Targeted Delivery of STAT-3 Modulator to Breast Cancer Stem-Like Cells Downregulates a Series of Stemness Genes

Despite significant improvement in survival rates of breast cancer patients, it is on rise in developing countries such as Brazil and China. Main concern associated with breast cancer has been its high malignancy with considerable metastatic potential and recurrence with irregular time lags (1–4). Years after removal of the primary tumor, recurrence of tumors at secondary locations often associate with higher mortality rate in cancer patients. Resistance to chemo- and radiotherapy, metastasis, and eventual relapse have been attributed to a distinct tumor subpopulation with “stem-like” cell property known as cancer stem cells (CSC; refs. 3, 5, 6). These cell populations had been associated with marked degree of cellular heterogeneity. To delegate unregulated growth of tumors via serial acquisition of genetic events resulted in the turning on of genes promoting proliferation, silencing of genes involved in inhibiting proliferation, and circumventing of genes involved in programmed cell death (7, 8). Survival of CSCs vary to dependability on wide ranges of genes and mechanisms like transglutaminase2 (TGM2) for epidermal squamous cell carcinoma stem cells, kinase-independent scaffolding functions of FAK for influencing cell survival and breast cancer stem cell (BCSC) proliferation (9–11) and emergence of castration resistant prostate cancer (CRPC) via androgen receptor (AR)-mediated survival pathways (12–14). A series of gene regulation could be correlated with CSCs (Fig. 1A).

These cell populations were identified with cell surface markers CD44⁺/CD24^−/low as was found in breast CSCs (BSC) based on mouse model (15). BSCs in mouse mammary tumors were also found to be overexpressing CD133 (16). Some other important genes associated with CSCs were LIN28A/LIN28B. They act mainly as oncogenes and found to be overexpressed in human malignancies to play important role in the maintenance of CSCs (17). LIN28B has also been firmly demonstrated as one of the critical molecules required for CSC growth and tumorigenesis in lung cancer (18). Downregulation of LIN28B decreased self-renewal capability of prostate CSCs. Among other markers, aldehyde dehydrogenase class I (ALDH1) has been identified as CSC-specific marker in multiple cancers. Current evidences also indicate that some specific pluripotency genes, such as OCT4, SOX2, NANOG, expressed in human cancer types as putative regulators of embryonic stem cell identity (19). EpCAM is expressed in a variety of human cancers, progenitor, and stem cells; thus, it is one of the markers that identifies tumor cells with high tumorigenicity (20). CXCR4 has a role not only in cancer metastasis but also in regulating CSCs in breast cancer (21).

Studies on BSCs were also significantly correlated with STATs (22). In recent years, STAT-3 has been well studied for its impending role in survival, invasion, and promotion of tumor cell proliferation, angiogenesis, immunosuppression, obesity, inflammation, and premetastatic niche formation (23). In addition to these, STAT3 plays a crucial role as potent immune checkpoint for multiple antitumor immune responses and immune cells, which are recruited to the tumor microenvironment to promote tumor progression (24–27). Thus, strategies that block STAT3 may prove efficacious for sustained cancer treatment. Several therapeutic approaches are being pursued, including inhibitors of STAT3 function, agents that block either dimerization or DNA binding by STAT3, and strategies to reduce STAT3 expression (28). In addition, cell surface receptor inhibitors, kinase inhibitors, STAT3 SH2 domain inhibitors, and inhibitors for STAT3 DNA-binding domain were used to disrupt STAT3 signaling and activity. Specifically, garcinol was found to inhibit phosphorylation and acetylation of STAT3 and preventing its dimerization (29), whereas U-STAT3 could bind AT-rich DNA sequences causing regulation of chromatin structure, and eventually recognition of secondary structures in addition to transcriptional activator functions (30). Acetylation on STAT3 increases its DNA binding, transactivational, and nuclear localization activity. Increase of STAT3 transactivation activity by acetylation could be the result of the tight DNA binding and increased STAT3 nuclear localization (31). Among these, STAT-3 inhibition approach can be highly effective for cancer treatment as normal cells can tolerate a reduction in STAT3 function, but cancer cells require constitutive STAT3 signaling for its survival.

