Next Article in Journal
Hydrophobic Amino Acid Tryptophan Shows Promise as a Potential Absorption Enhancer for Oral Delivery of Biopharmaceuticals
Next Article in Special Issue
Co-Administered Polymeric Nano-Antidotes for Improved Photo-Triggered Response in Glioblastoma
Previous Article in Journal
Chitosan-Based Polyelectrolyte Complexes for Doxorubicin and Zoledronic Acid Combined Therapy to Overcome Multidrug Resistance
Previous Article in Special Issue
Preparation of Reduction-Responsive Camptothecin Nanocapsules by Combining Nanoprecipitation and In Situ Polymerization for Anticancer Therapy
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Pharmaceutics
Volume 10
Issue 4
10.3390/pharmaceutics10040181
pharmaceutics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Targeted Theranostic Nanoparticles for Brain Tumor Treatment

by
Maria Mendes
1,2,
João José Sousa
1,3,
Alberto Pais
4 and
Carla Vitorino
1,2,3,*
1
Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal
2
Center for Neurosciences and Cell Biology (CNC), University of Coimbra, 3004-504 Coimbra, Portugal
3
LAQV, REQUIMTE, Group of Pharmaceutical Technology, 3000-548 Coimbra, Portugal
4
Coimbra Chemistry Centre, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
*
Author to whom correspondence should be addressed.
Pharmaceutics 2018, 10(4), 181; https://doi.org/10.3390/pharmaceutics10040181
Submission received: 9 August 2018 / Revised: 21 September 2018 / Accepted: 27 September 2018 / Published: 9 October 2018
(This article belongs to the Special Issue Nanotheranostics and Cancer: Where Are We Now?)
Browse Figures
Versions Notes

Abstract

:
The poor prognosis and rapid recurrence of glioblastoma (GB) are associated to its fast-growing process and invasive nature, which make difficult the complete removal of the cancer infiltrated tissues. Additionally, GB heterogeneity within and between patients demands a patient-focused method of treatment. Thus, the implementation of nanotechnology is an attractive approach considering all anatomic issues of GB, since it will potentially improve brain drug distribution, due to the interaction between the blood–brain barrier and nanoparticles (NPs). In recent years, theranostic techniques have also been proposed and regarded as promising. NPs are advantageous for this application, due to their respective size, easy surface modification and versatility to integrate multiple functional components in one system. The design of nanoparticles focused on therapeutic and diagnostic applications has increased exponentially for the treatment of cancer. This dual approach helps to understand the location of the tumor tissue, the biodistribution of nanoparticles, the progress and efficacy of the treatment, and is highly useful for personalized medicine-based therapeutic interventions. To improve theranostic approaches, different active strategies can be used to modulate the surface of the nanotheranostic particle, including surface markers, proteins, drugs or genes, and take advantage of the characteristics of the microenvironment using stimuli responsive triggers. This review focuses on the different strategies to improve the GB treatment, describing some cell surface markers and their ligands, and reports some strategies, and their efficacy, used in the current research.

1. Introduction

Drug delivery to the brain is a major challenge, due to the high brain protection against the entry of foreign molecules. Many molecules are described having action in the brain disorders that fail clinical testing, due to their inability to cross the blood–brain barrier (BBB). This imposes the need for developing more effective delivery strategies. Nanostructured delivery systems (NDS) are complex nanocarriers that have sparked particular interest in biological applications, such as therapy and diagnosis, in some cases as multifunctional nanosystems, claiming two applications at the same time. NDS can be structurally divided into two parts: an external layer (shell), able to be functionalized with a variety of small molecules, proteins, metal ions, and/or polymers, and an internal layer (core), which is essentially the central portion of the NPs and chemically composed of different materials or a simple reservoir (comprising drugs and contrast agents) as in the case of liposomes. They have the ability to carry various therapeutic molecules, including small molecules, proteins, peptides and genetic material. In this context, theranostic nanoparticles arise as promising systems bringing new opportunities to overcome the restrictions of current brain tumor treatment/diagnosis options in the clinic, protecting the drug from metabolism, conveying two or more drugs simultaneously with synergistic effect, enabling a controlled and specific release of the drug, thereby decreasing the respective side effects.
In this review, the brain tumor classification and biological features are described, followed by the obstacles imposed to an effective treatment. Subsequently, recent advances and clinical applications of nanoparticles (NPs) in brain tumor therapeutics are addressed, with focus on: (i) the several approaches for brain targeting; (ii) the combination of both imaging and therapeutic functions (i.e., theranostics); and (iii) the use of NDS for glioblastoma treatment, including current research, and pre-clinical and clinical investigation. The importance of nanotheranostics in a personalized medicine perspective and the difficulties found for the respective clinic translation are also considered.

2. Glioblastoma

Brain tumors are a heterogeneous group of primary and metastatic neoplasms in the central nervous system (CNS), characterized by poor prognosis and patient low survival rate. They are classified by the World Health Organization (WHO) according to a grade of malignancy that is closely related to diagnosis, varying from grade I, which is characterized by lesions with low proliferative potential and possibility of cure, to grade IV, which is described as cytological malignant, mitotically active neoplasms that are typically associated with extensive invasion of the surrounding healthy tissue and rapid proliferation linked to disease evolution (Table 1) [1]. Glioblastoma (GB), a grade IV glioma, is the most frequent primary brain tumor, the most aggressive and lethal in humans, with a patient survival rate between 8 and 14 months after diagnosis [2]. The poor prognosis is partly because of the multidrug resistance, limited surgical resection, critical importance of the residual glioma cells that have capacity to develop a new primary tumor, and surgery-dependent malignance. One of the most challenging problems in GB therapy is its particularly complex and heterogeneous molecular biology. Consequently, the response to the same treatment by different patients results in equally different prognosis. Current management of GB frequently consists of surgical resection, followed by radiotherapy (RT) and adjuvant chemotherapy, both treatments inducing DNA damage (Table 1) [3]. The low therapeutic efficacy, associated to a large side effects spectrum, involving damage in healthy tissues, require regular invasive dose regimens. Generally, the long-term patient quality of life is poor, because the outlying tissues must be subjected to treatment, otherwise the tumor will reappear, which make the treatment of GB even more difficult. The development of GB still varies according to sex, being more prevalence in males, age (>45 years) and existence of genetic disorders [4].
In the next section, the barriers to GB treatment, particularly, BBB and BBTB, are reviewed, as well as the emerging advances in the treatment of GB using NPs as a promising strategy, with emphasis on drug delivery, targeting and diagnosis in real-time.

2.1. Barriers and Transport Pathways for the Treatment of Glioblastoma

Several obstacles limit GB treatment efficacy, including the structural complexity of the brain, the blood–brain barrier (BBB) and blood–brain–tumor barrier (BBTB), the heterogeneous and invasive nature of the tumor, insufficient accumulation of drugs at the site of the tumor and resistance of chemotherapeutics.

2.1.1. Blood–Brain Barrier

The BBB severely restricts drug transport into the brain by serving as a physical (tight junctions), metabolic (enzymes) and immunological barrier [18]. The BBB is responsible for regulating the ionic composition for synaptic signaling function and providing brain nutrients, which prevents the entry of any macromolecules and protects the CNS from neurotoxic substances [18]. The anatomical structure of the BBB consists of a monolayer of non-fenestrated blood vessel endothelial cells attached by tight junctions (TJs) through the interaction of cell adhesion molecules, pericytes, and astrocytes, which provides a structural support by holding the cells together [19]. In addition, the barriers created by TJs among cerebral endothelial cells (ECs), the choroid plexus epithelial cells and the cells of the arachnoid epithelium prevent the access through the paracellular pathway [20,21]. The BBB microenvironment is constituted by macrophages, fibroblasts, neuronal cells, basal membranes and microglia [22]. The presence of numerous enzymes in cerebral ECs and efflux transport mechanisms, e.g., P-glycoprotein (P-gp), constitute major obstacles for molecules to cross the BBB. Several BBB transport pathways are described depending on physicochemical properties of drug molecules, such as paracellular aqueous pathways, transcellular lipophilic pathways, transport proteins, receptor-mediated transcytosis and adsorptive transcytosis (Figure 1). Passive diffusion depends on molecular weight and lipophilicity. Additionally, the capacity of molecules to form hydrogen bonds will limit their diffusion through the BBB. Only a few small molecule drugs cross the BBB by lipid-mediated free diffusion, unless the drug possesses a molecular weight of less than 400 Da and forms less than 8 hydrogen bonds [23,24]. The difficulty of crossing the BBB is even more evident in the case of large molecule drugs. About 100% of large molecule drugs do not pass the BBB, including proteins and enzymes, monoclonal antibodies, or gene therapy. Brain diffusion of exogenous molecules is limited by ATP-binding cassette (ABC) transporters, efflux transport proteins placed at the luminal endothelial cell membrane. Alternative pathways traversing the BBB have been investigated for their potential application in invasive drug delivery. In addition to the transcellular lipophilic pathway for small, lipophilic molecules, the other transport routes include adsorptive-mediated (AMT), carrier-mediated (CMT), and receptor-mediated transcytosis (RMT) have been employed for targeting the brain [25,26,27].

Adsorptive-Mediated Transport

Adsorptive-mediated transport (AMT) is a nonspecific process by which macromolecules are transported within membrane bound vesicles between apical and basolateral domains of polarized cells. This process is possible due to the abundance of polyanions surrounding the BBB endothelial cells that are able to interact electrostatically with circulating cationic molecules. This activity does not involve particular membrane receptors. The electrostatic interaction between positively-charged molecules and negative charge of BBB cells has been used to favor GB targeting. Cationic albumin-conjugated (CBSA), gemini surfactants, charged-cell penetrating peptides (CPP) or cationized immunoglobulin G are some examples of positive molecules that are strategically coupled to the surface of NDS [28,29,30,31,32,33,34,35]. However, electrostatic interactions at the BBB are not always consistent [36]. Surface charge can influence the interaction between nanoparticle and cells, affecting in particular processes such as cellular uptake, biodistribution, metabolism and excretion. Some works have demonstrated that positive-NPs are more easily internalized than neutral- and negative-NPs. However, positive-NPs have more tendency to adsorbed serum proteins and other biomolecules in circulation and consequently a new interface is formed, also known as corona [37,38,39,40]. These somewhat altered NPs display in vivo a behavior different from that of the original NPs, impacting upon the specific targeting between ligands and receptor [41]. Thus, the corona formation needs to be further studied, and directed to the biological application [42]. In addition, it should be taken into consideration that the original charge of the nanoparticle is likely to affect the characteristics of corona and this must be kept in mind when designing NPs, especially in case of brain delivery.

Carrier-Mediated Transcytosis

Carrier-mediated transcytosis (CMT) is substrate-selective and the transport rate is dependent on the degree of occupation of the carrier. CMT enables spontaneous internalization of small biomolecules, including nutrients (glucose), hormones, amino acids, bile salts, and monocarboxylic acids by passive diffusion. This type of transport is used for the delivery of nutrients, such as glucose, amino acids, and purine bases, to the brain. Eight different nutrient transport systems have been recognized, each one transporting a group of nutrients of the same structure [43]. Glucose is essential for brain function and crosses the BBB via a specific transporter by glucose receptors (GLUT). Beyond the nutrients, there are several amino acid transporters at the BBB to maintain brain homeostasis, including neutral amino acids transporter (NAAT), cationic amino acids transporter (CAATs), anionic amino acids transporters (AAATs) and beta amino acid transporter (βAATs) [44]. The choline transporter (ChT) is used for transportation of choline and thiamine to support the neurological supplies of brain [45,46]. Peptide (PT), fatty acid (FAT) and nucleoside transporters (NTs) are also expressed in the BBB (Table 2). Therefore, only drugs that closely mimic the endogenous carrier substrates will be taken up and transported into the brain. Nutrients and hormones or carrier systems, at the BBB level, have been exploited for brain delivery, increasing metabolic stability, reduced clearance, and improved BBB transport.

Receptor-Mediated Transcytosis

Receptor mediated transcytosis (RMT) is characterized by high specificity, selectivity and affinity and considered one of the best strategies for brain targeted drug delivery [60,61]. The mechanisms occur when the ligand binds to a transmembrane receptor, which is expressed on the apical plasma membrane of the endothelial cell (Figure 1). The transferrin receptor (TfR), the low density lipoprotein receptor (LDLR), the insulin receptor (IR) and the nicotinic acetylcholine receptors (nAChRs) are examples of receptor expression on the BBB, and could be targeted by ligands, such as endo- or exogenous ligands (Table 3). The TfR is one of the most characterized RMT for brain targeting, due to their high expression on endothelial cells on the brain capillary endothelial cells (BCECs) and tumor cells. Different transferrin-NDS for drug delivery through the BBB have been developed, and in vitro and in vivo brain-targeting efficiencies have been reported [62,63]. However, transferrin is a natural ligand, and consequently, TfR is saturated for the endogenous TF, having a natural competition between endogenous TF and the TF-NPs. For this reason, OX26 and RI7217 have been studied in order to avoid this competition [64,65,66]. Both are monoclonal antibodies with a high affinity for TfR. LDLR, expressed on the BCECs, have endogenous ligands including cholesterol and apolipoprotein (Apo) [67,68,69,70,71,72]. Angiopep-2, apolipoprotein B or E (ApoB or ApoE), polysorbate 80 (PS80) and, more recently, polyoxyethylene sorbitol oleate (PSO) have been described as exogenous ligands [73,74,75,76,77,78]. Insulin receptor (IR) is a transmembrane glycosylated protein sensible to the transport of blood-borne insulin into the brain [79,80]. Nicotinic acetylcholine receptors (nAChRs), highly expressed on the capillary endothelium of the brain, have been used to facilitate BBB crossing of NDS. The large expression of nAChRs in the brain and their susceptibility to the inhibition by peptide neurotoxins provide them the capacity to mediate peptide-based delivery of various therapeutic agents to the brain [81]. ABC (ATP-binding cassette) transporters are ATP-driven drug efflux pumps expressed in the BBB which embrace P-glycoprotein (P-gp) and members of the multidrug resistance related proteins (MDRs, especially MRP1, MRP2, MRP4 and MRP5), and breast cancer resistance protein (BCRP and ABCG2) [82,83]. These proteins are expressed at the luminal side of brain capillaries and are a barrier for the brain uptake of a huge diversity of lipophilic molecules, potentially toxic metabolites, xenobiotics, and drugs [84]. Even though different RMTs are described in the literature as possible active targets for the brain, they are also present in other biological barriers (e.g., intestinal membrane and liver) [85,86,87]. For this reason, this is an ineffective method for active targeting NPs. Thus, active targeting strategy needs to be well designed to avoid off-target NPs accumulation in other tissues.
Cell penetrating peptides (CPP), that show great capacity in BBB transport, have the ability to transport protein or peptides into cells in a nonspecific, receptor-independent manner. CPPs are small peptides with appealing capability of membrane translocation and cellular uptake. Moreover, CPPs have the advantage of being non-immunogenic when compared with antibodies, which make them interesting as targeting strategy for a broad range of therapeutics [88,89,90,91]. They can vehicle the molecules that are attached to them across the cell membrane, into the cytoplasm and to the nucleus, associated either through physical or covalent interactions. According to their physicochemical properties, CPPs can be grouped into different classes, such as cationic, hydrophobic, and amphipathic [92]. Some CPPs, named as activable cell-penetrating peptides (ACPPs), can be synthetized to be active under the action of certain triggers, when reached the target site, such as pH, proteinase, and UV light (Table 3) [93,94,95,96,97,98]. ACPPs are promising methods due to their stealth properties. Among all these triggers, enzyme-triggered systems have been widely studied and applied in tumor imaging and therapy. Recently, chemotherapeutic NDS decorated with CPPs for tumor treatment have been developed and assessed, including the GB [99,100,101]. They can intermediate the cellular uptake of a wide range of macromolecules and thus have called significant attention as drug delivery in vivo strategy. Different CPPs have been described, and their classification consider multiple approaches, such as source, function, sequence, mechanism of uptake, and biomedical application (Figure 2 and Table 1).
Another approach described in the literature is the conjugation of tumor targeting peptides (TTP) with CPP [102,103,104,105]. TTP are molecules that interact particularly with overexpressed receptors on tumor cells (cell markers are represented in Table 3). However, they may not be able to reach the target on their own. For this reason, the interaction between TTP and CPP has been investigated, used as a synergistic effect, facilitating the translocation of the conjugate unit to target tumor sites with enhanced specificity and selectivity [91]. Several experimental studies show that TTPs alone have considerably reduced easiness to translocate therapeutic molecules.

2.1.2. Blood–Brain–Tumor Barrier

The status, function and organization of the BBB is different depending on the brain disease. Barrier modification, in morphology and permeability, occurs depending on the progress of tumor. Thus, GB, a high-grade brain tumor, induces major alterations characterized by abnormal vascularization, resulting in a disrupted blood–brain–tumor barrier (BBTB). The BBTB is designed by brain tumor capillaries and forms a barrier that is different from the BBB. In addition, tight junctions of endothelial cells in a brain tumor scenario are compromised (Figure 3). The high metabolic stresses of GB produce hypoxic areas that have an increased expression of vascular endothelial growth factor (VEGF) and angiogenesis, with a dominant formation of abnormal vessels and, consequently, a dysfunctional BBTB. The fenestration in BBTB displays a significantly higher permeability compared to the BBB, allowing molecules with size below 12 nm to pass from the blood stream into the brain. Depending on the GB phase, there are regions in the brain that present fenestrations whose size is variable and can increase to a micron, more specifically in the third phase (Table 4). Thus, the BBTB is susceptible for nanocarriers and enhanced permeability and retention (EPR) effect, with a preferential accumulation in the tumor tissues [132,133]. However, the rapid progression of GB forced by the tumor aggressiveness, leads to a quick spread into the surrounding healthy tissues causing the BBTB damage and prompting EPR effect. The BBTB remains a hurdle for drug delivery, leading to heterogeneous drug accumulation, which compromises the therapeutic outcome. BBTB shows specific characteristics and overexpressed receptors that mediate ligand dependent drug delivery, which can be exploited to selectively enhance drug delivery to tumor tissues. Anti-angiogenic therapies are being applied as an adjuvant to regulate GB vasculature.
BBTB blood vessels contribute to the delivery of nutrients and oxygen to the tumor and accelerate glioma cell migration to other parts of the brain. Some overexpressed receptors on BBTB are receptor tyrosine kinases (RTKs). RTKs are described as high affinity cell surface receptors and mediate signal transductions with an essential function in the growth and progression of GB. VEGF receptors, epidermal growth factor receptors (EGFR) and platelet-derived growth factor receptor (PDGFR), provide a chance for glioma targeting drug delivery.
EGFR is a receptor tyrosine kinase and the most frequent amplified gene in GB, being responsible for the radiotherapy resistance. Activation of these receptors results in activation of multiple signaling pathways (e.g., the Ras/Raf/MEK/ERK1/2-mitogen-activated protein kinase (MAPK) pathway and the phosphatidylinositol 3′-kinase(PI3K)/Akt/mTOR pathway) [136]. EGFR plays a critical role in the development and progression of the diseases, affecting cell proliferation, migration, differentiation, inhibition of apoptosis and increased angiogenesis.
VEGF receptors (VEGFRs), including VEGFR-1, VEGFR-2, and VEGFR-3, are overexpressed in ECs to control tumor vasculature. As mentioned in Section 2.1.4., the high metabolic stress creates hypoxic areas, which lead to an increased expression of VEGF and angiogenesis. VEGF is one of the most crucial growth factors and plays an essential role in GB neovascularization by interacting with a number of signaling pathways, so targeting VEGF pathways would reduce tumor vasculature [134,135]. The identification of the VEGF pathway is a key regulator of angiogenesis.

2.1.3. Tumor Microenvironment

Tumor growth and progression are caused not only by cumulative gene mutations, but also by the significant influence of the surrounding tumor microenvironment (TME) [137]. TME is a dynamic space and is characterized by cellular heterogeneity, including endothelial cells (ECs), extracellular matrix (ECM), macrophages, fibroblasts, perivascular cells, and inflammatory cells [138]. All of these components are the key for governing cellular growth, the preservation of homeostasis, being involved in the regulation of the tumorigenic process (angiogenesis, lymphanogenesis, and inflammation). The TME has significantly contributed to the failure of conventional chemotherapy, and to the malignant progression, dictating the incomplete eradication of the tumor [139]. Tumor progress requires constant maintenance, which is dependent of the interaction of the immune cells and the TME. Consequently, cancer cells can control the immune cells so as to promote cancer development and related pathological processes. TME is likely to influence malignant cell growth by releasing proteins, growth factors, cytokines, and proteases that allow cancer cells motility and adhesion. In fact, the understanding of the function of the TME in tumor progression is critical to cancer eradication. Strategies that inhibit this support to tumor cells reduce chemoresistance and tumor recurrence [137,140,141]. These consider the modulation of the tumor extracellular matrix (ECM), immune cells and response to tumor hypoxia. Although there has been considerable progress in the use of nanoparticles directed at the TME, these new strategies still face many challenges in terms of their clinical impact.
The extracellular matrix (ECM) comprises all secreted soluble and insoluble components found in the extracellular space, e.g., collagen, elastin fibers, glycoproteins, proteoglycans, and hyaluronic acid (HA) [142]. ECM components and their complementary receptors (e.g., integrins and CD44) not only contribute to cellular organization, but also to cell behavior and brain tumor evolution, with an important role in processes, such as proliferation, survival and differentiation of cells. The cell development is ensured by ECM functionality, which provides the maintenance of structural integrity and the transport of nutrients and oxygen. Thus, ECM is multifunctional and can stimulate several mechanical and biochemical processes simultaneously, including an adhesive substrate which provides structure, present growth factors to their receptors, senses and transduces mechanical signals sequesters and stores growth factors. The highly-upregulated ECM molecules in TME have been extensively correlated with the malignancy of the tumor. Lactic acid, fatty acids, angiogenic growth factors, stromal cell-derived factor 1, angiopoietin 2, tenascin-C or connective tissue growth factors are some examples of ECM molecules which accumulate in the tumor microenvironment [135,143].
Protease and lipase are enzymes overexpressed by tumor cells that can be used as endogenous triggers for cancer targeting. Matrix metalloproteinases (MMPs), especially MMP-2 and MMP-9, are responsible for the changes in TME during tumor development. They mediate ECM degradation and support cancer cell metastasis and invasion. MMPs also regulate signaling pathways that control cell growth, inflammation, or angiogenesis.
The interaction of glioma cells with the ECM is largely mediated by mediated by cell surface receptors of the integrin. Integrins are extracellular matrix transmembrane receptors, including α6β4, α5β1, αvβ6, and αvβ3, that are overexpressed on GB, but not on normal brain tissues, and this represents a typical targeted treatment strategy directed to angiogenesis, tumor cell proliferation, inflammation and survival [144]. αvβ3- and αvβ5-associated angiogenesis are respectively dependent on tumor cell-secreted fibroblast growth factor (bFGF)/tumor necrosis factor (TNF)α and VEGF through an amplification loop leading to αvβ3/αvβ5 overexpression on EC [145,146,147,148,149,150]. Integrin-mediated signaling pathways have been found to promote the invasiveness and survival of glioma cells in brain microenvironment, more concretely they support the formation of the tumoral niche [151]. As such, integrins are a promise targeting for GB treatment due to their implication in tumor cell functions and their interaction with several pathways, including MAP kinase, Jun, NF-κB, and their location at the TME [110,145,152,153].
CD44 is a transmembrane glycoprotein expressed on normal cells and overexpressed in glioma cells [154]. CD44 is a cell membrane receptor that mediates cell–cell and cell–ECM interactions. CD44 serves as a surface receptor for ECM molecules such as hyaluronic acid (HA) and chondroitin sulfate proteoglycan (CSPGs). The HA–CD44 interaction and CD44 shedding from the cell surface were found to be associated with glioma cell motility, migration, and infiltration into the normal brain parenchyma [155].
Different types of immune cells, including T and B lymphocytes, natural killer T (NKT) cells, dendritic cells (DCs), tumor-associated macrophages (TAMs), tumor-associated fibroblasts (TAFs) and myeloid-derived suppressor cells (MDSCs) can infiltrate in the TME. GB is associated with several immunosuppressive cytokines. These molecules are secreted by immune cells and are responsible by blocking T-cell activation and proliferation, inhibiting IL-2 production, suppressing natural killer cell activity, and stimulating regulator T cells (Tregs), and support tumor growth, invasion and enhance angiogenesis [156]. Thus, targeting tumor-associated immune cells is described as an interesting strategy, due to the stimulation of immune response against cancer cells. Vaccination, checkpoint inhibitor molecules, adoptive cell therapy, and monoclonal antibodies are some examples of immunotherapy strategies. Some of them have already been recognized as an advantageous treatment [157].
Tumor-associated macrophages (TAMs) are inflammatory cells of the innate immune system, which represent ca. 30–40% of the cells in GBM; their presence has been correlated with poor prognosis in cancer [158]. Recent work has also addressed the effect of mesenchymal stem/stromal cells (MSCs) that constitute an attractive tool for cell-based cancer therapy mainly because of their ability to migrate to tumors and to release bioactive molecules [159,160]. TAMs in tumor microenvironment promote immune evasion and angiogenesis, stimulate cancer cell proliferation, immunosuppression, and support tumor growth and metastasis. TAMs are also described as a possible cause for drug resistance with radio protective effects, having been associated to therapy failure [161]. There are essentially two types of macrophages: one supporting the inflammatory response and antitumor immunity (M1/M(LPS)), having an important role in killing and removing tumor cells, and the other involved in tumorigenesis (M2/M(IL-4)), being associated to pro-tumorigenic activities angiogenesis, recruitment of leukocytes, and immune suppression [162,163]. TAMs targeting is a promising adjuvant approach for anti-cancer treatments (Figure 4) [162,164,165,166,167]. Indeed, different research groups have found that the NPs accumulate at high levels within TAMs, and that TAMs serve as “cellular drug reservoirs” [166,168,169,170]. Consequently, there is a reduction of actively targeted NPs to the target sites, and a significant decrease of the intratumoral NPs density. Due to the importance of TAMs, they are becoming the main target of new therapeutic strategies, and can be adopted for a future development and clinical use of NPs. As previously stated, TAMs are an important component in TME and execute tumor-protecting functions. Thus, a higher NPs accumulation in TAMs can be considered as an appealing strategy for cancer treatment, especially relevant in the context of therapies that increase or decrease infiltration of macrophages to tumors [171]. GB-associated macrophages are mainly bone marrow (BM)-derived infiltrating myeloid cells [172,173]. These cells arise in an early stage of tumor formation, and their location in the perivascular niche contribute to tumor progress. Recent studies showed that reducing their infiltration by genetic modulation significantly prolongs the survival in mice [173].
Fibroblasts and bone marrow-derived mesenchymal stem cells are activated through growth factors released by tumor cells in tumorigenic process [174]. Tumor-associated fibroblasts (TAFs) promote tumor development by secreting cytokines as VEGF, IL-6, and HGF, that are responsible by the induction of the tumor vascularization and subsequently stimulate cell proliferation. TAFs produce a high amount of proteoglycans, collagens and secrete different extracellular enzymes, such as MMPs, disintegrins, and plasmin [175].
The decrease of nutrient and oxygen transport by abnormal tumor vasculature results in hypoxic sections, which are commonly evidenced within most solid tumors. Hypoxia has correlation with the insufficient blood flow, while chronic hypoxia is the outcome of amplified oxygen diffusion distance [176]. The critical pathogenetic mechanisms for the development of hypoxia are structural and functional abnormalities in the tumor microvasculature, an increase in diffusion distances and tumor- or therapy-associated anemia leading to a reduced O2 transport capacity of the blood, which can stimulate an adaptive reaction [177]. The extent hypoxia depends on clinical size, stage, and grade. Therefore, this adaptive mechanism leads to a negative impact in radiotherapy and chemotherapeutics by reducing the oxygen level needed for free radical formation, which is critical for cell cancer death [178]. The hypoxia leads to the activation of the phosphatidylinositol-3 kinases (PI3K)-Protein Kinase B (Akt) pathway. Akt is involved in several cellular functions including cell proliferation, apoptosis resistance, cell survival and a diversity of metabolic functions. Thus, the activation of those pathways allows the activation of the hypoxia-inducible transcription factor 1 (HIF-1), a heterodimeric protein [179]. In normal tissues, HIF-1a is destroyed by the ubiquitin-proteasome system, but when the intracellular oxygen concentration decreases, HIF-1a is stabilized and translocated to the nucleus where it binds to HIF-1b. The HIF-1a and -1b dimers activate transcription of genes involved in angiogenesis, glucose transport, apoptosis resistance, metastasis and inflammation [180]. The pro-inflammatory components include membrane receptors RAGE and P2X7R; inducible enzymes, e.g., COX-2 and NOS-2; and proteins such as PTX3 [180]. Moreover, the hypoxia environment allows an increase of expression of chemokine (C-X-C motif) receptor 4 (CXCR4), one of the components responsible for the invasion and migration of tumor cells. Several approaches for targeting hypoxic tumor cells have been suggested, including gene therapy, specific targeting of HIFs, or targeting important pathways in hypoxic cells [181,182]. A consequence of hypoxia is the conversion of glucose into lactate to produce ATP, CO2 and carbonic acid. The low clearance of these acidic metabolic products causes a decrease in interstitial pH of solid tumors, including GB [183]. For this reason, the extracellular tumor pH (pHe) is around 5.7–7.2. To take advantage of this characteristic, different approaches have been developed, including pH-triggered-NPs, which increases drug accumulation inside the tumor and reduces the cytotoxicity to the normal tissues [184].

