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Drug delivery systems based on amphiphilic supramolecular macrocycles have garnered increased attention over the past two decades due to their ability to successfully formulate nanoparticles. Macrocyclic (MC) materials can self-assemble at lower concentrations without the need for surfactants and polymers, but surfactants are required to form and stabilize nanoparticles at higher concentrations. Using MCs to deliver both hydrophilic and hydrophobic guest molecules is advantageous. We developed two novel types of amphiphilic macrocycle nanoparticles (MC NPs) capable of delivering either Nile Red (NR) (a hydrophobic model) or Rhodamine B (RhB) (a hydrophilic model) fluorescent dyes. We extensively characterized the materials using various techniques to determine size, morphology, stability, hemolysis, fluorescence, loading efficiency (LE), and loading capacity (LC). We then loaded the CDK4/6 inhibitor Palbociclib (Palb) into both MC NPs using a solvent diffusion method. This yielded Palb-MC NPs in the size range of 65-90 nm. They exhibited high stability over time and in fetal bovine serum with negligible toxicity against erythrocytes. Cytotoxicity was minimal when tested against RAW macrophages, human fibroblast HDFn, and adipose stromal cells (ASCs) at higher concentrations of MC NPs. Cell viability studies were conducted with different concentrations of MC NPs, Palb-MC NPs, and free Palb against RAW macrophages, human U-87 GBM, and human M14 melanoma cell lines in vitro. Flow cytometry experiments revealed that blank MC NPs and Palb-MC NPs were selectively targeted to melanoma cells, resulting in cell death compared to the other two cell lines. Future work will focus on studying the biological effect of MC NPs including their binding affinity with molecules/receptors expressed on the M14 and other melanoma cell surfaces by molecular docking simulations. Subsequently, we will evaluate the MCs as a component of combination therapy in a murine melanoma model.

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Drug delivery systems based on amphiphilic supramolecular macrocycles have garnered increased attention over the past two decades due to their ability to successfully formulate nanoparticles. Macrocyclic (MC) materials can self-assemble at lower concentrations without the need for surfactants and polymers, but surfactants are required to form and stabilize nanoparticles at higher concentrations. Using MCs to deliver both hydrophilic and hydrophobic guest molecules is advantageous. We developed two novel types of amphiphilic macrocycle nanoparticles (MC NPs) capable of delivering either Nile Red (NR) (a hydrophobic model) or Rhodamine B (RhB) (a hydrophilic model) fluorescent dyes. We extensively characterized the materials using various techniques to determine size, morphology, stability, hemolysis, fluorescence, loading efficiency (LE), and loading capacity (LC). We then loaded the CDK4/6 inhibitor Palbociclib (Palb) into both MC NPs using a solvent diffusion method. This yielded Palb-MC NPs in the size range of 65-90 nm. They exhibited high stability over time and in fetal bovine serum with negligible toxicity against erythrocytes. Cytotoxicity was minimal when tested against RAW macrophages, human fibroblast HDFn , and adipose stromal cells (ASCs) at higher concentrations of MC NPs. Cell viability studies were conducted with different concentrations of MC NPs, Palb-MC NPs, and free Palb against RAW macrophages, human U-87 GBM, and human M14 melanoma cell lines in vitro. Flow cytometry experiments revealed that blank MC NPs and Palb-MC NPs were selectively targeted to melanoma cells, resulting in cell death compared to the other two cell lines. Future work will focus on studying the biological effect of MC NPs including their binding affinity with molecules/receptors expressed on the M14 and other melanoma cell surface by molecular docking simulations. Subsequently, we will evaluate the MCs as a component of combination therapy in a murine melanoma model.

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In the United States, over 100,000 women are diagnosed with a gynecologic malignancy every year, with ovarian cancer being the most lethal. One of the hallmark characteristics of ovarian cancer is the development of resistance to chemotherapeutics. While the exact mechanisms of chemoresistance are poorly understood, it is known that changes at the cellular and molecular level make chemoresistance challenging to treat. Improved therapeutic options are needed to target these changes at the molecular level. Using a precision medicine approach, such as gene therapy, genes can be specifically exploited to resensitize tumors to therapeutics. This review highlights traditional and novel gene targets that can be used to develop new and improved targeted therapies, from drug efflux proteins to ovarian cancer stem cells. The review also addresses the clinical relevance and landscape of the discussed gene targets.