STAT3 signaling is a major intrinsic pathway for cancer inflammation and capable of inducing a large number of genes that are crucial for inflammation including IL6, 10, 11, 17, 23, CXCL12, and COX-2. STAT3 is regarded as a direct transcriptional activator of VEGF gene (32). Constitutive activation of STAT3 upregulates VEGF expression and tumor angiogenesis in melanoma cells (33) and pancreatic cancer cells. Activation of STAT3 signaling in tumor cells or in inflammatory immune cells modulates secretion of various inflammatory factors such as IL6 and TNF that act as an immunosuppressor and increase the probability of survival of tumor cells (34). Abnormal expression of FGFRs is often linked with development and progression of a variety of human cancers and STAT3 as a mediator of amplified FGFR signaling (35).

In pursuit of a suitable STAT-3 inhibitor, we considered drug repurposing strategy. Drug repositioning of already approved agents helps to overcome physical limitations of poorly soluble drugs, off-target toxicity, and others. The approach represents an attractive way to achieve enhanced therapeutic efficacy and aids to substantial cost savings in drug development efforts. Niclosamide was originally FDA approved for treating patients with Taeniasis saginata as vermicide. Later on, it was studied in various transformed human cancer cells as an anticancer agent (36–40) via regulation of NFκB (39), Wnt/β-catenin (41), Notch (42), mTORC1 (43), and STAT3 (44) pathways and relates to stem-ness of CSCs. In specific studies, niclosamide was found to be highly effective against breast cancer and breast cancer stem-like cells (Fig. 1B; ref. 45). A nanomedicine approach is sought to explore the repositioning of this agent. In nanomedicine, the hydrophobic nature of drugs has favored its incorporation into many nanoparticle formulations, including amphiphilic lipid (46–48) or polymer-based particles (49). Although drug encapsulation in nanoparticles can enrich the local concentration of drug molecules and improved functional activity, but cannot completely ensure the reach of these unguided nanoparticles to desired sites/cells. In this study, a polymeric, niclosamide-incorporated, nanoparticle was conjugated with CD44-targeting peptide, generating CD44-NIC-Veh (CD44-tagged niclosamide-loaded nano-vehicles) for efficiently treating breast cancer–like cells (BSC). An array of in vitro and in vivo experiments was performed to evaluate functional activity of CD44-NIC-Veh with gene and protein expression studies (Fig. 1C).

Niclosamide was obtained from AK Scientific, Inc. Reagent-grade polyethylene glycol cetyl ether, and poly(styrene)-block-poly(acrylic acid) were obtained from Sigma Life Sciences and were used as received. Tetrahydrofuran was obtained from Avantor Performance Materials . A cellulosic membrane 20,000 Da MW cutoff (Thermo Scientific Inc.) cassettes were used for dialysis. Please see Supplementary Methods for preparation procedure of Nano-Veh and NIC-Veh particles, Cell viability assay protocol, procedure of FACS analysis of CD44⁺ cell populations, and apoptosis assay.

CD44-NIC-Veh was prepared by surface conjugation of anti–CD44-peptide (RLVSYNGIIFFLK) by 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) coupling. Prepared NIC-Veh (1 mL, 200 μmol/L of loaded niclosamide) was stirred at room temperature with EDC (0.1 μmol/L) for 20 minutes in DPBS (pH 7.4). Anti-CD44 antibody (0.18 mg, 0.1 μmol) and a catalytic amount of 4-Dimethylaminopyridine (DMAP) were further added. Mixture was stirred for next 12 hours at room temperature. At the end of the process, sample was purified from free isourea molecules (produced as byproduct of the EDC coupling) and unconsumed DMAP by dialysis against DPBS (pH = 7.4) using a 10,000 Da MWCO cellulose membrane for 24 hours. Purified samples were stored at 4°C till next use for physiochemical or biological studies.

Hydrodynamic diameter distribution and distribution averages for NIC-Veh, CD44-NIC-Veh, and controls in aqueous medium were determined by dynamic light scattering. Hydrodynamic diameters were determined using a Malvern Zetasizer ZS90 particle size analyzer. Measurements were made following dialysis (MWCO 20 kDa dialysis tubing, Spectrum Laboratories) of nanoparticle suspensions into deionized water (filtered through 0.2 μ filter). Nanoparticles were dialyzed against water before analysis. Scattered light was collected at a fixed angle of 90°. A photomultiplier aperture of 400 mm was used, and the incident laser power was adjusted to obtain a photon counting rate between 200 and 300 kcps. Only measurements for which the measured and calculated baselines of the intensity autocorrelation function agreed to within +0.1% were used to calculate nanoparticle hydrodynamic diameter values. All determinations were made in multiples of five consecutive measurements.