2.1.4. Glioma Stem Cells

Glioma stem cells (GSCs) characterize a subpopulation of tumor cells within GB which are possibly the cause of the increased resistance to conventional therapies, and, consequently, the major cells responsible for failure of treatment and high recurrence rates in GB. GSCs present the same characteristics of normal stem cells with the particularity of being oncogenic in their host and giving rise to a heterogeneous population of cells that comprise the tumor mass. Proliferation, self-renewal, multi-differentiation potential in vitro and tumorigenic capability in vivo are some of their mechanistic process (Figure 5).
Considering all these mechanisms, GSCs contribute to tumor beginning and therapeutic resistance, so this is one of the main reasons of the failure to eliminate the tumor cells (Figure 6) [191]. To improve the conventional therapies, it is possible to take advantage of stem cell marker expression. Thus, targeting cell surface markers and specific pathways that are essential for maintaining GSC represents a smart and important strategy for therapy of GB (Figure 5) [192,193,194]. The niches where GSCs reside are organized by immune cells, fibroblastic cells, endothelial cells, integrin receptors, ECM components, cytokines and growth factors. As such, targeting GSCs and their niches introduce the possibility to eradicate the likely basis of gliomas and their recurrence chance [158].

3. Strategies to Enhance the Permeability of the Blood–Brain Barrier for Treatment of Glioblastoma

The heterogeneity of GB, in combination with its high infiltrative nature, determine a poor outcome for standard treatments. To overcome these hurdles, different targeting strategies have been adopted for developing effective nanostructured delivery systems (NDS) to the brain. There are many strategies described to direct NPs to the brain tumor, including the use of nanotechnology coupled with passive, active or stimuli responsive targeting approaches (Figure 7) [195,196,197,198,199].

3.1. Nanoparticles for GB Treatment

Nanotechnology provides endless opportunities in the area of cancer treatment using targeted anticancer drug delivery systems. For that, NPs have to be appropriately studied and designed to accomplish the greatest therapeutic and/or diagnostic effect with reduced side effects, especially for chemotherapy drugs [200] (Figure 8). NPs are complex drug delivery systems, which can be structurally divided into the external layer (shell) and internal layer (core). The shell can be functionalized with a variety of small molecules, polymers, polysaccharides, proteins and metal ions; the core, a central part of the NPs, can be chemically combined with different materials. NPs are flexible and versatile, with an architecture that ensure small size, appropriate shape, and surface functionalization, in order to accomplish the objectives of the proposed function. NPs have been shown to improve pharmacokinetics of available drugs, by reducing drug biodistribution to non-target compartments, delivering the adequate amount of the drug into the right site, overcoming solubility and stability issues and allowing higher drug encapsulation. Regarding the complexity of BBB and/or BBTB, NPs offer the possibility to encapsulate hydrophilic anticancer drugs, increase the blood circulation and tissue distribution, with improvement of their preferential accumulation at the tumor site. Additionally, NPs have been described to overcome multi-drug resistance mechanisms [201]. Several nanostructured delivery systems (NDS) have been developed for brain tumor delivery, and depending on the nature and composition, they can be classified as organic NPs and inorganic NPs [202,203]. Organic NPs are described as being composed by organic compounds, including lipids, surfactants or polymers with the GRAS (generally regarded as safe) status, that offer an easy way for the encapsulation of molecules. Liposomes, polymeric nanoparticles, lipid nanoparticles, micelles/polymeric micelles, protein based nanoparticles are some examples of organic NPs. An extensive research is already reported with organic NPs for the GB treatment. The NPs performance has been assessed through in vitro and in vivo studies, and compared with the free drugs, and the results seem to be promising, showing the ability to transport drugs across the BBB in a more efficient way, with a preferential distribution in the brain [76,146,149,204,205,206,207,208,209,210,211,212,213,214,215]. On the other hand, inorganic NPs contain a solid core with physicochemical properties that can be attributed to their inorganic components, such as magnetic metal oxide or semiconductor material. Different types of inorganic NPs have been described and employed for biological applications, including iron oxide nanoparticles, mesoporous silica nanoparticles, gold nanoparticles and quantum dots. The main advantages of inorganic NPs are their robustness, resistance to enzymatic degradation and interesting intrinsic characteristics, such as optical, thermal, magnetic and electrical properties, that can be used for imaging and therapeutic approach. Considering their nature composition, inorganic NPs can be synthesized and modified in a way that facilitates the surface functionalization by incorporation of ligands or polymers, improving their biological function [216]. The use of biocompatible coatings has shown to reduce the toxicity associated to the presence of the heavy metal. Inorganic NPs have also been widely investigated for diagnostic applications, using their distinct abilities to respond to external stimuli and physiological changes [217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242]. As shown in different reviews, several types of NPs (magnetic, fluorescent, liposomal, polymeric, lipidic, among others) have already been designed and developed for crossing the BBB to GB therapy, considering passive, active and stimuli targeting approaches [6,133,243,244,245,246,247]. NPs are an interesting drug delivery system, presenting a high potential for improving patient outcomes. However, their translation from pre-clinical proof of concept to the demonstration of therapeutic value in the clinic remains a long, costly, and challenging path. The scaling up procedure, surface modification, biopersistence and toxicological aspects, recognition and quantification of NPs in the human body are some critical points that make difficult the translation. Several types of research focusing on NPs characterization, and in vitro and in vivo studies have been carried out, but many questions remain without answers. In vitro and in vitro studies for GB treatment, encompassing multiple biological targets, have been described and include gold nanoparticles, chitosan-based nanoparticle, curcumin-loaded PLGA-DSPE-PEG nanoparticles, curcumin-loaded RDP-liposomes, hyaluronic acid conjugated liposomes, iron oxide nanoparticle coated with chitosan-PEG-polyethyleneimine copolymer and CTX loading plasmid DNA encoding TRAIL, c(RGDyK)-pHA-PEG-DSPE-incorporated DOX loaded liposomes, and others [248,249,250,251,252,253,254,255]. These have been considered as effective against glioblastoma, and in vivo results show a potential application in diagnosis, with important therapeutic implications, resulting from a significant accumulation in the brain tumor regions. Only a small number of NPs have been evaluated in clinical trials, and fewer were extended to clinical practice [256]. In what follows, the reference of clinical trial is quoted, as extracted from clinicaltrial.gov. REF Nanoliposomal CPT-11 (NCT00734682 and NCT02022644), SGT-53 (liposomal nanocomplex encapsulating a wild type p53 DNA sequence) used in combination with temozolomide, NU-0129 (NCT03020017, gold nanoparticles based on spherical nucleic acid) and PEGylated liposomal DOX (NCT02766699, CaelyxTM, PEG-Dox) constitute some of the clinical trials that have been conducted in recent years, and illustrate the variety of theranostic approaches. NanoTherm (Aminosilane-coated SIONPs) and Opaxio (ester conjugate of α–poly(l)–glutamic acid (PGA) and paclitaxel) are NPs already implemented in clinic. However, the inability to effectively control the behavior of NPs inside the body, including biodistribution, toxicity and pharmacokinetics, represents a major limitation for using nanotechnology to diagnose and treat cancer [257,258,259].

3.2. Passive Targeting

Passive targeting resorts to brain tumor properties, including hyper-vascularizing, leaky and scarce lymphatic drainage system, to make drug available into the intratumoral space, while depriving healthy brain tissue. NPs dynamics through the brain depend on the integrity of the barrier, which may be compromised in the presence of some diseases, and on the size, geometry and surface properties of the actual particles. These parameters must be controlled to avoid uptake by the reticuloendothelial system (RES). To maximize circulation times and targeting ability, literature indicates NPs optimal size as less than 100 nm in diameter, and suggests the presence of an hydrophilic surface to circumvent clearance by macrophages within the RES [261]. Nanoparticles 100–400 nm in size did not show significant difference for overcoming the BBB. However, significant differences were observed when nanoparticle size was below 100 nm, for which the effects were more pronounced [262]. Some work focused on correlating the size of NPs to their biological effects [263,264,265]. It can be concluded that the size and the charge of nanoparticles are controversial in the effects promoted in vivo, and further studies are needed to clarify this subject. Thus, NPs have the advantage of the small size to provide a preferential accumulation at the site of brain tumor due to the morphology and permeability of the barrier, EPR effect (Figure 6) [201,266]. The EPR effect does not occur with the conventional chemotherapeutic molecules, due to the lack of specificity between normal and tumor tissues. However, the ability of drug diffusion is an important parameter that hinders the passive targeting strategies, due to the difficulty to control drug release. Therefore, to achieve an efficient EPR effect, NPs should be smaller than 100 nm and present a biocompatible surface (neutral charge and hydrophilic properties) to avoid the reticuloendothelial system (RES) [40,267].

3.3. Active Targeting

To increase the selectivity of drug release at the chosen sites of action, and achieve enhanced therapeutic efficacy, an active targeting approach is required [268]. These strategies consist in incorporating affinity molecules or taking advantage of influx transport systems expressed within the BBB/BBTB, into NPs surface, bearing in mind the specific characteristics of abnormal tissue, e.g., the differential expression of receptors or antigens in cancer cells (as described in Section 2.1). These include a wide range of peptides, antibodies or antibody fragments, aptamers and other small molecules [62,72,254,269,270,271]. GB is characterized by several molecular mechanisms of chemoresistance, so the development of actively targeted NPs to surface cell markers, signaling pathways and tumor microenvironment represents an interesting and challenging opportunity (Table 5). These approaches are accomplished by connecting specific ligands to the NPs structure, which allows a selective recognition of different receptors overexpressed in the tumor cell surfaces. The functionalization of the NPs surface improves therapeutic efficacy of cytotoxic drugs and overcomes the multidrug resistance (MDR).

3.4. Stimuli-Responsive Strategies

The lack of control over drug release has prompted the development of NPs tailored to respond to endogenous and/or exogenous stimuli (Figure 8). The benefits of internal-stimuli responsive NPs are evident, because the stimuli specifically exists in characteristic pathological sites [272,273,274]. The endogenous triggers, such as pH variations, enzymes, glucose or redox gradient, can be used depending on the disease pathological characteristics [275]. As previously discussed (Section 2.1.4.), tumors have an acidic pH in contrast to the normal tissues, so there is an opportunity to use pH-stimuli responsive NPs [276,277,278]. Due to their conformation changing or bond cleavage sensitive to different pH values, pH-responsive NPs allow the release of loaded drug in precise locations. This strategy has been applied by different research groups, and the results have been satisfactory [96,102,113,127,128,129,130,131,279]. The redox-sensitive NPs are used also as a stimuli response, due to the intrinsic redox gradients in the cells. Taking advantage of the higher concentration of glutathione (GSH) that regulates the intracellular redox condition, NPs with disulfide bonds are broken down and the cargo is released. This bond is unstable in high concentrations of GSH, being reduced to thiol groups inside the cells. The enzymatic-stimuli response is also an interesting approach, due to the high expression of enzymes in the tumor bulk, in particular extracellular matrix metalloproteinases (MMPs) [124,125,126,280,281,282].
In turn, the exogenous triggers use external forces, including temperature, magnetic field, ultrasound, light, electric pulse, or high radiation [283]. Targeting moieties can be combined directly or indirectly by covalent or non-covalent linkage.
The heterogeneity in the physiological conditions, the combination of endo- and exogenous stimuli-responsive NDS might be more favorable, allowing to target different environments. It is possible to combine triggers, such as pH/temperature, pH/redox, temperature/redox, and temperature/pH/redox, among others, which exhibit additional advantages in comparison to NDS employing single stimulus. This is a field that has attracted much attention in recent years [275,284].

4. Theranostics

The current progress in GB therapy and detection evidences that there has been no significant reduction in GB associated with death rates. The heterogeneity of the tumor, the unspecific drug delivery, the diagnosis failure in the primary stage detection are some of the reasons responsible for the treatment inefficiency. Thus, the combination of earlier detection and targeting therapy procedures, termed as theranostics, has been developed as a strategy to improve the GB treatment. The theranostic approach make possible to diagnose the GB, understand the location of the GB and the stage of disease, and also to percept the tumor progression. These strategies help to address the intra- and interpatient heterogeneity of GB, pointing out to a future application in personalized medicine. The use of a single and multimodal system appears to be one of the most promising characteristics of NPs application (Scheme 1).
In this context, a new technological concept has been introduced and designed as theranostic nanoparticles (TNPs) (Figure 9). TNPs are described as a combination of both organic and inorganic NPs to obtain multiple synergistic properties in a single NP, taking advantages of the drug delivery by organic NPs and imaging prompted by inorganic NPs [374,375,376,377]. The preparation methods and physicochemical characterization through in vitro evaluation on cell culture and in vivo studies have been described for a variety of TNPs. These NPs have shown interesting results during in vitro studies. However, considering the different diagnostic approaches, including magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, optical imaging (OI) and photoacoustic imaging (PAI), positron emission tomography (PET) and single photon emission CT (SPECT), there are still some challenges for their application in vivo. The imaging modalities are based on diverse physical principles, considering the method that allows the higher sensitivity and specificity to tissue contrast, quantitative and tissue penetration, and spatial resolution. Consequently, the TNPs concept needs an extensive in vivo investigation before their clinical translation.
In fact, several inorganic and organic NPs utilized in the diagnosis and drug delivery have been developed for different applications. Theranostic nanoparticles have shown attractive results in in vitro studies, but there are still some challenges for their application in vivo. For this reason, the major part of the research that has been described in the literature is about the preparation and characterization of TNPs with application in in vitro cell culture, still lacking the in vivo proof of concept. In the case of the treatment of human brain cancers, TNP have been developed [378,379,380,381,382,383], taking advantage of the specific GB characteristics described in the following sections. Gold and iron oxide-based nanoparticles have prompted particular attention as theranostic anti-cancer agent systems, combining in the same NPs drug delivery, imaging, and therapy [384,385]. Thus, TNPs can be used to avoid frequent and invasive dosing and improve patient compliance. Recently, a research group combined chemo-photothermal targeted therapy of glioma within one nanoparticle. A targeting peptide (IP)-modified mesoporous silica-coated graphene nanosheet (GSPI) was synthesized and characterized. Doxorubicin (DOX) was used as therapeutic component and GSPI nanoparticles as drug and diagnostic delivery system, integrating the response to heat and pH-stimuli. Only in vitro studies were performed and the results showed a higher rate of death of glioma cells and improved accumulation of GSPID [228]. In another work [386], targeted TNPs were developed, which included newer (small interference RNA, siRNA) and conventional (temozolomide, TMZ) therapeutics. To promote the targeting to glioma cells, chlorotoxin (CTX) peptide was conjugated with iron oxide nanoparticles that worked as drug carrier and allowed to monitor the changes in tumor volume by magnetic resonance imaging (MRI). TNPs were internalized by T98G glioblastoma cells in vitro leading to the enhancement of TMZ toxicity. The results in vivo indicated that the combination of the treatments with the TNPs loaded with TMZ led to significant retardation of tumor growth, as monitored by MRI. The multiple emulsion solvent evaporation method has been proposed as effective for high co-encapsulation of SPIONs and DOX into the poly (lactic-co-glycolic acid) (PLGA)-based NPs. A different strategy was designed, taking advantage of magnetic nanoparticles and polymeric materials for potential application in targeted therapy and imaging of malignant tumors. Thus, SPIONs and DOX were entrapped in the PLGA nanoparticles via a modified multiple emulsion solvent evaporation method. The NPs displayed an increased DOX release at pH 5.5 compared to pH 7.4; the targeted NPs enhanced cellular uptake of DOX in C6 glioma cells, exerting a higher cytotoxic effect when compared with DOX solution alone [387]. Taken together, TNPs may lead to an improved therapeutic efficacy over DOX solution in glioma tumor growth inhibition for therapeutic and diagnostic purposes. Considering a similar strategy, chitosan NPs used as a dual action carrier for DOX (as chemotherapeutic agent) and superparamagnetic iron oxide nanoparticles (SPIONs; as imaging agent) were developed [388]. The TNPs demonstrated a pH-sensitive drug release profile with a burst release at acid tumor environment. TNP-DOX were internalized and the in vitro magnetic resonance imaging (MRI) showed a decline in T2 relaxation times by increasing iron concentration. The imaging method also confirmed uptake of TNPs at the optimum concentration in C6 glioma cells. Gold nanoparticles (AuNPs) and superparamagnetic iron oxide nanoparticles (SPIONs) were combined in a unique NPs to deliver therapeutic and diagnostic agents for brain tumors. The potential applications of novel gold and SPION-loaded micelles (GSMs) coated by polyethylene glycol-polycaprolactone (PEG-PCL) polymer was also tested [385]. The results showed, by quantifying gh2ax DNA damage in GB cell lines, the radiosensitizing efficacy of these GSMs, and found that GSM administration in conjunction with radiation therapy led to ~2-fold increase in density of double-stranded DNA breaks. GSMs used as a contrast agent for the MRI studies were sensitive to detect and delineate tumor borders. These results indicated that GSMs may potentially be integrated into both imaging and treatment of brain tumors, helping a theranostic purpose as both an MRI-based contrast agent and a radiosensitizer. Hollow gold nanospheres (HAuNS) have demonstrated an intense photoacoustic signal and induced an efficient photothermal ablation (PTA) therapy [389]. According to the in vivo results, these hybrid NPs significantly prolonged the survival of tumor-bearing mice. The results revealed the feasibility of the NP image-guided local tumor PTA therapy using photoacoustic molecular imaging. The application of multitargeting in a single NPs has also been described, and some examples are mentioned. Targeting AuNPs with two or more receptor binding peptides for glioblastoma treatment have been developed [251]. AuNPs conjugated with peptides against both the epidermal growth factor and transferrin receptors, and also loaded with the photosensitizer phthalocyanine 4 (Pc 4) was studied and compared with AuNPs employing in vitro and in vivo studies. The dual-targeting hybrid nanoparticles displayed a synergistic effect in human glioma cells and showed a significant accumulation in the brain tumor regions in in vitro studies and in vivo studies, respectively.
The ability to perform multiple functions in biological systems, toxicity and biodistribution are the main requirements for the clinical translation of nanotheranostic concept. In general, the regulatory approval of NPs is challenging, due to their higher complexity as NDS. When TNPs, as multifunctional nanocarriers, are considered, the approval process has shown to be even more complicated, involving therapeutic, diagnostic and targeting agent assessments.

4.1. Personalized Medicine

Personalized medicine considers the pharmacogenetics, pharmacogenomics and pharmacoproteomic information as crucial for the prescription of therapeutics directed at each patient [390]. Thus, this new field considers the variability of each individual before developing an appropriate treatment strategy. The application of personalized medicine in the oncology field displays a promising strategy, due to the better understanding of the disease at a molecular level. Personalized medicine may be effective in the treatment and/or control of cancers with the implementation of a high specificity and accuracy of diagnosis [391]. Thus, the optimization of the treatment protocols becomes simpler and less expensive, associated with fewer toxicities and a high efficacy. Personalized cancer medicine (PCM) is defined as treatment based on the molecular characteristics of a tumor from an individual patient [392]. Recent researches have clarified several cellular and molecular mechanisms of tumor development, growth and metastasis with the identification of new cancer specific molecular targets. Taking advantage of pharmacogenetic, pharmacogenomic, pharmacoproteomic strategies, the detailed genetic and molecular profile of each patient, personalized medicine can help tailoring the design of nanoparticles. Targeted nanoparticles can interact with specific molecular biomarkers, which determine the evolution of the disease and the response to treatments [393]. Nanoparticles used in the personalized medicine are optimized treatment to each patient, taking into account the individual variability. However, critical steps are important in the personalized cancer therapy development, including a comprehensive assessment of biological characteristics of tumors from each individual and validated methods to identify the groups or subgroups of patients with more benefits in that therapy. Personalized medicine applied to a cancer presents a good example of a therapy relying on the individual genotype. The main difficulty in the translation to the clinic of nanoparticles in the context of personalized medicine is that it requires a comprehensive and detailed understanding of the potential toxicological risk associated to their use. If this difficulty can be overcome, clinical application of nanoparticles would allow to detect variation among patients, thus driving the clinical decisions and the elaboration of therapeutic protocols.
As described in Section 3, the GB heterogeneity, their invasiveness and the numerous mutations, contribute to the progression of the tumor and the treatment failure [394,395,396]. Due to the different patient responses to conventional oncological treatments, the use of nanotechnology associated with personalized medicine is promising for the improvement of current strategies and the success of the treatment (Scheme 2). Targeting tumor heterogeneity and immune system may be applied using multifunctional nanoparticles, which may help prevent recurrence in GB by specific eradication of tumor cells. TNPs can permit the co-development, in single nanoparticles, of therapy, imaging and targeting approach, matching the most effective treatment to the individual patient. Scheme S1 sums up the aspects that need to be taken into account for this purpose.
Thus, it is predicted that personalized medicine along with the knowledge of GB environment with use of TNPs will improve their therapeutic and diagnosis efficacy. TNPs for personalized medicine will emerge and enter clinical trials. However, before this becomes a reality, safety concerns, problems related to the maintenance of robustness and reproducibility in the up-scaling processes must be addressed.

4.2. Preclinical Phase and Clinical Trials

As it has been discussed, NPs are promising for applications in cancer theranostics because of their affinity and selectivity to tumor cells. In addition, they can simply be surface modified to increase their blood circulation times and make them functionalized with active targeting ligands. Recent advances in TNPs research have resulted in a number of formulations containing both drugs and imaging agents within a single formulation. However, despite the progress in the TNPs, their translation to the market has been a challenge. There are some researches focused on the preclinical trial phases, studying essentially the toxicity, pharmacodynamics, and safety profile of the TNPs. The main studies occur in vitro and in vivo, establishing the knowledge about the effect of a wide range of NPs doses to be tested, using cancer cell lines versus normal cell lines, and, as in a second step, in vivo assessment with appropriate animal models. Here, it is possible to evaluate the biocompatibility and the behavior of NPs with direct relation with the animal. The main purpose of the preclinical trials is to move forward the TNPs from the preliminary stage to the clinical phase.
Theranostic NPs, that combined organic nanoparticles (including liposomes, micelles/polymeric micelles, lipid nanoparticles, protein based nanoparticles) with co-delivery of drugs, and inorganic NPs (e.g., QDs, gold nanoparticles, and silica nanoparticles) as imaging contrast, have been developed and the major part of the results displayed a higher effectiveness than the commercial references [397,398,399,400,401,402,403,404,405]. The explosion of NPs for clinical imaging and therapy has not occurred yet. Their higher complexity and dubious reproducibility will create significant hurdles for clinical translation and regulatory approval. Although there are described several organic NPs for treatment and inorganic NPs for the imaging application approved or in clinical trials, these approaches did not represent a theranostic approach. INFeD®, DexIron®/Dexferrum Feridex®, FerahemeTM (Ferumoxytol), NanoTherm®, Venofer®, AuroLase Therapy and AuNPs-nanosensor are some inorganic nanoparticles in current clinical trials or approved. Only NanoTherm® is an intratumoral thermotherapy used for GB treatment, and the treatment is based on the principle of introducing magnetic nanoparticles directly into the tumor and then heating it using an alternating magnetic field [406]. A minimally invasive surgical procedure is used to introduce the magnetic fluid into the tumor followed by placing of the thermometry catheter in the treatment area to allow direct measurement of the temperature during thermotherapy. Although there are several TNPs under development, most of them do not yet possess a preclinical proof of concept, due to failure in the correlation between the in vitro and the in vivo results.

