowed to adhere on a glass coverslip placed on 6-well plates at a density of 1×10⁵ cells/well and were then treated for 2 h with 100 µg/mL of HA-CMR-CS-NPs, CMR-CS-NPs, free CMR, or left untreated. The treated cells were then washed with PBS twice and fixed with 4% PFA for 20 min. The fixed cells were then washed with PBS thrice and blocked with 1% bovine serum albumin (BSA) in PBS for 1 h. Afterward, treated cells were incubated with anti-CD44 Alexa Fluor™ 647 antibodies (1:100 dilution in primary antibody dilution buffer) overnight at 4°C followed by washing with PBS thrice. Afterward, cells were incubated with mounting media containing DAPI for 20 min at room temperature to stain cell nuclei. Finally, the fluorescent images of cells treated with different formulations were taken using the confocal microscope (Nikon eclipse Ti Melville, NY 11747 − 3064, USA) with a violet laser (405 nm) and blue laser (488 nm) at a magnification of 60×.

In addition, specific binding or co-localization of HA-functionalized CMR-CS-NPs and anti-CD44 Alexa Fluor™ 647 antibodies on CD44 receptors overexpressed on PC-3 and RAW 264.7 cells were also quantitatively assessed using the flow cytometry. Briefly, the PC-3 and RAW 264.7 cells were seeded into 6-well plates at a density of 1×10⁶ cells/well and incubated for 24 h. Next day, cells were treated with 100 µg/mL of HA-functionalized CMR-CS-NPs, unfunctionalized CMR-CS-NPs, free CMR, or left untreated overnight. The cells were then washed with PBS twice, scraped from the wells and centrifuged at 2000 rpm for 8 min at 4°C. Cell pellets were then resuspended in 100 µL of Flow Cytometry Staining (FACS) buffer containing 0.6 µg of anti-CD44 Alexa Fluor™ 647 antibody solution and were incubated at 4°C for 90 min in the dark. Subsequently, cells were centrifuged at 2000 rpm for 8 min at 4°C, washed with 1 mL of FASC buffer and then redispersed in 450 µL of cold PBS and subjected to analysis using BD FACSAria III flow cytometer. Standard fluidics, optical and electronic configuration was used to acquire data by BD FACSDiva software and resulting data was analyzed using FlowJo software (FlowJo LLC., Ashland, OR, USA)

2.18. Anti-metastatic efficacy

The migration of cancer cells plays paramount role in cancer progression, invasion, and metastasis; hence, we performed scratch assay to evaluate the effect of HA-MTX-ZA-CS-NPs on migration and proliferation of PC-3 cells. Briefly, 1×10⁵ PC-3 cells/well were seeded into 24-well plates and incubated for 24 h at 37°C to form confluent cell monolayer. Once monolayer confluency was achieved, a scratch was introduced in cell monolayer in a straight line using the 1 mm pipette tip. The cells were then treated with 100 µg/mL of HA-MTX-ZA-CS-NPs, unfunctionalized MTX-ZA-CS-NPs, free MTX + ZA, or remained untreated (control). Finally, the microscopic images were taken at 0 and 24 h using the light microscope (IM-3 OPTIKA).

2.19. Statistical analysis

All experiments were performed in triplicates independently and the results were presented as mean of three values ± standard deviation, unless mentioned otherwise. All results were statistically analyzed using Prism version 9 (GraphPad software, USA). For the comparison between two groups Student’s t-test was used and for multiple comparisons one-way analysis of variance (ANOVA) was employed.

3.1. Optimization of PNSPs by QbD approach

The PNSPs were prepared using the ionic gelation method and were optimized by employing the experimental QbD approach (Design Expert® software) in which effects of various CPPs and CMAs were studied on the desired CQAs of PNSPs [33]. The D-optimal response surface design indicated that investigated factors such as CS concentration (X₁), HA concentration (X₂) and homogenization (X₃) exerted a significant influence on CQAs of PNSPs (Table 2). The mean particle size (PS) of PNSPs was ranged from 161 nm to 2237 nm, PDI was ranged from 0.423 to 0.989, and zeta potential (ZP) was varied from 11 mV to 31.1 mV. A mathematical expression in the form of a second order polynomial equation was generated for each response (PS, PDI, and ZP) from the statistical analysis of the experimental design. The intercept and regression coefficients of the studied factors (X₁-X₃) were reported by these mathematical equations, as described below:

PS = 470.97 + 403.51X₁ + 680.85 X₂ + 7.19 X₃ + 199.92 X₁X₂-75.38 X₂X₃ + 517.07X₂²

PDI = 0.883 + 0.2064 X₁ + 0.0994X₂ + 0.0299X₃-0.0336X₁X₂-0.0089X₁X₃-0.0359X₂X₃-0.1940X₁²

ZP = 23.35-4.41X₁-2.48X₂ + 1.56X₃ + 1.96X₁X₂-0.3022X₁X₃-1.75X₂X₃-3.52X₁²

In accordance with outcomes of the experimental design (Table 3), models with highest adjusted R² and predicted R² and having a reasonable agreement between both parameters were chosen. The lack of fit test suggested that reduced quadratic model is the best fit to comprehend the influence of studied factors on the PS and quadratic models were best fit to understand the effect of studied factors on other two responses (PDI and ZP). The plot surfaces of all responses under the influence of studied factors have been presented in Figs. 2 and 3.

Table 3

Outcome of the experimental design.
Response	Model	R²	Adjusted R²	Predicted R²	Lack of fit p-value	Model p-value	Most significant terms
PS (nm)	Reduced quadratic	0.9843	0.9764	0.9651	< 0.0001	< 0.0001	X₁ (p < 0.0001) X₂ (p < 0.0001) X₁X₂ (p = 0.0002) X₂X₃ (p = 0.0434)
PDI	Quadratic	0.9584	0.9252	0.8734	0.1624	< 0.0001	X₁ (p < 0.0001) X₂ (p = 0.0002)
ZP (mV)	Quadratic	0.9208	0.8575	0.7308	0.7090	0.0001	X₁ (p < 0.0001) X₂ (p = 0.0033) X₃ (p = 0.0237) X₁X₂ (p = 0.0202) X₂X₃ (p = 0.0222)

3.1.1. Effect of CS concentration

PS is a critically important characteristic of PNSPs which imparts paramount impact on their colloidal stability, release behavior (burst or sustained), pharmacokinetics, tissue biodistribution (i.e., EPR), membrane permeability and diffusivity, therapeutic efficacy, clearance, and safety profile [34, 35]. In contrast to bigger PS, the PNSPs having relatively smaller PS (< 200 nm) showed better pharmacokinetic profile, diffusivity, tissue biodistribution, cell internalization efficiency, and therapeutic efficacy. The statistical analysis of our data indicated that CS concentration (X₁) exhibited a significant (p < 0.0001) impact on the PS of PNSPs (Table 3). A linear increase in the PS was observed when CS concentration was increased (0.1–0.5% w/v) and smallest PS (⁓161 nm) was obtained at 0.1% w/v CS concentration (Fig. 2). The consistent increase in PS with CS concentration was expected to be due to increased viscosity of CS solution which could hinder the ability of PNSPs to assemble and stabilize and ultimately results in formation of larger aggregates [26, 27]. Another explanation could be variation in the ionic strength of the solution at different CS concentrations. At acidic pH, CS acts as a polycation and TPP acts as polyanion, and the ionic entanglement between these two counter-ions results in the formation of PNSPs. However, an increase in CS concentration while keeping the TPP concentration unchanged might have resulted in week entanglement between CS and TPP and ultimately led to formation of bigger PNSPs [26, 27].