All the animal experiments were performed in accordance with the approved guidelines. The experimental animal protocol was approved by the Institutional Animal Care and Use Committee (IACUC), University of Illinois, Urbana–Champaign, and satisfied all University and National Institutes of Health (NIH, Bethesda, MD) rules for the humane use of laboratory animals. All animal experiments were designed to minimize the use of animals. To detect at least of 20% difference in tumor size, we decided to generate 2 tumors per animal as 5 mice per group. Athymic nude mice were procured from Charles River Laboratories International, Inc. Upon arrival, animals were allowed for one-week acclimation. Animals were housed as one animal per cage with free access to food and water. Animals were housed in Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign (Champaign, IL).

Isoflurane was used to anesthetized animals before injecting the MCF-7 cells suspended in Matrigel (50%, v/v). We subcutaneously injected approximately 5 × 10⁶ MCF-7 cells suspended in 40 μL of Matrigel using a Hamilton autoinjector syringe tipped with a 26 gauge 1/2″ long needle at two sites in the flanks of each mouse. Mice were monitored for recovery from the anesthesia. A minimum of 0.5 × 0.5 cm² size of tumors were grown on the back of mice after cell injection. We did not find any significant discomfort to the mice in the time span of the experiment. We monitored the mice daily for signs of discomfort and any behavior change. Mice body weight was measured every week for any significant change and found no more than 10%. Changes in parameters of physiologic function or abnormal behavior (shortness of breath, unsteady gait, abnormal eating behavior, physical abnormalities, rough hair coat due to lack of grooming, or lethargy) were reported to division of animal research. Criteria for stopping experiments or sacrificing animals were set up as animal body weight drops by 20% or tumor increase to 17 mm × 17 mm. Tumor size was determined by calculating the tumor volume via formula |${\rm{Tumor}}\,{\rm{volume}} = ( {{\rm{lengt}}{{\rm{h}}^2} \times {\rm{width}}} )/2$|

Animals were kept untreated till their tumors grew to a minimum of 5 mm × 5 mm before starting the treatment protocol. CD44-NIC-Veh were prepared at 5 mmol/L concentration and injected in tumors grown to at least 5 mm × 5 mm dimensions. Isoflurane–oxygen mixture anesthetic was maintained with 1%–2% isoflurane via an inlet tube in animal trap chamber. A second tube from the chamber was used to remove carbon dioxide and excess anesthetic. A 40-μL volume of formulation were injected per site on every fourth day and followed till 44th day for tumor growth and regression.

Biostatistical analysis was performed on tumor volume regression study results using one-way ANOVA considering volume of tumors in animals treated with Nano-Veh as a comparison. A P value of 0.05 was reported as statistically significant (indicated by *).

On the completion of tumor regression experiments, animals were euthanized under CO₂ influx. Dissections were performed on animals to collect tumors and stored in tissue cassettes dipped in 10% formalin. Samples were transferred to Leica ASP300 tissue processor for performing the tissue fixation. Steps of tissue incubation included processing with neutral buffered saline for 45 minutes, twice with ethanol (70%) for 45 minutes, ethanol (80%) for 45 minutes, twice with ethanol (95%) for 45 minutes, twice with absolute ethanol for 45 minutes, twice with xylene for 45 minutes, and finally thrice with paraffin wax for 45 minutes. Wax was melted at 65°C using a metal cast for submerging the processed tumors for paraffin embedding. Embedded tumor blocks were clamped in microtome (Leica) and sectioned at 7-μm thickness.

Paraffin-embedded sections (5-μm thickness) were subjected to hematoxylin and eosin (H&E) staining. H&E staining was performed by following the standard protocol provided by core facility at Institute of Genomic Biology (IGB). The morphologic changes of H&E-stained tissue with individual fixation were analyzed at magnification ×20 and ×40.