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Ovarian cancer has shown little improvement in survival among advanced-stage patients over the past decade. Current treatment strategies have been largely unsuccessful in treating advanced disease, with many patients experiencing systemic toxicity and drug-resistant metastatic cancer. This study evaluates novel fusogenic peptide carriers delivering short interfering RNA (siRNA) targeting casein kinase II, CSNK2A1, for reducing the aggressiveness of ovarian cancer. The peptides were designed to address two significant barriers to siRNA delivery: insufficient cellular uptake and endosomal entrapment. The three peptide variants developed, DIVA3, DIV3H, and DIV3W, were able to form monodisperse nanoparticle complexes with siRNA and protect siRNAs from serum and RNase degradation. Furthermore, DIV3W demonstrated optimal delivery of bioactive siRNAs into ovarian cancer cells with high cellular uptake efficiency and mediated up to 94% knockdown of CSNK2A1 mRNA compared with non-targeting siRNAs, resulting in decreased cell migration and recolonization in vitro. Intratumoral delivery of DIV3W-siCSNK2A1 complexes to subcutaneous ovarian tumors resulted in reduced CSNK2A1 mRNA and CK2α protein expression after 48 h and reduced tumor growth and migration in a 2-week multi-dosing regimen. These results demonstrate the potential of the DIV3W peptide to deliver bioactive siRNAs and confirms the role of CSNK2A1 in cell-cell communication and proliferation in ovarian cancer.

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Glioblastoma multiforme (GBM) is the most aggressive central nervous system tumor, and standard treatment, including surgical resection, radiation, and chemotherapy, has not significantly improved patient outcomes over the last 20 years. Temozolomide (TMZ), the prodrug most commonly used to treat GBM, must pass the blood-brain barrier and requires a basic pH to convert to its active form. Due to these barriers, less than 30% of orally delivered TMZ reaches the central nervous system and becomes bioactive. In this work, we have developed a novel biomaterial delivery system to convert TMZ to its active form and that shows promise for intracellular TMZ delivery. Self-assembling peptides were characterized under several different assembly conditions and evaluated for TMZ loading and conversion. Both solvent and method of assembly were found to affect the supramolecular and secondary structure of peptide assemblies. Additionally, as peptides degraded in phosphate-buffered saline, TMZ was rapidly converted to its active form. This work demonstrates that peptide-based drug delivery systems can effectively create a local stimulus during drug delivery while remaining biocompatible. This principle could be used in many future biomedical applications in addition to cancer treatment, such as wound healing and regenerative medicine.

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Current delivery strategies for cancer therapeutics commonly cause significant systemic side effects due to required high doses of therapeutic, inefficient cellular uptake of drug, and poor cell selectivity. Peptide-based delivery systems have shown the ability to alleviate these issues and can significantly enhance therapeutic loading, delivery, and cancer targetability. Peptide systems can be tailor-made for specific cancer applications. This review describes three peptide classes, targeting, cell penetrating, and fusogenic peptides, as stand-alone nanoparticle systems, conjugations to nanoparticle systems, or as the therapeutic modality. Peptide nanoparticle design, characteristics, and applications are discussed as well as peptide applications in the clinical space.

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Self-assembling peptides are a popular vector for therapeutic cargo delivery due to their versatility, tunability, and biocompatibility. Accurately predicting secondary and supramolecular structures of self-assembling peptides is essential for de novo peptide design. However, computational modeling of such assemblies is not yet able to accurately predict structure formation for many peptide sequences. This review identifies patterns in literature between secondary and supramolecular structures, primary sequences, and applications to provide a guide for informed peptide design. An overview of peptide structures, their applications as nanocarriers, and analytical methods for characterizing secondary and supramolecular structure is examined. A top-down approach is then used to identify trends between peptide sequence and assembly structure from the current literature, including an analysis of the drivers at work, such as local and nonlocal sequence effects and solution conditions.