5. Conclusions

GB is one of the most dismal and mortal diseases, with no effective treatment. The BBB and BBTB, as the main physiological barriers, heterogeneity and the invasive nature of GB, lead to an inadequate concentration of chemotherapeutics at the site of tumor, restricting current treatments. These difficulties can be overcome using nanotechnology, which has demonstrated to be an opportunity in the area of cancer treatment. Thus, the NPs utilization may lead to a breakthrough in brain cancer management, due to their small size, high surface functionalization and, more recently, the opportunity to co-develop treatment and imaging in a single NP. In this review, it is shown that optimization of NPs in theranostics is a multivariable, multi-objective task that does not allow to point in a single direction. Theranostic NPs are smart carriers, able to diagnose, deliver and monitor the therapeutic response in real-time. Targeting overexpressed proteins and receptors on brain cancer cells allows a specific release of cargo in the exact site. The knowledge about the chemotherapeutics concentration and safer pharmacokinetic profiles, with a real-time monitoring of biodistribution and target site accumulation, visualization of the target receptor density and assessment of the therapeutic efficacy may be beneficial in the selection of therapy and planning the treatment. In the coming years, the global perspective for the use of TNPs is clearly optimistic, in multifunctional applications and in combination with personalized medicine strategies, offering hope for their successful clinical translation. Providing treatment at the right time depends on right-time diagnosis. Personalized cancer planning, advance diagnosis, and suitable drugs for the right patient, with predictable side effects, can finally make this goal a reality. Modern multimodality treatment and care increase patient’s life quality and life expectancy. It is probable that, in the next years, TNPs will emerge and enter clinical trials.

Supplementary Materials

The following are available online at https://www.mdpi.com/1999-4923/10/4/181/s1, Scheme S1: Opportunities and challenges in the optimization of theranostic NPs as a multivariable, multi-objective approach.

Author Contributions

M.M., J.J.S., A.P. and C.V. contributed to the writing and editing of the paper.

Funding

The authors acknowledge Fundacção para a Ciência e a Tecnologia (FCT), Portuguese Agency for Scientific Research, for financial support through PhD research grants SFRH/BD/133996/2017 and the Research Project no. 016648 (Ref. POCI-01-0145-FEDER- 016648), the project PEst-UID/NEU/04539/2013, and COMPETE (Ref. POCI-01-0145-FEDER-007440). The Coimbra Chemistry Centre is supported by FCT, through the Project PEst-OE/QUI/UI0313/2014 and POCI-01-0145-FEDER-007630.