Total RNA was isolated from NIC-Veh–treated and control mice xenograft tumors using the RNeasy Mini Kit (Qiagen) as per the manufacturer's protocol. RNA pellets were dissolved in nuclease-free water and stored at −80°C until analysis. Quality of the isolated RNA was determined using a Nano Drop spectrophotometer (Thermo Scientific) and analyzed by an Agilent 2100 Bioanalyzer using an RNA Nano bioanalyzer chip to determine the RNA integrity as well as the presence/absence of gDNA by the Carver High-Throughput DNA Sequencing and Genotyping Unit (HTS Laboratory, University of Illinois, Urbana, IL). The concentration of the RNA was determined by the Qubit RNA HS Assay Kit (Thermo Fisher Scientific, Life Technologies) as per the manufacturer's protocol.

Reverse transcription of RNA was performed from 1 μg total RNA in the presence of RNase inhibitor, random hexamer primers (50 ng/μL), deoxynucleotides (dNTP, 10 mmol/L), SuperScript III reverse transcriptase (200 U/μL), and reverse transcriptase buffer in a 20-μL final reaction volume using SuperScript III First-Strand Synthesis System for RT-PCR kit (Invitrogen, Life Technologies).

Relative quantification of the genes was performed by using Power SYBR Green PCR Master Mix (2X; Applied Biosystems) in TaqMan ABI 7900 Real-Time PCR system (Applied Biosystems). Relative expression of a total of 32 genes, that is, STAT3, MYC, BCL2, IL10, MCL1, IL11, MMP9, MUC1, EGFR, COX2, IFNG, VEGF, CD44, CD24, PROM1, LIN28A, LIN28B, ALDH1A1, POU5F1, NOTCH1, SOX2, CTGF, MMP1, EPCAM, FGFR1, ERBB2, CXCR4, PROCR, TGFB1, CTNNB1, WNT1, and WNT2 were studied. The housekeeping gene GAPDH was used as endogenous control to normalize for differences in reverse transcription efficiency. The thermal cycling conditions for real-time PCR were one cycle of 50°C for 2 minutes (AmpErase uracil-N-glycosylase activation) and 95°C for 10 minutes (AmpliTaq Gold activation), followed by 40 cycles of 95°C for 15 seconds (denaturation) and 60°C for 1 minute (annealing and extension). Gene expression levels were calculated using the 2^−ΔΔC_t method relative to the internal control.

Western blotting was used to examine the expression of four proteins (STAT3, pSTAT3, CD24, and CD44). Total protein content in the tumors was extracted using Minute Total Protein Extraction Kit (Invent Biotechnologies) as per the manufacturer's protocol. The protein concentrations of the samples were determined by a colorimetric assay using Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). Twenty-five micrograms of protein extracts were separated by gradient (4%–20%) SDS-PAGE and then transferred to a nitrocellulose membrane (Bio-Rad) using a wet transfer unit (company name), blocked with 2.5% BSA in TBS-Tween buffer (0.12 mol/L Tris-base, 1.5 mol/L NaCl, 0.1% Tween 20) for an hour at room temperature, and incubated overnight at 4°C with the appropriate primary antibodies; β-actin (1:3,000), CD24 (1:3,000), CD44 (1:3,000), STAT3 (1: 3,000), and pSTAT3 (1:3,000). This was followed by incubation with a horseradish peroxidase–conjugated goat anti-mouse secondary antibody (Thermo Scientific) for an hour and subsequent washing in TBST. The blots were developed using the Chemiluminescent Kit (Thermo Scientific) to detect the target protein as per the manufacturer's protocol.

Protocol of CD44 peptide conjugation on NIC-Veh nanoparticles, physicochemical properties of NIC-Veh, bright-field images of breast cancer cells after various treatments, flow-assisted cell scanning histograms and cell growth analysis posttreatment in MCF-7 and MDA-MB231 cells, histograms of PI-stained MDA-MB231 cells after various treatments, H&E performed on tumor cross sections from animals treated with NIC-Veh and CD44-NIC-Veh, IHC performed on tumor cross sections from animals treated with CD44-NIC-Veh and NIC-Ve, relative RNA expression of “stemness genes” in tumor tissue, preparation procedure of Nano-Veh and NIC-Veh particles, cell viability assay protocol, procedure of FACS analysis of CD44⁺ cell populations, and apoptosis assay have been described in detail in the Supplementary methods.