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In this study we developed electrospun cellulose acetate nanofibers (CANFs) that were loaded with a model non-steroidal anti-inflammatory drug (NSAID) (ibuprofen, Ib) and coated with poly(acrylamide) (poly-AAm) hydrogel polymer using two consecutive steps: an electrospinning process followed by photopolymerization of AAm. Coated and non-coated CANF formulations were characterized by several microscopic and spectroscopic techniques to evaluate their physicochemical properties. An analysis of the kinetic release profile of Ib showed noticeable differences due to the presence or absence of the poly-AAm hydrogel polymer. Poly-AAm coating facilitated a constant release rate of drug as opposed to a more conventional burst release. The non-coated CANFs showed low cumulative drug release concentrations (ca. 35 and 83% at 5 and 10% loading, respectively). Conversely, poly-AAm coated CANFs were found to promote the release of drug (ca. 84 and 99.8% at 5 and 10% loading, respectively). Finally, the CANFs were found to be superbly cytocompatible.

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Due to the lack of early symptoms and difficulty of accurate diagnosis, ovarian cancer is the most lethal gynecological cancer faced by women. First-line therapy includes a combination of tumor resection surgery and chemotherapy regimen. However, treatment becomes more complex upon recurrence due to development of drug resistance. Drug resistance has been linked to many mechanisms, including efflux transporters, apoptosis dysregulation, autophagy, cancer stem cells, epigenetics, and the epithelial-mesenchymal transition. Thus, developing and choosing effective therapies is exceptionally complex. There is a need for increased specificity and efficacy in therapies for drug-resistant ovarian cancer, and research in targeted nanoparticle delivery systems aims to fulfill this challenge. Although recent research has focused on targeted nanoparticle-based therapies, few of these therapies have been clinically translated. In this review, non-viral nanoparticle delivery systems developed to overcome drug-resistance in ovarian cancer were analyzed, including their structural components, surface modifications, and drug-resistance targeted mechanisms.

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In cell-based research, the process of visually monitoring cells generates large image datasets that need to be evaluated for quantifiable information in order to track the effectiveness of treatments in vitro. With the traditional, end-point assay-based approach being error-prone, and existing computational approaches being complex, we tested existing machine learning frameworks to find methods that are relatively simple, yet powerful enough to accomplish the goal of analyzing cell microscopy data. This paper details the machine learning pipeline for pixel-based classification and object-based classification. Furthermore, it compares the performances of three classifiers. The classifiers evaluated were the fast-random forest (RF), the sequential minimal optimization (SMO), and the Bayesian network (BN). Images were first preprocessed using smoothing and contrast methods found in FIJI. For pixel-based classification, the preprocessed images were fed into the Trainable Waikato Segmentation (TWS). For object-based classification, training and classification were conducted within the Waikato Environment for Knowledge Analysis (WEKA) interface. All classifiers' performance was evaluated using the WEKA experimental explorer. In terms of performance, the BN had the lowest classification accuracy for both the pixel-based and object-based model. The object-based SMO classifier had the best performance with the lowest mean absolute error of 0.05. The TWS and WEKA interface allows users to easily create and train classifiers for image analysis. However, for analyzing large image datasets, they are not ideal. Grapical abstract.

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Macromolecule-based therapeutic agents, particularly proteins, antigens, monoclonal antibodies, transcription factors, nucleic acids, and gene editing enzymes, have the potential to offer cures for previously untreatable diseases. However, they present an enormous delivery challenge due to poor absorption and rapid metabolism in the body. Polymersomes have tremendous potential in delivering these agents to their desired intracellular location due to increased circulation times, decreased macromolecule degradation, and decreased immune responses. In this Review, we highlight the key factors in design, development, and improved performance of these vesicles for macromolecular delivery. The recent progress made toward preclinical application of these vesicles for protein and gene delivery is also covered.

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Glioblastoma multiforme is the most common and aggressive primary brain tumor. Even with aggressive treatment including surgical resection, radiation, and chemotherapy, patient outcomes remain poor, with five-year survival rates at only 10%. Barriers to treatment include inefficient drug delivery across the blood brain barrier and development of drug resistance. Because gliomas occur due to sequential acquisition of genetic alterations, gene therapy represents a promising alternative to overcome limitations of conventional therapy. Gene or nucleic acid carriers must be used to deliver these therapies successfully into tumor tissue and have been extensively studied. Viral vectors have been evaluated in clinical trials for glioblastoma gene therapy but have not achieved FDA approval due to issues with viral delivery, inefficient tumor penetration, and limited efficacy. Non-viral vectors have been explored for delivery of glioma gene therapy and have shown promise as gene vectors for glioma treatment in preclinical studies and a few non-polymeric vectors have entered clinical trials. In this review, delivery systems including viral, non-polymeric, and polymeric vectors that have been used in glioblastoma multiforme (GBM) gene therapy are discussed. Additionally, advances in glioblastoma gene therapy using viral and non-polymeric vectors in clinical trials and emerging polymeric vectors for glioma gene therapy are discussed.