Acknowledgments

The authors acknowledge Fundacção para a Ciência e a Tecnologia (FCT), Portuguese Agency for Scientific Research, for financial support through the Research Project no. 016648 (Ref. POCI-01-0145-FEDER- 016648), the project PEst-UID/NEU/04539/2013, and COMPETE (Ref. POCI-01-0145-FEDER-007440). The Coimbra Chemistry Centre is sup- ported by FCT, through the Project PEst-OE/QUI/UI0313/2014 and POCI-01-0145-FEDER-007630. Maria Mendes acknowledge the PhD research grants SFRH/BD/133996/2017 assigned by FCT.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Louis, D.N.; Perry, A.; Reifenberger, G.; Von Deimling, A.; Figarella-Branger, D.; Cavenee, W.K.; Ohgaki, H.; Wiestler, O.D.; Kleihues, P.; Ellison, D.W. The 2016 World Health Organization classification of tumors of the central nervous system: A summary. Acta Neuropathol. 2016, 131, 803–820. [Google Scholar] [CrossRef] [PubMed]
  2. Preusser, M.; De Ribaupierre, S.; Wöhrer, A.; Erridge, S.C.; Hegi, M.; Weller, M.; Stupp, R. Current concepts and management of glioblastoma. Ann. Neurol. 2011, 70, 9–21. [Google Scholar] [CrossRef] [PubMed]
  3. Jendrossek, V.; Belka, C.; Bamberg, M. Novel chemotherapeutic agents for the treatment of glioblastoma multiforme. Expert Opin. Investig. Drugs 2003, 12, 1899–1924. [Google Scholar] [CrossRef] [PubMed]
  4. Chandana, S.R.; Movva, S.; Arora, M.; Singh, T. Primary brain tumors in adults. Am. Fam. Physician 2008, 77, 1423–1430. [Google Scholar] [PubMed]
  5. Young, R.M.; Jamshidi, A.; Davis, G.; Sherman, J.H. Current trends in the surgical management and treatment of adult glioblastoma. Ann. Transl. Med. 2015, 3, 121. [Google Scholar] [PubMed]
  6. Pourgholi, F.; hajivalili, M.; Farhad, J.N.; Kafil, H.S.; Yousefi, M. Nanoparticles: Novel vehicles in treatment of Glioblastoma. Biomed. Pharmacother. 2016, 77, 98–107. [Google Scholar] [CrossRef] [PubMed]
  7. Hildebrandt, B.; Wust, P.; Ahlers, O.; Dieing, A.; Sreenivasa, G.; Kerner, T.; Felix, R.; Riess, H. The cellular and molecular basis of hyperthermia. Crit. Rev. Oncol. Hematol. 2002, 43, 33–56. [Google Scholar] [CrossRef]
  8. Jie, X.; Hua, L.; Jiang, W.; Feng, F.; Feng, G.; Hua, Z. Clinical application of a dendritic cell vaccine raised against heat-shocked glioblastoma. Cell Biochem. Biophys. 2012, 62, 91–99. [Google Scholar] [CrossRef] [PubMed]
  9. Palucka, K.; Banchereau, J. Cancer immunotherapy via dendritic cells. Nat. Rev. Cancer 2012, 12, 265. [Google Scholar] [CrossRef] [PubMed]
  10. Pellegatta, S.; Poliani, P.L.; Corno, D.; Menghi, F.; Ghielmetti, F.; Suarez-Merino, B.; Caldera, V.; Nava, S.; Ravanini, M.; Facchetti, F. Neurospheres enriched in cancer stem-like cells are highly effective in eliciting a dendritic cell-mediated immune response against malignant gliomas. Cancer Res. 2006, 66, 10247–10252. [Google Scholar] [CrossRef] [PubMed]
  11. Xu, Q.; Liu, G.; Yuan, X.; Xu, M.; Wang, H.; Ji, J.; Konda, B.; Black, K.L.; Yu, J.S. Antigen-specific T-cell response from dendritic cell vaccination using cancer stem-like cell-associated antigens. Stem Cells 2009, 27, 1734–1740. [Google Scholar] [CrossRef] [PubMed]
  12. Polivka, J.; Holubec, L.; Kubikova, T.; Priban, V.; Hes, O.; Pivovarcikova, K.; Treskova, I. Advances in experimental targeted therapy and immunotherapy for patients with glioblastoma multiforme. Anticancer Res. 2017, 37, 21–33. [Google Scholar] [CrossRef] [PubMed]
  13. Chistiakov, D.A.; Chekhonin, I.V.; Chekhonin, V.P. The EGFR variant III mutant as a target for immunotherapy of glioblastoma multiforme. Eur. J. Pharmacol. 2017, 810, 70–82. [Google Scholar] [CrossRef] [PubMed]
  14. Kwiatkowska, A.; Nandhu, M.S.; Behera, P.; Chiocca, E.A.; Viapiano, M.S. Strategies in gene therapy for glioblastoma. Cancers (Basel) 2013, 5, 1271–1305. [Google Scholar] [CrossRef] [PubMed]
  15. Oliveira, D.V.C.; Costanzi-Strauss, E.; Strauss, B.E. A bicistronic adenoviral vector for glioblastoma gene therapy. In Proceedings of the AACR International Conference Held in Cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine, São Paulo, Brazil, 4–6 May 2017. [Google Scholar]
  16. Yu, D.; Khan, O.F.; Suvà, M.L.; Dong, B.; Panek, W.K.; Xiao, T.; Wu, M.; Han, Y.; Ahmed, A.U.; Balyasnikova, I.V.; et al. Multiplexed RNAi therapy against brain tumor-initiating cells via lipopolymeric nanoparticle infusion delays glioblastoma progression. Proc. Natl. Acad. Sci. USA 2017, 114, E6147–E6156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Okura, H.; Smith, C.A.; Rutka, J.T. Gene therapy for malignant glioma. Mol. Cell. Ther. 2014, 2, 21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Serlin, Y.; Shelef, I.; Knyazer, B.; Friedman, A. Anatomy and physiology of the blood–brain barrier. In Seminars in Cell & Developmental Biology; Elsevier: Amsterdam, The Netherlands, 2015; Volume 38, pp. 2–6. [Google Scholar]
  19. Saunders, N.R.; Habgood, M.D.; Møllgård, K.; Dziegielewska, K.M. The biological significance of brain barrier mechanisms: Help or hindrance in drug delivery to the central nervous system? F1000Reaserch 2016, 5. [Google Scholar] [CrossRef] [PubMed]
  20. Haseloff, R.F.; Dithmer, S.; Winkler, L.; Wolburg, H.; Blasig, I.E. Transmembrane proteins of the tight junctions at the blood–brain barrier: Structural and functional aspects. In Seminars in Cell & Developmental Biology; Elsevier: Amsterdam, The Netherlands, 2015; Volume 38, pp. 16–25. [Google Scholar]
  21. Daneman, R.; Prat, A. The blood–brain barrier. Cold Spring Harb. Perspect. Biol. 2015, 7, a020412. [Google Scholar] [CrossRef] [PubMed]
  22. Obermeier, B.; Daneman, R.; Ransohoff, R.M. Development, maintenance and disruption of the blood-brain barrier. Nat. Med. 2013, 19, 1584–1596. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Pardridge, W.M. Drug transport across the blood–brain barrier. J. Cereb. Blood Flow Metab. 2012, 32, 1959–1972. [Google Scholar] [CrossRef] [PubMed]
  24. Zhao, Z.; Nelson, A.R.; Betsholtz, C.; Zlokovic, B.V. Establishment and dysfunction of the blood-brain barrier. Cell 2015, 163, 1064–1078. [Google Scholar] [CrossRef] [PubMed]
  25. Hervé, F.; Ghinea, N.; Scherrmann, J.-M. CNS delivery via adsorptive transcytosis. AAPS J. 2008, 10, 455–472. [Google Scholar] [CrossRef] [PubMed]
  26. Thuenauer, R.; Müller, S.K.; Römer, W. Pathways of protein and lipid receptor-mediated transcytosis in drug delivery. Expert Opin. Drug Deliv. 2017, 14, 341–351. [Google Scholar] [CrossRef] [PubMed]
  27. Wei, X.; Chen, X.; Ying, M.; Lu, W. Brain tumor-targeted drug delivery strategies. Acta Pharm. Sin. B 2014, 4, 193–201. [Google Scholar] [CrossRef] [PubMed]
  28. Parikh, T.; Bommana, M.M.; Squillante, E., III. Efficacy of surface charge in targeting pegylated nanoparticles of sulpiride to the brain. Eur. J. Pharm. Biopharm. 2010, 74, 442–450. [Google Scholar] [CrossRef] [PubMed]
  29. Lu, W.; Wan, J.; Zhang, Q.; She, Z.; Jiang, X. Aclarubicin-loaded cationic albumin-conjugated pegylated nanoparticle for glioma chemotherapy in rats. Int. J. Cancer 2007, 120, 420–431. [Google Scholar] [CrossRef] [PubMed]
  30. Thöle, M.; Nobmann, S.; Huwyler, J.; Bartmann, A.; Fricker, G. Uptake of cationized albumin coupled liposomes by cultured porcine brain microvessel endothelial cells and intact brain capillaries. J. Drug Target. 2002, 10, 337–344. [Google Scholar] [CrossRef] [PubMed]
  31. Lu, W.; Tan, Y.-Z.; Hu, K.-L.; Jiang, X.-G. Cationic albumin conjugated pegylated nanoparticle with its transcytosis ability and little toxicity against blood–brain barrier. Int. J. Pharm. 2005, 295, 247–260. [Google Scholar] [CrossRef] [PubMed]
  32. Sharma, R.; Kamal, A.; Abdinejad, M.; Mahajan, R.K.; Kraatz, H.-B. Advances in the synthesis, molecular architectures and potential applications of gemini surfactants. Adv. Colloid Interface Sci. 2017, 248, 35–68. [Google Scholar] [CrossRef] [PubMed]
  33. Gharagozloo, M.; Rafiee, A.; Chen, D.W.; Foldvari, M. A flow cytometric approach to study the mechanism of gene delivery to cells by gemini-lipid nanoparticles: An implication for cell membrane nanoporation. J. Nanobiotechnol. 2015, 13, 62. [Google Scholar] [CrossRef] [PubMed]
  34. Almeida, J.A.S.; Marques, E.F.; Jurado, A.S.; Pais, A.C.C. The effect of cationic gemini surfactants upon lipid membranes. An experimental and molecular dynamics simulation study. Phys. Chem. Chem. Phys. 2010, 12, 14462–14476. [Google Scholar] [CrossRef] [PubMed]
  35. Cruz, R.Q.; Morais, C.M.; Cardoso, A.M.; Silva, S.G.; Vale, M.L.; Marques, E.F.; de Lima, M.C.P.; Jurado, A.S. Enhancing glioblastoma cell sensitivity to chemotherapeutics: A strategy involving survivin gene silencing mediated by gemini surfactant-based complexes. Eur. J. Pharm. Biopharm. 2016, 104, 7–18. [Google Scholar] [CrossRef] [PubMed]
  36. Lockman, P.R.; Koziara, J.M.; Mumper, R.J.; Allen, D.D. Nanoparticle surface charges alter blood-brain barrier integrity and permeability. J. Drug Target. 2004, 12, 635–641. [Google Scholar] [CrossRef] [PubMed]
  37. Vitorino, C.V. Nanomedicine: Principles, properties and regulatory issues. Front. Chem. 2018, 6, 360. [Google Scholar]
  38. Forest, V.; Pourchez, J. Preferential binding of positive nanoparticles on cell membranes is due to electrostatic interactions: A too simplistic explanation that does not take into account the nanoparticle protein corona. Mater. Sci. Eng. C 2017, 70, 889–896. [Google Scholar] [CrossRef] [PubMed]
  39. Wang, H.-X.; Zuo, Z.-Q.; Du, J.-Z.; Wang, Y.-C.; Sun, R.; Cao, Z.-T.; Ye, X.-D.; Wang, J.-L.; Leong, K.W.; Wang, J. Surface charge critically affects tumor penetration and therapeutic efficacy of cancer nanomedicines. Nanotoday 2016, 11, 133–144. [Google Scholar] [CrossRef]
  40. Rosenblum, D.; Joshi, N.; Tao, W.; Karp, J.M.; Peer, D. Progress and challenges towards targeted delivery of cancer therapeutics. Nat. Commun. 2018, 9, 1410. [Google Scholar] [CrossRef] [PubMed]
  41. Jo, D.H.; Kim, J.H.; Lee, T.G.; Kim, J.H. Size, surface charge, and shape determine therapeutic effects of nanoparticles on brain and retinal diseases. Nanomed. Nanotechnol. Biol. Med. 2015, 11, 1603–1611. [Google Scholar] [CrossRef] [PubMed]
  42. Kurtz-Chalot, A.; Villiers, C.; Pourchez, J.; Boudard, D.; Martini, M.; Marche, P.N.; Cottier, M.; Forest, V. Impact of silica nanoparticle surface chemistry on protein corona formation and consequential interactions with biological cells. Mater. Sci. Eng. C 2017, 75, 16–24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Barar, J.; Rafi, M.A.; Pourseif, M.M.; Omidi, Y. Blood-brain barrier transport machineries and targeted therapy of brain diseases. BioImpacts 2016, 6, 225–248. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Hawkins, R.A.; O’kane, R.L.; Simpson, I.A.; Vina, J.R. Structure of the blood-brain barrier and its role in the transport of amino acids. J. Nutr. 2006, 136, 218S–226S. [Google Scholar] [CrossRef] [PubMed]
  45. Li, J.; Guo, Y.; Kuang, Y.; An, S.; Ma, H.; Jiang, C. Choline transporter-targeting and co-delivery system for glioma therapy. Biomaterials 2013, 34, 9142–9148. [Google Scholar] [CrossRef] [PubMed]
  46. Iwao, B.; Yara, M.; Hara, N.; Kawai, Y.; Yamanaka, T.; Nishihara, H.; Inoue, T.; Inazu, M. Functional expression of choline transporter like-protein 1 (CTL1) and CTL2 in human brain microvascular endothelial cells. Neurochem. Int. 2016, 93, 40–50. [Google Scholar] [CrossRef] [PubMed]
  47. Du, D.; Chang, N.; Sun, S.; Li, M.; Yu, H.; Liu, M.; Liu, X.; Wang, G.; Li, H.; Liu, X. The role of glucose transporters in the distribution of p-aminophenyl-α-d-mannopyranoside modified liposomes within mice brain. J. Control. Release 2014, 182, 99–110. [Google Scholar] [CrossRef] [PubMed]
  48. Ying, X.; Wen, H.E.; Lu, W.-L.; Du, J.; Guo, J.; Tian, W.; Men, Y.; Zhang, Y.; Li, R.-J.; Yang, T.-Y. Dual-targeting daunorubicin liposomes improve the therapeutic efficacy of brain glioma in animals. J. Control. Release 2010, 141, 183–192. [Google Scholar] [CrossRef] [PubMed]
  49. Pérez-Escuredo, J.; Van Hée, V.F.; Sboarina, M.; Falces, J.; Payen, V.L.; Pellerin, L.; Sonveaux, P. Monocarboxylate transporters in the brain and in cancer. Biochim. Biophys. Acta (BBA)-Mol. Cell Res. 2016, 1863, 2481–2497. [Google Scholar] [CrossRef] [PubMed]
  50. Nawashiro, H.; Otani, N.; Uozumi, Y.; Ooigawa, H.; Toyooka, T.; Suzuki, T.; Katoh, H.; Tsuzuki, N.; Ohnuki, A.; Shima, K. High expression of l-type amino acid transporter 1 in infiltrating glioma cells. Brain Tumor Pathol. 2005, 22, 89–91. [Google Scholar] [CrossRef] [PubMed]
  51. Kobayashi, K.; Ohnishi, A.; Promsuk, J.; Shimizu, S.; Kanai, Y.; Shiokawa, Y.; Nagane, M. Enhanced tumor growth elicited by L-type amino acid transporter 1 in human malignant glioma cells. Neurosurgery 2008, 62, 493–504. [Google Scholar] [CrossRef] [PubMed]
  52. Geier, E.G.; Schlessinger, A.; Fan, H.; Gable, J.E.; Irwin, J.J.; Sali, A.; Giacomini, K.M. Structure-based ligand discovery for the Large-neutral Amino Acid Transporter 1, LAT-1. Proc. Natl. Acad. Sci. USA 2013, 110, 5480–5485. [Google Scholar] [CrossRef] [PubMed]
  53. Abbott, N.J.; Patabendige, A.A.K.; Dolman, D.E.M.; Yusof, S.R.; Begley, D.J. Structure and function of the blood-brain barrier. Neurobiol. Dis. 2010, 37, 13–25. [Google Scholar] [CrossRef] [PubMed]
  54. Smith, Q.R. Transport of glutamate and other amino acids at the blood-brain barrier. J. Nutr. 2000, 130, 1016S–1022S. [Google Scholar] [CrossRef] [PubMed]
  55. Romano, A.; Koczwara, J.B.; Gallelli, C.A.; Vergara, D.; Di Bonaventura, M.V.M.; Gaetani, S.; Giudetti, A.M. Fats for thoughts: An update on brain fatty acid metabolism. Int. J. Biochem. Cell Biol. 2017, 84, 40–45. [Google Scholar] [CrossRef] [PubMed]
  56. Hamilton, J.A. Kellen Brunaldi A model for fatty acid transport into the brain. J. Mol. Neurosci. 2007, 33, 12–17. [Google Scholar] [CrossRef] [PubMed]
  57. Strickland, M.; Stoll, E.A. Metabolic reprogramming in glioma. Front. Cell Dev. Biol. 2017, 5, 43. [Google Scholar] [CrossRef] [PubMed]
  58. Guo, D.; Bell, E.H.; Chakravarti, A. Lipid metabolism emerges as a promising target for malignant glioma therapy. CNS Oncol. 2013, 2, 289–299. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Molina-Arcas, M.; Casado, F.J.; Pastor-Anglada, M. Nucleoside transporter proteins. Curr. Vasc. Pharmacol. 2009, 7, 426–434. [Google Scholar] [CrossRef] [PubMed]
  60. Wang, Y.-Y.; Lui, P.C.W.; Li, J.Y. Receptor-mediated therapeutic transport across the blood-brain barrier. Immunotherapy 2009, 1, 983–993. [Google Scholar] [CrossRef] [PubMed]
  61. Fang, F.; Zou, D.; Wang, W.; Yin, Y.; Yin, T.; Hao, S.; Wang, B.; Wang, G.; Wang, Y. Non-invasive approaches for drug delivery to the brain based on the receptor mediated transport. Mater. Sci. Eng. C 2017, 76, 1316–1327. [Google Scholar] [CrossRef] [PubMed]
  62. Ulbrich, K.; Hekmatara, T.; Herbert, E.; Kreuter, J. Transferrin-and transferrin-receptor-antibody-modified nanoparticles enable drug delivery across the blood-brain barrier (BBB). Eur. J. Pharm. Biopharm. 2009, 71, 251–256. [Google Scholar] [CrossRef] [PubMed]
  63. Chang, J.; Jallouli, Y.; Kroubi, M.; Yuan, X.; Feng, W.; Kang, C.; Pu, P.; Betbeder, D. Characterization of endocytosis of transferrin-coated PLGA nanoparticles by the blood-brain barrier. Int. J. Pharm. 2009, 379, 285–292. [Google Scholar] [CrossRef] [PubMed]
  64. Monsalve, Y.; Tosi, G.; Ruozi, B.; Belletti, D.; Vilella, A.; Zoli, M.; Vandelli, M.A.; Forni, F.; López, B.L.; Sierra, L. PEG-g-chitosan nanoparticles functionalized with the monoclonal antibody OX26 for brain drug targeting. Nanomedicine 2015, 10, 1735–1750. [Google Scholar] [CrossRef] [PubMed]
  65. Aktaş, Y.; Yemisci, M.; Andrieux, K.; Gürsoy, R.N.; Alonso, M.J.; Fernandez-Megia, E.; Novoa-Carballal, R.; Quiñoá, E.; Riguera, R.; Sargon, M.F. Development and brain delivery of chitosan-PEG nanoparticles functionalized with the monoclonal antibody OX26. Bioconjug. Chem. 2005, 16, 1503–1511. [Google Scholar] [CrossRef] [PubMed]
  66. Liu, Z.; Zhao, H.; Shu, L.; Zhang, Y.; Okeke, C.; Zhang, L.; Li, J.; Li, N. Preparation and evaluation of Baicalin-loaded cationic solid lipid nanoparticles conjugated with OX26 for improved delivery across the BBB. Drug Dev. Ind. Pharm. 2015, 41, 353–361. [Google Scholar] [CrossRef] [PubMed]
  67. Nikanjam, M.; Blakely, E.A.; Bjornstad, K.A.; Shu, X.; Budinger, T.F.; Forte, T.M. Synthetic nano-low density lipoprotein as targeted drug delivery vehicle for glioblastoma multiforme. Int. J. Pharm. 2007, 328, 86–94. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Song, H.; Li, Y.; Lee, J.; Schwartz, A.L.; Bu, G. Low-density lipoprotein receptor-related protein 1 promotes cancer cell migration and invasion by inducing the expression of matrix metalloproteinases 2 and 9. Cancer Res. 2009, 69, 879–886. [Google Scholar] [CrossRef] [PubMed]
  69. Zhang, N.; Tao, J.; Hua, H.; Sun, P.; Zhao, Y. Low-density lipoprotein peptide-combined DNA nanocomplex as an efficient anticancer drug delivery vehicle. Eur. J. Pharm. Biopharm. 2015, 94, 20–29. [Google Scholar] [CrossRef] [PubMed]
  70. Radwan, A.A.; Fares, K. Alanazi Targeting cancer using cholesterol conjugates. Saudi Pharm. J. 2014, 22, 3–16. [Google Scholar] [CrossRef] [PubMed]
  71. Neves, A.R.; Queiroz, J.F.; Lima, S.A.C.; Reis, S. Apo E-Functionalization of Solid Lipid Nanoparticles Enhances Brain Drug Delivery: Uptake Mechanism and Transport Pathways. Bioconjug. Chem. 2017, 28, 995–1004. [Google Scholar] [CrossRef] [PubMed]
  72. Rajora, M.; Ding, L.; Valic, M.; Jiang, W.; Overchuk, M.; Chen, J.; Zheng, G. Tailored theranostic apolipoprotein E3 porphyrin-lipid nanoparticles target glioblastoma tumours. Chem. Sci. 2017, 8, 5371–5384. [Google Scholar] [CrossRef] [PubMed]
  73. Yusuf, M.; Khan, M.; Khan, R.A.; Maghrabi, I.A.; Ahmed, B. Polysorbate-80-coated, polymeric curcumin nanoparticles for in vivo anti-depressant activity across BBB and envisaged biomolecular mechanism of action through a proposed pharmacophore model. J. Microencapsul. 2016, 33, 646–655. [Google Scholar] [CrossRef] [PubMed]
  74. Shao, K.; Huang, R.; Li, J.; Han, L.; Ye, L.; Lou, J.; Jiang, C. Angiopep-2 modified PE-PEG based polymeric micelles for amphotericin B delivery targeted to the brain. J. Control. Release 2010, 147, 118–126. [Google Scholar] [CrossRef] [PubMed]
  75. Han, W.; Yin, G.; Pu, X.; Chen, X.; Liao, X.; Huang, Z. Glioma targeted delivery strategy of doxorubicin-loaded liposomes by dual-ligand modification. J. Biomater. Sci. Polym. Ed. 2017, 28, 1695–1712. [Google Scholar] [CrossRef] [PubMed]
  76. Kim, J.S.; Shin, D.H.; Kim, J.-S. Dual-targeting immunoliposomes using angiopep-2 and Cd133 antibody for glioblastoma stem cells. J. Control. Release 2018, 269, 245–257. [Google Scholar] [CrossRef] [PubMed]
  77. Li, C.; Li, S.; Tu, T.; Qi, X.; Xiong, Y.; Du, S.; Shen, Y.; Tu, J.; Sun, C. Paclitaxel-loaded cholesterol-conjugated polyoxyethylene sorbitol oleate polymeric micelles for glioblastoma therapy across the blood-brain barrier. Polym. Chem. 2015, 6, 2740–2751. [Google Scholar] [CrossRef]
  78. Li, C.; Sun, C.; Li, S.; Han, P.; Sun, H.; Ouahab, A.; Shen, Y.; Xu, Y.; Xiong, Y.; Tu, J. Novel designed polyoxyethylene nonionic surfactant with improved safety and efficiency for anticancer drug delivery. Int. J. Nanomed. 2014, 9, 2089–2100. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Pardridge, W.M.; Kang, Y.-S.; Buciak, J.L.; Yang, J. Human insulin receptor monoclonal antibody undergoes high affinity binding to human brain capillaries in vitro and rapid transcytosis through the blood–brain barrier in vivo in the primate. Pharm. Res. 1995, 12, 807–816. [Google Scholar] [CrossRef] [PubMed]
  80. Ulbrich, K.; Knobloch, T.; Kreuter, J. Targeting the insulin receptor: Nanoparticles for drug delivery across the blood–brain barrier (BBB). J. Drug Target. 2011, 19, 125–132. [Google Scholar] [CrossRef] [PubMed]
  81. Zhan, C.; Li, B.; Hu, L.; Wei, X.; Feng, L.; Fu, W.; Lu, W. Micelle-based brain-targeted drug delivery enabled by a nicotine acetylcholine receptor ligand. Angew. Chem. Int. Ed. 2011, 50, 5482–5485. [Google Scholar] [CrossRef] [PubMed]
  82. Rama, A.R.; Alvarez, P.J.; Madeddu, R.; Aranega, A. ABC transporters as differentiation markers in glioblastoma cells. Mol. Biol. Rep. 2014, 41, 4847–4851. [Google Scholar] [CrossRef] [PubMed]
  83. Miller, D.S. Regulation of ABC Transporters Blood-Brain Barrier. The Good, the Bad, and the Ugly, 1st ed.; Elsevier Inc.: Amsterdam, The Netherlands, 2015; Volume 125. [Google Scholar]
  84. Dean, M. ABC transporters, drug resistance, and cancer stem cells. J. Mammary Gland Biol. Neoplasia 2009, 14, 3–9. [Google Scholar] [CrossRef] [PubMed]
  85. Ganugula, R.; Arora, M.; Guada, M.; Saini, P.; Kumar, M.N.V.R. Noncompetitive Active Transport Exploiting Intestinal Transferrin Receptors for Oral Delivery of Proteins by Tunable Nanoplatform. ACS Macro Lett. 2017, 6, 161–164. [Google Scholar] [CrossRef]
  86. Ussar, S.; Haering, M.-F.; Fujisaka, S.; Lutter, D.; Lee, K.Y.; Li, N.; Gerber, G.K.; Bry, L.; Kahn, C.R. Regulation of glucose uptake and enteroendocrine function by the intestinal epithelial insulin receptor. Diabetes 2017. [Google Scholar] [CrossRef] [PubMed]
  87. Feldman, R.D.; Ding, Q.; Chorazyczewski, J.; Gros, R. GPER Regulation of LDL Receptor Expression in Human Hepatocytes. Atheroscler. Suppl. 2018, 32, 58. [Google Scholar] [CrossRef]
  88. Suhorutsenko, J.; Oskolkov, N.; Arukuusk, P.; Kurrikoff, K.; Eriste, E.; Copolovici, D.-M.; Langel, U. Cell-penetrating peptides, PepFects, show no evidence of toxicity and immunogenicity in vitro and in vivo. Bioconjug. Chem. 2011, 22, 2255–2262. [Google Scholar] [CrossRef] [PubMed]
  89. Kim, H.Y.; Yum, S.Y.; Jang, G.; Ahn, D.-R. Discovery of a non-cationic cell penetrating peptide derived from membrane-interacting human proteins and its potential as a protein delivery carrier. Sci. Rep. 2015, 5, 11719. [Google Scholar] [Green Version]
  90. Liu, R.; Li, X.; Xiao, W.; Lam, K.S. Tumor-targeting peptides from combinatorial libraries. Adv. Drug Deliv. Rev. 2017, 110, 13–37. [Google Scholar] [CrossRef] [PubMed]
  91. Dissanayake, S.; Denny, W.A.; Gamage, S.; Sarojini, V. Recent developments in anticancer drug delivery using cell penetrating and tumor targeting peptides. J. Control. Release 2017, 250, 62–76. [Google Scholar] [CrossRef] [PubMed]
  92. Milletti, F. Cell-penetrating peptides: Classes, origin, and current landscape. Drug Discov. Today 2012, 17, 850–860. [Google Scholar] [CrossRef] [PubMed]
  93. Wang, S.; Chen, R. pH-Responsive, Lysine-based, hyperbranched polymers mimicking endosomolytic cell-penetrating peptides for efficient intracellular delivery. Chem. Mater. 2017. [Google Scholar] [CrossRef]
  94. Hu, X.; Tan, J.J.; Ye, S. Reversible Activation of pH-Responsive Cell-Penetrating Peptides in Model Cell Membrane Relies on the Nature of Lipid. J. Phys. Chem. C 2017, 121, 15181–15187. [Google Scholar] [CrossRef]
  95. Yoo, J.; Rejinold, N.S.; Lee, D.; Jon, S.; Kim, Y.-C. Protease-activatable cell-penetrating peptide possessing ROS-triggered phase transition for enhanced cancer therapy. J. Control. Release 2017, 264, 89–101. [Google Scholar] [CrossRef] [PubMed]
  96. He, H.; Sun, L.; Ye, J.; Liu, E.; Chen, S.; Liang, Q.; Shin, M.C.; Yang, V.C. Enzyme-triggered, cell penetrating peptide-mediated delivery of anti-tumor agents. J. Control. Release 2016, 240, 67–76. [Google Scholar] [CrossRef] [PubMed]
  97. Lee, D.; Noh, I.; Yoo, J.; Rejinold, N.S.; Kim, Y.-C. pH-controllable cell-penetrating polypeptide that exhibits cancer targeting. Acta Biomater. 2017, 57, 187–196. [Google Scholar] [CrossRef] [PubMed]
  98. Yang, Y.; Yang, Y.; Xie, X.; Cai, X.; Mei, X. Preparation and characterization of photo-responsive cell-penetrating peptide-mediated nanostructured lipid carrier. J. Drug Target. 2014, 22, 891–900. [Google Scholar] [CrossRef] [PubMed]
  99. Liu, Y.; Mei, L.; Yu, Q.; Xu, C.; Qiu, Y.; Yang, Y.; Shi, K.; Zhang, Q.; Gao, H.; Zhang, Z. Multifunctional tandem peptide modified paclitaxel-loaded liposomes for the treatment of vasculogenic mimicry and cancer stem cells in malignant glioma. ACS Appl. Mater. Interfaces 2015, 7, 16792–16801. [Google Scholar] [CrossRef] [PubMed]
  100. Higa, M.; Katagiri, C.; Shimizu-Okabe, C.; Tsumuraya, T.; Sunagawa, M.; Nakamura, M.; Ishiuchi, S.; Takayama, C.; Kondo, E.; Matsushita, M. Identification of a novel cell-penetrating peptide targeting human glioblastoma cell lines as a cancer-homing transporter. Biochem. Biophys. Res. Commun. 2015, 457, 206–212. [Google Scholar] [CrossRef] [PubMed]
  101. Opačak-Bernardi, T.; Ryu, J.S.; Raucher, D. Effects of cell penetrating Notch inhibitory peptide conjugated to elastin-like polypeptide on glioblastoma cells. J. Drug Target. 2017, 25, 523–531. [Google Scholar] [CrossRef] [PubMed]