CD44-NIC-Veh particles were prepared by conjugating NIC-Veh particles (mixed micelles of polyethylene cetyl ether with polystyrene-b-polyacrylic acid; Supplementary Methods) with CD44-targeting peptide (RLVSYNGIIFFLK) using EDC/DMAP coupling method (Supplementary Fig. S1). Prepared formulations (Nano-Veh, NIC-Veh and CD44-NIC-Veh) were characterized for size, stability, drug loading, and release patterns along with anhydrous morphologic distributions. Drug loading and release efficiency of CD44-NIC-Veh was found to be around 55% ± 10% (Fig. 2A) and 70% ± 15%, respectively (Fig. 2B). The average hydrodynamic diameter was approximately 100 ± 25 nm in the case of the CD44-NIC-Veh (Fig. 2C). Anhydrous morphologic distribution and surface topography of CD44-NIC-Vehs were analyzed by transmission electron microscopy (TEM). TEM studies showed size of approximately 100 nm for CD44-NIC-Vehs (Supplementary Fig. S2D). CD44-NIC-Veh formulations under low pH conditions of approximately 4.6 showed destabilization like in case of NIC-Veh (Supplementary Fig. S2B), whereas Nano-Veh were more stable at lower pH values (Supplementary Fig. S2C). Hydrodynamic diameter of Nano-Veh and NIC-Veh was found to be approximately 90 ± 15 nm (Supplementary Fig. S2B and S2C), whereas Nic-Veh resulted in a drug loading of 80% ± 15%, but could release only approximately 20% ± 10% (96 hours; Supplementary Fig. S2D). A higher drug release level in CD44-conjugated CD44-NIC-Veh particles helped in drug release. Anhydrous morphology and surface topography of NIC-Veh by TEM (Supplementary Fig. S2E) and AFM (Supplementary Fig. S2F) gave a size of approximately 50 nm and height profile 10 nm, respectively. An AFM analysis of CD44-NIC-Veh nanoparticles revealed height profile of approximately 20 nm (Supplementary Fig. S2G).

Specific detection of CD44⁺ MCF-7 cell population was done by flow cytometry experiments performed on CD44 antibody–tagged MCF-7 cells while visualized under bright field microscopy (Supplementary Fig. S3). Cells were treated with niclosamide and CD44-NIC-Veh with 10 μmol/L for 72 hours (Supplementary Methods). Cells were also treated with NIC-Veh or NanoVh, nanoparticles with no niclosamide as controls of different niche. At the end of the incubation, cells were further incubated with 2 μg rat anti-mouse CD44 mAb conjugated to fluorescein isothiocyanate (FITC, Life Technologies, Thermo Fisher Scientific) in 2-mL DMEM. DPBS washed (thrice) cells were used for analysis by flow cytometry. Around 10% of growing MCF-7 cell population (Supplementary Fig. S4A) was found to be CD44⁺ possessing stem-like cancer cell properties (Supplementary Fig. S4B). Any decrease in CD44⁺ population would indicate the loss of stemness in cancer cells and if it was achieved after treatment would correlate with stem cell regression ability of the treating agent. It was noticed that treatment with NanoVeh did not alter the CD44⁺ population (Supplementary Fig. S4C) to any significant level, whereas niclosamide (Supplementary Fig. S4D) and NIC-Veh (Supplementary Fig. S4E) only reduced it to approximately 20%–30%. Maximum reduction in CD44⁺ cells was reported for CD44-NIC-Veh treatment, with a regression effect as low as approximately 60% of total CD44⁺ population, that is, 4% of total population with CD44⁺ character (Supplementary Fig. S4F and S4G). The overall change in cancer cell population was studied by MTT assay. An additional cancer cell line of breast origin, MDA-MB231 (triple-negative breast cancer) was also used for overall cell growth inhibition study and found to be little less responsive against CD44-NIC-Veh treatment (Supplementary Fig. S4H) as in case of MCF-7 (Supplementary Fig. S4I), although in both the cases, IC₅₀ was found to be approximately 2 μmol/L across 48-hour time point. After establishing mechanistic function of niclosamide-loaded Nano-Veh in MCF-7 cells, experiments were performed in MDA-MB231 to find the cause of lower response. Activity mechanism of niclosamide-loaded Nano-Veh in MDA-MB231 was established by performing apoptosis assay. Propidium iodide (PI) is a known DNA binder a good indicator of genetic DNA integrity. PI-stained cells with high DNA degradation, resulting from induced apoptosis (Supplementary Methods), show lower red fluorescence in flow-assisted cell studies (Supplementary Fig. S5). An improved apoptosis induction efficiency was found in case of MDA-MB231 cells treated with CD44-NIC-Veh (Supplementary Fig. S5E) with approximately 25% cells in apoptotic region of cell histogram compared with nontargeted NIC-Veh treatment (∼15%; Supplementary Fig. S5D) and niclosamide alone (∼10%; Supplementary Fig. S5C) where blank particles (Nano-Veh; Supplementary Fig. S5B) were not effective to any significant level. These results signify the effect of CD44-targeting–mediated improvements in induced apoptosis in MDA-MB231, but also indicate lower efficiency compared with MCF-7.