Another important property of a nanocarrier is the PDI (size distribution index) which indicates consistency and aggregation potential of nanocarriers. PDI also has a great impact on the colloidal stability of the nanosystem; a narrow PDI (value nearest to zero) indicates more stable nanosystem due to lesser tendency of Ostwald ripening upon exposure to the fluctuating temperature and vice versa [26, 27]. The statistical analysis of our data obtained from QbD approach indicated that CS concentration (X₁) has a significant (p < 0.0001) influence on PDI (Y₂) of PNSPs (Table 3). In general, an increase in CS concentration resulted in an increased PDI of PNSPs with smallest PDI (0.423) obtained at 0.1% w/v CS concentration (Table 2).

Zeta potential (ZP) is also a paramount characteristic which has great impact on the colloidal stability, aggregation potential, membrane permeability and diffusivity, pharmacokinetics, tissue distribution, cell uptake, clearance, and therapeutic efficacy of PNSPs [34, 35]. Our results indicated that CS concentration (X₁) has a significant (p < 0.0001) effect on ZP (Y₃) of PNSPs (Table 3), and as per our desired goals highest ZP (31 mV) was obtained at 0.1% w/v CS concentration (Table 2). The cationic charge of CS-NPs is due to protonated amino groups (–NH₃⁺) on the contour of CS when dissolve in an acidic medium. The increase in CS concentration contributes more positive charge due to higher protonation of amino groups and thus results in greater zeta potential [26, 27]. Moreover, a significant 2-FI effect was noted on PS (p = 0.0002) and ZP (p = 0.0202) between CS (X₁) and HA concentrations (X₂). These findings clearly demonstrated that CS concentration is an imperative CMA which should be considered while designing the PNSPs because it significantly affects different CQAs (e.g., PS, PDI, and ZP), and exhibits significant 2-FI effect with other factors such as HA concentration (Table 3).

3.1.2. Effect of HA concentration

HA functionalization of PNSPs was carried out to aid CD44-mediated dual targeting of PC-3 cells and M2-macrophages (RAW 264.7 cells) having overexpressed CD44 receptors on their cell surface. HA functionalization not only improve active targetability of various cells, but also improves blood compatibility of PNSPs. Our results indicated that HA concentration (X₂) exhibits a significant (p < 0.0001) impact on the PS (Y₁) of PNSPs (Table 3). The PS of PNSPs was significantly increased from 161 nm to 2237 nm when HA concentration was increased from 0.001–0.05% w/v, and the smallest PS (⁓161 nm) was obtained at lowest concentration of HA (0.001% w/v) (Table 2). HA is a polyanionic molecule which develops good ionic interaction with polycationic molecules like CS. The incubation of PNSPs (CS-NPs) with HA was expectedly resulted in ionic adsorption of anionic HA chain on the corona of cationic CS-NPs. The ionic adsorption of HA chains on the contour of CS-NPs was appeared in the form an additional polymeric layer (coating), and the increase in HA concentration increase the thickness of surface coating and would ultimately increase the mean PS of PNSPs [26–28].

HA concentration (X₂) has also shown a significant (p = 0.0002) influence on PDI (Y₂) of PNSPs ranging from 0.423 to 0.989 when HA concentration was increased from 0.001–0.05% w/v. This could be due to variation in polyelectrolyte complexation and self-assembly between CS and HA because of change in viscosity of the solution at different HA concentrations. At relatively lower HA concentrations, PNSPs with narrow PDI were produced and the lowest PDI (0.423) was obtained at lowest HA concentration (0.001% w/v). The statistical analysis of our resulting data also demonstrated a significant (p = 0.0033) effect of HA concentration (X₂) on ZP (Y₃) of PNSPs. An increase in HA concentration from 0.001–0.05% w/v results in a consistent decrease in ZP of PNSPs (Fig. 2), and in accordance with our optimization goals, highest ZP (⁓31 mV) was obtained at lowest HA concentration (0.001% w/v). An obvious decline in the ZP of PNSPs upon increasing the HA concentration was expected to be due to neutralization of cationic charge (amino groups, –NH₃⁺) on CS-NPs due to ionic adsorption of polyanionic HA molecules on the cationic contour of PNSPs [26, 27]. In addition, a significant 2-FI effect was noted on PS (p = 0.0002) and ZP (p = 0.0202) due to interaction between CS (X₁) and HA concentrations (X₂), and a moderately significant 2-FI effect was observed on PS (p = 0.0434) and ZP (p = 0.0222) due to interaction between HA concentration (X₂) and homogenization (X₃). These results indicated that HA concentration is an essential factor to be considered while preparing PNSPs.

3.1.3. Effect of homogenization

A complete solubilization of CS into acidified water (0.2% v/v acetic acid in water) is highly crucial for preparation of CS-NPs via ionic gelation method. Any insoluble polymer residue does not participate in the ionic crosslinking process with the polyanion (e.g., TPP). Therefore, to ensure a complete solubilization of CS prior to the ionic gelation process, we employed an additional homogenization step in which PNSPs dispersion were subjected to an additional homogenization step for 30 min using the T23 digital ULTRA TURRAX stirrer homogenizer (IKA, Germany) at 15,000 rpm.

The statistical analysis of our data revealed that additional homogenization (X₃) has no significant effect on PS (Y₁) and PDI (Y₂); however, a moderately significant (p = 0.0237) effect was noticed on ZP (Y₃) of PNSPs. Moreover, a moderately significant 2-FI effect on PS (p = 0.0434) and ZP (p = 0.0222) was observed due to interaction with HA concentration (X₂). These findings indicated that additional homogenization is not essential to produce desired PNSPs; however, it may have some impact on physicochemical properties.

3.1.4. Selection of optimal PNSPs formulation

Based on our optimization results, PNSPs produced with 0.1% (w/v) CS concentration, 0.002% HA concentration, and an additional homogenization for 30 min were found to be the most desirable. The optimized formulation exhibited a desirability value of 0.964 which indicates a high level of optimization for all the CQAs (Fig. 3). In accordance with our optimization goals (Table 1), the CQAs of the optimized PNSPs were PS of ⁓160 nm, PDI of 0.45, and ZP of ⁓30 mV (Fig. 3).