  102. Shi, K.; Long, Y.; Xu, C.; Wang, Y.; Qiu, Y.; Yu, Q.; Liu, Y.; Zhang, Q.; Gao, H.; Zhang, Z. Liposomes combined an integrin αvβ3-specific vector with pH-responsible cell-penetrating property for highly effective antiglioma therapy through the blood–brain barrier. ACS Appl. Mater. Interfaces 2015, 7, 21442–21454. [Google Scholar] [CrossRef] [PubMed]
  103. Wang, D.; Guo, M.; Yu, J.; Wang, X.; Zhang, Q.; Yang, X.; Li, J.; Zhao, C.; Feng, B. Glioma targeting peptide in combination with the P53 C terminus inhibits glioma cell proliferation in vitro. Cytotechnology 2017, 70, 153–161. [Google Scholar] [CrossRef] [PubMed]
  104. Eriste, E.; Kurrikoff, K.; Suhorutšenko, J.; Oskolkov, N.; Copolovici, D.M.; Jones, S.; Laakkonen, P.; Howl, J.; Langel, U. Peptide-based glioma-targeted drug delivery vector gHoPe2. Bioconjug. Chem. 2013, 24, 305–313. [Google Scholar] [CrossRef] [PubMed]
  105. Liu, Y.; Lu, Z.; Mei, L.; Yu, Q.; Tai, X.; Wang, Y.; Shi, K.; Zhang, Z.; He, Q. Tandem peptide based on structural modification of poly-arginine for enhancing tumor targeting efficiency and therapeutic effect. ACS Appl. Mater. Interfaces 2017, 9, 2083–2092. [Google Scholar] [CrossRef] [PubMed]
  106. Qin, Y.; Chen, H.; Yuan, W.; Kuai, R.; Zhang, Q.; Xie, F.; Zhang, L.; Zhang, Z.; Liu, J.; He, Q. Liposome formulated with TAT-modified cholesterol for enhancing the brain delivery. Int. J. Pharm. 2011, 419, 85–95. [Google Scholar] [CrossRef] [PubMed]
  107. Sharma, G.; Modgil, A.; Layek, B.; Arora, K.; Sun, C.; Law, B.; Singh, J. Cell penetrating peptide tethered bi-ligand liposomes for delivery to brain in vivo: Biodistribution and transfection. J. Control. Release 2013, 167, 1–10. [Google Scholar] [CrossRef] [PubMed]
  108. Joshi, S.; Cooke, J.R.N.; Ellis, J.A.; Emala, C.W.; Bruce, J.N. Targeting brain tumors by intra-arterial delivery of cell-penetrating peptides: A novel approach for primary and metastatic brain malignancy. J. Neurooncol. 2017, 135, 497–506. [Google Scholar] [CrossRef] [PubMed]
  109. Zong, T.; Mei, L.; Gao, H.; Cai, W.; Zhu, P.; Shi, K.; Chen, J.; Wang, Y.; Gao, F.; He, Q. Synergistic dual-ligand doxorubicin liposomes improve targeting and therapeutic efficacy of brain glioma in animals. Mol. Pharm. 2014, 11, 2346–2357. [Google Scholar] [CrossRef] [PubMed]
  110. Liu, Y.; Mei, L.; Yu, Q.; Zhang, Q.; Gao, H.; Zhang, Z.; He, Q. Integrin αvβ3 targeting activity study of different retro-inverso sequences of RGD and their potentiality in the designing of tumor targeting peptides. Amino Acids 2015, 47, 2533–2539. [Google Scholar] [CrossRef] [PubMed]
  111. Gao, H.; Yang, Z.; Zhang, S.; Cao, S.; Pang, Z.; Yang, X.; Jiang, X. Glioma-homing peptide with a cell-penetrating effect for targeting delivery with enhanced glioma localization, penetration and suppression of glioma growth. J. Control. Release 2013, 172, 921–928. [Google Scholar] [CrossRef] [PubMed]
  112. Yao, H.; Wang, K.; Wang, Y.; Wang, S.; Li, J.; Lou, J.; Ye, L.; Yan, X.; Lu, W.; Huang, R. Enhanced blood-brain barrier penetration and glioma therapy mediated by a new peptide modified gene delivery system. Biomaterials 2015, 37, 345–352. [Google Scholar] [CrossRef] [PubMed]
  113. Kobayashi, N.; Niwa, M.; Yang, H.; Yoshida, T. Nucleolar localization signals of LIM kinase 2 function as a cell-penetrating peptide. Protein Pept. Lett. 2010, 17, 1480–1488. [Google Scholar] [CrossRef] [PubMed]
  114. Liu, Y.; Li, J.; Shao, K.; Huang, R.; Ye, L.; Lou, J.; Jiang, C. A leptin derived 30-amino-acid peptide modified pegylated poly-l-lysine dendrigraft for brain targeted gene delivery. Biomaterials 2010, 31, 5246–5257. [Google Scholar] [CrossRef] [PubMed]
  115. Sharma, S.; Mann, A.P.; Mölder, T.; Kotamraju, V.R.; Mattrey, R.; Teesalu, T.; Ruoslahti, E. Vascular changes in tumors resistant to a vascular disrupting nanoparticle treatment. J. Control. Release 2017, 268, 49–56. [Google Scholar] [CrossRef] [PubMed]
  116. Petersen, S.; Barchanski, A.; Taylor, U.; Klein, S.; Rath, D.; Barcikowski, S. Penetratin-Conjugated Gold Nanoparticles-Design of Cell-Penetrating Nanomarkers by Femtosecond Laser Ablation. J. Phys. Chem. C 2010, 115, 5152–5159. [Google Scholar] [CrossRef]
  117. Yang, Y.; Yang, Y.; Xie, X.; Cai, X.; Zhang, H.; Gong, W.; Wang, Z.; Mei, X. PEGylated liposomes with NGR ligand and heat-activable cell-penetrating peptide–doxorubicin conjugate for tumor-specific therapy. Biomaterials 2014, 35, 4368–4381. [Google Scholar] [CrossRef] [PubMed]
  118. Balzeau, J.; Pinier, M.; Berges, R.; Saulnier, P.; Benoit, J.-P.; Eyer, J. The effect of functionalizing lipid nanocapsules with NFL-TBS. 40-63 peptide on their uptake by glioblastoma cells. Biomaterials 2013, 34, 3381–3389. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  119. Walker, L.; Perkins, E.; Kratz, F.; Raucher, D. Cell penetrating peptides fused to a thermally targeted biopolymer drug carrier improve the delivery and antitumor efficacy of an acid-sensitive doxorubicin derivative. Int. J. Pharm. 2012, 436, 825–832. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  120. Dunkin, C.M.; Pokorny, A.; Almeida, P.F.; Lee, H.-S. Molecular dynamics studies of transportan 10 (Tp10) interacting with a POPC lipid bilayer. J. Phys. Chem. B 2010, 115, 1188–1198. [Google Scholar] [CrossRef] [PubMed]
  121. Aroui, S.; Dardevet, L.; Ajmia, W.; de Boisvilliers, M.; Perrin, F.; Laajimi, A.; Boumendjel, A.; Kenani, A.; Muller, J.M.; De Waard, M. A Novel Platinum–Maurocalcine Conjugate Induces Apoptosis of Human Glioblastoma Cells by Acting through the ROS-ERK/AKT-p53 Pathway. Mol. Pharm. 2015, 12, 4336–4348. [Google Scholar] [CrossRef] [PubMed]
  122. Bera, S.; Kar, R.K.; Mondal, S.; Pahan, K.; Bhunia, A. Structural Elucidation of the Cell-Penetrating Penetratin Peptide in Model Membranes at the Atomic Level: Probing Hydrophobic Interactions in the Blood–Brain Barrier. Biochemistry 2016, 55, 4982–4996. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Zhang, L.; Zhang, Y.; Tai, L.; Jiang, K.; Xie, C.; Li, Z.; Lin, Y.-Z.; Wei, G.; Lu, W.; Pan, W. Functionalized cell nucleus-penetrating peptide combined with doxorubicin for synergistic treatment of glioma. Acta Biomater. 2016, 42, 90–101. [Google Scholar] [CrossRef] [PubMed]
  124. Gao, H.; Zhang, S.; Cao, S.; Yang, Z.; Pang, Z.; Jiang, X. Angiopep-2 and activatable cell-penetrating peptide dual-functionalized nanoparticles for systemic glioma-targeting delivery. Mol. Pharm. 2014, 11, 2755–2763. [Google Scholar] [CrossRef] [PubMed]
  125. Ke, W.; Zha, Z.; Mukerabigwi, J.F.; Chen, W.; Wang, Y.; He, C.; Ge, Z. Matrix metalloproteinase-responsive multifunctional peptide-linked amphiphilic block copolymers for intelligent systemic anticancer drug delivery. Bioconjug. Chem. 2017, 28, 2190–2198. [Google Scholar] [CrossRef] [PubMed]
  126. Harris, T.J.; von Maltzahn, G.; Lord, M.E.; Park, J.; Agrawal, A.; Min, D.; Sailor, M.J.; Bhatia, S.N. Protease-Triggered Unveiling of Bioactive Nanoparticles. Small 2008, 4, 1307–1312. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  127. Zhao, B.-X.; Zhao, Y.; Huang, Y.; Luo, L.-M.; Song, P.; Wang, X.; Chen, S.; Yu, K.-F.; Zhang, X.; Zhang, Q. The efficiency of tumor-specific pH-responsive peptide-modified polymeric micelles containing paclitaxel. Biomaterials 2012, 33, 2508–2520. [Google Scholar] [CrossRef] [PubMed]
  128. Zhao, Y.; Ren, W.; Zhong, T.; Zhang, S.; Huang, D.; Guo, Y.; Yao, X.; Wang, C.; Zhang, W.-Q.; Zhang, X. Tumor-specific pH-responsive peptide-modified pH-sensitive liposomes containing doxorubicin for enhancing glioma targeting and anti-tumor activity. J. Control. Release 2016, 222, 56–66. [Google Scholar] [CrossRef] [PubMed]
  129. Yao, J.; Ma, Y.; Zhang, W.; Li, L.; Zhang, Y.; Zhang, L.; Liu, H.; Ni, J.; Wang, R. Design of new acid-activated cell-penetrating peptides for tumor drug delivery. PeerJ 2017, 5, e3429. [Google Scholar] [CrossRef] [PubMed]
  130. Wang, Y.; Shi, K.; Zhang, L.; Hu, G.; Wan, J.; Tang, J.; Yin, S.; Duan, J.; Qin, M.; Wang, N. Significantly enhanced tumor cellular and lysosomal hydroxychloroquine delivery by smart liposomes for optimal autophagy inhibition and improved antitumor efficiency with liposomal doxorubicin. Autophagy 2016, 12, 949–962. [Google Scholar] [CrossRef] [PubMed]
  131. Jiang, T.; Zhang, Z.; Zhang, Y.; Lv, H.; Zhou, J.; Li, C.; Hou, L.; Zhang, Q. Dual-functional liposomes based on pH-responsive cell-penetrating peptide and hyaluronic acid for tumor-targeted anticancer drug delivery. Biomaterials 2012, 33, 9246–9258. [Google Scholar] [CrossRef] [PubMed]
  132. Berghoff, A.S.; Preusser, M. Role of the Blood–Brain Barrier in Metastatic Disease of the Central Nervous System, 1st ed.; Elsevier B.V.: Amsterdam, The Netherlands, 2018; Volume 149. [Google Scholar]
  133. Karim, R.; Palazzo, C.; Evrard, B.; Piel, G. Nanocarriers for the treatment of glioblastoma multiforme: Current state-of-the-art. J. Control. Release 2016, 227, 23–37. [Google Scholar] [CrossRef] [PubMed]
  134. Angara, K.; Rashid, M.H.; Shankar, A.; Ara, R.; Iskander, A.; Borin, T.F.; Jain, M.; Achyut, B.R.; Arbab, A.S. Vascular mimicry in glioblastoma following anti-angiogenic and anti-20-HETE therapies. Histol. Histopathol. 2017, 32, 917–928. [Google Scholar] [PubMed]
  135. Arbab, A.S.; Rashid, M.H.; Angara, K.; Borin, T.F.; Lin, P.-C.; Jain, M.; Achyut, B.R. Major challenges and potential microenvironment-targeted therapies in glioblastoma. Int. J. Mol. Sci. 2017, 18, 2732. [Google Scholar] [CrossRef] [PubMed]
  136. Alifieris, C.; Dimitrios, T. Trafalis. Glioblastoma multiforme: Pathogenesis and treatment. Pharmacol. Ther. 2015, 152, 63–82. [Google Scholar] [CrossRef] [PubMed]
  137. Kanapathipillai, M.; Brock, A.; Ingber, D.E. Nanoparticle targeting of anti-cancer drugs that alter intracellular signaling or influence the tumor microenvironment. Adv. Drug Deliv. Rev. 2014, 79, 107–118. [Google Scholar] [CrossRef] [PubMed]
  138. Winquist, R.J.; Boucher, D.M.; Wood, M.; Furey, B.F. Targeting cancer stem cells for more effective therapies: Taking out cancer’s locomotive engine. Biochem. Pharmacol. 2009, 78, 326–334. [Google Scholar] [CrossRef] [PubMed]
  139. Finger, E.C.; Giaccia, A.J. Hypoxia, inflammation, and the tumor microenvironment in metastatic disease. Cancer Metastasis Rev. 2010, 29, 285–293. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  140. Hadi, L.A.; Anelli, V.; Guarnaccia, L.; Navone, S.; Beretta, M.; Moccia, F.; Tringali, C.; Urechie, V.; Campanella, R.; Marfia, G. A bidirectional crosstalk between glioblastoma and brain endothelial cells potentiates the angiogenic and proliferative signaling of sphingosine-1-phosphate in the glioblastoma microenvironment. Biochim. Biophys. Acta (BBA)-Mol. Cell Biol. Lipids 2018, 1863, 1179–1192. [Google Scholar] [CrossRef] [PubMed]
  141. Liu, J.; Chen, Q.; Feng, L.; Liu, Z. Nanomedicine for tumor microenvironment modulation and cancer treatment enhancement. Nano Today 2018, 21, 55–73. [Google Scholar] [CrossRef]
  142. Shimizu, T.; Kurozumi, K.; Ishida, J.; Ichikawa, T.; Date, I. Adhesion molecules and the extracellular matrix as drug targets for glioma. Brain Tumor Pathol. 2016, 33, 97–106. [Google Scholar] [CrossRef] [PubMed]
  143. Faissner, A.; Roll, L.; Theocharidis, U. Tenascin-C in the matrisome of neural stem and progenitor cells. Mol. Cell. Neurosci. 2017, 81, 22–31. [Google Scholar] [CrossRef] [PubMed]
  144. Desgrosellier, J.S.; Cheresh, D.A. Integrins in cancer: Biological implications and therapeutic opportunities. Nat. Rev. Cancer 2010, 10, 9–22. [Google Scholar] [CrossRef] [PubMed]
  145. Malric, L.; Monferran, S.; Gilhodes, J.; Boyrie, S.; Dahan, P.; Skuli, N.; Sesen, J.; Filleron, T.; Kowalski-Chauvel, A.; Moyal, E.C.-J. Interest of integrins targeting in glioblastoma according to tumor heterogeneity and cancer stem cell paradigm: An update. Oncotarget 2017, 8, 86947–86968. [Google Scholar] [CrossRef] [PubMed]
  146. Chen, C.; Duan, Z.; Yuan, Y.; Li, R.; Pang, L.; Liang, J.; Xu, X.; Wang, J. Peptide-22 and cyclic RGD functionalized liposomes for glioma targeting drug delivery overcoming BBB and BBTB. ACS Appl. Mater. Interfaces 2017, 9, 5864–5873. [Google Scholar] [CrossRef] [PubMed]
  147. Zhang, X.; Li, X.; Hua, H.; Wang, A.; Liu, W.; Li, Y.; Fu, F.; Shi, Y.; Sun, K. Cyclic hexapeptide-conjugated nanoparticles enhance curcumin delivery to glioma tumor cells and tissue. Int. J. Nanomed. 2017, 12, 5717–5732. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  148. Fang, Y.; Jiang, Y.; Zou, Y.; Meng, F.; Zhang, J.; Deng, C.; Sun, H.; Zhong, Z. Targeted glioma chemotherapy by cyclic RGD peptide-functionalized reversibly core-crosslinked multifunctional poly(ethylene glycol)-b-poly(ε-caprolactone) micelles. Acta Biomater. 2017, 50, 396–406. [Google Scholar] [CrossRef] [PubMed]
  149. Song, S.; Mao, G.; Du, J.; Zhu, X. Novel RGD containing, temozolomide-loading nanostructured lipid carriers for glioblastoma multiforme chemotherapy. Drug Deliv. 2016, 23, 1404–1408. [Google Scholar] [CrossRef] [PubMed]
  150. Gao, H.; Xiong, Y.; Zhang, S.; Yang, Z.; Cao, S.; Jiang, X. RGD and interleukin-13 peptide functionalized nanoparticles for enhanced glioblastoma cells and neovasculature dual targeting delivery and elevated tumor penetration. Mol. Pharm. 2014, 11, 1042–1052. [Google Scholar] [CrossRef] [PubMed]
  151. Paolillo, M.; Serra, M.; Schinelli, S. Integrins in glioblastoma: Still an attractive target? Pharmacol. Res. 2016, 113, 55–61. [Google Scholar] [CrossRef] [PubMed]
  152. Friedmann-Morvinski, D.; Narasimamurthy, R.; Xia, Y.; Myskiw, C.; Soda, Y.; Verma, I.M. Targeting NF-κB in glioblastoma: A therapeutic approach. Sci. Adv. 2016, 2, e1501292. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  153. Kannappan, V.; Wang, Z.; Liu, P.; Brown, S.; Butcher, M.K.; Azar, M.K.; Bian, X.; Armesilla, A.; Darling, J.; Wang, W. PP54. Nano-encapsulated disulfiram targets glioblastoma stem cells in vitro and in vivo by modulation of hypoxia-nf-kb pathway. Neuro. Oncol. 2017, 19, i15. [Google Scholar] [CrossRef]
  154. Park, H.-Y.; Lee, K.-J.; Lee, S.-J.; Yoon, M.-Y. Screening of peptides bound to breast cancer stem cell specific surface marker CD44 by phage display. Mol. Biotechnol. 2012, 51, 212–220. [Google Scholar] [CrossRef] [PubMed]
  155. Dosio, F.; Arpicco, S.; Stella, B.; Fattal, E. Hyaluronic acid for anticancer drug and nucleic acid delivery. Adv. Drug Deliv. Rev. 2016, 97, 204–236. [Google Scholar] [CrossRef] [PubMed]
  156. Razavi, S.-M.; Lee, K.E.; Jin, B.E.; Aujla, P.S.; Gholamin, S.; Li, G. Immune evasion strategies of glioblastoma. Front. Surg. 2016, 3. [Google Scholar] [CrossRef] [PubMed]
  157. Brown, C.E.; Badie, B.; Barish, M.E.; Weng, L.; Ostberg, J.R.; Chang, W.-C.; Naranjo, A.; Starr, R.; Wagner, J.; Wright, C. Bioactivity and safety of IL13Rα2-redirected chimeric antigen receptor CD8+ T cells in patients with recurrent glioblastoma. Clin. Cancer Res. 2015, 21, 4062–4072. [Google Scholar] [CrossRef] [PubMed]
  158. Hambardzumyan, D.; Bergers, G. Glioblastoma: Defining tumor niches. Trends Cancer 2015, 1, 252–265. [Google Scholar] [CrossRef] [PubMed]
  159. Pacioni, S.; D’Alessandris, Q.G.; Giannetti, S.; Morgante, L.; Coccè, V.; Bonomi, A.; Buccarelli, M.; Pascucci, L.; Alessandri, G.; Pessina, A. Human mesenchymal stromal cells inhibit tumor growth in orthotopic glioblastoma xenografts. Stem Cell Res. Ther. 2017, 8, 53. [Google Scholar] [CrossRef] [PubMed]
  160. Herrera-Perez, R.M.; Voytik-Harbin, S.L.; Sarkaria, J.N.; Pollok, K.E.; Fishel, M.L.; Rickus, J.L. Presence of stromal cells in a bioengineered tumor microenvironment alters glioblastoma migration and response to STAT3 inhibition. PLoS ONE 2018, 13, e0194183. [Google Scholar] [CrossRef] [PubMed]
  161. Noy, R.; Pollard, J.W. Tumor-associated macrophages: From mechanisms to therapy. Immunity 2014, 41, 49–61. [Google Scholar] [CrossRef] [PubMed]
  162. Ngambenjawong, C.; Heather, H.G.; Pun, S.H. Progress in tumor-associated macrophage (TAM)-targeted therapeutics. Adv. Drug Deliv. Rev. 2017, 114, 206–221. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Chanmee, T.; Ontong, P.; Konno, K.; Itano, N. Tumor-associated macrophages as major players in the tumor microenvironment. Cancers (Basel) 2014, 6, 1670–1690. [Google Scholar] [CrossRef] [PubMed]
  164. Ries, C.H.; Cannarile, M.A.; Hoves, S.; Benz, J.; Wartha, K.; Runza, V.; Rey-Giraud, F.; Pradel, L.P.; Feuerhake, F.; Klaman, I. Targeting tumor-associated macrophages with anti-CSF-1R antibody reveals a strategy for cancer therapy. Cancer Cell 2014, 25, 846–859. [Google Scholar] [CrossRef] [PubMed]
  165. Peterson, T.E.; Kirkpatrick, N.D.; Huang, Y.; Farrar, C.T.; Marijt, K.A.; Kloepper, J.; Datta, M.; Amoozgar, Z.; Seano, G.; Jung, K. Dual inhibition of Ang-2 and VEGF receptors normalizes tumor vasculature and prolongs survival in glioblastoma by altering macrophages. Proc. Natl. Acad. Sci. USA 2016, 113, 4470–4475. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  166. Singh, Y.; Pawar, V.K.; Meher, J.G.; Raval, K.; Kumar, A.; Shrivastava, R.; Bhadauria, S.; Chourasia, M.K. Targeting tumor associated macrophages (TAMs) via nanocarriers. J. Control. Release 2017, 254, 92–106. [Google Scholar] [CrossRef] [PubMed]
  167. Mercurio, L.; Ajmone-Cat, M.A.; Cecchetti, S.; Ricci, A.; Bozzuto, G.; Molinari, A.; Manni, I.; Pollo, B.; Scala, S.; Carpinelli, G. Targeting CXCR4 by a selective peptide antagonist modulates tumor microenvironment and microglia reactivity in a human glioblastoma model. J. Exp. Clin. Cancer Res. 2016, 35, 55. [Google Scholar] [CrossRef] [PubMed]
  168. Miller, M.A.; Zheng, Y.-R.; Gadde, S.; Pfirschke, C.; Zope, H.; Engblom, C.; Kohler, R.H.; Iwamoto, Y.; Yang, K.S.; Askevold, B. Tumour-associated macrophages act as a slow-release reservoir of nano-therapeutic Pt (IV) pro-drug. Nat. Commun. 2015, 6, 8692. [Google Scholar] [CrossRef] [PubMed]
  169. Silva, V.L. Exploiting the cancer niche: Tumor-associated macrophages and hypoxia as promising synergistic targets for nano-based therapy. J. Control. Release 2017, 253, 82–96. [Google Scholar] [CrossRef] [PubMed]
  170. Goswami, K.K.; Ghosh, T.; Ghosh, S.; Sarkar, M.; Bose, A.; Baral, R. Tumor promoting role of anti-tumor macrophages in tumor microenvironment. Cell. Immunol. 2017, 316, 1–10. [Google Scholar] [CrossRef] [PubMed]
  171. Vinogradov, S.; Warren, G.; Wei, X. Macrophages associated with tumors as potential targets and therapeutic intermediates. Nanomedicine 2014, 9, 695–707. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  172. Bowman, R.L.; Joyce, J.A. Therapeutic targeting of tumor-associated macrophages and microglia in glioblastoma. Immunotherapy 2014, 6, 663–666. [Google Scholar] [CrossRef] [PubMed]
  173. Chen, Z.; Feng, X.; Herting, C.J.; Garcia, V.A.; Nie, K.; Pong, W.W.; Rasmussen, R.; Dwivedi, B.; Seby, S.; Wolf, S.A. Cellular and molecular identity of tumor-associated macrophages in glioblastoma. Cancer Res. 2017. [Google Scholar] [CrossRef] [PubMed]
  174. Bussard, K.M.; Mutkus, L.; Stumpf, K.; Gomez-Manzano, C.; Marini, F.C. Tumor-associated stromal cells as key contributors to the tumor microenvironment. Breast Cancer Res. 2016, 18, 84. [Google Scholar] [CrossRef] [PubMed]
  175. Kumar, V.; Donthireddy, L.; Marvel, D.; Condamine, T.; Wang, F.; Lavilla-Alonso, S.; Hashimoto, A.; Vonteddu, P.; Behera, R.; Goins, M.A. Cancer-associated fibroblasts neutralize the anti-tumor effect of CSF1 receptor blockade by inducing PMN-MDSC infiltration of tumors. Cancer Cell 2017, 32, 654–668. [Google Scholar] [CrossRef] [PubMed]
  176. Talks, K.L.; Turley, H.; Gatter, K.C.; Maxwell, P.H.; Pugh, C.W.; Ratcliffe, P.J.; Harris, A.L. The expression and distribution of the hypoxia-inducible factors HIF-1α and HIF-2α in normal human tissues, cancers, and tumor-associated macrophages. Am. J. Pathol. 2000, 157, 411–421. [Google Scholar] [CrossRef]
  177. Vaupel, P.; Kelleher, D.K.; Höckel, M. Oxygenation status of malignant tumors: Pathogenesis of hypoxia and significance for tumor therapy. In Seminars in Oncology; Elsevier: Amsterdam, The Netherlands, 2001; Volume 28, pp. 29–35. [Google Scholar]
  178. Vaupel, P.; Mayer, A.; Hockel, M. Tumor hypoxia and malignant progression. Methods Enzymol. 2004, 23, 335–354. [Google Scholar]
  179. Masoud, G.N.; Li, W. HIF-1α pathway: Role, regulation and intervention for cancer therapy. Acta Pharm. Sin. B 2015, 5, 378–389. [Google Scholar] [CrossRef] [PubMed]
  180. Tafani, M.; Di Vito, M.; Frati, A.; Pellegrini, L.; De Santis, E.; Sette, G.; Eramo, A.; Sale, P.; Mari, E.; Santoro, A. Pro-inflammatory gene expression in solid glioblastoma microenvironment and in hypoxic stem cells from human glioblastoma. J. Neuroinflamm. 2011, 8, 32. [Google Scholar] [CrossRef] [PubMed]
  181. Wigerup, C.; Sven, P.; Bexell, D. Therapeutic targeting of hypoxia and hypoxia-inducible factors in cancer. Pharmacol. Ther. 2016, 164, 152–169. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  182. Dubois, L.J.; Niemans, R.; van Kuijk, S.J.A.; Panth, K.M.; Parvathaneni, N.-K.; Peeters, S.G.J.A.; Zegers, C.M.L.; Rekers, N.H.; van Gisbergen, M.W.; Biemans, R. New ways to image and target tumour hypoxia and its molecular responses. Radiother. Oncol. 2015, 116, 352–357. [Google Scholar] [CrossRef] [PubMed]
  183. Damaghi, M.; Wojtkowiak, J.W.; Gillies, R.J. pH sensing and regulation in cancer. Front. Physiol. 2013, 4, 1–10. [Google Scholar] [CrossRef] [PubMed]
  184. Lee, E.S.; Gao, Z.; Bae, Y.H. Recent progress in tumor pH targeting nanotechnology. J. Control. Release 2008, 132, 164–170. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  185. Ma, Y.; Cheng, Z.; Liu, J.; Torre-Healy, L.; Lathia, J.D.; Nakano, I.; Guo, Y.; Thompson, R.C.; Freeman, M.L.; Wang, J. Inhibition of Farnesyltransferase Potentiates NOTCH-Targeted Therapy against Glioblastoma Stem Cells. Stem Cell Rep. 2017, 9, 1948–1960. [Google Scholar] [CrossRef] [PubMed]
  186. Yuan, X.; Wu, H.; Xu, H.; Xiong, H.; Chu, Q.; Yu, S.; Wu, G.S.; Wu, K. Notch signaling: An emerging therapeutic target for cancer treatment. Cancer Lett. 2015, 369, 20–27. [Google Scholar] [CrossRef] [PubMed]
  187. Zanotti, S.; Canalis, E. Notch signaling and the skeleton. Endocr. Rev. 2016, 37, 223–253. [Google Scholar] [CrossRef] [PubMed]
  188. Natsumeda, M.; Maitani, K.; Liu, Y.; Miyahara, H.; Kaur, H.; Chu, Q.; Zhang, H.; Kahlert, U.D.; Eberhart, C.G. Targeting notch signaling and autophagy increases cytotoxicity in glioblastoma neurospheres. Brain Pathol. 2016, 26, 713–723. [Google Scholar] [CrossRef] [PubMed]
  189. Gray, G.K.; McFarland, B.C.; Nozell, S.E.; Benveniste, E.N. NF-κB and STAT3 in glioblastoma: Therapeutic targets coming of age. Expert Rev. Neurother. 2014, 14, 1293–1306. [Google Scholar] [CrossRef] [PubMed]
  190. Xia, P.; Xu, X.-Y. PI3K/Akt/mTOR signaling pathway in cancer stem cells: From basic research to clinical application. Am. J. Cancer Res. 2015, 5, 1602. [Google Scholar] [PubMed]
  191. Liebelt, B.D.; Shingu, T.; Zhou, X.; Ren, J.; Shin, S.A.; Hu, J. Glioma stem cells: Signaling, microenvironment, and therapy. Stem Cells Int. 2016, 2016. [Google Scholar] [CrossRef] [PubMed]
  192. Chen, J.; Kesari, S.; Rooney, C.; Strack, P.R.; Chen, J.; Shen, H.; Wu, L.; Griffin, J.D. Inhibition of notch signaling blocks growth of glioblastoma cell lines and tumor neurospheres. Genes Cancer 2010, 1, 822–835. [Google Scholar] [CrossRef] [PubMed]
  193. Cho, J.-H.; Kim, A.-R.; Kim, S.-H.; Lee, S.-J.; Chung, H.; Yoon, M.-Y. Development of a novel imaging agent using peptide-coated gold nanoparticles toward brain glioma stem cell marker CD133. Acta Biomater. 2017, 47, 182–192. [Google Scholar] [CrossRef] [PubMed]
  194. Plaks, V.; Kong, N.; Werb, Z. The cancer stem cell niche: How essential is the niche in regulating stemness of tumor cells? Cell Stem Cell 2015, 16, 225–238. [Google Scholar] [CrossRef] [PubMed]
  195. Pinto, M.P.; Arce, M.; Yameen, B.; Vilos, C. Targeted brain delivery nanoparticles for malignant gliomas. Nanomedicine 2017, 12, 59–72. [Google Scholar] [CrossRef] [PubMed]
  196. Sato, Y.; Sakurai, Y.; Kajimoto, K.; Nakamura, T.; Yamada, Y.; Akita, H.; Harashima, H. Innovative Technologies in Nanomedicines: From Passive Targeting to Active Targeting/From Controlled Pharmacokinetics to Controlled Intracellular Pharmacokinetics. Macromol. Biosci. 2017, 17. [Google Scholar] [CrossRef] [PubMed]
  197. Wang, M.; Thanou, M. Targeting nanoparticles to cancer. Pharmacol. Res. 2010, 62, 90–99. [Google Scholar] [CrossRef] [PubMed]
  198. Wadajkar, A.S.; Dancy, J.G.; Hersh, D.S.; Anastasiadis, P.; Tran, N.L.; Woodworth, G.F.; Winkles, J.A.; Kim, A.J. Tumor-targeted nanotherapeutics: Overcoming treatment barriers for glioblastoma. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2017, 9. [Google Scholar] [CrossRef]