The tumor regression ability of CD44-NIC-Veh was verified by treating xenograft tumors generated from MCF-7 cells in nude mice. Tumors grown to a minimum size of 0.5 × 0.5 cm were injected with CD44-NIC-Veh (Tumor #5B, 5C, 15A, 15B, 24A) and Nano-Veh [Tumor #6B, 6D, 7A, 20D (termed as C)] in 40-μL volume four times and followed till total of 44 days before sacrificing and collecting the tumor tissue (Fig. 3A). All group of animals were made by random assignments and found to show no biostatistical significant in tumor size on the first day of treatment injections. Tumor sizes were followed for 44 days but first injection was given only at 24th day, when tumors gained a minimum size of around 5 mm × 5 mm. The volume of grown tumors were followed for regression along the time of investigation using caliper measurements and found to be biologically significant in reducing the tumor size for CD44-NIC-Veh treatment compared with Nano-Veh–treated tumors (Fig. 3B). Tumors treated with blank nanoparticles (Nano-Veh) were grown as high as 200% larger compared with treated ones (Fig. 3C). One-way ANNOVA was applied considering volume of tumors on animals treated with Nano-Veh as comparison line for volume of tumors on animals treated with CD44-NIC-Veh. P = 0.05 was reported as statistically significant (indicated by *; Fig. 3B and C).

Liver enzymes and kidney function were evaluated after administration of CD44-NIC-Veh in rodents (n = 3). Our preliminary results indicated that an initial (2 hours) negligible influence on mice liver function (BUN = 20 ± 3 mg/dL; creatinine = 0.5 ± 0 mg/dL; albumin = 3.7 ± 0.2 g/dL; AST = 192 ± 35 μL and ALT = 56 ± 2 μL) 2 hours postinjection of CD44-NIC-Veh, which then begins to resolve toward normal physiologic levels 24 hours posttreatment (BUN = 17 ± 3 mg/dL; creatinine = 0.2 ± 0 mg/dL; albumin = 2.8 ± 0.2 g/dL; AST = 132 ± 35 μL, and ALT = 42 ± 2 μL). This suggests the burden of CD44-NIC-Veh on the liver and kidneys is an acute response that resolves as the CD44-NIC-Veh are subsequently metabolized and secreted. Although an in-depth safety study is warranted, this preliminary experiment points to the overall safety of the particles.

Tumor reduction was further corroborated with histopathologic analyses. The signs of tissue damage resulting from the treatment of CD44-NIC-Veh were clearly evident. Representative tissue sections from group of animals treated with Nano-Veh (Supplementary Fig. S6A and S6B) and CD44-NIC-Veh (Supplementary Fig. S6C and S6D) were used to compare histologic features generated posttreatments. Significantly fragmented nuclei and retracted cytoplasm were seen across the sections from CD44-NIC-Veh–treated tumors at ×20 (Supplementary Fig. S6C) and ×40 magnification (Supplementary Fig. S6D). These signs further support the induction of apoptosis in CD44-NIC-Veh–treated tumors.