For passive targeting of tumor tissues (EPR effect) and interaction with various biological targets (i.e., receptors, enzymes, etc.), PS, PDI and ZP of PNSPs play a paramount role [9–11]. The PNSPs exhibiting a PS of < 200 nm, narrow PDI (nearest to zero), and cationic ZP (> 30 mV) are favorite for passive tumor targeting. The smaller PNSPs can relatively more permeable through underdeveloped capillaries and leaky endothelium in the tumor tissue and can retain in tumor tissues for days and even weeks due to lack of lymphatic drainage [16, 17]. Moreover, installation of HA as a targeting ligand on the surface of PNSPs for selective targeting of CD44 receptors that are heavily expressed on PC cells and M2-macrophages could be a smarter approach to achieve desired therapeutic outcomes for treatment of PC.

3.1.5. %EE and %LC

The optimized nanoformulations (MTX-ZA-CS-NPs and HA-MTX-ZA-CS-NPs) were subjected to measurement of %EE and %LC. The resulting data suggested good %EE of both drugs (MTX 85.3% and ZA 79.2%) in MTX-ZA-CS-NPs; however, the EE% of both drugs was surprisingly higher in case of HA-MTX-ZA-CS-NPs (MTX 92.5% and ZA 87.6%). This was attributed to additional HA coating on the surface of HA-PNSPs which might resist desorption of adsorbed drug molecules with ultimate higher %EE. Likewise, %LC of both drugs was also higher in case of HA-MTX-ZA-CS-NPs (MTX 37.1% and ZA 31.8%) compared to MTX-ZA-CS-NPs (MTX 32.4% and ZA 26.7%). The optimized PNSPs were subjected to ultracentrifugation and lyophilization prior to further testing.

3.2. FT-IR analysis

In this technique, test sample is exposed to IR radiations and some of the radiations are absorbed by the sample and unabsorbed (transmitted) radiations are recorded in the form a fingerprint. Every molecule has a unique fingerprint, and any conformational changes in the fingerprint indicates a possible chemical change in the structure of a molecule. Therefore, to qualitatively validate successful encapsulation of chemotherapeutic agents (MTX and ZA) and functionalization of PNSPs with HA, we performed FT-IR analysis (Fig. 4A). The most important characteristic peaks appeared in the FT-IR spectra of pure CS were 3374 cm^− 1 (–OH stretching), 2880 cm^− 1 (C-H stretching), 1654 cm^− 1 (C = O stretching), 1595 cm^− 1 (N-H bending), 1378 cm^− 1 and 1323 cm^− 1 (C-N stretching), and 1074 cm^− 1 (C-O-C stretching) [26–28]. The FT-IR spectra of HA has also shown various characteristic peaks at 3410 cm^− 1 (–OH stretching), 2899 cm^− 1 (C-H stretching), 1613 cm^− 1 (C = O stretching), 1410 cm^− 1 (N-H bending), and 1044 cm^− 1 (C-O-C stretching). MTX spectra identified characteristics peaks at 3355 cm^− 1 (–OH stretching), 1645 cm^− 1 and 1603 cm^− 1 (C = O stretching), 1405 cm^− 1 (C-H bending), and 1208 cm^− 1 (C-O-C stretching). ZA spectra displayed different peaks at 3576 cm^− 1 and 3442 cm^− 1 (–OH stretching), 2880 cm^− 1 (C-H stretching), 1640 cm^− 1 (C = O stretching), 1580 cm^− 1 (N-H bending), 1375 cm^− 1 and 1323 cm^− 1 (C-N stretching), and 1094 cm^− 1 (C-O-C stretching). Upon the interpretation of resulted fingerprints, it was noticed that the characteristic peak of –OH stretching (3374 cm^− 1) in the spectra of pure CS was shifted to 3266 cm^− 1 and 3242 cm^− 1 in the spectra of MTX-ZA-CS-NPs and HA-MTX-ZA-CS-NPs, respectively (Fig. 4A). These shifts indicate enhanced hydrogen bonding and atomic interactions between CS (–NH₃⁺), encapsulated drugs (MTX and ZA), and HA molecules. Similarly, the characteristic peak of C-H stretching which was appeared at 2880 cm^− 1 in CS spectra was shifted to 2937 cm^− 1 and 2951 cm^− 1 in the spectra of MTX-ZA-CS-NPs and HA-MTX-ZA-CS-NPs, respectively (Fig. 4A). These shifts (carbon–hydrogen stretching) also indicate conformational changes in the chemical structure of CS due to probable interactions between CS, MTX, ZA, and HA. Other conformational changes were witnessed through shifting of 1654 cm^− 1 (C = O stretching) and 1595 cm^− 1 (N-H bending) peaks in the pure CS spectra to 1735 cm^− 1 (C = O stretching) and 1648 cm^− 1 (N-H bending) in the spectra of HA-MTX-ZA-CS-NPs (Fig. 4A). Moreover, the characteristic peaks appeared at 1378 cm^− 1 and 1323 cm^− 1 (C-N stretching) in the pure CS spectra were also shifted to 1352 cm^− 1 and 1379 cm^− 1 (C-N stretching) in the spectra of HA-MTX-ZA-CS-NPs. All these conformational changes in the fingerprint of HA-PNSPs in comparison to pure CS validated loading of MTX and ZA on CS matrix and functionalization with HA (Fig. 4A).

3.3. XRD analysis

XRD works on the principle of irradiating a test material with monochromatic X-rays and then measuring the intensity and scattering angle of radiation that leaves the test material. Any conformational changes in the crystallographic structure (amorphous or crystalline) or atomic orientation of a material is recorded in the form of intensity and scattering angles [26, 27]. Our results indicated that XRD diffractogram of pure CS depicted two broader peaks at 2θ 10.2˚ and 19.7˚ which indicated amorphous nature of CS (Fig. 4B) [26, 27]. The XRD pattern of HA showed one broader peak at 2θ 19.8˚ and no sharp peaks which also indicates amorphous crystallography. On the other hand, XRD diffractogram of MTX displayed multiple sharp peaks at 2θ 9.3˚, 12.9˚, 14.4˚, 16.4˚, 19.5˚, and 26.9˚, which indicated its crystalline nature. Likewise, the XRD pattern of ZA showed multiple sharp peaks at 2θ 12.6˚, 12.7˚, 25.6˚, 29.1˚, and 35.0˚ which identifies its crystalline nature. The XRD pattern of MTX-ZA-CS-NPs and HA-MTX-ZA-CS-NPs displayed some characteristic peaks with low intensity at 2θ 9.5˚, 17.9˚, 18.9˚, 19.9˚, and 22.9˚ which specifies increase in crystallinity of PNSPs compared to pure CS. This distinct conformational change in the crystallographic structure of CS from amorphous to slightly crystalline is expected to be due to encapsulation of crystalline drugs (MTX and ZA) in the polymeric matrix of CS. Moreover, it was found that two characteristic peaks appeared in the XRD patter of pure CS were shifted from 2θ 10.2˚ and 19.7˚ to 2θ 9.5˚ and 17.9˚ (Fig. 4B) which also validate changes in the chemical composition and structure of CS after encapsulation of drugs and functionalization with HA [26, 27].