  199. Lee, G.Y.; Qian, W.P.; Wang, L.; Wang, Y.A.; Staley, C.A.; Satpathy, M.; Nie, S.; Mao, H.; Yang, L. Theranostic nanoparticles with controlled release of gemcitabine for targeted therapy and MRI of pancreatic cancer. ACS Nano 2013, 7, 2078–2089. [Google Scholar] [CrossRef] [PubMed]
  200. Tzeng, S.Y.; Green, J.J. Therapeutic nanomedicine for brain cancer. Ther. Deliv. 2013, 4, 687–704. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  201. Bertrand, N.; Wu, J.; Xu, X.; Kamaly, N.; Farokhzad, O.C. Cancer nanotechnology: The impact of passive and active targeting in the era of modern cancer biology. Adv. Drug Deliv. Rev. 2014, 66, 2–25. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  202. Kumar, A.; Lee, J.-Y.; Kim, H.-S. Selective fluorescence sensing of 3, 5-dinitrosalicylic acid based on pyrenesulfonamide-functionalized inorganic/organic hybrid nanoparticles. J. Ind. Eng. Chem. 2016, 44, 82–89. [Google Scholar] [CrossRef]
  203. Di Martino, A.; Guselnikova, O.A.; Trusova, M.E.; Postnikov, P.S.; Sedlarik, V. Organic-inorganic hybrid nanoparticles controlled delivery system for anticancer drugs. Int. J. Pharm. 2017, 526, 380–390. [Google Scholar] [CrossRef] [PubMed]
  204. Gao, J.-Q.; Lv, Q.; Li, L.-M.; Tang, X.-J.; Li, F.-Z.; Hu, Y.-L.; Han, M. Glioma targeting and blood-brain barrier penetration by dual-targeting doxorubincin liposomes. Biomaterials 2013, 34, 5628–5639. [Google Scholar] [CrossRef] [PubMed]
  205. Liu, X.; Madhankumar, A.B.; Miller, P.A.; Duck, K.A.; Hafenstein, S.; Rizk, E.; Slagle-Webb, B.; Sheehan, J.M.; Connor, J.R.; Yang, Q.X. MRI contrast agent for targeting glioma: Interleukin-13 labeled liposome encapsulating gadolinium-DTPA. Neuro Oncol. 2015, 18, 691–699. [Google Scholar] [CrossRef] [PubMed]
  206. Jhaveri, A.; Deshpande, P.; Pattni, B.; Torchilin, V. Transferrin-targeted, resveratrol-loaded liposomes for the treatment of glioblastoma. J. Control. Release 2018, 277, 89–101. [Google Scholar] [CrossRef] [PubMed]
  207. Belhadj, Z.; Zhan, C.; Ying, M.; Wei, X.; Xie, C.; Yan, Z.; Lu, W. Multifunctional targeted liposomal drug delivery for efficient glioblastoma treatment. Oncotarget 2017, 8, 66889–66900. [Google Scholar] [CrossRef] [PubMed]
  208. Chai, Z.; Hu, X.; Wei, X.; Zhan, C.; Lu, L.; Jiang, K.; Su, B.; Ruan, H.; Ran, D.; Fang, R.H. A facile approach to functionalizing cell membrane-coated nanoparticles with neurotoxin-derived peptide for brain-targeted drug delivery. J. Control. Release 2017, 264, 102–111. [Google Scholar] [CrossRef] [PubMed]
  209. Danhier, F.; Messaoudi, K.; Lemaire, L.; Benoit, J.-P.; Lagarce, F. Combined anti-Galectin-1 and anti-EGFR siRNA-loaded chitosan-lipid nanocapsules decrease temozolomide resistance in glioblastoma: In vivo evaluation. Int. J. Pharm. 2015, 481, 154–161. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  210. Chen, Z.; Lai, X.; Song, S.; Zhu, X.; Zhu, J. Nanostructured lipid carriers based temozolomide and gene co-encapsulated nanomedicine for gliomatosis cerebri combination therapy. Drug Deliv. 2016, 23, 1369–1373. [Google Scholar] [CrossRef] [PubMed]
  211. Wu, M.; Fan, Y.; Lv, S.; Xiao, B.; Ye, M.; Zhu, X. Vincristine and temozolomide combined chemotherapy for the treatment of glioma: A comparison of solid lipid nanoparticles and nanostructured lipid carriers for dual drugs delivery. Drug Deliv. 2016, 23, 2720–2725. [Google Scholar] [CrossRef] [PubMed]
  212. Qu, J.; Zhang, L.; Chen, Z.; Mao, G.; Gao, Z.; Qu, J.; Zhang, L.; Chen, Z.; Mao, G.; Gao, Z.; et al. Nanostructured lipid carriers, solid lipid nanoparticles, and polymeric nanoparticles: Which kind of drug delivery system is better for glioblastoma chemotherapy? Nanostructured lipid carriers, solid lipid nanoparticles, and polymeric nanoparticles. Drug Deliv. 2016, 23, 3048–3416. [Google Scholar] [CrossRef] [PubMed]
  213. Kuo, Y.-C.; Cheng, S.-J. Brain targeted delivery of carmustine using solid lipid nanoparticles modified with tamoxifen and lactoferrin for antitumor proliferation. Int. J. Pharm. 2016, 499, 10–19. [Google Scholar] [CrossRef] [PubMed]
  214. Kuo, Y.-C.; Lee, C.-H. Inhibition Against Growth of Glioblastoma Multiforme In Vitro Using Etoposide-Loaded Solid Lipid Nanoparticles with p-Aminophenyl-α-d-Manno-Pyranoside and Folic Acid. J. Pharm. Sci. 2015, 104, 1804–1814. [Google Scholar] [CrossRef] [PubMed]
  215. Graverini, G.; Piazzini, V.; Landucci, E.; Pantano, D.; Nardiello, P.; Casamenti, F.; Pellegrini-Giampietro, D.E.; Bilia, A.R.; Bergonzi, M.C. Solid lipid nanoparticles for delivery of andrographolide across the blood-brain barrier: In vitro and in vivo evaluation. Colloids Surf. B Biointerfaces 2018, 161, 302–313. [Google Scholar] [CrossRef] [PubMed]
  216. Nam, J.; Won, N.; Bang, J.; Jin, H.; Park, J.; Jung, S.; Jung, S.; Park, Y.; Kim, S. Surface engineering of inorganic nanoparticles for imaging and therapy. Adv. Drug Deliv. Rev. 2013, 65, 622–648. [Google Scholar] [CrossRef] [PubMed]
  217. Anselmo, A.C.; Mitragotri, S. A Review of Clinical Translation of Inorganic Nanoparticles. AAPS J. 2015, 17, 1041–1054. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  218. Gupta, A.K.; Gupta, M. Synthesis and surface engineering of iron oxide nanoparticles for biomedical applications. Biomaterials 2005, 26, 3995–4021. [Google Scholar] [CrossRef] [PubMed]
  219. Sherwood, J.; Xu, Y.; Lovas, K.; Qin, Y.; Bao, Y. Surface functionalization of dopamine coated iron oxide nanoparticles for various surface functionalities. J. Magn. Magn. Mater. 2017, 427, 220–224. [Google Scholar] [CrossRef]
  220. Yoon, J.; Cho, S.H.; Seong, H. Multifunctional ultrasmall superparamagnetic iron oxide nanoparticles as a theranostic agent. Colloids Surf. A Physicochem. Eng. Asp. 2017, 520, 892–902. [Google Scholar] [CrossRef]
  221. Zanganeh, S.; Hutter, G.; Spitler, R.; Lenkov, O.; Mahmoudi, M.; Shaw, A.; Pajarinen, J.S.; Nejadnik, H.; Goodman, S.; Moseley, M. Iron oxide nanoparticles inhibit tumour growth by inducing pro-inflammatory macrophage polarization in tumour tissues. Nat. Nanotechnol. 2016, 11, 986. [Google Scholar] [CrossRef] [PubMed]
  222. Baalousha, M.; Manciulea, A.; Cumberland, S.; Kendall, K.; Lead, J.R. Aggregation and surface properties of iron oxide nanoparticles: Influence of pH and natural organic matter. Environ. Toxicol. Chem. 2008, 27, 1875–1882. [Google Scholar] [CrossRef] [PubMed]
  223. Bharti, C.; Gulati, N.; Nagaich, U.; Pal, A. Mesoporous silica nanoparticles in target drug delivery system: A review. Int. J. Pharm. Investig. 2015, 5, 124–133. [Google Scholar] [CrossRef] [PubMed]
  224. Slowing, I.I.; Trewyn, B.G.; Giri, S.; Lin, V. Mesoporous silica nanoparticles for drug delivery and biosensing applications. Adv. Funct. Mater. 2007, 17, 1225–1236. [Google Scholar] [CrossRef]
  225. Kwon, S.; Singh, R.K.; Perez, R.A.; Abou Neel, E.A.; Kim, H.-W.; Chrzanowski, W. Silica-based mesoporous nanoparticles for controlled drug delivery. J. Tissue Eng. 2013, 4, 2041731413503357. [Google Scholar] [CrossRef] [PubMed]
  226. Chen, Z.; Tan, Y.; Xu, K.; Zhang, L.; Qiu, B.; Guo, L.; Lin, Z.; Chen, G. Stimulus-response mesoporous silica nanoparticle-based chemiluminescence biosensor for cocaine determination. Biosens. Bioelectron. 2016, 75, 8–14. [Google Scholar] [CrossRef] [PubMed]
  227. Hu, J.-J.; Liu, L.-H.; Li, Z.-Y.; Zhuo, R.-X.; Zhang, X.-Z. MMP-responsive theranostic nanoplatform based on mesoporous silica nanoparticles for tumor imaging and targeted drug delivery. J. Mater. Chem. B 2016, 4, 1932–1940. [Google Scholar] [CrossRef]
  228. Lee, J.E.; Lee, N.; Kim, T.; Kim, J.; Hyeon, T. Multifunctional mesoporous silica nanocomposite nanoparticles for theranostic applications. Acc. Chem. Res. 2011, 44, 893–902. [Google Scholar] [CrossRef] [PubMed]
  229. Carrasco, S.; Benito-Peña, E.; Navarro-Villoslada, F.; Langer, J.; Sanz-Ortiz, M.N.; Reguera, J.; Liz-Marzán, L.M.; Moreno-Bondi, M.C. Multibranched gold–mesoporous silica nanoparticles coated with a molecularly imprinted polymer for label-free antibiotic surface-enhanced raman scattering analysis. Chem. Mater. 2016, 28, 7947–7954. [Google Scholar] [CrossRef]
  230. Dhamecha, D.; Jalalpure, S.; Jadhav, K.; Jagwani, S.; Chavan, R. Doxorubicin loaded gold nanoparticles: Implication of passive targeting on anticancer efficacy. Pharmacol. Res. 2016, 113, 547–556. [Google Scholar] [CrossRef] [PubMed]
  231. Amoli-Diva, M.; Sadighi-Bonabi, R.; Pourghazi, K. Switchable on/off drug release from gold nanoparticles-grafted dual light-and temperature-responsive hydrogel for controlled drug delivery. Mater. Sci. Eng. C 2017, 76, 242–248. [Google Scholar] [CrossRef] [PubMed]
  232. Manivasagan, P.; Bharathiraja, S.; Bui, N.Q.; Lim, I.G.; Oh, J. Paclitaxel-loaded chitosan oligosaccharide-stabilized gold nanoparticles as novel agents for drug delivery and photoacoustic imaging of cancer cells. Int. J. Pharm. 2016, 511, 367–379. [Google Scholar] [CrossRef] [PubMed]
  233. Shaikh, T.; Pandey, A.; Talpur, F.N.; Kaushik, A.; Niazi, J.H. Gold nanoparticles based sensor for in vitro analysis of drug-drug interactions using imipramine and isoniazid drugs: A proof of concept approach. Sens. Actuators B Chem. 2017, 252, 1055–1062. [Google Scholar] [CrossRef]
  234. Bishop, C.J.; Stephany, Y.; Green, J.J. Degradable polymer-coated gold nanoparticles for co-delivery of DNA and siRNA. Acta Biomater. 2015, 11, 393–403. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  235. Perche, F.; Yi, Y.; Hespel, L.; Mi, P.; Dirisala, A.; Cabral, H.; Miyata, K.; Kataoka, K. Hydroxychloroquine-conjugated gold nanoparticles for improved siRNA activity. Biomaterials 2016, 90, 62–71. [Google Scholar] [CrossRef] [PubMed]
  236. Chithrani, B.D.; Ghazani, A.A.; Chan, W.C. Determining the size and shape dependence of gold nanoparticle uptake into mammalian cells. Nano Lett. 2006, 6, 662–668. [Google Scholar] [CrossRef] [PubMed]
  237. Resch-Genger, U.; Grabolle, M.; Cavaliere-Jaricot, S.; Nitschke, R.; Nann, T. Quantum dots versus organic dyes as fluorescent labels. Nat. Methods 2008, 5, 763–775. [Google Scholar] [CrossRef] [PubMed]
  238. Khodadadei, F.; Safarian, S.; Ghanbari, N. Methotrexate-loaded nitrogen-doped graphene quantum dots nanocarriers as an efficient anticancer drug delivery system. Mater. Sci. Eng. C 2017, 79, 280–285. [Google Scholar] [CrossRef] [PubMed]
  239. Chand, S.; Thakur, N.; Katyal, S.C.; Barman, P.B.; Sharma, V.; Sharma, P. Recent developments on the synthesis, structural and optical properties of chalcogenide quantum dots. Sol. Energy Mater. Sol. Cells 2017, 168, 183–200. [Google Scholar] [CrossRef]
  240. Svitkova, V.; Blaskovicova, J.; Tekelova, M.; Kallai, B.M.; Ignat, T.; Horackova, V.; Skladal, P.; Kopel, P.; Adam, V.; Farkasova, D. Assessment of CdS quantum dots effect on UV damage to DNA using a DNA/quantum dots structured electrochemical biosensor and DNA biosensing in solution. Sens. Actuators B Chem. 2017, 243, 435–444. [Google Scholar] [CrossRef]
  241. Li, Z.; Xu, W.; Wang, Y.; Shah, B.R.; Zhang, C.; Chen, Y.; Li, Y.; Li, B. Quantum dots loaded nanogels for low cytotoxicity, pH-sensitive fluorescence, cell imaging and drug delivery. Carbohydr. Polym. 2015, 121, 477–485. [Google Scholar] [CrossRef] [PubMed]
  242. Madhankumar, A.B.; Mrowczynski, O.; Patel, S.; Weston, C.; Zacharia, B.; Glantz, M.; Siedlecki, C.; Xu, L.; Connor, J.R. Interleukin-13 conjugated quantum dots for identification of glioma initiating cells and their extracellular vesicles. Acta Biomater. 2017, 58, 205–213. [Google Scholar] [CrossRef] [PubMed]
  243. Sun, C.; Ding, Y.; Zhou, L.; Shi, D.; Sun, L.; Webster, T.J.; Shen, Y. Noninvasive nanoparticle strategies for brain tumor targeting. Nanomed. Nanotechnol. Biol. Med. 2017, 13, 2605–2621. [Google Scholar] [CrossRef] [PubMed]
  244. Aparicio-Blanco, J.; Torres-Suárez, A.-I. Towards tailored management of malignant brain tumors with nanotheranostics. Acta Biomater. 2018, 73, 52–63. [Google Scholar] [CrossRef] [PubMed]
  245. Miranda, A.; Blanco-Prieto, M.J.; Sousa, J.; Pais, A.; Vitorino, C. Breaching barriers in glioblastoma. Part II: Targeted drug delivery and lipid nanoparticles. Int. J. Pharm. 2017, 531, 389–410. [Google Scholar] [CrossRef] [PubMed]
  246. Saraiva, C.; Praça, C.; Ferreira, R.; Santos, T.; Ferreira, L.; Bernardino, L. Nanoparticle-mediated brain drug delivery: Overcoming blood–brain barrier to treat neurodegenerative diseases. J. Control. Release 2016, 235, 34–47. [Google Scholar] [CrossRef] [PubMed]
  247. Cheng, Y.; Morshed, R.A.; Auffinger, B.; Tobias, A.L.; Lesniak, M.S. Multifunctional nanoparticles for brain tumor imaging and therapy. Adv. Drug Deliv. Rev. 2014, 66, 42–57. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  248. Orunoğlu, M.; Kaffashi, A.; Pehlivan, S.B.; Şahin, S.; Söylemezoğlu, F.; Karlı-Oğuz, K.; Mut, M. Effects of curcumin-loaded PLGA nanoparticles on the RG2 rat glioma model. Mater. Sci. Eng. C 2017, 78, 32–38. [Google Scholar] [CrossRef] [PubMed]
  249. Zhao, M.; Zhao, M.; Fu, C.; Yu, Y.; Fu, A. Targeted therapy of intracranial glioma model mice with curcumin nanoliposomes. Int. J. Nanomed. 2018, 13, 1601–1610. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  250. Dixit, S.; Novak, T.; Miller, K.; Zhu, Y.; Kenney, M.E.; Broome, A.-M. Transferrin receptor-targeted theranostic gold nanoparticles for photosensitizer delivery in brain tumors. Nanoscale 2015, 7, 1782–1790. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  251. Dixit, S.; Miller, K.; Zhu, Y.; McKinnon, E.; Novak, T.; Kenney, M.E.; Broome, A.-M. Dual receptor-targeted theranostic nanoparticles for localized delivery and activation of photodynamic therapy drug in glioblastomas. Mol. Pharm. 2015, 12, 3250–3260. [Google Scholar] [CrossRef] [PubMed]
  252. Belhadj, Z.; Ying, M.; Cao, X.; Hu, X.; Zhan, C.; Wei, X.; Gao, J.; Wang, X.; Yan, Z.; Lu, W. Design of Y-shaped targeting material for liposome-based multifunctional glioblastoma-targeted drug delivery. J. Control. Release 2017, 255, 132–141. [Google Scholar] [CrossRef] [PubMed]
  253. Fang, C.; Wang, K.; Stephen, Z.R.; Mu, Q.; Kievit, F.M.; Chiu, D.T.; Press, O.W.; Zhang, M. Temozolomide nanoparticles for targeted glioblastoma therapy. ACS Appl. Mater. Interfaces 2015, 7, 6674–6682. [Google Scholar] [CrossRef] [PubMed]
  254. Hayward, S.L.; Wilson, C.L.; Kidambi, S. Hyaluronic acid-conjugated liposome nanoparticles for targeted delivery to CD44 overexpressing glioblastoma cells. Oncotarget 2016, 7, 34158–34171. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  255. Wang, K.; Kievit, F.M.; Jeon, M.; Silber, J.R.; Ellenbogen, R.G.; Zhang, M. Nanoparticle-mediated target delivery of trail as gene therapy for glioblastoma. Adv. Healthc. Mater. 2015, 4, 2719–2726. [Google Scholar] [CrossRef] [PubMed]
  256. Rabanel, J.M.; Latreille, P.L.; Lalloz, A.; Hildgen, P.; Banquy, X. Chapter 4-Nanostructured Nanoparticles for Improved Drug Delivery; Elsevier Inc.: Amsterdam, The Netherlands, 2017. [Google Scholar]
  257. Bregoli, L.; Movia, D.; Gavigan-Imedio, J.D.; Lysaght, J.; Reynolds, J.; Prina-Mello, A. Nanomedicine applied to translational oncology: A future perspective on cancer treatment. Nanomed. Nanotechnol. Biol. Med. 2016, 12, 81–103. [Google Scholar] [CrossRef] [PubMed]
  258. Wicki, A.; Witzigmann, D.; Balasubramanian, V.; Huwyler, J. Nanomedicine in cancer therapy: Challenges, opportunities, and clinical applications. J. Control. Release 2015, 200, 138–157. [Google Scholar] [CrossRef] [PubMed]
  259. Hare, J.I.; Lammers, T.; Ashford, M.B.; Puri, S.; Storm, G.; Barry, S.T. Challenges and strategies in anti-cancer nanomedicine development: An industry perspective. Adv. Drug Deliv. Rev. 2017, 108, 25–38. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  260. Mendes, M.; Sousa, J.; Pais, A.; Vitorino, C. Clinical applications of nanostructured drug delivery systems: From basic research to translational medicine. In Core-Shell Nanostructures for Drug Delivery and Theranostics; Elsevier: Amsterdam, The Netherlands, 2018; pp. 43–116. [Google Scholar]
  261. Blanco, E.; Shen, H.; Ferrari, M. Principles of nanoparticle design for overcoming biological barriers to drug delivery. Nat. Biotechnol. 2015, 33, 941–951. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  262. Gao, K.; Jiang, X. Influence of particle size on transport of methotrexate across blood brain barrier by polysorbate 80-coated polybutylcyanoacrylate nanoparticles. Int. J. Pharm. 2006, 310, 213–219. [Google Scholar] [CrossRef] [PubMed]
  263. Tang, L.; Fan, T.M.; Borst, L.B.; Cheng, J. Synthesis and biological response of size-specific, monodisperse drug–silica nanoconjugates. ACS Nano 2012, 6, 3954–3966. [Google Scholar] [CrossRef] [PubMed]
  264. Kim, J.H.; Kim, J.H.; Kim, K.-W.; Kim, M.H.; Yu, Y.S. Intravenously administered gold nanoparticles pass through the blood–retinal barrier depending on the particle size, and induce no retinal toxicity. Nanotechnology 2009, 20, 505101. [Google Scholar] [CrossRef] [PubMed]
  265. Davis, M.E.; Chen, Z.; Shin, D.M. Nanoparticle therapeutics: An emerging treatment modality for cancer. In Nanoscience And Technology: A Collection of Reviews from Nature Journals; World Scientific: Singapore, 2010; pp. 239–250. [Google Scholar]
  266. Wohlfart, S.; Gelperina, S.; Kreuter, J. Transport of drugs across the blood-brain barrier by nanoparticles. J. Control. Release 2012, 161, 264–273. [Google Scholar] [CrossRef] [PubMed]
  267. Yuan, F.; Dellian, M.; Fukumura, D.; Leunig, M.; Berk, D.A.; Torchilin, V.P.; Jain, R.K. Vascular permeability in a human tumor xenograft: Molecular size dependence and cutoff size. Cancer Res. 1995, 55, 3752–3756. [Google Scholar] [PubMed]
  268. Mikitsh, J.L.; Chacko, A.-M. Pathways for small molecule delivery to the central nervous system across the blood-brain barrier. Perspect. Med. Chem. 2014, 6, 11. [Google Scholar] [CrossRef] [PubMed]
  269. Parayath, N.N.; Amiji, M.M. Therapeutic targeting strategies using endogenous cells and proteins. J. Control. Release 2017, 258, 81–94. [Google Scholar] [CrossRef] [PubMed]
  270. Guo, J.; Schlich, M.; Cryan, J.F.; O’Driscoll, C.M. Targeted drug delivery via folate receptors for the treatment of brain cancer: Can the promise deliver? J. Pharm. Sci. 2017, 106, 3413–3420. [Google Scholar] [CrossRef] [PubMed]
  271. Razpotnik, R.; Novak, N.; Čurin Šerbec, V.; Rajcevic, U. Targeting Malignant Brain Tumors with Antibodies. Front. Immunol. 2017, 8, 1181. [Google Scholar] [CrossRef] [PubMed]
  272. Kang, T.; Li, F.; Baik, S.; Shao, W.; Ling, D.; Hyeon, T. Surface design of magnetic nanoparticles for stimuli-responsive cancer imaging and therapy. Biomaterials 2017, 136, 98–114. [Google Scholar] [CrossRef] [PubMed]
  273. Cheng, W.; Gu, L.; Ren, W.; Liu, Y. Stimuli-responsive polymers for anti-cancer drug delivery. Mater. Sci. Eng. C 2014, 45, 600–608. [Google Scholar] [CrossRef] [PubMed]
  274. Liu, M.; Du, H.; Zhang, W.; Zhai, G. Internal stimuli-responsive nanocarriers for drug delivery: Design strategies and applications. Mater. Sci. Eng. C 2017, 71, 1267–1280. [Google Scholar] [CrossRef] [PubMed]
  275. Lu, N.; Huang, P.; Fan, W.; Wang, Z.; Liu, Y.; Wang, S.; Zhang, G.; Hu, J.; Liu, W.; Niu, G. Tri-stimuli-responsive biodegradable theranostics for mild hyperthermia enhanced chemotherapy. Biomaterials 2017, 126, 39–48. [Google Scholar] [CrossRef] [PubMed]
  276. Gerweck, L.E.; Seetharaman, K. Cellular pH Gradient in Tumor versus Normal Tissue: Potential Exploitation for the Treatment of Cancer Advances in Brief Cellular. Cancer Res. 1996, 56, 1194–1198. [Google Scholar] [PubMed]
  277. Karimi, M.; Eslami, M.; Sahandi-Zangabad, P.; Mirab, F.; Farajisafiloo, N.; Shafaei, Z.; Ghosh, D.; Bozorgomid, M.; Dashkhaneh, F.; Hamblin, M.R. pH-Sensitive stimulus-responsive nanocarriers for targeted delivery of therapeutic agents. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2016, 8, 696–716. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  278. Liu, R.; Li, D.; He, B.; Xu, X.; Sheng, M.; Lai, Y.; Wang, G.; Gu, Z. Anti-tumor drug delivery of pH-sensitive poly (ethylene glycol)-poly (l-histidine-)-poly (l-lactide) nanoparticles. J. Control. Release 2011, 152, 49–56. [Google Scholar] [CrossRef] [PubMed]
  279. Al-Ahmady, Z.S.; Al-Jamal, W.; Bossche, J.V.; Bui, T.T.; Drake, A.F.; Mason, A.J.; Kostarelos, K. Lipid–peptide vesicle nanoscale hybrids for triggered drug release by mild hyperthermia in vitro and in vivo. ACS Nano 2012, 6, 9335–9346. [Google Scholar] [CrossRef] [PubMed]
  280. Shi, N.-Q.; Gao, W.; Xiang, B.; Qi, X.-R. Enhancing cellular uptake of activable cell-penetrating peptide–doxorubicin conjugate by enzymatic cleavage. Int. J. Nanomed. 2012, 7, 1613–1621. [Google Scholar]
  281. Liu, Z.; Xiong, M.; Gong, J.; Zhang, Y.; Bai, N.; Luo, Y.; Li, L.; Wei, Y.; Liu, Y.; Tan, X. Legumain protease-activated TAT-liposome cargo for targeting tumours and their microenvironment. Nat. Commun. 2014, 5, 4280. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  282. Gu, G.; Xia, H.; Hu, Q.; Liu, Z.; Jiang, M.; Kang, T.; Miao, D.; Tu, Y.; Pang, Z.; Song, Q. PEG-co-PCL nanoparticles modified with MMP-2/9 activatable low molecular weight protamine for enhanced targeted glioblastoma therapy. Biomaterials 2013, 34, 196–208. [Google Scholar] [CrossRef] [PubMed]
  283. Movahedi, F.; Hu, R.G.; Becker, D.L.; Xu, C. Stimuli-responsive liposomes for the delivery of nucleic acid therapeutics. Nanomed. Nanotechnol. Biol. Med. 2015, 11, 1575–1584. [Google Scholar] [CrossRef] [PubMed]
  284. Kim, J.; Lee, Y.M.; Kim, H.; Park, D.; Kim, J.; Kim, W.J. Phenylboronic acid-sugar grafted polymer architecture as a dual stimuli-responsive gene carrier for targeted anti-angiogenic tumor therapy. Biomaterials 2016, 75, 102–111. [Google Scholar] [CrossRef] [PubMed]
  285. Kuo, Y.-C.; Wang, I.-H. Using catanionic solid lipid nanoparticles with wheat germ agglutinin and lactoferrin for targeted delivery of etoposide to glioblastoma multiforme. J. Taiwan Inst. Chem. Eng. 2017, 77, 73–82. [Google Scholar] [CrossRef]
  286. Zhang, J.; Chen, N.; Wang, H.; Gu, W.; Liu, K.; Ai, P.; Yan, C.; Ye, L. Dual-targeting superparamagnetic iron oxide nanoprobes with high and low target density for brain glioma imaging. J. Colloid Interface Sci. 2016, 469, 86–92. [Google Scholar] [CrossRef] [PubMed]
  287. Feng, X.; Yao, J.; Gao, X.; Jing, Y.; Kang, T.; Jiang, D.; Jiang, T.; Feng, J.; Zhu, Q.; Jiang, X. Multi-targeting peptide-functionalized nanoparticles recognized vasculogenic mimicry, tumor neovasculature, and glioma cells for enhanced anti-glioma therapy. ACS Appl. Mater. Interfaces 2015, 7, 27885–27899. [Google Scholar] [CrossRef] [PubMed]
  288. Gao, H.; Qian, J.; Cao, S.; Yang, Z.; Pang, Z.; Pan, S.; Fan, L.; Xi, Z.; Jiang, X.; Zhang, Q. Precise glioma targeting of and penetration by aptamer and peptide dual-functioned nanoparticles. Biomaterials 2012, 33, 5115–5123. [Google Scholar] [CrossRef] [PubMed]
  289. Roth, L.; Agemy, L.; Kotamraju, V.R.; Braun, G.; Teesalu, T.; Sugahara, K.N.; Hamzah, J.; Ruoslahti, E. Transtumoral targeting enabled by a novel neuropilin-binding peptide. Oncogene 2012, 31, 3754–3763. [Google Scholar] [CrossRef] [PubMed]
  290. Luo, L.-M.; Huang, Y.; Zhao, B.-X.; Zhao, X.; Duan, Y.; Du, R.; Yu, K.-F.; Song, P.; Zhao, Y.; Zhang, X. Anti-tumor and anti-angiogenic effect of metronomic cyclic NGR-modified liposomes containing paclitaxel. Biomaterials 2013, 34, 1102–1114. [Google Scholar] [CrossRef] [PubMed]
  291. Ying, M.; Shen, Q.; Zhan, C.; Wei, X.; Gao, J.; Xie, C.; Yao, B.; Lu, W. A stabilized peptide ligand for multifunctional glioma targeted drug delivery. J. Control. Release 2016, 243, 86–98. [Google Scholar] [CrossRef] [PubMed]
  292. Pasqualini, R.; Koivunen, E.; Kain, R.; Lahdenranta, J.; Sakamoto, M.; Stryhn, A.; Ashmun, R.A.; Shapiro, L.H.; Arap, W.; Ruoslahti, E. Aminopeptidase N is a receptor for tumor-homing peptides and a target for inhibiting angiogenesis. Cancer Res. 2000, 60, 722–727. [Google Scholar] [PubMed]
  293. Jiang, X.; Xin, H.; Ren, Q.; Gu, J.; Zhu, L.; Du, F.; Feng, C.; Xie, Y.; Sha, X.; Fang, X. Nanoparticles of 2-deoxy-D-glucose functionalized poly(ethylene glycol)-co-poly(trimethylene carbonate) for dual-targeted drug delivery in glioma treatment. Biomaterials 2014, 35, 518–529. [Google Scholar] [CrossRef] [PubMed]
  294. Byeon, H.J.; Lee, S.; Min, S.Y.; Lee, E.S.; Shin, B.S.; Choi, H.-G.; Youn, Y.S. Doxorubicin-loaded nanoparticles consisted of cationic-and mannose-modified-albumins for dual-targeting in brain tumors. J. Control. Release 2016, 225, 301–313. [Google Scholar] [CrossRef] [PubMed]
  295. Zong, T.; Mei, L.; Gao, H.; Shi, K.; Chen, J.; Wang, Y.; Zhang, Q.; Yang, Y.; He, Q. Enhanced glioma targeting and penetration by dual-targeting liposome co-modified with T7 and TAT. J. Pharm. Sci. 2014, 103, 3891–3901. [Google Scholar] [CrossRef] [PubMed]