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OBJECTIVES: Despite significant advances in cancer treatment, the prognosis for oral cancer remains poor in comparison to other cancer types, including breast, skin, and prostate. As a result, more effective therapeutic modalities are needed for the treatment of oral cancer. Consequently, in the present study, we examined the feasibility of using a dual peptide carrier approach, combining an epidermal growth factor receptor (EGFR)-targeting peptide with an endosome-disruptive peptide, to mediate targeted delivery of small interfering RNAs (siRNAs) into EGFR-overexpressing oral cancer cells and induce silencing of the targeted oncogene, cancerous inhibitor of protein phosphatase 2A (CIP2A). MATERIALS AND METHODS: Fluorescence microscopy, real-time PCR, Western blot analysis, and in vivo bioimaging of mice containing orthotopic xenograft tumors were used to examine the ability of the dual peptide carrier to mediate specific delivery of bioactive siRNAs into EGFR-overexpressing oral cancer cells/tissues. RESULTS: Co-complexation of the EGFR-targeting peptide, GE11R9, with the endosome-disruptive 599 peptide facilitated the specific uptake of siRNAs into oral cancer cells overexpressing EGFR in vitro with optimal gene silencing observed at a 60:30:1 (GE11R9:599:siRNA) molar ratio. Furthermore, when administered systemically to mice bearing xenograft oral tumors, this dual peptide complex mediated increased targeted delivery of siRNAs into tumor tissues in comparison to the 599 peptide alone and significantly enhanced CIP2A silencing. CONCLUSION: Herein we provide the first report demonstrating the clinical potential of a dual peptide strategy for siRNA-based therapeutics by synergistically mediating the effective targeting and delivery of bioactive siRNAs into EGFR-overexpressing oral cancer cells.

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Intracellular delivery and endosomal escape of functional small interfering RNAs (siRNAs) remain major barriers limiting the clinical translation of RNA interference (RNAi)-based therapeutics. Recently, we demonstrated that a cell-penetrating endosome-disruptive peptide we synthesized, termed 599, enhanced the intracellular delivery and bioavailability of siRNAs designed to target the CIP2A oncoprotein (siCIP2A) into oral cancer cells and consequently inhibited oral cancer cell invasiveness and anchorage-independent growth in vitro. Thus, to further assess the therapeutic potential of the 599 peptide in mediating RNAi-based therapeutics for oral cancer and its prospective applicability in clinical settings, the objective of the current study was to determine whether intratumoral dosing of the 599 peptide-siCIP2A complex could induce silencing of CIP2A and consequently impair tumor growth using a xenograft oral cancer mouse model. Our results demonstrate that the 599 peptide is able to protect siRNAs from degradation by serum and ribonucleases in vitro and upon intratumoral injection in vivo, confirming the stability of the 599 peptide-siRNA complex and its potential for therapeutic utility. Moreover, 599 peptide-mediated delivery of siCIP2A to tumor tissue induces CIP2A silencing without any associated toxicity, consequently resulting in reduction of the mitotic index and significant inhibition of tumor growth. Together, these data suggest that the 599 peptide carrier is a clinically effective mediator of RNAi-based cancer therapeutics.

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The goals of bioengineering strategies for targeted cancer therapies are (1) to deliver a high dose of an anticancer drug directly to a cancer tumor, (2) to enhance drug uptake by malignant cells, and (3) to minimize drug uptake by nonmalignant cells. Effective cancer-targeting therapies will require both passive- and active-targeting strategies and a thorough understanding of physiologic barriers to targeted drug delivery. Designing a targeted therapy includes the selection and optimization of a nanoparticle delivery vehicle for passive accumulation in tumors, a targeting moiety for active receptor-mediated uptake, and stimuli-responsive polymers for control of drug release. The future direction of cancer targeting is a combinatorial approach, in which targeting therapies are designed to use multiple-targeting strategies. The combinatorial approach will enable combination therapy for delivery of multiple drugs and dual ligand targeting to improve targeting specificity. Targeted cancer treatments in development and the new combinatorial approaches show promise for improving targeted anticancer drug delivery and improving treatment outcomes.

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