Tumor growth regression could be corroborated with STAT-3 inhibition in CD44-NIC-Veh–treated animals. Loss in level of STAT-3 phosphorylation has been established as the process of niclosamide-mediated phosphoSTAT-3 (pSTAT-3) inhibition, indicating the possibility of CD44-NIC-Veh working in similar way. To image the extent of pSTAT-3 protein expression (red) in CD44-NIC-Veh–treated tumors, immune-labeling was performed on paraffin-embedded tumor sections. Immunolabeling was performed by following standard protocol. β-Actin (green) was used as background protein for all the sections investigated. Representative CD44 antibody immune-labeled cross sections of tumors treated with CD44-NIC-Veh (Fig. 4A–F) and NanoVeh (Fig. 4G–L) revealed the downregulation activity of CD44-NIC-Veh with drastic decrease in pSTAT-3 level. Sections were treated with pSTAT-3 antibody (red) against basal protein β-actin (green) around cell nuclei (blue) to show significantly high level of pSTAT-3 in NanoVeh–treated tumors compared with tumors treated with CD44-NIC-Veh (Supplementary Fig. S7).

To further support our findings that CD44-NIC-Veh treatment caused inhibition of STAT3, we studied the expression of the STAT3 downstream target genes by quantitative PCR. An average of gene expression values from five control tumor samples was used as base for comparative change calculation. Expression of 11 downstream target genes of STAT3, that is, MYC, BCL2, IL10, MCL1, IL11, MMP9, MUC1, EGFR, COX2, IFNG, and VEGF were studied. No significant difference in expression of STAT3 transcript was found between control and treatment samples indicating that CD44-NIC-Veh did not interfere with the STAT3 transcription (Fig. 5). The expression of all the studied STAT3 downstream target genes were downregulated (Fig. 5) indicating that CD44-NIC-Veh treatment caused inhibition of STAT3. Overall, CD44-NIC-Veh treatment does not affect total STAT3 transcription but induces downregulation of the STAT3 target genes, which supports our earlier findings that CD44-NIC-Veh inhibits phosphorylation of STAT3 in turn making it inactive and host cells lose their survival ability under treatment condition.

In recent years, CSCs have been recognized as important components in carcinogenesis, and could form basis of many tumor types. To evaluate the role of STAT3 in CSC self-renewal, we have studied the expression of a panel of CSC marker genes that are reported to be involved in the regulation of self-renewal of the CSCs. An average of gene expression values from five control tumor samples was used as base for comparative change calculation. Expression of a total of 20 “stemness genes” namely CD44, CD24, PROM1, LIN28A, LIN28B, ALDH1A1, POU5F1, NOTCH1, SOX2, CTGF, MMP1, EPCAM, FGFR1, ERBB2, CXCR4, PROCR, TGFB1, CTNNB1, WNT1, and WNT2 were studied in control tumors and tumors treated with CD44-NIC-Veh. CD44 expression was downregulated in treated tumors, whereas CD24 was upregulated indicating a reduction of CD44⁺ cell population and increase in CD24⁺ cell population in CD44-NIC-Veh–treated tumors (Supplementary Fig. S8). Significantly reduced expressions of all the other stemness genes were found in tumors treated with CD44-NIC-Veh in comparison with control tumors (Supplementary Fig. S8), indicating a reduction of the CSC population in treated samples. Overall, inactivation of STAT3 by CD44-NIC-Veh reduced of CSC population in mice xenograft tumors.

Niclosamide inhibits STAT3 by blocking its phosphorylation. To validate this, Western blot analysis was used to determine the effect of CD44-NIC-Veh on the expression of total and phosphorylated STAT3. Figure 6A–C depicts that CD44-NIC-Veh treatment induced downregulation of phosphorylated STAT3, whereas no difference in total STAT3 protein expression between control and treated samples was observed, indicating that CD44-NIC-Veh inhibits the posttranslational phosphorylation of the STAT3. We further studied the effect of CD44-NIC-Veh treatment on the expression of CD44 and CD24 proteins in mice xenograft tumors. It was found that following treatment, the expression level of CD24 was upregulated (Fig. 6D) and CD44 was downregulated (Fig. 6E) because of which the ratio of CD24 to CD44 in treated samples was significantly higher compared with the control samples (Fig. 6F).