  296. Wei, L.; Guo, X.Y.; Yang, T.; Yu, M.Z.; Chen, D.W.; Wang, J.C. Brain tumor-targeted therapy by systemic delivery of siRNA with Transferrin receptor-mediated core-shell nanoparticles. Int. J. Pharm. 2016, 510, 394–405. [Google Scholar] [CrossRef] [PubMed]
  297. Ruan, S.; Yuan, M.; Zhang, L.; Hu, G.; Chen, J.; Cun, X.; Zhang, Q.; Yang, Y.; He, Q.; Gao, H. Tumor microenvironment sensitive doxorubicin delivery and release to glioma using angiopep-2 decorated gold nanoparticles. Biomaterials 2015, 37, 425–435. [Google Scholar] [CrossRef] [PubMed]
  298. Kuo, Y.-C.; Hsu, C.-C. Anti-melanotransferrin and apolipoprotein E on doxorubicin-loaded cationic solid lipid nanoparticles for pharmacotherapy of glioblastoma multiforme. J. Taiwan Inst. Chem. Eng. 2017, 77, 10–20. [Google Scholar] [CrossRef]
  299. Wang, Z.; He, Q.; Zhao, W.; Luo, J.; Gao, W. Tumor-homing, pH-and ultrasound-responsive polypeptide-doxorubicin nanoconjugates overcome doxorubicin resistance in cancer therapy. J. Control. Release 2017, 264, 66–75. [Google Scholar] [CrossRef] [PubMed]
  300. Chen, Y.; Zhang, M.; Jin, H.; Li, D.; Xu, F.; Wu, A.; Wang, J.; Huang, Y. Glioma dual-targeting nanohybrid protein toxin constructed by intein-mediated site-specific ligation for multistage booster delivery. Theranostics 2017, 7, 3489–3503. [Google Scholar] [CrossRef] [PubMed]
  301. Zamykal, M.; Martens, T.; Matschke, J.; Günther, H.S.; Kathagen, A.; Schulte, A.; Peters, R.; Westphal, M.; Lamszus, K. Inhibition of intracerebral glioblastoma growth by targeting the insulin-like growth factor 1 receptor involves different context-dependent mechanisms. Neuro. Oncol. 2014, 17, 1076–1085. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  302. Iaboni, M.; Fontanella, R.; Rienzo, A.; Capuozzo, M.; Nuzzo, S.; Santamaria, G.; Catuogno, S.; Condorelli, G.; De Franciscis, V.; Esposito, C.L. Targeting insulin receptor with a novel internalizing aptamer. Mol. Ther. Acids 2016, 5, e365. [Google Scholar] [CrossRef] [PubMed]
  303. Muthu, M.S.; Kulkarni, S.A.; Xiong, J.; Feng, S.-S. Vitamin E TPGS coated liposomes enhanced cellular uptake and cytotoxicity of docetaxel in brain cancer cells. Int. J. Pharm. 2011, 421, 332–340. [Google Scholar] [CrossRef] [PubMed]
  304. Agrawal, P.; Singh, R.P.; Kumari, L.; Sharma, G.; Koch, B.; Rajesh, C.V.; Mehata, A.K.; Singh, S.; Pandey, B.L.; Muthu, M.S. TPGS-chitosan cross-linked targeted nanoparticles for effective brain cancer therapy. Mater. Sci. Eng. C 2017, 74, 167–176. [Google Scholar] [CrossRef] [PubMed]
  305. Dai, Z.; Yao, Q.; Zhu, L. MMP2-sensitive peg–lipid copolymers: A new type of tumor-targeted p-glycoprotein inhibitor. ACS Appl. Mater. Interfaces 2016, 8, 12661–12673. [Google Scholar] [CrossRef] [PubMed]
  306. Johansson, E.; Grassi, E.S.; Pantazopoulou, V.; Tong, B.; Lindgren, D.; Berg, T.J.; Pietras, E.J.; Axelson, H.; Pietras, A. CD44 interacts with HIF-2α to modulate the hypoxic phenotype of perinecrotic and perivascular glioma cells. Cell Rep. 2017, 20, 1641–1653. [Google Scholar] [CrossRef] [PubMed]
  307. Onnis, B.; Rapisarda, A.; Melillo, G. Development of HIF-1 inhibitors for cancer therapy. J. Cell. Mol. Med. 2009, 13, 2780–2786. [Google Scholar] [CrossRef] [PubMed]
  308. Rodríguez-Cabello, J.C.; Piña, M.J.; Ibáñez-Fonseca, A.; Fernández-Colino, A.; Arias, F.J. Nanotechnological approaches to therapeutic delivery using elastin-like recombinamers. Bioconjug. Chem. 2015, 26, 1252–1265. [Google Scholar] [CrossRef] [PubMed]
  309. Ryu, J.S.; Raucher, D. Anti-tumor efficacy of a therapeutic peptide based on thermo-responsive elastin-like polypeptide in combination with gemcitabine. Cancer Lett. 2014, 348, 177–184. [Google Scholar] [CrossRef] [PubMed]
  310. Zhang, B.; Shen, S.; Liao, Z.; Shi, W.; Wang, Y.; Zhao, J.; Hu, Y.; Yang, J.; Chen, J.; Mei, H. Targeting fibronectins of glioma extracellular matrix by CLT1 peptide-conjugated nanoparticles. Biomaterials 2014, 35, 4088–4098. [Google Scholar] [CrossRef] [PubMed]
  311. Ruoslahti, E. Tumor penetrating peptides for improved drug delivery. Adv. Drug Deliv. Rev. 2016, 110, 3–12. [Google Scholar] [CrossRef] [PubMed]
  312. He, S.; Cen, B.; Liao, L.; Wang, Z.; Qin, Y.; Wu, Z.; Liao, W.; Zhang, Z.; Ji, A. A tumor-targeting cRGD-EGFR siRNA conjugate and its anti-tumor effect on glioblastoma in vitro and in vivo. Drug Deliv. 2017, 24, 471–481. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  313. Quader, S.; Liu, X.; Chen, Y.; Mi, P.; Chida, T.; Ishii, T.; Miura, Y.; Nishiyama, N.; Cabral, H.; Kataoka, K. cRGD peptide-installed epirubicin-loaded polymeric micelles for effective targeted therapy against brain tumors. J. Control. Release 2017, 258, 56–66. [Google Scholar] [CrossRef] [PubMed]
  314. Kulhari, H.; Telukutla, S.R.; Pooja, D.; Shukla, R.; Sistla, R.; Bansal, V.; Adams, D.J. Peptide grafted and self-assembled poly(γ-glutamic acid)-phenylalanine nanoparticles targeting camptothecin to glioma. Nanomedicine 2017, 12, 1661–1674. [Google Scholar] [CrossRef] [PubMed]
  315. Hou, J.; Diao, Y.; Li, W.; Yang, Z.; Zhang, L.; Chen, Z.; Wu, Y. RGD peptide conjugation results in enhanced antitumor activity of PD0325901 against glioblastoma by both tumor-targeting delivery and combination therapy. Int. J. Pharm. 2016, 505, 329–340. [Google Scholar] [CrossRef] [PubMed]
  316. Thysiadis, S.; Katsamakas, S.; Dalezis, P.; Chatzisideri, T.; Trafalis, D.; Sarli, V. Novel c (RGDyK)-based conjugates of POPAM and 5-fluorouracil for integrin-targeted cancer therapy. Future Med. Chem. 2017, 9, 2181–2196. [Google Scholar] [CrossRef] [PubMed]
  317. Qin, H.; Ding, Y.; Mujeeb, A.; Zhao, Y.; Nie, G. Tumor microenvironment targeting and responsive peptide-based nanoformulations for improved tumor therapy. Mol. Pharmacol. 2017. [Google Scholar] [CrossRef] [PubMed]
  318. Zhou, J.; Yu, J.; Gao, L.; Sun, L.; Peng, T.; Wang, J.; Zhu, J.; Lu, W.; Zhang, L.; Yan, Z. iNGR-modified liposomes for tumor vascular targeting and tumor tissue penetrating delivery in the treatment of glioblastoma. Mol. Pharm. 2017, 14, 1811–1820. [Google Scholar] [CrossRef] [PubMed]
  319. Huang, N.; Cheng, S.; Zhang, X.; Tian, Q.; Pi, J.; Tang, J.; Huang, Q.; Wang, F.; Chen, J.; Xie, Z. Efficacy of NGR peptide-modified PEGylated quantum dots for crossing the blood-brain barrier and targeted fluorescence imaging of glioma and tumor vasculature. Nanomed. Nanotechnol. Biol. Med. 2017, 13, 83–93. [Google Scholar] [CrossRef] [PubMed]
  320. Jiao, Z.; Li, Y.; Pang, H.; Zheng, Y.; Zhao, Y. Pep-1 peptide-functionalized liposome to enhance the anticancer efficacy of cilengitide in glioma treatment. Colloids Surf. B Biointerfaces 2017, 158, 68–75. [Google Scholar] [CrossRef] [PubMed]
  321. Wang, B.; Lv, L.; Wang, Z.; Jiang, Y.; Lv, W.; Liu, X.; Wang, Z.; Zhao, Y.; Xin, H.; Xu, Q. Improved anti-glioblastoma efficacy by IL-13Rα2 mediated copolymer nanoparticles loaded with paclitaxel. Sci. Rep. 2015, 5, 16589. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  322. Hicks, M.J.; Chiuchiolo, M.J.; Ballon, D.; Dyke, J.P.; Aronowitz, E.; Funato, K.; Tabar, V.; Havlicek, D.; Fan, F.; Sondhi, D. Anti-Epidermal Growth Factor Receptor Gene Therapy for Glioblastoma. PLoS ONE 2016, 11, e0162978. [Google Scholar] [CrossRef] [PubMed]
  323. Li, J.; Zhou, Y.; Wang, H.; Gao, Y.; Li, L.; Hwang, S.H.; Ji, X.; Hammock, B.D. COX-2/sEH dual inhibitor PTUPB suppresses glioblastoma growth by targeting epidermal growth factor receptor and hyaluronan mediated motility receptor. Oncotarget 2017, 8, 87353. [Google Scholar] [CrossRef] [PubMed]
  324. Taylor, E.T.; Furnari, B.F.; Cavenee, W.K. Targeting EGFR for treatment of glioblastoma: Molecular basis to overcome resistance. Curr. Cancer Drug Targets 2012, 12, 197–209. [Google Scholar] [CrossRef] [PubMed]
  325. Eller, J.L.; Longo, S.L.; Hicklin, D.J.; Canute, G.W. Activity of anti-epidermal growth factor receptor monoclonal antibody C225 against glioblastoma multiforme. Neurosurgery 2002, 51, 1005–1014. [Google Scholar] [PubMed]
  326. Wei, J.; Cui, J.; Zhou, X.; Fang, C.; Tan, Y.; Chen, L.; Yang, C.; Liu, M.; Kang, C. F25P preproinsulin abrogates the secretion of pro-growth factors from EGFRvIII cells and suppresses tumor growth in an EGFRvIII/wt heterogenic model. Cancer Lett. 2016, 380, 1–9. [Google Scholar] [CrossRef] [PubMed]
  327. Han, J.; Chu, J.; Chan, W.K.; Zhang, J.; Wang, Y.; Cohen, J.B.; Victor, A.; Meisen, W.H.; Kim, S.; Grandi, P. CAR-engineered NK cells targeting wild-type EGFR and EGFRvIII enhance killing of glioblastoma and patient-derived glioblastoma stem cells. Sci. Rep. 2015, 5, 11483. [Google Scholar] [CrossRef] [PubMed]
  328. Westphal, M.; Cecile, L.M.; Lamszus, K. EGFR as a target for glioblastoma treatment: An unfulfilled promise. CNS Drugs 2017, 31, 723–735. [Google Scholar] [CrossRef] [PubMed]
  329. Choi, B.D.; Archer, G.E.; Mitchell, D.A.; Heimberger, A.B.; McLendon, R.E.; Bigner, D.D.; Sampson, J.H. EGFRvIII-Targeted Vaccination Therapy of Malignant Glioma. Brain Pathol. 2009, 19, 713–723. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  330. Shankar, A.; Jain, M.; Lim, M.J.; Angara, K.; Zeng, P.; Arbab, S.A.; Iskander, A.S.M.; Ara, R.; Arbab, A.S.; Achyut, B.R. Anti-VEGFR2 driven nuclear translocation of VEGFR2 and acquired malignant hallmarks are mutation dependent in glioblastoma. J. Cancer Sci. Ther. 2016, 8, 172–178. [Google Scholar] [CrossRef] [PubMed]
  331. Momeny, M.; Moghaddaskho, F.; Gortany, N.K.; Yousefi, H.; Sabourinejad, Z.; Zarrinrad, G.; Mirshahvaladi, S.; Eyvani, H.; Barghi, F.; Ahmadinia, L. Blockade of vascular endothelial growth factor receptors by tivozanib has potential anti-tumour effects on human glioblastoma cells. Sci. Rep. 2017, 7, 44075. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  332. Biel, N.M.; Dietmar, W. Siemann Targeting the Angiopoietin-2/Tie-2 axis in conjunction with VEGF signal interference. Cancer Lett. 2016, 380, 525–533. [Google Scholar] [CrossRef] [PubMed]
  333. Roomi, M.W.; Kalinovsky, T.; Rath, M.; Niedzwiecki, A. Modulation of MMP-2 and MMP-9 secretion by cytokines, inducers and inhibitors in human glioblastoma T-98G cells. Oncol. Rep. 2017, 37, 1907–1913. [Google Scholar] [CrossRef] [PubMed]
  334. Aroui, S.; Aouey, B.; Chtourou, Y.; Meunier, A.-C.; Fetoui, H.; Kenani, A. Naringin suppresses cell metastasis and the expression of matrix metalloproteinases (MMP-2 and MMP-9) via the inhibition of ERK-P38-JNK signaling pathway in human glioblastoma. Chem. Biol. Interact. 2016, 244, 195–203. [Google Scholar] [CrossRef] [PubMed]
  335. Piromkraipak, P.; Sangpairoj, K.; Tirakotai, W.; Chaithirayanon, K.; Unchern, S.; Supavilai, P.; Power, C.; Vivithanaporn, P. Cysteinyl leukotriene receptor antagonists inhibit migration, invasion, and expression of mmp-2/9 in human glioblastoma. Cell. Mol. Neurobiol. 2017, 38, 559–573. [Google Scholar] [CrossRef] [PubMed]
  336. Cohen-Inbar, O.; Zaaroor, M. Glioblastoma multiforme targeted therapy: The Chlorotoxin story. J. Clin. Neurosci. 2016, 33, 52–58. [Google Scholar] [CrossRef] [PubMed]
  337. Chung, E.J.; Cheng, Y.; Morshed, R.; Nord, K.; Han, Y.; Wegscheid, M.L.; Auffinger, B.; Wainwright, D.A.; Lesniak, M.S.; Tirrell, M. V Fibrin-binding, peptide amphiphile micelles for targeting glioblastoma. Biomaterials 2014, 35, 1249–1256. [Google Scholar] [CrossRef] [PubMed]
  338. Zhao, J.; Zhang, B.; Shen, S.; Chen, J.; Zhang, Q.; Jiang, X.; Pang, Z. CREKA peptide-conjugated dendrimer nanoparticles for glioblastoma multiforme delivery. J. Colloid Interface Sci. 2015, 450, 396–403. [Google Scholar] [CrossRef] [PubMed]
  339. Kim, M.Y.; Kim, O.R.; Choi, Y.S.; Lee, H.; Park, K.; Lee, C.-T.; Kang, K.W.; Jeong, S. Selection and characterization of tenascin C targeting peptide. Mol. Cells 2012, 33, 71–77. [Google Scholar] [CrossRef] [PubMed]
  340. Peterson, T.E. Dual Targeting of Angiopoietin-2 and VEGF Signaling for the Treatment of Glioblastoma; Harvard University: Cambridge, MA, USA, 2015. [Google Scholar]
  341. Sato, A.; Mizobuchi, Y.; Nakajima, K.; Shono, K.; Fujihara, T.; Kageji, T. Blocking COX-2 induces apoptosis and inhibits cell proliferation via the Akt/survivin- and Akt/ID3 pathway in low-grade-glioma. J. Neurooncol. 2017, 132, 231–238. [Google Scholar] [CrossRef] [PubMed]
  342. Wang, X.; Yu, Z.; Wang, C.; Cheng, W.; Tian, X.; Huo, X.; Wang, Y.; Sun, C.; Feng, L.; Xing, J. Alantolactone, a natural sesquiterpene lactone, has potent antitumor activity against glioblastoma by targeting IKKβ kinase activity and interrupting NF-κB/COX-2-mediated signaling cascades. J. Exp. Clin. Cancer Res. 2017, 36, 93. [Google Scholar] [CrossRef] [PubMed]
  343. Zhou, P.; Qin, J.; Li, Y.; Li, G.; Wang, Y.; Zhang, N.; Chen, P.; Li, C. Combination therapy of PKCζ and COX-2 inhibitors synergistically suppress melanoma metastasis. J. Exp. Clin. Cancer Res. 2017, 36, 115. [Google Scholar] [CrossRef] [PubMed]
  344. Jiang, G.; Zhang, L.; Wang, J.; Zhou, H. Baicalein induces the apoptosis of U251 glioblastoma cell lines via the NF-kB-p65-mediated mechanism. Animal Cells Syst. (Seoul) 2016, 20, 296–302. [Google Scholar] [CrossRef] [Green Version]
  345. Zou, M.; Duan, Y.; Wang, P.; Gao, R.; Chen, X.; Ou, Y.; Liang, M.; Wang, Z.; Yuan, Y.; Wang, L. DYT-40, a novel synthetic 2-styryl-5-nitroimidazole derivative, blocks malignant glioblastoma growth and invasion by inhibiting AEG-1 and NF-κB signaling pathways. Sci. Rep. 2016, 6, 27331. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  346. Zhang, L.; Ren, X.; Cheng, Y.; Liu, X.; Allen, J.E.; Zhang, Y.; Yuan, Y.; Huang, S.-Y.; Yang, W.; Berg, A. The NFκB inhibitor, SN50, induces differentiation of glioma stem cells and suppresses their oncogenic phenotype. Cancer Biol. Ther. 2014, 15, 602–611. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  347. Cahill, K.E.; Morshed, R.A.; Yamini, B. Nuclear factor-κB in glioblastoma: Insights into regulators and targeted therapy. Neuro. Oncol. 2015, 18, 329–339. [Google Scholar] [CrossRef] [PubMed]
  348. Li, B.; Xu, W.W.; Lam, A.K.Y.; Wang, Y.; Hu, H.-F.; Guan, X.Y.; Qin, Y.R.; Saremi, N.; Tsao, S.W.; He, Q.-Y. Significance of PI3K/AKT signaling pathway in metastasis of esophageal squamous cell carcinoma and its potential as a target for anti-metastasis therapy. Oncotarget 2017, 8, 38755. [Google Scholar] [CrossRef] [PubMed]
  349. Bumpers, H.; Huang, M.-B.; Katkoori, V.; Manne, U.; Bond, V. Nef-M1, a CXCR4 peptide antagonist, enhances apoptosis and inhibits primary tumor growth and metastasis in Breast Cancer. J. Cancer Ther. 2013, 4, 898. [Google Scholar] [CrossRef] [PubMed]
  350. Katkoori, V.R.; Basson, M.D.; Bond, V.C.; Manne, U.; Bumpers, H.L. Nef-M1, a peptide antagonist of CXCR4, inhibits tumor angiogenesis and epithelial-to-mesenchymal transition in colon and breast cancers. Oncotarget 2015, 6, 27763. [Google Scholar] [CrossRef] [PubMed]
  351. Kapur, A.; Beres, T.; Rathi, K.; Nayak, A.P.; Czarnecki, A.; Felder, M.; Gillette, A.; Ericksen, S.S.; Sampene, E.; Skala, M.C. Oxidative stress via inhibition of the mitochondrial electron transport and Nrf-2-mediated anti-oxidative response regulate the cytotoxic activity of plumbagin. Sci. Rep. 2018, 8, 1073. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  352. Scodeller, P.; Simón-Gracia, L.; Kopanchuk, S.; Tobi, A.; Kilk, K.; Säälik, P.; Kurm, K.; Squadrito, M.L.; Kotamraju, V.R.; Rinken, A. Precision Targeting of Tumor Macrophages with a CD206 Binding Peptide. Sci. Rep. 2017, 7, 14655. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  353. Cannarile, M.A.; Weisser, M.; Jacob, W.; Jegg, A.-M.; Ries, C.H.; Rüttinger, D. Colony-stimulating factor 1 receptor (CSF1R) inhibitors in cancer therapy. J. Immunother. Cancer 2017, 5, 53. [Google Scholar] [CrossRef] [PubMed]
  354. Cieslewicz, M.; Tang, J.; Jonathan, L.Y.; Cao, H.; Zavaljevski, M.; Motoyama, K.; Lieber, A.; Raines, E.W.; Pun, S.H. Targeted delivery of proapoptotic peptides to tumor-associated macrophages improves survival. Proc. Natl. Acad. Sci. USA 2013, 110, 15919–15924. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  355. Segers, F.M.E.; Yu, H.; Molenaar, T.J.M.; Prince, P.; Tanaka, T.; van Berkel, T.J.C.; Biessen, E.A.L. Design and validation of a specific scavenger receptor class AI binding peptide for targeting the inflammatory atherosclerotic plaque. Arterioscler. Thromb. Vasc. Biol. 2012, 32, 971–978. [Google Scholar] [CrossRef] [PubMed]
  356. Hierro, C.; Rodon, J.; Tabernero, J. Fibroblast growth factor (FGF) receptor/FGF inhibitors: Novel targets and strategies for optimization of response of solid tumors. In Seminars in Oncology; Elsevier: Amsterdam, The Netherlands, 2015; Volume 42, pp. 801–819. [Google Scholar]
  357. Babina, I.S.; Nicholas, C. Turner. Advances and challenges in targeting FGFR signalling in cancer. Nat. Rev. Cancer 2017, 17, 318–332. [Google Scholar] [CrossRef] [PubMed]
  358. Ader, I.; Delmas, C.; Skuli, N.; Bonnet, J.; Schaeffer, P.; Bono, F.; Cohen-Jonathan-Moyal, E.; Toulas, C. Preclinical evidence that SSR128129E–A novel small-molecule multi-fibroblast growth factor receptor blocker–Radiosensitises human glioblastoma. Eur. J. Cancer 2014, 50, 2351–2359. [Google Scholar] [CrossRef] [PubMed]
  359. Ji, T.; Ding, Y.; Zhao, Y.; Wang, J.; Qin, H.; Liu, X.; Lang, J.; Zhao, R.; Zhang, Y.; Shi, J. Peptide assembly integration of fibroblast-targeting and cell-penetration features for enhanced antitumor drug delivery. Adv. Mater. 2015, 27, 1865–1873. [Google Scholar] [CrossRef] [PubMed]
  360. Atzori, M.G.; Tentori, L.; Ruffini, F.; Ceci, C.; Lisi, L.; Bonanno, E.; Scimeca, M.; Eskilsson, E.; Daubon, T.; Miletic, H. The anti-vascular endothelial growth factor receptor-1 monoclonal antibody D16F7 inhibits invasiveness of human glioblastoma and glioblastoma stem cells. J. Exp. Clin. Cancer Res. 2017, 36, 106. [Google Scholar] [CrossRef] [PubMed]
  361. Liang, D.; Wang, A.; Yang, Z.; Liu, Y.; Qi, X. Enhance cancer cell recognition and overcome drug resistance using hyaluronic acid and α-tocopheryl succinate based multifunctional nanoparticles. Mol. Pharm. 2015, 12, 2189–2202. [Google Scholar] [CrossRef] [PubMed]
  362. Santoni, M.; Burattini, L.; Nabissi, M.; Beatrice Morelli, M.; Berardi, R.; Santoni, G.; Cascinu, S. Essential role of Gli proteins in glioblastoma multiforme. Curr. Protein Pept. Sci. 2013, 14, 133–140. [Google Scholar] [CrossRef] [PubMed]
  363. Cenciarelli, C.; Marei, H.E.S.; Zonfrillo, M.; Pierimarchi, P.; Paldino, E.; Casalbore, P.; Felsani, A.; Vescovi, A.L.; Maira, G.; Mangiola, A. PDGF receptor alpha inhibition induces apoptosis in glioblastoma cancer stem cells refractory to anti-Notch and anti-EGFR treatment. Mol. Cancer 2014, 13, 247. [Google Scholar] [CrossRef] [PubMed]
  364. Chiarini, F.; Evangelisti, C.; McCubrey, J.A.; Martelli, A.M. Current treatment strategies for inhibiting mTOR in cancer. Trends Pharmacol. Sci. 2015, 36, 124–135. [Google Scholar] [CrossRef] [PubMed]
  365. Luwor, R.B.; Kaye, A.H.; Zhu, H.-J. Transforming growth factor-beta (TGF-β) and brain tumours. J. Clin. Neurosci. 2008, 15, 845–855. [Google Scholar] [CrossRef] [PubMed]
  366. Bierie, B.; Moses, H.L. Transforming growth factor beta (TGF-β) and inflammation in cancer. Cytokine Growth Factor Rev. 2010, 21, 49–59. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  367. Pearson, J.R.D.; Regad, T. Targeting cellular pathways in glioblastoma multiforme. Signal Transduct. Target. Ther. 2017, 2, 17040. [Google Scholar] [CrossRef] [PubMed]
  368. Phuphanich, S.; Raizer, J.; Chamberlain, M.; Canelos, P.; Narwal, R.; Hong, S.; Miday, R.; Nade, M.; Laubscher, K. Phase II study of MEDI-575, an anti-platelet-derived growth factor-α antibody, in patients with recurrent glioblastoma. J. Neurooncol. 2017, 131, 185–191. [Google Scholar] [CrossRef] [PubMed]
  369. Batchelor, T.T.; Gerstner, E.R.; Ye, X.; Desideri, S.; Duda, D.G.; Peereboom, D.; Lesser, G.J.; Chowdhary, S.; Wen, P.Y.; Grossman, S. Feasibility, phase I, and phase II studies of tandutinib, an oral platelet-derived growth factor receptor-β tyrosine kinase inhibitor, in patients with recurrent glioblastoma. Neuro. Oncol. 2017, 19, 567–575. [Google Scholar] [CrossRef] [PubMed]
  370. Joglekar-Javadekar, M.; Van Laere, S.; Bourne, M.; Moalwi, M.; Finetti, P.; Vermeulen, P.B.; Birnbaum, D.; Dirix, L.Y.; Ueno, N.; Carter, M. Characterization and targeting of platelet-derived growth factor receptor alpha (PDGFRA) in inflammatory breast cancer (IBC). Neoplasia 2017, 19, 564–573. [Google Scholar] [CrossRef] [PubMed]
  371. Altaba, A.R. Hedgehog signaling and the Gli code in stem cells, cancer, and metastases. Sci. Signal. 2011, 4, pt9. [Google Scholar]
  372. Yu, S.; Ping, Y.; Yi, L.; Zhou, Z.; Chen, J.; Yao, X.; Gao, L.; Wang, J.M.; Bian, X. Isolation and characterization of cancer stem cells from a human glioblastoma cell line U87. Cancer Lett. 2008, 265, 124–134. [Google Scholar] [CrossRef] [PubMed]
  373. Hyvönen, M.; Enbäck, J.; Huhtala, T.; Lammi, J.; Sihto, H.; Weisell, J.; Joensuu, H.; Rosenthal-Aizman, K.; El-Andaloussi, S.; Langel, U. Novel target for peptide-based imaging and treatment of brain tumors. Mol. Cancer Ther. 2014, 13, 996–1007. [Google Scholar] [CrossRef] [PubMed]
  374. Sailor, M.J.; Park, J. Hybrid nanoparticles for detection and treatment of cancer. Adv. Mater. 2012, 24, 3779–3802. [Google Scholar] [CrossRef] [PubMed]
  375. Schmieder, A.H.; Caruthers, S.D.; Zhang, H.; Williams, T.A.; Robertson, J.D.; Wickline, S.A.; Lanza, G.M. Three-dimensional MR mapping of angiogenesis with α5β1 (ανβ3)-targeted theranostic nanoparticles in the MDA-MB-435 xenograft mouse model. FASEB J. 2008, 22, 4179–4189. [Google Scholar] [CrossRef] [PubMed]
  376. Jokerst, V.J.; Gambhir, S.S. Molecular imaging with theranostic nanoparticles. Acc. Chem. Res. 2011, 44, 1050–1060. [Google Scholar] [CrossRef] [PubMed]
  377. Ma, X.; Zhao, Y.; Liang, X.-J. Theranostic nanoparticles engineered for clinic and pharmaceutics. Acc. Chem. Res. 2011, 44, 1114–1122. [Google Scholar] [CrossRef] [PubMed]
  378. Yao, J.; Hsu, C.-H.; Li, Z.; Kim, T.; Hwang, L.-P.; Lin, Y.-C.; Lin, Y.-Y. Magnetic resonance nano-theranostics for glioblastoma multiforme. Curr. Pharm. Des. 2015, 21, 5256–5266. [Google Scholar] [CrossRef] [PubMed]
  379. Bhojani, M.S.; Van Dort, M.; Rehemtulla, A.; Ross, B.D. Targeted imaging and therapy of brain cancer using theranostic nanoparticles. Mol. Pharm. 2010, 7, 1921–1929. [Google Scholar] [CrossRef] [PubMed]
  380. Thomas, E.; Colombeau, L.; Gries, M.; Peterlini, T.; Mathieu, C.; Thomas, N.; Boura, C.; Frochot, C.; Vanderesse, R.; Lux, F. Ultrasmall AGuIX theranostic nanoparticles for vascular-targeted interstitial photodynamic therapy of glioblastoma. Int. J. Nanomed. 2017, 12, 7075–7088. [Google Scholar] [CrossRef] [PubMed]
  381. Mohanty, S.; Chen, Z.; Li, K.; Morais, G.R.; Klockow, J.; Yerneni, K.; Pisani, L.; Chin, F.T.; Mitra, S.; Cheshier, S. A novel theranostic strategy for MMP-14 expressing glioblastomas impacts survival. Mol. Cancer Ther. 2017. [Google Scholar] [CrossRef] [PubMed]
  382. Sun, L.; Joh, D.Y.; Al-Zaki, A.; Stangl, M.; Murty, S.; Davis, J.J.; Baumann, B.C.; Alonso-Basanta, M.; Kao, G.D.; Tsourkas, A. Theranostic application of mixed gold and superparamagnetic iron oxide nanoparticle micelles in glioblastoma multiforme. J. Biomed. Nanotechnol. 2016, 12, 347–356. [Google Scholar] [CrossRef] [PubMed]
  383. Daldrup-Link, H.E. Rethinking brain cancer therapy: Tumor enzyme activatable theranostic nanoparticles. Mol. Imaging 2017, 16. [Google Scholar] [CrossRef] [PubMed]
  384. Shevtsov, M.A.; Nikolaev, B.P.; Yakovleva, L.Y.; Dobrodumov, A.V.; Zhakhov, A.V.; Mikhrina, A.L.; Pitkin, E.; Parr, M.A.; Rolich, V.I.; Simbircev, A.S. Recombinant interleukin-1 receptor antagonist conjugated to superparamagnetic iron oxide nanoparticles for theranostic targeting of experimental glioblastoma. Neoplasia 2015, 17, 32–42. [Google Scholar] [CrossRef] [PubMed]
  385. Stephen, Z.R.; Kievit, F.M.; Veiseh, O.; Chiarelli, P.A.; Fang, C.; Wang, K.; Hatzinger, S.J.; Ellenbogen, R.G.; Silber, J.R.; Zhang, M. Redox-responsive magnetic nanoparticle for targeted convection-enhanced delivery of O 6-benzylguanine to brain tumors. ACS Nano 2014, 8, 10383–10395. [Google Scholar] [CrossRef] [PubMed]
  386. Yoo, B.; Ifediba, M.A.; Ghosh, S.; Medarova, Z.; Moore, A. Combination treatment with theranostic nanoparticles for glioblastoma sensitization to TMZ. Mol. Imaging Biol. 2014, 16, 680–689. [Google Scholar] [CrossRef] [PubMed]
  387. Mosafer, J.; Teymouri, M.; Abnous, K.; Tafaghodi, M.; Ramezani, M. Study and evaluation of nucleolin-targeted delivery of magnetic PLGA-PEG nanospheres loaded with doxorubicin to C6 glioma cells compared with low nucleolin-expressing L929 cells. Mater. Sci. Eng. C 2017, 72, 123–133. [Google Scholar] [CrossRef] [PubMed]