3.4. NMR analysis

NMR spectroscopy is a highly linear technique. The high-resolution ¹H, ¹³C NMR and 2D NOESY spectra of CS, MTX, ZA, HA, MTX-ZA-CS-NPs, and HA-MTX-ZA-CS-NPs samples were recorded in DMSO-d6 using Bruker Avance III Ascend spectrometer. The ¹H NMR spectrum of MTX-ZA-CS-NPs sample, when compared with the spectra of MTX and ZA displayed less intensity of aromatic signals of MTX resonated at δ 8.5, 7.70 and 6.82 along with the absence of aromatic proton signal resonated at δ 8.2 and methylene protons signals at δ 4.79 (Fig. 4C). ZA aromatic proton signals resonated at δ 8.9, 7.6, 7.5 exhibited the upfield shift of aromatic protons resonated at δ 6.8 and 8.5 in HA-MTX-ZA-CS-NPs ¹H NMR spectrum with slight shift of methylene protons of ZA (δ 4.5 to 4.4) (Fig. 4C), which clearly showed that hydrogen bonding was established between CS, MTX, ZA, and HA molecules. This complexation was further confirmed through HSQC assignments (¹H-¹³C) and weak aromatic protons coupling in DQF-COSY interactions. Furthermore, this was proven through 2D NOESY interactions.

3.5. Morphology

The dimensions (i.e., size, shape, surface morphology, etc.) of nanomaterials play a paramount role in the colloidal stability, pharmacokinetics, biodistribution, tissue accumulation, anticancer efficacy, and clearance from the body. The nanomaterials with relatively smaller size, spherical shape, and smooth surface morphology would result in better absorption, distribution, transmembrane diffusivity, cellular uptake, and therapeutic efficacy [26, 27, 35]. Herein, the surface morphology of our optimized nanoformulations was assessed using the SEM technique. The SEM image of unfunctionalized PNSPs (MTX-ZA-CS-NPs) displayed a uniform narrow distribution of spherical particles ranging from 80–100 nm (Fig. 5c). The HA-functionalized PNSPs (HA-MTX-ZA-CS-NPs) were also found uniformly distributed and spherical in shape, but they were slightly bigger in size (⁓120–160 nm) compared to unfunctionalized PNSPs (Fig. 5d). Moreover, HA-PNSPs have shown trivial tendency of agglomeration which was not observed in unfunctionalized PNSPs. It has also noted that particle size scale appeared in the SEM images (⁓80–120 nm) was relatively smaller than that of measured in DLS technique (Nano-ZS Zetasizer) (⁓150–180 nm) (Fig. 5a) which was attributed to dehydrating effect (evaporation of solvent) of lyophilization process resulting in moderate shrinkage of PNSPs. Having assessed ultra-fine particle size (⁓160 nm), spherical shape, and smooth surface morphology, we anticipated that our nanoformulation (HA-PNSPs) could be a plausible candidate for optimum cellular uptake and anticancer efficacy against PC cells and RAW 264.7 cells (M2-macrophages).

3.6. Storage stability

The storage stability of colloidal particles is highly crucial for intended application. The most imperative consideration in designing a nanoformulation is the interactions between dispersed particles (DLVO theory) and with dispersion medium (electrical double layer phenomenon) during storage. The electrical properties (surface charge) of nanomaterials are responsible for these interactions, and it may result in reversible (flocculation) or irreversible agglomeration (coagulation) of dispersed PNSPs which could ultimately impact the stability, performance, and safety of nanoformulation. Hence, we performed colloidal stability of our optimized nanoformulations (HA-PNSPs and PNSPs). Our research group has previously established that storage of PNSPs in the refrigerator (2–8°C) preserves their physicochemical properties [26, 27]; therefore, we adapted the same protocol and evaluated the storage stability of our new nanoformulations. The obtained results suggested that both nanoformulations remain stable over a period of 8 weeks when stored in the refrigerator. No significant changes in the mean particle size of MTX-ZA-CS-NPs (varied from ⁓90 nm to ⁓107 nm) and HA-MTX-ZA-CS-NPs (varied from ⁓164 nm to ⁓187 nm) (Fig. 5e) were evident throughout the storage period. On the other hand, zeta potential was varied from 33.2 mV to 34.6 mV for unfunctionalized PNSPs and from 28.7 mV to 32.8 mV for HA-PNSPs (Fig. 5f). These insignificant changes in the particle size and zeta potential suggested that both nanoformulations remained stable upon storage with no apparent tendency of flocculation and coagulation, particularly when stored in a buffered dispersion medium (PBS, pH 7.4).

3.7. In vitro drug release kinetics

The mechanism of drug release from a polymeric matrix system (e.g., PNSPs) depends on its physicochemical characteristics, nature, type of polymerization, and degradability. There are three possible mechanisms of drug release from a polymeric matrix system including, 1) diffusion, 2) degradation, and 3) swelling. Drug diffusion is the most common mechanism of drug release from a polymeric matrix where the encapsulated drug(s) diffuse out from the polymeric matrix based on concentration gradient by passing through pores of 3-D crosslinked polymeric network [36, 37]. Depending upon the nature of polymer used, encapsulated drug(s) may also release from a polymeric matrix due to erosion or degradation of polymer in the biological environment. Some polymers absorb water or other fluid(s) and undergo swelling and ultimately release encapsulated drug(s) in the release media. The swelling of polymers can also be triggered by various factors such as change in pH, temperature, light, and ionic strength [36–38].

Our results depicted that both optimized nanoformulations (PNSPs and HA-PNSPs) exhibited a biphasic release pattern with ⁓50% release from unfunctionalized PNSPs and ⁓40% release from HA-functionalized PNSPs within first 5 h followed by a sustained release over 3–4 days. Interestingly, the release of both encapsulated drugs was more pronounced at pH 5.0 (Fig. 5h) compared to pH 7.4 (Fig. 5g) at 37°C. This was expected to be due to swelling of CS matrix (increase in mesh size) because of strong repulsion between alike amino groups (–NH₃⁺) on the adjacent CS chains. It has also noted that HA-functionalized PNSPs (HA-MTX-ZA-CS-NPs) displayed a relatively slower release of both drugs (⁓60% MTX and ⁓40% ZA) compared to unfunctionalized PNSPs (⁓70% MTX and ⁓60% ZA) until 72 h (Fig. 5g & h). This could be due to neutralization of amino groups (–NH₃⁺) on adjacent CS chains because of adsorption of polyanionic HA, which could have undermined ionic repulsion between alike charges and ultimately less swelling of CS network [36]. Another possible explanation could be the existence of an additional layer of HA coating on CS matrix which could have restricted swelling of CS network with ultimate lesser diffusion of encapsulated drugs [26, 27]. The release data also depicted that ZA release was relatively slower than MTX from both nanoformulations which could be due to hydrophilic nature of ZA causing good interaction with CS chains and thus restrict its release from the polymeric matrix [36–38]. Overall, pH-responsive and sustained release rates of both encapsulated drugs from the optimized nanoformulation (HA-PNSPs) signify its potential to selectively deliver the chemotherapeutic drugs to TME which is slightly acidic compared to healthy body tissues [36].

3.8. Molecular docking

The phenotypic existence of CD44 receptors that are heavily expressed on different types of cancer make it an attractive biological target for site-specific delivery of chemotherapeutics. CD44 receptor contains a segment called “hyaluronan binding domain” which accommodates the hyaluronic acid oligosaccharide. This binding domain is a shallow surface groove which consists of many unique amino acids capable of establishing a strong hydrogen bonding with the corresponding HA. Therefore, to achieve CD44-mediated targeting, we evaluated the affinity and surface binding characteristics of HA-PNSPs by conducting molecular docking experiment between HA and hyaluronan binding domain of CD44.

Results of molecular docking experiment depicted a perfect fit between HA binding conformation and hyaluronan binding domain (Fig. 6a) with an affinity score of -8.7 Kcal/mole. HA was able to establish five conventional hydrogen bond interactions with five key amino acid residues including, Glu-37, Tyr-42, Cys-77, Ala-98, and Arg-150 (Fig. 6b). In addition, HA oligosaccharide was able to establish an attractive ionic interaction with a key amino acid residue labelled as Arg-78 (Fig. 6c). Taken together, some Alkyl/Pi-Alkyl interactions were also apparent between HA and three amino acid residues such as Tyr-42, Tyr-79, and Leu-107. Another set of hydrophobic interactions (Van-Der Waal, carbon-hydrogen, and Pi-Donor hydrogen) noted between HA and corresponding amino acid residues include Asn-25, Thr-27, His-35, Gly-40, Arg-41, Glu-75, Ile-88, Cys-97, Ala-99, and Tyr-114 (Fig. 6c). Overall, the results of molecular docking study along with high in-silico affinity score for specific binding of HA-PNSPs with the cell surface receptors CD44 evidenced an exceptional ability of our nanoformulation for targeted delivery of chemotherapeutics to cancer cells (PC-3) and M2-macrophages (RAW 264.7 cells) in the TME.

3.9. Cell culture studies

3.9.1. Cytotoxicity and IC₅₀

The cytotoxicity assay is a widely used biological technique to assess viability, cell damage (changes in cell morphology), and potency (IC₅₀) of cytotoxic compounds. Therefore, we carried out cytotoxicity test (MTT assay) against two different cell lines (PC-3 and RAW 264.7 cells). Our results indicated that PC-3 cells treated with blank CS-NPs and HA-CS-NPs displayed > 90% viability after 24 h treatment (Fig. 7a). These results were consistent with light microscopy images showing no apparent changes in PC-3 cells morphology when treated with blank CS-NPs and HA-CS-NPs (Fig. 7b). These findings indicated adequate biocompatibility of blank CS-NPs and HA-CS-NPs against both cell lines. A significant (⁓50%) decline in PC-3 cells viability was evidenced when treated with free drugs (MTX + ZA) compared to control (untreated) group. In consistent with these results, a marked disruption in cell membrane was observed in PC-3 cells treated with free drugs (MTX + ZA) which confirmed synergistic cytotoxic effect of both anticancer agents. The viability of PC-3 cells was dropped to 23.4% and 8.9% when treated with MTX-ZA-CS-NPs and HA-MTX-ZA-CS-NPs, respectively (Fig. 7a). The microscopic examination of these PC-3 cells apparently displayed cell detachment, cell membrane disruption, and leakage of cellular contents, indicating apoptosis and cell death (Fig. 7b). This observation was further validated by calculating the IC₅₀ values of test formulations against PC-3 cells. The lowest IC₅₀ value of HA-MTX-ZA-CS-NPs (2.817 µg) compared to MTX-ZA-CS NPs (4.324 µg) and free drugs (MTX + ZA) (10.47 µg) was evident (Fig. 7c) which was attributed to their paramount internalization efficiency into PC-3 cells compared to other formulations [39, 40].

Similar results were also observed in RAW 264.7 cells. The RAW 264.7 cells treated with blank CS-NPs and HA-CS-NPs displayed > 85% cell viability which indicates their adequate biocompatibility (Fig. 7d). The cell viability was significantly dropped when RAW 264.7 cells were treated with HA-MTX-ZA-CS-NPs (28%) compared to MTX-ZA-CS-NPs (40%) and free MTX + ZA (48%). The microscopic examination of RAW 264.7 cells treated with HA-MTX-ZA-CS-NPs depicted obvious morphological changes including shrinkage of cells, membrane disruption, and leakage of cellular contents compared to cells treated with other formulations (Fig. 7e). Moreover, IC₅₀ value of HA-MTX-ZA-CS-NPs (⁓15 µg) was significantly lower than MTX-ZA-CS-NPs (⁓25 µg) and free MTX + ZA (⁓32 µg) (Fig. 7f). The lowest cell viability and IC₅₀ value of HA-MTX-ZA-CS-NPs was attributed to enhanced CD44-mediated internalization into RAW 264.7 cells which ultimately induce apoptosis and autophagy in cancer cells and macrophages [39, 40].

3.9.2. Cell uptake efficiency

Cell internalization is critically important for a chemotherapeutic moiety for inducing cancer cell apoptosis, autophagy, and anticancer efficacy. Thus, to confirm cell uptake efficiency of HA-CMR-CS-NPs into PC-3 and RAW 264.7 cells in comparison with uncoated CMR-CS-NPs and free CMR, we employed confocal laser scanning microscopy (CLSM) and flow cytometry. In fluorescence microscopy, CMR (indicated as bright green color) is widely used as a fluorescent probe due to its emission spectrum therefore we used it as a model agent. DAPI (indicated as bright blue color) is commonly used for visualization of nuclei of target cells.

The CLSM image obtained for control (untreated) PC-3 cells displayed no apparent green color which suggested no cellular internalization (Fig. 8A–merge). The PC-3 cells treated with free CMR displayed low intensity of green color which indicated poor cell uptake efficiency of free CMR that could be due to its hydrophobic nature and poor cell penetrability. On the other hand, PC-3 cells treated with PNSPs (CMR-CS-NPs and HA-CMR-CS-NPs) depicted good cell internalization; however, intensity of green color was more pronounced in case of HA-functionalized CMR-CS-NPs (Fig. 8A–merge). The paramount cell internalization of HA-CMR-CS-NPs was attributed to CD44-mediated endocytosis due to interaction between HA (as a targeting ligand) and CD44 receptors overexpressed on PC-3 cells [41, 42]. The presence of bright green color in the periphery of bright blue color indicates that internalized HA-CMR-CS-NPs were primarily localized in the cytoplasm around the nuclei of PC-3 cells (Fig. 8A–merge). The cell uptake efficiency also largely depends on physicochemical properties (i.e., size, shape, surface chemistry, etc.) and composition of NPs. Owing to their ultra-fine PS (⁓160 nm), good surface charge (⁓30 mV), smooth spherical morphology, and functionalization with HA (as a targeting ligand), HA-CMR-CS-NPs demonstrated exceptional cell internalization into PC-3 cells [42, 43].

Taken together, cell internalization efficiency of optimized nanoformulations was also validated in RAW 264.7 cells (Fig. 8B–merge). The RAW 264.7 cells treated with free CMR displayed low fluorescent intensity (bright green color) indicating poor cell uptake efficiency of free CMR which could be due to its hydrophobicity and low permeability. On the other hand, CLSM images of RAW 264.7 cells treated with HA-CMR-CS-NPs and CMR-CS-NPs depicted good intensity of fluorescence which signified their higher internalization efficiency than free CMR. Like PC-3 cells, HA-functionalized CMR-CS-NPs showed highest cell uptake in RAW 264.7 cells compared to uncoated CMR-CS-NPs which is likely to be due to CD44-mediated endocytosis [44, 45]. These findings signify our rational behind HA-functionalization of PNSPs for selective targeting of chemotherapeutics to cancer cells (PC-3) and M2-TAMs (RAW 264.7 cells) for treatment of PC.

The cell internalization efficiency was also confirmed using the flow cytometry which is a well-recognized technique to quantitatively measure the uptake and accumulation of fluorescent probe in target cells. The obtained results were presented in Fig. 9, where x-axis represents relative fluorescence intensity and y-axis represents number of cells. It was evident that PC-3 cells treated with free CMR showed only 23.2% uptake compared to control (untreated) that showed no cell uptake (Fig. 9a). The poor uptake of free CMR into PC-3 cells was expected to be due to its physicochemical properties such as hydrophobicity and low permeability. The uptake of CMR into PC-3 cells was remarkably improved when delivered in the form of PNSPs (Fig. 9a), and highest cell uptake efficiency (93.9%) was depicted by HA-CMR-CS-NPs which was attributed to interaction of HA with CD44 receptors overexpressed on PC-3 cells (Fig. 9a) [44, 45]. The nanoscaled dimensions of HA-PNSPs also contribute to enhance cellular uptake of CMR in comparison to free CMR. The mean fluorescent intensity, which indicates cellular accumulation of fluorescent probe, was also quantitated using the flow cytometry (Fig. 9b). Results showed that mean fluorescent intensity obtained with HA-functionalized CMR-CS-NPs was significantly higher than unfunctionalized CMR-CS-NPs (**p = 0.0046) and free CMR (****p < 0.0001). These findings were consistent with CLSM outcomes.

Like PC-3 cells, flow cytometry was also employed to quantify cellular internalization of various formulations into RAW 264.7 cells (Fig. 9c & d). The RAW 264.7 cells treated with free CMR showed only 11.1% uptake and no apparent uptake in case of control (untreated) group. On the other hand, both PNSPs (CMR-CS-NPs and HA-CMR-CS-NPs) were efficiently taken up by the RAW 264.7 cells; however, cellular uptake was exceptional in case of HA-functionalized PNSPs (54%) which was attributed to heavily expressed CD44 receptors on RAW 264.7 cells surface (Fig. 9c) [44, 45]. These results were also validated by computing the mean fluorescent intensity of different test groups (Fig. 9d). As witnessed in PC-3 cells, the mean fluorescent intensity of RAW 264.7 cells treated with HA-CMR-CS-NPs was significantly (****p < 0.0001) higher than CMR-CS-NPs and free CMR, demonstrating highest CMR accumulation in RAW 264.7 cells when treated with HA-PNSPs (Fig. 9d). These findings demonstrate that HA-functionalization of PNSPs is a promising approach to improve CD44-mediated cell internalization into cancer cells and M2-TAMs [42–45].

3.10. Specific CD44-mediated endocytosis

The co-localization analysis, also known as competitive binding assay, is a common technique to evaluate trafficking of NPs into the target cells. We performed this experiment to find out the mechanism of cell internalization of our optimized nanoformulations. In this assay, we used a fluorescent antibody (anti-CD44 Alexa Fluor™ 647) which possesses a competitive binding affinity for CD44 receptors. Briefly, PC-3 cells were treated with HA-CMR-CS-NPs, CMR-CS-NPs, free CMR, or left untreated (control) and were subsequently exposed to anti-CD44 Alexa Fluor™ 647 antibody. The treated PC-3 cells were then analyzed using the CLSM and flow cytometry.

The resulting CLSM merged image of control (untreated) group depicted uniformly dispersed PC-3 cells with intact nuclei (acquiring bright blue color) surrounded by cell membrane with heavily expressed CD44 receptors (acquiring bright red color after binding with anti-CD44 antibody) (Fig. 10a). The CLSM merged image of PC-3 cells treated with free CMR showed a week intensity of blended fluorescence (green + red) which indicated poor co-localization of CMR at CD44 receptors. The intensity of blended fluorescence (green + red) was greatly improved in PC-3 cells treated with nanoformulations, particularly the intensity of fluorescence was distinguishing in HA-CMR-CS-NPs which was attributed to co-localization of HA-CMR-CS-NPs at CD44 receptors (Fig. 10a). These findings illustrated that HA-functionalized PNSPs mainly adapt CD44-mediated endocytosis pathway for internalization into PC-3 cells to induce apoptosis [46, 47]. On the other hand, PC-3 cells treated with unfunctionalized CMR-CS-NPs displayed a modest intensity of blended fluorescence which indicated that CD44-mediated endocytosis was not predominant mechanism of cell internalization for unfunctionalized PNSPs (Fig. 10a).

The mechanism of selective uptake of HA-functionalized CMR-CS-NPs into PC-3 cells was also investigated using the flow cytometry. In this quantitative analysis, we mainly focused on competitive binding of anti-CD44 antibody on CD44 receptors that was recorded as magnitude of fluorescent intensity. The zero fluorescent intensity measured in the control (untreated) group indicated no binding between anti-CD44 antibody and CD44 receptors because this group was taken as a baseline (Fig. 10b). The fluorescent intensity was highest (59.2) when PC-3 cells were treated with anti-CD44 antibody alone, which indicated that all CD44 receptors on PC-3 cells were competitively occupied by anti-CD44 antibody. The magnitude of fluorescent intensity was slightly decreased (56.7) when PC-3 cells were treated with free CMR which could be due to binding of some of the free CMR molecules on CD44 receptors which resulted in decrease in the total number of CD44 receptors available for binding with anti-CD44 antibody. The magnitude of fluorescent intensity was significantly dropped when PC-3 cells were treated with CMR-CS-NPs (25.7) but the fluorescent intensity was lowest when PC-3 cells were treated with HA-functionalized CMR-CS-NPs (1.19) (Fig. 10b). This was expected to be due to competitive binding of HA-CMR-CS-NPs to majority of CD44 receptors, resulting in only few CD44 receptors available for binding with anti-CD44 antibody [47, 48]. These results were consistent with CLSM outcomes that HA-functionalized PNSPs mainly rely on CD44-mediated endocytosis for internalization into PC-3 cells.

The CD44-mediated endocytosis of HA-functionalized PNSPs into PC-3 cells was also confirmed in terms of total expression of CD44 receptors on PC-33 cells using the flow cytometry (Fig. 10c). The resulting data depicted that the mean fluorescence intensity, which indicates binding of CD44 receptors with anti-CD44 antibody, was highest in PC-3 cells treated with anti-CD44 antibody alone. The mean fluorescence intensity was gradually dropped when PC-3 cells were treated with different formulations, particularly when treated with nanoformulations (Fig. 10c). The mean fluorescence intensity was lowest when PC-3 cells were treated with HA-CMR-CS-NPs, validating that majority of CD44 receptors were competitively bind with HA-CMR-CS-NPs [46–48].

The competitive binding assay for evaluating the co-localization and CD44 expression was also carried out using the RAW 264.7 cells. The resulting CLSM merged image of control (untreated) showed uniformly dispersed nuclei (acquiring bright blue color) surrounded by intact cell membrane having overexpressed CD44 receptors (acquiring bright red color due to interaction with anti-CD44 antibody) (Fig. 11a). A week intensity of blended fluorescence (green + red) was witnessed in CLSM merged image of RAW 264.7 cells treated with free CMR which indicated that apparently a few CD44 receptors were co-localized with CMR. The fluorescence intensity was increased when RAW 264.7 cells were treated with CMR-CS-NPs and HA-CMR-CS-NPs, and highest intensity of blended fluorescence (green + red) was noted in HA-CMR-CS-NPs group (Fig. 11a). These results showed good co-localization of HA-CMR-CS-NPs on CD44 receptors which warranted that HA-functionalized PNSPs utilize CD44-mediated endocytosis pathway for internalization into RAW 264.7 cells [49, 50].

Like PC-3 cells, the selective uptake of HA-functionalized CMR-CS-NPs into RAW 264.7 cells via CD44-mediated endocytosis was also confirmed using the flow cytometry. The zero value of fluorescent intensity in case of control (untreated) indicated no apparent binding of CD44 receptors with anti-CD44 antibody (Fig. 11b). The fluorescent intensity was marginally high (CD44 expression 37.5) when RAW 264.7 cells were treated with anti-CD44 antibody alone, demonstrating that all CD44 receptors were occupied by anti-CD44 antibody. A slight shift in the fluorescent intensity toward left (CD44 expression of 37.0) in case of free CMR could be due to binding of CMR to some of the CD44 receptors, but the results were insignificant (Fig. 11b). The competitive binding of anti-CD44 antibody on CD44 receptors was markedly decreased when RAW 264.7 cells were pretreated with CMR-CS-NPs (CD44 expression 14.3) which demonstrated that moderate number of CD44 receptors were occupied by CMR-CS-NPs. The fluorescent intensity showed highest drop (CD44 expression 1.02) when RAW 264.7 cells were treated with HA-functionalized CMR-CS-NPs (Fig. 11b). The lowest CD44 expression observed in HA-CMR-CS-NPs group validated that majority of CD44 receptors on RAW 264.7 cells were occupied by HA-CMR-CS-NPs and only a few CD44 receptors were available for binding with anti-CD44 antibody [49, 50]. These results were consistent with CLSM outcomes that HA-functionalized PNSPs mainly rely on CD44-mediated endocytosis for internalization into RAW 264.7 cells.

The CD44 expression of RAW 264.7 cells treated with different test formulations was also quantified using the flow cytometry (Fig. 11c). It was noted that the mean fluorescence intensity was highest in RAW 264.7 cells treated with anti-CD44 antibody alone; however, a noticeable decrease in the fluorescent intensity was observed when cells were treated with free CMR and CMR-CS-NPs. The mean fluorescence intensity was lowest when RAW 264.7 cells were treated with HA-CMR-CS-NPs (Fig. 11c), which indicated that CD44-mediated endocytosis is the predominant mechanism for HA-CMR-CS-NPs to get internalized into RAW 264.7 cells [51].

3.11. Anti-metastatic efficacy

Cancer metastasis is one of the promising phenotypes of advanced stage PC that is associated with low DFS and OS rates among the PC patients [10, 17, 24]. It develops when cancer cells migrate from the primary tumor site to distant parts of the body where they develop secondary tumor. Herein, we performed scratch assay to explore the anti-metastatic efficacy of our optimized nanoformulations (HA-MTX-ZA-CS-NPs) via evaluating the proliferation and migration of PC-3 cells. For comparison purpose, microscopic images of scratch-induced gap were captured at two different time points (0 h and 24 h). In the control (untreated) group at 24 h, PC-3 cells showed a grave ability of proliferation and migration with barely visible scratch-induced gap. Likewise, a week anti-proliferative and anti-migratory effect was observed in PC-3 cells treated with free MTX + ZA which could be due to poor cell uptake efficiency and CD44-mediated endocytosis that results in a feeble apoptosis and autophagy in PC-3 cells. On the other hand, a clearly visible scratch-induced gap was evident in PC-3 cells treated with nanoformulations, particularly when treated with HA-MTX-ZA-CS-NPs. The PC-3 cells treated with unfunctionalized MTX-ZA-CS-NPs displayed few cell colonies within scratch-induced gap after 24 h which indicated moderate cell mitosis, but proliferation and migration of PC-3 cells in this group was lesser than control (untreated) and free drugs. On the other hand, no apparent cell colonies and migration was evident in PC-3 cells treated with HA-functionalized MTX-ZA-CS-NPs after 24 h, which demonstrated an exceptional anti-metastatic efficacy [51, 52]. This was attributed to highest cytotoxicity, cell uptake efficiency, CD44-mediated endocytosis, and induction of apoptosis in PC-3 cells treated with HA-PNSPs.

In this research, CS-based PNSPs were fabricated via ionic-gelation method for simultaneous delivery of MTX and ZA for treatment of PC. Aiming to alleviate cancer progression and metastasis, the fabricated PNSPs were functionalized with HA to competitively bind to CD44 receptors and provoke dual action against PC cells and M2-macrophages residing in TME. Since the physicochemical properties (i.e., particle size, shape, surface chemistry, etc.) of nanomaterials play paramount role in intracellular delivery, therefore, quality-by-design strategy using the Design Expert® software was employed for optimization of PNSPs. A robust relationship between studied factors (CMAs and CPPs) and physicochemical properties of PNSPs advocated that CS concentration, HA concentration, and homogenization are essential factors that should be considered while optimizing the PNSPs. Based on optimization results, PNSPs produced with 0.1% (w/v) CS concentration, 0.002% HA concentration, and 30 min homogenization exhibited most desirable physicochemical properties including, PS ⁓160 nm, PDI 0.453, and ZP ⁓30 mV. The successful loading of both drugs (MTX & ZA) in polymeric matrix of PNSPs and functionalization with HA were confirmed by several distinct conformational changes in the FTIR spectra, XRD diffractogram, and NMR spectra of PNSPs. The SEM image of optimized HA-functionalized PNSPs displayed smooth spherical morphology, nanoscaled dimension (⁓120–160 nm), and minor tendency of agglomeration which was expected to be due to dehydration effect of lyophilization. Moreover, no significant changes in physicochemical properties (e.g., particle size, PDI, and zeta potential), agglomeration tendency, and flocculation and coagulation behavior were evident, when HA-PNSPs were refrigerated in a buffered medium (PBS, pH 7.4) for 8 weeks. The in vitro release study revealed that developed HA-PNSPs exhibited pH-responsive sustained release behavior, which signify their ability to selectively deliver encapsulated chemotherapeutic agents to TME which is slightly acidic compared to other body tissues. For selective CD44-mediated targeting, molecular docking experiment was performed which depicted a perfect fit between HA and hyaluronan binding domain on CD44 receptors. Five distinct hydrogen bonding interactions, some Alkyl/Pi-Alkyl interactions, and several hydrophobic interactions were evident between HA and various key amino acid residues of CD44 receptors. The lowest viability of PC-3 cells (< 10%) and RAW 264.7 cells (< 30%) along with smallest IC₅₀ values (2.8 µg against PC-3 cells and 15.2 µg against RAW 264.7 cells) warranted a paramount anticancer potency of HA-MTX-ZA-CS-NPs. The powerful cytotoxic efficacy of HA-MTX-ZA-CS-NPs was also validated in terms of cell uptake efficiency and results depicted highest internalization in both PC-3 and RAW 264.7 cells. The mechanism of cellular internalization was investigated using the competitive binding assay and resulting micrographs of CLSM and flow cytometry revealed that HA-functionalized PNSPs employed CD44-mediated endocytosis pathway for internalization into PC-3 and RAW 264.7 cells. Taken together, HA-functionalized PNSPs displayed exceptional anti-metastatic efficacy by mitigating the proliferation and migration of PC-3 cells. These findings evidenced that HA-functionalization is a promising technique for dual action against PC-3 and M2-macrophages to alleviate the cancer progression and metastasis in PC. Having assessed remarkable outcomes against PC, we anticipated that HA-functionalized PNSPs could also be a promising anticancer nanomedicine against other types of cancer; however, substantial in vivo evaluations are highly warranted prior to further development of this product.

Ethics approval and consent to participate

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Consent for publication

Not applicable

Availability of data and materials

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Competing interests

Authors reported no competing interest in the present work.

Funding

This work was supported by SEED grant and Postgraduate Research Fund provided by the University of Sharjah, United Arab Emirates.

Authors' contributions

ZH conceptualized the methodology, analysed the data, mentored throughout writing, editing, and proofreading of the manuscript. MAN conducted all the experiments and wrote the original draft, JJ assisted in cell culture work and analysis of data, HT conducted molecular docking study and analysed the data, MQ performed final editing and proofreading.

Acknowledgements

Authors would like to greatly acknowledge College of Pharmacy, University of Sharjah and Research Institute for Medical and Health Sciences (RIMHS) for providing financial support and resources to accomplish this research project.

Authors' information

Authors and affiliations

Department of Pharmaceutics and Pharmaceutical Technology, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates

Mahnoor Ahmed Naseem, Mutasem Rawas-Qalaji, Zahid Hussain

Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates

Jayalakshmi Jagal, Hamadeh Tarazi, Mutasem Rawas-Qalaji, Zahid Hussain

Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates

Hamadeh Tarazi

Dr. Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL 33326, USA

Mutasem Rawas-Qalaji

Department of Pharmacology, Faculty of Dentistry, Universiti Teknologi MARA, Sungai Buloh Campus, Selangor Branch, Sungai Buloh 47000, Selangor, Malaysia

Hnin Ei Thu

Corresponding author

Correspondence to Zahid Hussain.

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No competing interests reported.

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Dual Targeting of Prostate Cancer Cells and Tumor-Associated Macrophages for Mitigating Tumorigenesis and Metastasis: Hyaluronic Acid Functionalized Polymeric Nanospheres for CD44-Mediated Active Targeting

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Abstract

Figures

Highlights

1. Introduction

2. Material and methods

2.1. Materials

2.2. Quality by Design (QbD) for optimization of HA-PNSPs

2.3. Selection of optimal nanosystem

2.4. Method validation

2.5. Preparation of MTX/ZA co-loaded PNSPs (MTX-ZA-CS-NPs)

2.6. Functionalization of MTX-ZA-CS-NPs with HA

2.7. Physicochemical characterization

2.8. Measurements of %EE and %LC

2.9. Fourier transform infra-red (FT-IR) spectrophotometric analysis

2.10. X-ray diffraction (XRD) analysis

2.11. Nuclear magnetic resonance (NMR) spectroscopic analysis

2.12. Morphological examination

2.13. Storage colloidal stability

2.14. In vitro drug release kinetics

2.15. Molecular docking

2.16. Cell culture studies

2.16.1. Cytotoxicity and IC50

2.16.2. Cell uptake efficiency

2.17. Specific CD44-mediated cell internalization

2.18. Anti-metastatic efficacy

2.19. Statistical analysis

3. Results and discussion

3.1. Optimization of PNSPs by QbD approach

3.1.1. Effect of CS concentration

3.1.2. Effect of HA concentration

3.1.3. Effect of homogenization

3.1.4. Selection of optimal PNSPs formulation

3.1.5. %EE and %LC

3.2. FT-IR analysis

3.3. XRD analysis

3.4. NMR analysis

3.5. Morphology

3.6. Storage stability

3.7. In vitro drug release kinetics

3.8. Molecular docking

3.9. Cell culture studies

3.9.1. Cytotoxicity and IC50

3.9.2. Cell uptake efficiency

3.10. Specific CD44-mediated endocytosis

3.11. Anti-metastatic efficacy

4. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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2.16.1. Cytotoxicity and IC₅₀

3.9.1. Cytotoxicity and IC₅₀