CSCs have been highlighted lately, because of the opinion that these CSCs are the culprits for therapeutic resistance, metastasis and recurrence of the tumors, and therefore, might be selected as the target of treatment. The issue of cancer resurrection and metastasis have been largely attributed to the presence of stem-like cancer cells. In case of breast cancer, a subpopulation of cells expressing the CD44⁺/CD24⁻ phenotype have been reported to represent such stem-like populations. Selective delivery of STAT3 modulators by using CD44 targeted nano-vehicle could offer a strategy for regression of BCSCs. STAT family proteins are latent cytoplasmic transcription factors initially discovered as acute phase response factors (22). In resting cells, STATs are generally located in the cytoplasm in their inactive state. Phosphorylation of specific tyrosine residue is an essential step for STAT activation. Once activated, STAT dimerizes to other STATs by reciprocal SH2 phosphotyrosine interaction, leading to its translocation into the nucleus followed by its binding to the specific enhancer elements for initiation of transcription. Of the STAT family of proteins, STAT3 has received greatest attention as it is involved in a number of oncogenic signaling pathways and intracellular signal transduction pathways. STAT3 regulate Cyclin D1, cMyc, BclXL, Mcl1 and p53, thereby regulating cellular proliferation and survival. It has been found that cancer cells harboring aberrant STAT3 activity have elevated levels of antiapoptotic (Mcl-1, Bcl-2, and Bcl-xL) and cell-cycle regulating proteins (cyclin D1 and c-Myc). STAT3 plays a crucial role in cell invasion by regulating the matrix metalloproteinases (MMP), including MMP-9 and MMP-1.

Our initial study focused on the self-assembly of an amphiphilic polymer in presence of niclosamide (50). This exciting finding led us delve deeper to establish effects in vivo after active targeting to cells with stem-ness and follow variations on genetic framework of the cells. Micellar particles with CD44-targeting peptides have been developed to efficiently downregulate STAT-3 proteins in vitro and in vivo. Although IC₅₀ for niclosamide in MCF-7 was found to be lower, drug resistant nature of stem like cancer cells obligated us to use of a higher concentration (10 μmol/L) to observe significant change in stem-like cell population. Treatments with lower concentrations did not produce any significant effect in stem-like cell populations. A decrease in CD44⁺ cell population positively correlated with total number of dead cancer cells with “stemness” property. A constant population of cancer cells will have certain percentage of CD44⁺ cells and any nonspecific death of cancer cells (including cells with stemness characteristics) would not change the overall percentage of CD44⁺ cell population. Only a case of specifically high level of cell death in cancer cell population with stemness property would lead to overall decrease in the percentage of CD44⁺ cells. The whole purpose of the study was looking at stemness genes after CD44 targeting and not to make a simple activity comparison. Primarily because of this, animal experiments were performed only by using CD44-NIC-Veh as treatment. Downregulation of all the chosen CSC marker genes was observed in mice xenograft tumors treated with CD44-NIC-Vehs compared with the control samples Nano-Veh. The results of the study indicate that CD44-NIC-Veh deactivates STAT3 causing a reduction of CD44+/CD24⁻ CSC populations with appropriately followed gene and protein regulations of “stemness” characteristics. With these results in hand, our future studies will focus on an in-depth safety evaluation of these particles and their biodistributive properties in rodents. Although more in-depth animal studies will be necessary to understand the behavior of each component in vivo, our results indicated remarkable efficacy and preliminary safety with an already FDA-approved drug, which should facilitate its eventual clinical translation.

No potential conflicts of interest were disclosed.

Conception and design: S.K. Misra, D. Pan

Development of methodology: S.K. Misra, D. Pan

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S.K. Misra, A. De

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): S.K. Misra, A. De

Writing, review, and/or revision of the manuscript: S.K. Misra, A. De, D. Pan

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D. Pan

Study supervision: D. Pan

The authors thank UIUC, National Institute of Health and Children's Discovery Institute for financial assistance. TEM and AFM were carried out at Frederick Seitz MRL Central research facilities, UIUC. Animal experiments and IHC experiments were performed in Carl R. Woese Institute for Genomic Biology, UIUC. We also acknowledge help from Ayako Ohoka in studying size and stability of nanoparticles. This work was supported by grant from the NIH/NHLBI (1R42HL135965-01A1, to D. Pan).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.