  388. Gholami, L.; Tafaghodi, M.; Abbasi, B.; Daroudi, M.; Kazemi Oskuee, R. Preparation of superparamagnetic iron oxide/doxorubicin loaded chitosan nanoparticles as a promising glioblastoma theranostic tool. J. Cell. Physiol. 2018. [Google Scholar] [CrossRef] [PubMed]
  389. Lu, W.; Melancon, M.P.; Xiong, C.; Huang, Q.; Elliott, A.; Song, S.; Zhang, R.; Flores, L.G.; Gelovani, J.G.; Wang, L.V. Effects of photoacoustic imaging and photothermal ablation therapy mediated by targeted hollow gold nanospheres in an orthotopic mouse xenograft model of glioma. Cancer Res. 2011, 71, 6116–6121. [Google Scholar] [CrossRef] [PubMed]
  390. Vant’s Veer, L.J.; Bernards, R. Personalized cancer medicine. In Encyclopedia of Cancer; Springer: New York, NY, USA, 2008; pp. 2291–2295. [Google Scholar]
  391. Bode, A.M.; Dong, Z. Precision oncology-the future of personalized cancer medicine? NPJ Precis. Oncol. 2017, 1. [Google Scholar] [CrossRef] [PubMed]
  392. Wistuba, I.I.; Gelovani, J.G.; Jacoby, J.J.; Davis, S.E.; Herbst, R.S. Methodological and practical challenges for personalized cancer therapies. Nat. Rev. Clin. Oncol. 2011, 8, 135. [Google Scholar] [CrossRef] [PubMed]
  393. Sau, S.; Tatiparti, K.; Alsaab, H.O.; Kashaw, S.K.; Iyer, A.K. A tumor multicomponent targeting chemoimmune drug delivery system for reprograming the tumor microenvironment and personalized cancer therapy. Drug Discov. Today 2018, 23, 1344–1356. [Google Scholar] [CrossRef] [PubMed]
  394. Weller, M.; Stupp, R.; Hegi, M.; Wick, W. Individualized targeted therapy for glioblastoma: Fact or fiction? Cancer J. 2012, 18, 40–44. [Google Scholar] [CrossRef] [PubMed]
  395. Zhu, J.-J.; Wong, E. Personalized medicine for glioblastoma: Current challenges and future opportunities. Curr. Mol. Med. 2013, 13, 358–367. [Google Scholar] [PubMed]
  396. Ene, C.I.; Holland, E.C. Personalized medicine for gliomas. Surg. Neurol. Int. 2015, 6, S89. [Google Scholar] [PubMed]
  397. Muthu, M.S.; Kulkarni, S.A.; Raju, A.; Feng, S.-S. Theranostic liposomes of TPGS coating for targeted co-delivery of docetaxel and quantum dots. Biomaterials 2012, 33, 3494–3501. [Google Scholar] [CrossRef] [PubMed]
  398. Wen, C.-J.; Sung, C.T.; Aljuffali, I.A.; Huang, Y.-J.; Fang, J.-Y. Nanocomposite liposomes containing quantum dots and anticancer drugs for bioimaging and therapeutic delivery: A comparison of cationic, PEGylated and deformable liposomes. Nanotechnology 2013, 24, 325101. [Google Scholar] [CrossRef] [PubMed]
  399. Kumar, R.; Kulkarni, A.; Nagesha, D.K.; Sridhar, S. In vitro evaluation of theranostic polymeric micelles for imaging and drug delivery in cancer. Theranostics 2012, 2, 714–722. [Google Scholar] [CrossRef] [PubMed]
  400. Guo, J.; Hong, H.; Chen, G.; Shi, S.; Nayak, T.R.; Theuer, C.P.; Barnhart, T.E.; Cai, W.; Gong, S. Theranostic unimolecular micelles based on brush-shaped amphiphilic block copolymers for tumor-targeted drug delivery and positron emission tomography imaging. ACS Appl. Mater. Interfaces 2014, 6, 21769–21779. [Google Scholar] [CrossRef] [PubMed]
  401. Kuang, Y.; Zhang, K.; Cao, Y.; Chen, X.; Wang, K.; Liu, M.; Pei, R. Hydrophobic IR-780 dye encapsulated in CRGD-conjugated solid lipid nanoparticles for NIR imaging-guided photothermal therapy. ACS Appl. Mater. Interfaces 2017, 9, 12217–12226. [Google Scholar] [CrossRef] [PubMed]
  402. Sarvagalla, S.; Hsieh, H.P.; Coumar, M.S. Therapeutic polymeric nanoparticles and the methods of making and using thereof: A patent evaluation of WO2015036792. Expert Opin. Ther. Pat. 2016, 26, 751–755. [Google Scholar] [CrossRef] [PubMed]
  403. Lee, J.; Jeong, E.J.; Lee, Y.K.; Kim, K.; Kwon, I.C.; Lee, K.Y. Optical Imaging and Gene Therapy with Neuroblastoma-Targeting Polymeric Nanoparticles for Potential Theranostic Applications. Small 2016, 12, 1201–1211. [Google Scholar] [CrossRef] [PubMed]
  404. Flores, C.Y.; Achilli, E.; Grasselli, M. Radiation-induced preparation of core/shell gold/albumin nanoparticles. Radiat. Phys. Chem. 2017, 142, 60–62. [Google Scholar] [CrossRef]
  405. Croissant, J.G.; Zhang, D.; Alsaiari, S.; Lu, J.; Deng, L.; Tamanoi, F.; AlMalik, A.M.; Zink, J.I.; Khashab, N.M. Protein-gold clusters-capped mesoporous silica nanoparticles for high drug loading, autonomous gemcitabine/doxorubicin co-delivery, and in-vivo tumor imaging. J. Control. Release 2016, 229, 183–191. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  406. Maier-Hauff, K.; Ulrich, F.; Nestler, D.; Niehoff, H.; Wust, P.; Thiesen, B.; Orawa, H.; Budach, V.; Jordan, A. Efficacy and safety of intratumoral thermotherapy using magnetic iron-oxide nanoparticles combined with external beam radiotherapy on patients with recurrent glioblastoma multiforme. J. Neurooncol. 2011, 103, 317–324. [Google Scholar] [CrossRef] [PubMed]
Pharmaceutics 10 00181 g001 550
Figure 1. Brain tumor structure and therapeutic brain delivery strategies for targeting the physiological blood–brain barrier (BBB), including transcellular lipophilic diffusion, paracellular hydrophobic diffusion, carrier mediated endocytosis, ATP-binding cassette (ABC)-transporters, adsorptive mediated transcytosis and receptor mediated endocytosis. In addition, it is represented the tumor microenvironment with tumor cells, glioma stem cells, CD4+ helper T cells, CD8+ cytotoxic T cells, fibroblasts, macrophages, growth factors, enzymes and proteins.
Figure 1. Brain tumor structure and therapeutic brain delivery strategies for targeting the physiological blood–brain barrier (BBB), including transcellular lipophilic diffusion, paracellular hydrophobic diffusion, carrier mediated endocytosis, ATP-binding cassette (ABC)-transporters, adsorptive mediated transcytosis and receptor mediated endocytosis. In addition, it is represented the tumor microenvironment with tumor cells, glioma stem cells, CD4+ helper T cells, CD8+ cytotoxic T cells, fibroblasts, macrophages, growth factors, enzymes and proteins.
Pharmaceutics 10 00181 g001
Pharmaceutics 10 00181 g002 550
Figure 2. Intracellular pathways of cell entry for charged-cell penetrating peptides (CPPs): (A) Transient toroid pore formation; (B) membrane potential; (C) adaptative translocation; (D) micropinocytosis; and (E) clathrin-mediated endocytosis and caveolae/lipid raft-mediated endocytosis.
Figure 2. Intracellular pathways of cell entry for charged-cell penetrating peptides (CPPs): (A) Transient toroid pore formation; (B) membrane potential; (C) adaptative translocation; (D) micropinocytosis; and (E) clathrin-mediated endocytosis and caveolae/lipid raft-mediated endocytosis.
Pharmaceutics 10 00181 g002
Pharmaceutics 10 00181 g003 550
Figure 3. Morphology and permeability phases of the BBTB.
Figure 3. Morphology and permeability phases of the BBTB.
Pharmaceutics 10 00181 g003
Pharmaceutics 10 00181 g004 550
Figure 4. Tumor-associated macrophages (TAMs) in tumor microenvironment: macrophages phenotypic differentiation into either M1 or M2 subtype. M2 is the subtype of TAM involved in tumorigenesis and description of receptors, chemokines, cytokines and growth factor as targeting approaches [161].
Figure 4. Tumor-associated macrophages (TAMs) in tumor microenvironment: macrophages phenotypic differentiation into either M1 or M2 subtype. M2 is the subtype of TAM involved in tumorigenesis and description of receptors, chemokines, cytokines and growth factor as targeting approaches [161].
Pharmaceutics 10 00181 g004
Pharmaceutics 10 00181 g005 550
Figure 5. Glioma stem cells (GSCs) mechanistic process, including proliferation, self-renewal, multidifferentiation and tumorigenic capability, and possible surface markers/pathways for targeting approaches [145,185,186,187,188,189,190].
Figure 5. Glioma stem cells (GSCs) mechanistic process, including proliferation, self-renewal, multidifferentiation and tumorigenic capability, and possible surface markers/pathways for targeting approaches [145,185,186,187,188,189,190].
Pharmaceutics 10 00181 g005
Pharmaceutics 10 00181 g006 550
Figure 6. Influence of the targeting approach on GSC function. The application of conventional therapies (A) lead to resistance of GSCs (B). GSCs cells, which are present in the specific perivascular niches, restart their growth process and develop tumor cells, due to their high number of surface markers, differentiation markers, and distinctive stimuli, such as cytokines, growth factors and the angiogenesis process (C). In this context, a targeting approach strategy involving the binding to the surface markers or cytokines, which are responsible for tumor growth or cytokines inhibition, may be an excellent strategy against GSCs (D), avoiding tumor recurrence (E).
Figure 6. Influence of the targeting approach on GSC function. The application of conventional therapies (A) lead to resistance of GSCs (B). GSCs cells, which are present in the specific perivascular niches, restart their growth process and develop tumor cells, due to their high number of surface markers, differentiation markers, and distinctive stimuli, such as cytokines, growth factors and the angiogenesis process (C). In this context, a targeting approach strategy involving the binding to the surface markers or cytokines, which are responsible for tumor growth or cytokines inhibition, may be an excellent strategy against GSCs (D), avoiding tumor recurrence (E).
Pharmaceutics 10 00181 g006
Pharmaceutics 10 00181 g007 550
Figure 7. Strategies to enhance the permeability of the blood–brain barrier for treatment of GB.
Figure 7. Strategies to enhance the permeability of the blood–brain barrier for treatment of GB.
Pharmaceutics 10 00181 g007
Pharmaceutics 10 00181 g008 550
Figure 8. Schematic representation of core–shell nanostructures and possible modifications (Reprinted from [260] with permission from Elsevier, 2018).
Figure 8. Schematic representation of core–shell nanostructures and possible modifications (Reprinted from [260] with permission from Elsevier, 2018).
Pharmaceutics 10 00181 g008
Pharmaceutics 10 00181 sch001 550
Scheme 1. The main goal of the use of theranostic NPs.
Scheme 1. The main goal of the use of theranostic NPs.
Pharmaceutics 10 00181 sch001
Pharmaceutics 10 00181 g009 550
Figure 9. Two prototypes of theranostic nanoparticles, combining lipid nanoparticles and gold nanoparticles, with characteristics such as small size (<100 nm), active targeting (tumor targeting and cell penetrating peptides) and a stimuli-responsive targeting (pH or temperature): (A) AuNPs attached on the NPs surface by electrostatic interaction; and (B) AuNPs with lipophilic characteristics encapsulated in NPs.
Figure 9. Two prototypes of theranostic nanoparticles, combining lipid nanoparticles and gold nanoparticles, with characteristics such as small size (<100 nm), active targeting (tumor targeting and cell penetrating peptides) and a stimuli-responsive targeting (pH or temperature): (A) AuNPs attached on the NPs surface by electrostatic interaction; and (B) AuNPs with lipophilic characteristics encapsulated in NPs.
Pharmaceutics 10 00181 g009
Pharmaceutics 10 00181 sch002 550
Scheme 2. Personalized medicine strategy considering the use of theranostic nanoparticles.
Scheme 2. Personalized medicine strategy considering the use of theranostic nanoparticles.
Pharmaceutics 10 00181 sch002
Table
Table 1. Current glioblastoma (GB) treatments: limitations and advantages.
Table 1. Current glioblastoma (GB) treatments: limitations and advantages.
Current TreatmentsProsConsReferences
Surgical resectionSignificant increase in survival rate.
Possibility to apply radio-and chemotherapy, in order to remove residual tumor cells.		Damage of the surrounding cortex or brainstem structures, due to the diffuse nature of the tumor and inability to remove it.[5]
RadiotherapyMost frequent treatment.Tumor response depends on its size.
Acute side effects, such as damage of the epithelial surface, mouth, throat, gastrointestinal ulcers, swelling and infertility.
Late effects, including fibrosis, hair loss, lymphedema and heart diseases.
Effect only on the periphery of the tumor, with the core still being able to proliferate.		[6]
ChemotherapyCytotoxic and cytostatic agents act in tumor cells death through multiple mechanisms: angiogenesis, pro-differentiation, growth factor pathways and inhibition of tumor invasion. (e.g., temozolomide)Several side effects including nerve damage, nausea, hair loss, vomiting, infertility, diarrhea, insomnia and skin rash.
Effect only on the periphery of the tumor, with the core still being able to proliferate.		[6]
HyperthermiaTumor cell eradication based on generation of heat at the target site. It induces physiological changes, which lead to their apoptosis.
Temperature ranges from 41 °C to 46 °C, activating many intracellular and extracellular degradation mechanisms.		Late effects including problems associated with heart, blood vessels, and other major organs.[6,7]
ImmunotherapyPromotion of an enhanced anti-tumor immune response with an adequate antigen presentation, and circumvention of immunosuppressive mechanisms.
Immunotherapy may include:T-Cell based vaccine therapies:
EGFRvIII vaccine, heat-shock protein (HSP) vaccine, dendritic cell (DC) vaccines, adoptive T-cell therapy.
Immune Checkpoint Inhibition: Anti-PD1, anti-CTLA4.
Adoptive T-Cell Therapy: chimeric antigen receptors (CARs) targeting proteins (IL-13 receptor, Her2, EphA2, and EGFRvIII.		Low response rates: only a relatively reduced fraction of patients obtain clinical benefit.
Potential increase in the magnitude, frequency, and onset of side effects.
Severe immunological reactions, including a systemic cytokine release syndrome (“cytokine storm”), cause a delayed and/or inappropriate response, and may contribute to tissue damage.		[6,8,9,10,11,12,13]
Gene TherapyDirect inhibition of the expression of oncogenes and normalization of tumor suppressor gene expression.
Gene therapy include:
Suicide genes: HSV-TK, CDA, carboxypeptidase G2 and CYP450.
Immunomodulatory genes: IFN-beta, IL-4, -12, -18, -23.
Oncolytic virotherapy: Herpes simplex virus, CR adenovirus, measles virus.Tumor-suppressor genes: p53, p16, p27 and PTEN.		Deficiency of antigen presenting cells inside the brain.
Inefficient distribution, resulting in a poor delivery of a gene to the tumor cells.		[14,15,16,17]
Table
Table 2. Specific transporters expressed on BBB.
Table 2. Specific transporters expressed on BBB.
Type of TransportExample LigandsBiological SignificanceReference
Glucose receptors (GLUT)Mannose; GlucoseGLT1 targeting occurs when the NPs are coated with mannose[47,48]
Monocarboxylate transporter (MCT)Lactate; Short-chain fatty acids; Biotin; Salicylic acid; Valproic acid; Phenylbutyrate; 3,5,3’-triiodo-l-thyronineMCT inhibitors: MCT1 and MCT2 would play a role in tumor maintenance; MCT4 would increase tumor aggressiveness[49]
Neutral amino acids transporter (NAAT)Tyrosine; Thyroid hormones (e.g., triiodothyronine); Asparagine; Histidine; Isoleucine; Leucine; Methionine; Phenylalanine; Threonine; TryptophanTransportation of neutral amino acids and some drugs, such as L-dopa and anticonvulsant gabapentin[50,51,52,53]
Cationic amino acids transporter (CAATs)Arginine; Lysine[43]
Anionic amino acids transporters (AAATs)l-glutamate; l-aspartate [44,54]
ßeta amino acid transporter (ßAATs)Beta (β)-alanine[44]
Choline transporter (ChT)Choline; ThiamineSupport of the neurological supplies of brain[45,46]
Peptide transporters (PT)Oligopeptide transporters (e.g., PepT1, PepT2);
Polypeptide transport system (e.g., Oatp2, OAT-K1, OATP)		Covalently linked to a vehicle: chlorotoxin-based strategies
Fatty acid transporters (FAT)Fatty acidsGlioma cells use fatty acids as a substrate for energy production.
Targeting lipid metabolism is a promising approach in treating malignant gliomas
Energetic role: stimulate numerous neural functions, or performing potential pharmacological targeting		[55,56,57,58]
Nucleoside transporters (NTs)Nucleoside transporters (ENT1, ENT2, ENT3, and ENT4);
Concentration nucleoside transporters (CNT2)		NTs act as second messengers in many signal transduction pathways, in maintaining the homeostasis of the nucleosides within the CNS, such as adenosine, to keep it available to bind to receptors
Important for recycling pathways for nucleosides transportation into CNS tissue that brain cannot synthesize		[59]
Table
Table 3. Cell penetrating peptides described in the literature for the application on glioblastoma treatment.
Table 3. Cell penetrating peptides described in the literature for the application on glioblastoma treatment.
CPPsSequenceMechanism of ActionType of InteractionTTPReferences
Transactivating-transduction (TAT)AYGRKKRRQRRREndocytosis Micropinocytosis
Pore formation		RGD[106,107,108,109]
R8 (cell penetrating peptide octa-arginine)RRRRRRRRAffinity to neuropilin-1 (NRP-1)RGD[110]
IL-13p (Interleukin 13 peptide)TAMRAVDKLLLHLKKLFREGQFNRNFESIIICRDRTAffinity to IL13Rα2 receptor[111]
LIMK2 NoLS (nucleolar translocation signal (NoLS) sequence of the LIM Kinase 2 (LIMK2))KKRT LRKN DRKK RC[112,113]
Leptin30C-terminal (YQQVLTSLPSQNVLQIANDLENLRDLLHLLC)transcytosis across the BBBmediated endocytosis pathway.[114]
peptide1-NS∆TCTWLKYH(unknown)[100]
D(KLAKLAK)2Disruption of the mitochondria membrane NGR
CGKRK		[115]
pVecLLIILRRRIRKQAHAHSK-NH2non-endocytic pathwaygHoPe2[104]
PenetratinCKRRMKWKKDirect penetration, endocytosis[116,117]
NFL-TBSDirect penetration, endocytosis[118]
SynB1
SynB3		RGGRLSYSRRRFSTSTGR RRLSYSRRRFDirect penetration, endocytosisConjugated with elastin-like polypeptide[101,119]
Transportan 10
(TP10)		AGYLLGKINLKALAALAKKILMembrane Potential-[120]
D-Maurocalcine
(D-MCa)		Cys3−Cys17, Cys10−Cys21, and Cys16−Cys32
(Positive-charge)		Membrane Potential-[121]
DK17DRQIKIWFQNRRMKWKK-NH2Membrane Potential-[122]
CB5005KLKLALALALAVQRKRQKLMPMembrane Potentialblocking agent of the NF-kB pathway-[123]
ACPR8-EEEEEEEE (E8) Membrane Potential (R8)MMP-responsive (E8)Angiopep-2[124]
GPLGVRGDGMMP-responsive RGD[125]
polyarginine peptides(NH2-RRRRGRRRRKGC)MMP-responsive[126]
(CKRRMKNvocWKNvo0cKNvoc)Derived from CKRRMKWKKcellular uptake after rapidly cleaving the photolabile-protective group.photo-responsiveness[98]
LNPKKRT LRKN DRKK RCnucleolar translocation signalpH-responsive [112]
H7K(R2)2RRK(HHHHHHH)RRcross cell membranes in a seemingly energy-independent mannerpH-responsive [127,128]
TH(AGYLLGHINLHHLAHL(Aib)HHIL-NH2histidine-rich TH peptide pH-responsiveRGD[102,129,130]
R6H4RRRRRRHHHHClathrin-mediated Caveolae/lipid raft-mediatedpH-responsive HA[131]
Table
Table 4. Description of the morphology and permeability phases of the blood–brain–tumor barrier (BBTB).
Table 4. Description of the morphology and permeability phases of the blood–brain–tumor barrier (BBTB).
GB Phases Morphology BBTBPermeability BBTB
First phaseInitial phase of malignant brain tumorsBrain capillaries provide enough nutrients for their growth.
The capillaries are continuous and non-fenestrated.		BBTB integrity is not compromised
Second phaseProgression of the tumorCancer cells invade neighboring healthy cerebral tissues.
High metabolic demands.
Tumor volume increase.
New capillaries have fenestrations (12 nm)		BBTB integrity is compromised, increasing the permeability and the molecules with size below 12 nm may pass through.
Third phaseTumor growthInter-endothelial gaps are formed between cerebral endothelial cells
Fenestration size increase from 48 nm to 1 µm.		BBTB damage and enhanced permeability and retention (EPR) effect favors NPs accumulation in the tumor tissues.
Table
Table 5. List of actively targeted nanoparticles (NPs) to surface cell markers, signaling pathways and tumor microenvironment directed essentially at GB treatment.
Table 5. List of actively targeted nanoparticles (NPs) to surface cell markers, signaling pathways and tumor microenvironment directed essentially at GB treatment.
TargetingMoleculesReferences
BBB
Ecs; P32; Neuropin (NRP-1/2); Aminopeptidase N (CD13)Wheat germ agglutinin (WGA), Folic acid (FA), CVNHPAFACGYGHTMYYHHYQHHL-NH2, TNG; (TGNYKALHPHNG); LyP-1 (CGNKRTRGC); iNGR (CRNGRGPDC), L-peptide A7R (termed LA7R); NGR[285,286,287,288,289,290,291,292]
Glucose receptors (GLUT)2-deoxy-D-glucose; Mannose[293,294]
Transferrin receptor (Tfr)T7 (HAIYPRH); Angiopep-2; Transferrin (Tfpep); Melanotransferrin (MT); OX26 and RI7217[64,65,66,251,295,296,297,298]
Low density lipoprotein receptor (LDLR)Polypeptide LHRH-ELP-C8; Trichosanthin (TCS); Angiopep-2 (TFFYGGSRGKRNNFKTEEY); Lactoferrin (Lf); apolipoprotein E (ApoE); Polysorbate 80; polyoxyethylene sorbitol oleate (PSO)[73,74,75,76,77,78,79,124,285,298,299,300]
Insulin receptor (IR)Cixutumumab; GL56; 83-14 Mab; 29B4 Mab[79,80,301,302]
ABC (ATP-binding cassette)d-Alpha-tocopheryl polyethylene glycol 1000 succinate (TPGS); Polysorbate 80; Polyoxyethylene sorbitol oleate (PSO)[77,78,79,80,299,303,304,305]
TME
Hypoxic responseHIF-1α inhibitor; EZN-2968; Hsp90; CAIX inhibitor; LyP-1 (CGNKRTRGC)[181,306,307]
Acid pHTH peptide (AGYLLGHINLHHLAHL [Aib]HHIL-NH2); pHLIP (ACEQNPIYWARYADWLFTTPLLLLDLALLVDADET); R6H4; H7K(R2)2; LNP[96,102,112,127,128,129,130,131,279]
Enzymatic alterationsR9; TAT; LMWP; ACP; GPLGVRGDG; polyarginine peptides [124,125,126,280,281,282]
TemperatureL-zipper peptide; (VSSLESKVSSLESKVSKLESKKSKLESKVSKLESKVSSLESK); ELP (VPGXG)[308,309,310]
BBTB
IntegrinsRGD; c(RGDyK); NGR[146,150,286,311,312,313,314,315,316,317,318,319]
13 receptorα2 (IL-13Rα2)Pep-1 (CGEMGWVRC)[320,321]
EGFRCetuximab; Inhibitor of COX-2 (e.g., Celecoxib); 125I-mab 425; PKI166; Canertinib; Pelitinib Monoclonal antibody C225; D(KLAKLAK)2; Epidermal growth factor (egfpep)[251,322,323,324,325]
EGFR variant III mutant (EGFRVII)F25P preproinsulin; CAR-engineered NK cell lines such as NK-92; Rindopepimut; D2C7-IT; PEPvIII (H-Leu-Glu-Glu-Lys-Lys-Gln-Asn-Tyr-Val-Val-Thr-Asp-His-Cys-OH)[326,327,328,329]
VEGF-1, -2Vatalanib; Bevacizumab; Tivozanib; L-peptide A7R (termed LA7R); K237 (HTMYYHHYQHHL-NH2)[287,330,331,332]
ECM
Matrix metalloproteinases (MMPs)inhibitor of matrix protease-3 (TIMP-3); histone deacetylase inhibitors; Chlorotoxin; LMWP[253,333,334,335,336]
Fibrincysteineearginineeglutamic acidelysineealanine (CREKA)[337,338]
Tenascin-CFHK (FHKHKSPALSPV)[143,339]
Angiopoietin 2MEDI3617; AMG780; Nesvacumab (REGN910); CVX-060[332,340]
Cox-2COX-2 inhibitors: celecoxib; Alantolactone; Plumbagin[341,342,343]
NF-kBBaicalein (BA); DYT-40; SN50; Natural compounds: Curcumin, Resveratrol, 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO); Non-steroidal anti-inflammatory drugs: Irinotecan and celecoxib; Sulfasalazine, Disulfiram, Glutathione; Antibodies (bortezomib, lactacystin, and MG132)[153,189,344,345,346,347]
TAMS
Cxcl12/cxcr4Plenrixafor (DY-[NMe]DOrn-R-2Nal-G); Peptide R (RACRFFC); NT21MP (LGASWHRPDKCCLGYQKRPLP); Nef-M1 (NAACAWLEAQ)[167,348,349,350]
Nrp-1/2LyP-1 (CGNKRTRGC); TT1 (CKRGARSTC); Plumbagin[351]
Multi-ligand endocytic receptor mannose receptor (CD206/MRC1)CSPGAKVRC[352]
Colony stimulating factor 1 (CSF1)Emactuzumab (RG7155); AMG820; IMC-CS4 (LY3022855); PLX7486[353]
CD11b+ F4/80high M2-like tamsM2pep (YEQDPWGVKWWY)[354,355]
CSF-1rRG7155[164]
Tumor fibroblasts
Fibroblast growth factor (FGF)brivanib, nindetanib, cediranib, lenvatinib, sulfatinib, dovitinib, ponatinib and lucitanib; SSR12819E; C2KG2R9[356,357,358,359]
Glioma Stem Cells, Invasion and Metastasis
VEGFRD16F7[360]
CD44HA; Peptide 7 (FNLPLPSRPLLR)[154,361]
CD133GL1 (LLADTTHHRPWT); CBP4[193,362]
PI3k/Akt/mTorPP242, P30 and NVP-BEZ235; Temsirolimus; Sirolimus; Everolimus; XL765 (SAR245409)[363,364]
Transforming growth factor-beta (TGF-β)AP-12009; SD-208, SB-431542; PDX; LY2109761 and LY364947 (HTS466284)[365,366,367]
Platelet-derived growth factor (PDGF)MEDI-575; Tandutinib (MLN518); Crenolanib (CP-868-596)[368,369,370]
HedgehogGL1 peptide (LLADTTHHRPWT); CVNHPAFAC-NH2; CK (CVNHPAFAC-HTMYYHHYQHHL)[287,371,372]
Mammary-derived growth inhibitor (MDGI)CooP (CGLSGLGVA)[373]

Share and Cite

MDPI and ACS Style

Mendes, M.; Sousa, J.J.; Pais, A.; Vitorino, C. Targeted Theranostic Nanoparticles for Brain Tumor Treatment. Pharmaceutics 2018, 10, 181. https://doi.org/10.3390/pharmaceutics10040181

AMA Style

Mendes M, Sousa JJ, Pais A, Vitorino C. Targeted Theranostic Nanoparticles for Brain Tumor Treatment. Pharmaceutics. 2018; 10(4):181. https://doi.org/10.3390/pharmaceutics10040181

Chicago/Turabian Style

Mendes, Maria, João José Sousa, Alberto Pais, and Carla Vitorino. 2018. "Targeted Theranostic Nanoparticles for Brain Tumor Treatment" Pharmaceutics 10, no. 4: 181. https://doi.org/10.3390/pharmaceutics10040181

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop