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Review

Enhancing Skin Cancer Immunotheranostics and Precision Medicine through Functionalized Nanomodulators and Nanosensors: Recent Development and Prospects

Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Aljouf 72388, Saudi Arabia
Int. J. Mol. Sci. 2023, 24(4), 3493; https://doi.org/10.3390/ijms24043493
Submission received: 31 December 2022 / Revised: 23 January 2023 / Accepted: 27 January 2023 / Published: 9 February 2023
(This article belongs to the Special Issue Immunomodulation of Skin Cancer)

Abstract

:
Skin cancers, especially melanomas, present a formidable diagnostic and therapeutic challenge to the scientific community. Currently, the incidence of melanomas shows a high increase worldwide. Traditional therapeutics are limited to stalling or reversing malignant proliferation, increased metastasis, or rapid recurrence. Nonetheless, the advent of immunotherapy has led to a paradigm shift in treating skin cancers. Many state-of-art immunotherapeutic techniques, namely, active vaccination, chimeric antigen receptors, adoptive T-cell transfer, and immune checkpoint blockers, have achieved a considerable increase in survival rates. Despite its promising outcomes, current immunotherapy is still limited in its efficacy. Newer modalities are now being explored, and significant progress is made by integrating cancer immunotherapy with modular nanotechnology platforms to enhance its therapeutic efficacy and diagnostics. Research on targeting skin cancers with nanomaterial-based techniques has been much more recent than other cancers. Current investigations using nanomaterial-mediated targeting of nonmelanoma and melanoma cancers are directed at augmenting drug delivery and immunomodulation of skin cancers to induce a robust anticancer response and minimize toxic effects. Many novel nanomaterial formulations are being discovered, and clinical trials are underway to explore their efficacy in targeting skin cancers through functionalization or drug encapsulation. The focus of this review rivets on theranostic nanomaterials that can modulate immune mechanisms toward protective, therapeutic, or diagnostic approaches for skin cancers. The recent breakthroughs in nanomaterial-based immunotherapeutic modulation of skin cancer types and diagnostic potentials in personalized immunotherapies are discussed.

1. Introduction

The global burden of skin cancer has increased tremendously over the past decades, reaching an epidemic proportion in many regions of the western world [1,2]. It has profoundly impacted public health, impeding socio-economic development in several countries. Skin cancer is primarily presented in keratinocyte carcinoma (nonmelanoma) and malignant melanoma. Keratinocyte carcinoma is further classified as basal cell carcinoma (BCC) or cutaneous squamous cell carcinoma (CSCC). BCC, accounting for 80% of skin cancers, is the least aggressive of all skin cancers and is usually not fatal. CSCCs are limited to the upper and middle layers of the skin and account for 20% of the cases. Though not a life-threatening condition, it can turn aggressive and spread to other parts of the skin if not treated at an early stage. Squamous and basal cell carcinomas are primarily associated with excessive sun or ultraviolet (UV) light exposure. Contrarily, melanomas represent a more heterogeneous and complex cancer type, spanning both benign and malignant cancerous transformations. As a result of its ability to infiltrate various cell types, melanomas are associated with diverse clinical outcomes representing the major cause of mortality due to skin cancers. Melanoma skin cancer (MSC) is developed by uncontrolled proliferation and invasive spreading of abnormal melanocytes. Melanomas are predominantly pigmented, but a small percentage of cutaneous melanomas are amelanotic [3,4], which poses difficulty in its early diagnosis, leading to a delayed therapeutic intervention [5,6]. Melanomas represent the fastest-increasing cancer globally, with an annual increase of 3–8% in the incidence among the European population [1]. Key etiological factors for melanoma include UV and ionizing radiations and chemical carcinogens.
Genetic predisposition with familial germline CDKN2A mutations or sporadic mutations in MAPK pathways is observed in many clinical cases of melanoma [7,8]. BRAF and nRAS mutations are associated with cutaneous melanomas, whereas GNAQ and GNA11 mutations are more common in uveal melanomas [9]. The KIT mutations are predominantly associated with mucosal and acral melanomas [10]. Immunologically distinct expression of programmed cell death protein 1 ligand 1 (PDL1) and programmed cell death protein 1 ligand 2 (PDL2) is observed in various melanoma cells [11]. Immune checkpoints modulation and alteration in the PI3K-AKT-PTEN pathway play an important role in its development and progression [12]. Even with the progress of therapeutic intervention methodologies, melanomas remain the most aggressive skin cancer, with an index of 15–20% five-year survival rate (Cancer statistics, 2019). Presently newer prospects have been explored by the research community to overcome the bottleneck encountered in the theranostics and imaging of skin cancer through the use of functionalized nanomaterials such as liposomes, carbon-based, metal-based, dendrimers, cubosomes, lipid-based, polymer-based, micelles, virus-based, exosomes, and cell membrane-coated nanomaterials [13].

2. Immune Mechanisms in Skin Cancers

Immune cells and immune organs protect the overall integrity of the human system through a sophisticated interplay between maintaining tolerance for self-antigens and mounting a robust immune response to eliminate foreign antigens. The two axes of immunity, innate and adaptive immune mechanisms, consolidate the final effect of an immune response. Macrophages, dendritic cells (DC), and natural killer cells (NK) maintain the first line of defense against non-self-antigens, manifested as inflammation. The innate immune response is followed by an intricate network of specific adaptive immune mechanisms levitating the elimination of non-self.
The cancer microenvironment is a non-self component of the body enriched in innate and adaptive immune cells, specifically tumor-infiltrating lymphocytes (TIL) and tumor-associated macrophages (TAM). The cellular composition of the tumor microenvironment (TME) significantly impacts tumor initiation and progression, exerting either an anti-tumor or pro-tumor effect [14]. In all types of skin cancers, infiltration of TAM and regulatory T-cells (Tregs) is observed [15]. Both cell types distinctly induce immunosuppression, thereby promoting tumorigenesis. In nonmelanoma cancers, the tumor microenvironment is specifically enriched in genetically diverse fibroblasts that increase the heterogeneity of tumor-associated antigenic repertoire [16]. Melanomas are infiltrated by macrophage migration inhibitory factors, T-regs, myeloid-derived suppressor cells (MDSCs), and natural killer (NK) cells [17,18]. Nonmelanoma cancers exhibit a strong link with immunosuppressive human microenvironments, which sometimes show regression upon improvement in immune surveillance [19].
Cancer growth and proliferation are maintained by a dynamic process of three phases (elimination, equilibrium, and escape (E3), representing the immune editing mechanism) [20]. The response of the immune system to tumor growth is represented by immunoediting, a dynamic process consisting of three distinct phases: elimination, equilibrium, and escape of the cancer cells (Figure 1). Effective host innate and adaptive immune surveillance can trace and destroy tumor cells during the elimination phase. Some immune-resistant variants that emerge in the tumor microenvironment can partially evade the innate and adaptive response and progress to equilibrium. The immune effectors cannot eliminate these variants but render them dormant. The stand-off between the host immunity and tumor cells can sometimes lead to evasion of the immune control, enabling tumor cell variants to proliferate unrestricted, establishing a full-fledged tumor or proliferating cancer (Figure 1).
Dendritic cells (DC) are the major players in counteracting immunosuppressive melanoma and nonmelanoma cancers. Through a functional intersection of cytotoxic T-cell and immune checkpoint receptors, DC can skew the immunosuppressive tumor microenvironment involving endothelial cells, TAM, T-regs, MDSCs, and NK cells toward immune infiltration and immune responsiveness [14]. This disrupts the tolerogenic nature of the tumor microenvironment, potentiating the elimination of the tumor. DC also interacts with Toll-like receptors, ligand-inducing type-1 interferon (IFN), and several proinflammatory cytokines and chemokines. TLR ligation promotes DC maturation, enhancing their antigen presentation potential. Effective antigen presentation of immature T-cells is the hallmark for optimal activation of adaptive immunity and hence tumor regression.
In addition, the DC interaction with TLR ligands induces the production of type-I IFNs and other proinflammatory cytokines within the TME [21]. This interplay also promotes DC maturation and enhances antigen presentation ability to naïve T-cells, thus effectively activating adaptive immunity [20]. A notable feature of effective immune filtration to curtail tumor proliferation is the optimal density, composition, and distribution of cytotoxic T-cells in the stroma, facilitating tumor regression and enhancing the therapeutic efficacy of the drugs and vaccines [22].

3. Classical Diagnostic and Treatment Modalities for Skin Cancers

Accurate skin cancer diagnosis remains critical to deciding a successful line of therapy. Classical diagnostic procedures include invasive and noninvasive methods [23]. Both methods encounter complexities and challenges of under or over-diagnosis, and identifying the right cancer type requires considering alternative modalities. Diagnostic approaches for nonmelanoma cancers (BCC and CSCC) usually require a skin biopsy and histopathologic examination to observe the tissue for any cancerous growth [24].

3.1. Skin Biopsy

Skin biopsy is also a therapeutic approach for nonmelanoma cancers if the entire tissue needs to be removed. There are many types of skin biopsies, such as shave (tangential) biopsy, punch biopsy, and excisional and incisional biopsies [25]. Shave biopsy is suitable for monitoring the top layers of the skin, punch biopsy extracts deeper skin layers, excisional biopsy removes the entire area of the tumor and, incisional biopsy extracts a small portion of the tumor. Since BCC and CSCC commonly do not spread beyond the skin tissue, alternative or additional diagnoses are usually not considered; however, if a spread is suspected, a lymph node biopsy is carried out to confirm through fine needle aspiration (FNA). Small fragments of lymph nodes are removed and microscopically analyzed.

3.2. Noninvasive Techniques

Many noninvasive techniques are now used to detect skin cancers with high accuracy. These techniques include dermoscopy, reflectance confocal microscopy, optical coherence microscopy photography, spectroscopy, thermography, multispectral imaging, electrical bio-impedance, and computer-aided techniques [26,27].
Dermoscopy: The commonly used dermoscopic techniques enable the identification of specific features of skin lesions. It supplements biopsy techniques by providing a complete assessment of the skin lesion to identify the most suitable biopsy sampling site. Melanoma and nonmelanomas are discreetly identified based on specific dermoscopic patterns in the lesions [28,29,30,31]. Though an effective noninvasive diagnostic tool, dermoscopy can only be applied to the upper dermis [27].
Reflectance confocal microscopy: Reflectance confocal microscopy (RCM) is a comparatively new technique for assessing and diagnosing skin cancers. The method harnesses the high reflective qualities of keratin and melanin in the skin tissue. Through the infrared light source, RCM facilitates the visualization of deeper layers of the skin and hence is considered an optical biopsy. Nonetheless, accurate diagnosis through RCM necessitates technical proficiency [32,33].
Optical coherence tomography: Optical coherence tomography (OCT) is another technique to assess skin tumors. Low-power infrared laser light captures real-time images up to 2 mm underneath the skin surface [34]. The technique requires no pretreatment. Thus far, the technique has been used to diagnose basal cell carcinomas; however, the diagnostic accuracy of malignant melanomas has been minimal [35].
Photodynamic Visualization and Therapy: Photodynamic visualization (PDV) is a noninvasive fluorescent laser-based mechanism for monitoring skin cancers. A photosensitizer is targeted at the cancer site and visualized using a fluorescent light source. Conventional methods use 5-aminolevulinic acid in a gel form applied to the skin, which is converted to colored protoporphyrin IX (Pp-IX) in the cells [36]. The photoreactive and physical features of Pp-IX facilitate its clinical use in diagnosis and therapy for skin cancers. Other molecules including cysteine cathepsin proteases and adjuvants such as Vit D are also used as selective fluorescence probes and adjuvants [37,38]. PDV is useful in assessing nonmelanomas; however, identifying melanomas through PDV has provided variable results. Currently, many photosensitizers are developed as nanoparticle formulations or as chemicals. The development of new photosensitizers, porphylipoprotein and talaporphyrin sodium, metal complex base, aggregation-induced emission, and doped carbon dot-based photosensitizers have received considerable attention in cancer treatment [39,40,41,42]. The use of nanoparticle-based PDV has enhanced the rate of detection of nonmelanoma and melanoma skin cancers with promising therapeutic potential [43,44]. Photosensitizers are also employed as a therapeutic mechanism against skin cancers. Photodynamic therapy uses specific photosensitizers that are first targeted to the tumor tissue. Subsequently, fluorescence activation of photosensitizers converts them into cytotoxic reactive oxygen species (ROS) to induce targeted cancer cell death. Technical caveats, such as lack of effective targeting and availability of enhanced and safe photosensitizers, have impeded the use of PDT in cancer cell therapeutics. However, the recent incorporation of nanomaterials for skin theranostics has successfully overcome many technical and therapeutic bottlenecks [45].
Immunodiagnostics and Immunotherapy: Immunodiagnosis of skin cancers has been tested since the 1970s with encouraging results in staging and clinical management of the disease [46,47]. Tumor-specific antigens are identified within the tumor microenvironment through specific monoclonal antibodies. Nonetheless, the expression of antigens within the tumor site and across different patients has shown variation in antigen expression [47]. Hence, proper diagnosis using antibodies requires screening for more than one tumor-specific antigen [48]. Furthermore, diagnostic modalities such as radioactivity have limited the use of immunodiagnosis as a common diagnostic method for skin cancer. Currently, combinational approaches are being studied to maximize the diagnostic potential of immunological diagnostic techniques. Immunobiological loaded microneedle devices are used as diagnostic and therapeutic modalities [49,50]. These microneedles deliver the loaded drug/antibodies in deeper layers of the skin, which are released near tumor cells as a means of tumor detection [50]. Microneedle devices can also synergize with other therapeutic and diagnostic interventions, such as photothermal or photodynamic visualization, for enhanced results [51].
The immunotherapeutic treatment method depends upon the modulation of the host immune mechanism to induce regulatory, stimulatory, or suppressive responses toward the tumor. The host anti-tumor responses are activated through innate immune mechanisms that increase the number of immune effectors or subdue the suppressive tumor microenvironment [52]. Strategies to modulate immune response include immunomodulatory molecules, monoclonal antibodies, therapeutic vaccines, small immunomodulatory molecules, etc. [53]. These molecules facilitate antigen uptake, optimal processing, and presentation to naive T-cells, activating and expanding the repertoire to naïve T-cells. Finally, an intense effector response is launched against cancer cells. Though an effective strategy observed in patients, immune activation can sometimes reach abnormally high levels, risking adverse immune effects. Furthermore, poor therapeutic targeting and insufficient understanding of the immunological skew within the TME have limited immunotherapy for many cancers. Additionally, advanced delivery systems for site-specific targeting of immunotherapeutic agents are needed [52]. Skin cancer immunotherapy as a treatment modality has been much more recent compared to other cancers. It has evolved with the improvement in understanding the immunologic features of nonmelanoma and melanoma cancers. This treatment method for skin cancers has been a paradigm for cancer immunotherapeutics, especially due to their T-cell immunogenicity. Immunotherapy for skin cancers has shown higher success rates than other cancers. Therapy using anti-PD-1 (anti-programmed-death 1) for melanomas, BCC, CSCC, and Kaposi’s sarcoma has shown a 40% response rate [54,55]. Cytokine therapy using Type-1 interferon and interleukin has been tested, but high toxicity and low response rates limited its use in mainstream therapeutics [56,57,58].

4. Nanomaterials in Diagnosis and Immunotherapy of Skin Cancers

Nanomaterials are versatile small molecules with at least one dimension ranging in size from 100 nm. Nanoparticles harbor an inherent capacity to interact with the effectors of immune response and can modify their functions to cause immunostimulation or immunosuppression [59,60]. Depending upon the type and progress of the disease, the response can be either harmful or beneficial. The structure of nanomaterials, such as size, composition, surface chemistry, and molecular interactions with the target cell, propels useful or toxic immunomodulation [61,62]. As a consequence of interaction with cellular components, unanticipated reactions such as hypersensitivity or inflammation may also result [63]. Ensuring an effective and safe clinical result necessities a thorough understanding of the structure-function chemistry of nanoparticles at a cellular interface. Nanoparticles can incorporate many functional components, demonstrate spatiotemporal regulation [64,65,66], and facilitate the topical delivery of drugs, vaccines, and therapeutic and diagnostic material. With enhanced theranostic potential and minimal toxicity, topical delivery has been sought after, especially in skin diseases and cancers. Currently, nanosystems are extensively investigated for their potential to improve or modulate immune responses against cancer, imparting cancer protection or preventing recurrence. Though only a few nanomodulators have been tested on different skin cancers, a sudden thrust is observed in nanomaterial-based theranostic studies against skin cancers.
Recently, computational approaches, such as Box Behnken and Central Composite Design, have been integrated into simulating the molecular dynamics, assessing resilience and interaction of nanoparticles with the cellular microenvironment [67,68,69]. This has expanded the repertoire of nanomaterials and nanosystems to be tested for cancers. This design of experimental methodology enables in silico assessment of area-to-volume ratio, optimal drug loading and controlled release, tensile strength, in vivo safety and stability, etc., of the nanomaterial. Computational designs have introduced a breakthrough in developing nanoparticle-based next-generation interventions such as drugs and vaccine targeting, immunomodulation, and drug discovery, reducing the bench-to-bedside gap [70,71].
Nanoparticles demonstrate an exclusively enhanced permeability and retention (EPR) effect in addition to substantially reduced cytotoxicity and property of functionalization. Nanosystem-based skin cancer therapeutic approaches span carcinoma targeting nanoparticles, specific cancer cells targeting functionalized nanomaterials, and active targeting through receptor-mediated delivery. The repertoire of nanoparticles for skin cancer targeting is extensive, encompassing nanoshells, liposomes, ethosomes, nanostructured lipid carriers, polymeric nanoparticles, nanospheres, solid lipid nanoparticles, fullerenes, dendrimers, quantum dots, carbon nanotubes, etc. (Figure 2).
Skin cancer therapy has harnessed the potential of nanosystems with good efficacy to overcome several bottlenecks of conventional therapy and underdiagnosis in the research setting. Many types of nanomodalities have been tested for skin cancers, especially melanomas. Nanomaterials used for skin cancer therapeutic span a wide range, including liposomes, carbon nanotubes, dendrimers, metallic formulations, and protein-based nanoformulations. Currently, graphene and graphene oxide nanocomposites have demonstrated efficacy as optical and electrochemical biosensors for the detection of early stage cancers. The ultraslim dimensions and excellent electrical and thermal conductivity, and mechanical tensility make graphene nanoparticles a unique biomolecules and cellular sensing tool for early cancer detection [72,73]. Recently, local applications of drug or immune-based nanoformulations for skin cancer therapeutics have been explored with considerable success. Topical delivery is a promising alternative to generalized therapy with reduced systemic toxicity, irritation risk, and optimal permeation [74]. Furthermore, drug resistance in cancers can pose therapeutic ineffectiveness, and hence various drugs and dosages need to be tested in nanoparticles. It is evident that currently, nanotheranostics in skin cancers is at its initial stage demanding animal and clinical evaluations before translating into clinical use.

5. Nanomodulation of Mitochondrial Function as Immunotherapy against Skin Cancers

Similar to other cancers, the initiation and progression of skin cancer are also modulated by mitochondria-driven energy metabolism [75]. Mitochondrial regulation of TME and the development of metabolic heterogeneity substantiates cancer cell proliferation and immune evasion [76]. Cancer cells circumvent cellular apoptosis and maintain a high biosynthetic and bioenergetics potential, carefully regulated by mitochondria. Owing to the pivotal role of mitochondria in metabolism, oxidative and nitrosative stress management, bioenergetics, and modulation of apoptosis targeted nanotherapies to reverse program TME, and immune evasion can potentiate effective cancer management and therapy. Targeting mitochondrial functions through drug and biomolecule-encapsulated nanomaterials has the potential to initiate a ripple effect in the tumor microenvironments, promoting a therapeutic response [77,78,79].
In mice models of melanomas, mitochondrial complex-I targeted therapy has shown promising effects in abrogating cancer progression through a concerted effect on oxygen consumption, cell signaling, and cell cycle [80]. It is demonstrated that cancer cells develop nanotubes to physically extract mitochondria from immune cells. This unique hijack machinery within the TME metabolically empowers the cancer cells in addition to depleting immune cells [80]. Hence, mitochondria-mediated crosstalk between the immune and metabolic components of cancer presents mitochondrial targeting by nanomaterials as one of the major cancer therapeutic strategies. Currently, CAR (chimeric antigen receptors) T-cell therapy has revolutionized the treatment of various cancers. Many clinical trials with CAR T-cell therapy for various cancers are under clinical trials (NCT04348643, NCT04348643, NCT01454596, NCT04877613) [81]. However, adoptively transferred cells do not consistently demonstrate effective persistence in patients. Nanomaterial-mediated targeting and reprogramming of mitochondrial pathways central to the function and survival of T-cells may facilitate effective results in patients.

6. Nanomaterials Enriching the Repertoire of Immunotherapeutic Modules against Skin Cancer

Nanomaterial-based nanosystem applications have been incorporated into many therapeutic modules for almost all types of cancers. Nanosystems have been effectively used in drug delivery, tumor targeting, immunomodulation, cellular imaging, and image-directed tumor ablation (Figure 2). Nanoparticles can be customized according to the therapeutic need (Table 1). They can circumvent biological barriers and deliver drugs and other therapeutic agents to the targeted tumor microenvironments, thereby escalating the treatment efficiency and reducing side effects. Nanoparticles can easily penetrate the skin and deeper tissues and be propelled to specific tumor sites for targeted delivery of encapsulated drugs or other biomolecules [82]. Recently, extensive research efforts have been channelized to develop effective nanoparticles with the potential to functionalize them according to the theranostic need. Recent research has diversified from the traditional use of nanoparticles in drug delivery and biodistribution to channelize and skew immunological responses beneficially. Though some nanoformulations for cancer therapy have reached clinical use, most nanotherapeutics are in the developmental phase [83] (Table 1).

6.1. Liposomes

Attributable to their ability to encapsulate drugs and antigens with different physicochemical properties, functionalized liposomes have been used in cancer therapy as targeted delivery vehicles [84]. The liposomal surface can be modified by pH and fusogenic material to achieve targeted antigen delivery, leading to the cross-presentation of exogenous antigen through the cytoplasmic pathway [85]. Several bottlenecks that are encountered in cancer immunotherapeutic approaches can be resolved through liposome-based systems. Liposomes can improve antigen delivery by directing it to surface receptors on APC/T-cells by selective release of antigens for an effective cross-presentation, improving the vaccine potential. Toll-like receptors, bioactive polysaccharides, and lipids as adjuvants can enhance the immune-activating potential of the liposomes. Adjuvants that counter immunosuppressive tumor microenvironments can enhance the anti-tumor effect of the antigen-loaded liposomes. Simultaneous delivery of liposome-encapsulated drugs in combination with radiotherapy, chemotherapy, and radiotherapy can lead to better results [86]. Currently, metal complex-based liposomes have been developed to maximize the therapeutic potential and reduce side effects [85]. These complexes are under clinical trials in many immunological applications for enhanced cellular targeting and drug delivery. Skin cancer immunotherapy can benefit from developing a purposeful design of metal-complexed liposomes targeted to immunosuppressive melanoma microenvironments [85].

6.2. Metallic Nanoparticles

Metallic nanosystems used in cancer theranostics include aluminum oxide, iron oxide, gold, silver, titanium dioxide, and zinc oxide nanomaterials for immunomodulation [18,87,88,89,90,91,92]. A diverse array of immunotherapeutic applications, such as the delivery of immunomodulators, induction of tumor-dependent antigen release, targeted vaccine therapy, improved antigen presentation, ROS generation, perturbing tumor microenvironments, etc., have successfully utilized metallic nanoparticles [93,94]. Silver nanoparticles functionalized with bovine serum albumin coating (BSA) demonstrated multimodal therapeutic potential. These particles visibly show cytocidal activity in melanoma cultures and promising inhibiting effects on angiogenesis in vitro. These BSA-ligated silver nanoparticles also exhibit a marked light-to-heat conversion ability and hence could be used in photothermal therapies for skin cancers [92]. Gold nanoparticles (GNP) are also prominent in cancer targeting and immunotherapy [95,96]. As excellent biocompatible materials, GNPs are efficient antigen and adjuvant delivery vehicles for inducing a cytotoxic T-cell response, can artificially present antigens, and can be functionalized to provide co-stimulation. GNP can bind with human DC to help activate cytokine production [97]. GNP demonstrates a high plasmonic effect, reduced cytotoxicity, and ability of diverse functionalization [98,99]. Cancer immunotherapy has used GNPs in combination with TNF-α, TGF-β, the PD-1 inhibitor, TLR-7 agonist, specialized antibodies, and other tumor cell death factors or/and immunostimulants. Iron oxide (ferrites) based metallic nanoparticles can be molded into magnetite nanosystems. These nanoparticles comprise a magnetic inner shell coated with specific immunomodulators. Magnetic nanoparticles have proved effective in magnetic hyperthermia-mediated cancer immunotherapy [100,101]. Fe3O4-SiO2 cancer-specific antigens functionalized magnetic nanosystem encapsulated in the cell membrane demonstrated a pronounced NK cell-based immunotherapy [102]. Drug-functionalized Ferric oxide (FeO) nanoconjugates have proven effective in modulating cancer cell apoptosis, metabolic reprogramming, DNA toxicity, etc. [103,104,105].

6.3. Carbon Nanotubes

Carbon nanotubes (CN) are carbon-based cylindrical single-walled or multi-walled carbon tubes with exceptional thermal, optical, and electronic conductivity, which enables diverse functionalization and loading potential. These nanotubes can achieve high targetability within the tumor cells and in the extracellular tumor microenvironment [106]. Pertinent to their extraordinary hydrophobic feature transport of drugs, biomolecules and sensor compounds can be easily targeted in a site-specific manner. Furthermore, the ease of functionalization with various biomolecules and biomimetics for sensing, imaging, and therapeutics makes CN one of the major players in cancer theranostics spanning diverse cancers [107].
CNs can target tumor antigens’ (ovalbumin, cytosine-phosphate-guanine oligodeoxynucleotide, etc.) presentation of APCs [108]. Doxorubicin-conjugated CN can be targeted at melanoma sites to induce cell death [109]. Polypyrrole-coated carbon nanotube composite is recently synthesized as an effective sonosenitizer, wherein low-intensity UV irradiation can enhance its treatment potential [110]. Carbon nanotubes recreate properties such as cell transport and targeting. CN, especially single-walled nanotubes, can be used in conjunction with photothermal therapy, potentiating an enhanced targeted treatment [111].

6.4. Polymeric Nanoparticles

Polymeric nanoparticles (PN) are biodegradable polymers used in cancer theranostics with a unique capacity for surface functionalization, stability and malleability of size and morphology, and efficient therapeutic payload potential. Various biodegradable polymers are used in the synthesis of polymeric nanoparticles, such as poly(lactide) (PLA), poly(lactide-co-glycolide) (PLGA) copolymers, poly (ɛ-caprolactone) (PCL), and poly(amino acids) and some natural polymers such as alginate, gelatin, albumin, etc. PN is generally used as a pH-sensitive modality to administer drugs and immunotherapeutics [112]. Immunodiagnostic approaches with PN have significantly enhanced computed tomography imaging and targeted chemotherapy of melanomas. Bioadhesive PN-based camptothecin targeting can be achieved by PLA attached to hyperbranched polyglycerol (HPG). The PLA-HPG nanosystem showed selective binding to the SCC tumor cells and matrix. This binding enhanced targeted intratumor delivery and therapeutic efficiency of the drug [113]. Targeted PN functionalized with oncolytic peptide LTX-315 substantiated with CpG adjuvant and PD-1 antibody system resulted in long-term immunotherapeutic effects in mouse models [114].
(R848)-loaded PN was demonstrated to target the mitochondria of melanoma cells effectively. Combined with near-infrared photothermal therapy and immune checkpoint blockers, the (R848)-loaded PN facilitated tumor immunosuppression, subsequently achieving anti-tumor effects [75]. PGLA encapsulating TLR7 and TLR8 agonists increased cytokine secretion through its effect on APC. Through enhanced co-stimulation, the nanoparticles led to the expansion of CD8+ T-cells and substantiated CTL response, resulting in significant therapeutic efficacy in melanomas and other cancers [115]. Though exceptional delivery vehicles, PN also exhibits high cytotoxicity and poor stability in vivo, requiring further technical reprogramming to be effectively translated to clinical settings.

6.5. Dendrimers

Dendrimers are compact, biocompatible, and highly branched artificial molecules with modifiable functionality. Dendrimer-based nanosystems can maneuver different biological barriers in the bloodstream with the least effect on their efficacy. Effectively functionalized dendrimers and dendrimer hybrids have been investigated as promising immunotherapeutics. They can combine numerous functional groups within their compact molecular dimension. Many types of dendrimers, such as poly(phosphorhydrazone) (PPH) dendrimers (ABP)-capped phosphorous dendrimers, aza-bisphosphonate, etc., are being tested. Glycodendrimers have enormous potential to activate Th1 response and NK cell activity [116]. Due to their affinity for lectin-like receptors, glycodendrimers can enhance DC cross-presentation of antigens, inhibit chemokines and cytokines production, and enhance anti-tumor immunity within the tumor milieu [117]. Lactose-terminated dendrimers can produce a robust immunostimulatory effect by activation of signaling response that functions through NFAT, NFκB, and AP-1 pathways. ABP-capped dendrimers potentiate an anti-inflammatory effect through the induction of IL-4, IL-10, and IL-13 cytokines and decreasing inflammatory surface CD64 and CD13 [118,119].
Furthermore, through its interaction with monocytes, ABP-capped dendrimers subdue CD4+ T-cell proliferation and NK cell activity. Carbosilane dendrimers limit M2 macrophage polarization by reducing IL-10 production in M2 macrophages. This favors anti-tumor response by switching M2 macrophage phenotype to M1, thereby facilitating an anticancer response [120]. PAMAM G3 dendrimers substituted with R-glycidol and celecoxib/simvastatin demonstrate an efficient, targeted drug delivery potential and can be tested for immunotherapeutics [121].

7. Pharmacokinetics and Toxicology of Nanomaterial Repertoire Enabling Cancer Theranostics

The incorporation of various nanoformulations in cancer theranostics has diversified and enhanced the potential of skin cancer immunotherapeutics and personalized medicine. Nonetheless, their inherent small size and high cellular permeability can alter pharmacokinetic effects and toxicity. Researchers have tediously worked to optimize nanoformulations for various medical uses, especially cancers.
Liposomal nanoparticles have a huge repertoire generated by combinations of cholesterol, phospholipids, polyethylene glycol, etc., imparting diverse functionality and use in different TME and cellular targeting. Though the physiochemical properties of liposomes are the least pharmacologically active and well tolerated in many models, the type of targeted environment, dose and time of exposure, and surface functionalization can impart toxicity [122]. Liposomes are demonstrated to interact with healthy cells and proteins in circulation, altering their functions. Animal studies have shown cell-dependent toxicity of the drugs and nucleic acid-loaded cationic liposomes, which were toxic to macrophages and monocytic cell lines but not to T-cells. The toxicity increased with higher zeta potential and some combinations of liposomal constituents [123]. Liposomes can interact with the mononuclear phagocyte system (MPS) [124]. Thus, in addition to the target cells, the therapeutic payload is directed to the phagocytic cells of the lymph nodes, bone marrow, liver, and spleen, impairing their functions. Few studies have also demonstrated that the dose of the therapeutic drug and composition of the liposome can cause aggregation and induction of edema, necrosis, and inflammation at the site of the entry. A meta-analysis study has evaluated that an average of 1% of the nanoparticles reach the targeted tumors [125,126]. Hence, systemic effects remain a challenge that needs to be addressed by various in vitro toxicology assessment methods. Some liposomal drug formulations are also associated with the induction of complement pathways and hypersensitivity reactions in addition to increased blood clearance [127,128]. Overall, the full potential of liposome-based immunotherapeutics can be achieved through careful assessment and understanding of various formulations of liposomes with the cellular and immune machinery.
Metallic nanoparticles such as superparamagnetic iron oxide, which were FDA-approved, and widely used diagnostic nanomaterials, have been pulled off due to their toxic potential. Studies have noted ROS production, inflammation, lactate dehydrogenase leakage, mitochondrial dysfunction, and DNA strand breaks due to some metallic nanoparticles. Metal and metal oxide nanoparticles of Ag, TiO2, Ni, and ZnO translocate to the lung and gastrointestinal system and reach systemic circulation further accumulating on MPS and the liver [129]. Metallic nanoparticles also demonstrate a high potential to accumulate in sub-cellular organelles. Lysosomal interaction of metallic nanoparticles leads to ROS production, and the release of reactive ions that may inflict DNA damage, inflammation, and genotoxicity [130]. Polymeric nanoparticles have a wide application in cancer drug delivery and diagnostics. In spite of being the most tunable nanomolecules, it has a broad range of associated toxicities. The adverse effects of polymeric nanosystems are due to the quantum size effects, monomer aggregation linked to ROS generation, cytotoxicity, and DNA damage, in addition to their toxic degradation mechanism [131]. Cancer theranostics have harnessed CN as a modular platform due to their adaptable physicochemical and mechanical properties. Nevertheless, these advanced properties of CN also are a cause for concern. CNs have been tested as modular drug trafficking modalities for cancers in animal models. Some studies record that CN can induce immunotoxicity, neurotoxicity, and toxic effects on the lung, liver, cardiovascular system, etc [132]. Small molecular weight CN can induce inflammation with slow recovery in addition to the generation of ROS and induction of inflammatory responses [132]. Developmental toxicity was also observed in mice with pronounced teratogenic effects, fetal malformation, and miscarriages. In mice, CN demonstrated the development of atherosclerotic plaque, arrhythmia, and vasomotor dysfunction. However, the toxic impact of CN has thus far been associated with its size and high surface area [133]. Studies to modulate the synthesis, functionalization, and encapsulated drug concentrations and assessment of cytotoxicity in animal models are crucial.
Toxicology studies on generation 4, 5, and, 6 PAMAM dendrimers indicate detrimental effects on mammalian cells in a dose-dependent manner [134]. The toxicity assessment in human intestinal, endothelial, and skin cells demonstrated a correlation with the number of amine groups on the dendrimer surface [135]. Studies have indicated that surface modification that modifies the surface to a neutral or anionic state can reduce the toxicity index of PAMAM dendrimers. Studies have shown the toxic effects of dendrimer spanning aggregation of many blood proteins and ROS generation leading to DNA damage [136]. Generation-5 PAMAM dendrimer, when administered through the intranasal route, can lead to acute lung failure [137]. PAMAM dendrimers with amine termini have higher toxicity as compared to PAMAM dendrimers with carboxylic acid termini. Studies on surface modification, appropriate dosage, and therapeutic methodology assessment can enhance the biocompatibility of PAMAM dendrimer.

8. Nanoimmunotherapeutics and Precision Medicine in Skin Cancer: Research and Clinical Trials

Nanosystem-based immunotherapeutics for skin cancer manifests either through a potent anti-tumor immune response or channelizing immune defense mechanism to disrupt the immunosuppressive nature of the tumor. Several nanoparticle-based immunotherapeutic modalities have been tested, and some have reached clinical trials. A few effective modalities, such as cancer nanovaccines, immune checkpoint inhibitors, oncolytic virus therapy, and adoptive cell transfer, which have enhanced skin cancer therapy by breaching the therapeutic bottleneck, are discussed.

8.1. Nanoparticle-Formulated RNA

RNA-based immunomodulation of cancers is now being explored to enhance the therapeutic efficacy of existing immunotherapy. Many modalities are used, such as regulating cellular function through mRNA, siRNA, or stimulating immune components, specifically TLRs or cytosolic RIG-I [81,138,139]. RNA-based immunomodulation can be achieved to full potency only through nanoparticle encapsulated delivery systems, which facilitate overcoming ineffective target cell delivery, degradation through RNases, cross membrane diffusion difficulties, etc. Many materials have been tested for delivering mRNA including lipids, lipid and protein derivatives, and polymers [140,141,142,143]. Lipid nanoparticle encapsulated mRNA vaccines have shown promising results in diseases as diverse as viral and bacterial infections and cancers. However yet to be established in skin cancers [144,145]. The ability of mRNA to translate to protein directly precluded many bottlenecks associated with conventional therapeutics besides a higher potential to activate immune components with sustained responses. mRNA-based therapeutics also limit the risks associated with radiation and chemotherapy and are among the safest vaccine approach [81]. Usually modeled using mRNA encoding TAM, mRNA vaccines can manipulate immune mechanisms, leading to long-standing responses by activating memory T-cells [95]. Lipid- mRNA formulations have proven efficacious in preclinical testing. These formulations target mRNA to DC and facilitate its endocytosis. The intracellular delivery in mRNA targeting can be achieved using the functionalization of pH-sensitive lipids or polymers. Furthermore, it helps escape mRNA from endosomal degradation [143].
Considering its ability to circumvent mRNA instability within the cellular milieu, mRNA as skin cancer vaccines hold an enhanced potential as a therapy. Some mRNA vaccines have been tested in patients. These vaccines can be made in vitro without using inactivated pathogens or particulate material as conventional vaccines [146]. This enables customization to incorporate any specific nucleotide sequence. Nanoparticles containing mRNA-based treatment for skin cancers, especially melanomas, may provide better therapeutic avenues with fewer side effects and higher curative potential [147] (Figure 3). Some mRNA nanodrugs for the treatment of melanoma are now in clinical trials [148]. Nanoparticle-assisted delivery system-based RNA therapeutics is expected to offer tremendous potential for treating skin cancers.

8.2. Nanoparticle-Enabled Dendritic Cells Vaccines

Dendritic cell (DC) vaccines are currently used for melanoma therapy. Being the most important antigen-presenting cells, DC can help regulate immune activation and overcome tolerance to modulate cancer immune responses. DC can act as adjuvants in initiating immune responses or as effectors to redirect cytotoxic CD8+ T-cells against melanoma. Unlike other skin cancer immunotherapy approaches, the percentage of patients that can benefit from DC therapy is higher, owing to their potential to overcome distinct immunosuppressive or immunotolerant tumor microenvironments [149,150]. To enhance the potential of DC as therapeutic vaccines, modulation of their outer structures with modular nanomaterials has gained interest. DC can be appropriately programmed ex vivo for adoptive vaccination to induce specific in vivo anti-tumor immune responses. DC vaccines require isolating or in vitro culturing precursor cells from peripheral blood and loading them with tumor-associated antigens. These DCs are matured through the application of specific stimulatory molecules [151]. Many technical strategies have been explored to effectively potentiate DC to engender a directed and robust anti-tumor response. Integration of methodologies that can orchestrate efficient tumor antigen cross-presentation, T-cell co-stimulation, effector cell polarization, targeted migration, and avoiding immunodominance of DC are needed to maximize the potential of DC vaccines. Manipulating DC vaccines through the spatiotemporally controllable and modifiable function of nanomaterials has shown promise against skin cancers in both in vitro and in vivo studies [152] (Figure 3). Combination therapy with monocyte-derived DC vaccines can be loaded with preferentially expressed antigens of melanoma or whole apoptotic cell substances, cell-derived mRNA. This nanoformulation can be targeted in a site-specific manner through functionalized nanoparticles [153]. Silencing PD-1 in DC vaccines increases CD8+ priming [154]. Antigenic RNA silencing PD-1/2 through nanoparticle vehicles that translocate siRNA to DC can induce robust CD8+ stimulation [155]. Nanoparticle-based mRNA-transfected DC maintains the phenotypic nature and migration potential of DCs [156]. RNA-modified DC vaccine can also help overcome tumor resistance to therapy generated by auto-inductive loops developed by checkpoint inhibitors and tumor milieu, making skin cancer resistant to many traditional treatments [157]. Neoadjuvant and neoantigens obtained from tumor sites loaded in DC cells as effective vaccines [153]. The use of nanomaterial in DC-based therapy allows for the incorporation of various functional molecules to enhance antigen presentation and overcome several methodological deficiencies [158,159]. Biocompatible nanomaterials also alleviate the toxicity of the treatment modality, besides increasing the therapeutic effect of cancer DC [160]. Nanoencapsulation improves the biophysical-chemical properties of antigenic formulations and imparts quality enhancement, antigen protection, and antigen presentation. Furthermore, DC can be conjugated with functional molecules to mediate crosstalk with APC and TME to complement and reinforce DC-based immunotherpeutics. Nanoparticles associated DC are expected to increase their in vivo circulation span and limit their degradation.

8.3. Nanoparticle-Based Immune Checkpoint Inhibitors

Immune checkpoint receptor pathways are immune synapses that directly or indirectly orchestrate cell-to-cell communication. In cancers, immune checkpoint inhibitors (ICI) abate T-lymphocyte responses and skew the deregulated immune system to induce CD8+ T-cell mediated cancer killing. FDA-approved monoclonal (mAb) anti-CTLA4 and anti-PD-1 antibodies as ICI have been successful in the management of advanced melanoma. Based on a patient study, anti-CTLA and PD-1 have shown significant tumor regression and long-term cancer management in nearly 50% of patients [161]. In a retrospective cohort (2010–2019) study comprising 16,831 metastatic melanoma patients, the use of ICI in addition to immunotherapy showed a marked improvement in survival [162]. Anti-CTLA4 and anti-PD-1 therapy have demonstrated the therapeutic promise of overall 5-year survival in advanced melanomas, with the curtailment of brain metastases [163]. The addition of an anti-LAG3 antibody to combined anti-CTLA4 and anti-PD-1 therapy demonstrates a progression-free survival, as observed in phase 3 trials. The use of PD-1 inhibitors is established as a standard of care in stage III or IV high-risk melanomas as adjuvant therapy [163]. Nonetheless, the development of autoimmune toxicities associated with immune-related adverse effects is some of the drawbacks of ICI requiring immediate management. Being different from an actual autoimmune disease, these adverse immune events have no specific management available [164]. The intrinsic property of the nanomaterial is harnessed to ameliorate potential injuries and adverse reactions and potentiate long-lasting responses. Nanoparticles can be functionalized to precisely and accurately target the delivery of more than one ICI and can be specifically localized to inhibitor or both stimulatory and inhibitory checkpoints. Nanosystem-based ICI treatment can enhance the bioavailability of antibodies and limit systemic toxicity. Functionalized nanosystems conjugated mAb can easily maneuver through dense tumor microenvironments and reach the target, a drawback observed in conventional mAb therapy. PEGylated and non-PEGylated liposomes encapsulating anti-CTLA-4 mAb targeting tested in cancer models have shown efficient localization within 18 h of injection [165]. Low concentrations of adenylate cyclase (AC) inhibitor conjugated with poly(sarcosine)-block-poly(L-glutamic acid γ-benzyl ester) (polypept(o)id) nanoparticle enhances anti-tumor activity in combination with regulatory T-cells. Nanotargeted AC reduces anti-inflammatory myeloid cells and checkpoint receptors on T-cells, preventing tumor immune escape [166]. Thus, nanotechnology serves as a good interface for effective ICI targeting within skin cancers microenvironments (Figure 3).

8.4. Nanoparticle-Enabled Adoptive Cell Therapy

The TME targeting of NK cells using adoptive cell transfer (ACT) has gained success due to its orchestrated, specific, and selective function toward various cancers. Many clinical trials have been conducted with effective treatment results and an unmatchable adjuvant to conventional therapies. These clinical trials investigate the potential of adoptive transfer modalities for solid and liquid malignancies (www.clinicaltrials.gov, accessed on 7 January 2023). Adoptive cell transfer of macrophages expressing chimeric antigens has been tested in many tumors [167,168]. Though a promising therapeutic approach, NK-based ACT has encountered several limitations. Attributable to inadequate homing of the cell, low cytotoxicity, limited contact with tumor cells, and the overall immunosuppressive microenvironment. Similarly, macrophage-based adoptive cell therapy has achieved higher success rates in conjunction with nanoparticles. Macrophage-based adoptive therapy conjugated with copper sulfide nanoparticles has demonstrated substantial tumor regression in mouse melanoma models [169]. Thus, nanoparticles enhance ACT irrespective of tumor antigen presentation. Bone marrow-derived macrophages induce reactive oxygen species (ROS) production, increased PD-1 expression, and phagocytic activity when used with intratumoral administration of copper sulfide nanoparticles, subsequently prolonging survival rate in mice models [169]. Further, nanoparticles have facilitated overcoming the limitation associated with T-cell therapy, including restricted intratumoral delivery, suboptimal activation, and intratumoral dysfunction attributed to immunosuppressive TME. Nanoparticles can be functionalized explicitly for robust activation of T-cells ex vivo and conjugated onto T-cells for enhanced T-cell therapy [170] (Figure 3). Liposomal nanoparticles with IL-2 and TGF β can mediate macrophage and NK cell homing and infiltration in the tumor site, and nanocomposite containing IFNγ or IL-2 can facilitate the conversion of immunosuppressive TME to more immunoresponsive environment enhancing NK tumor recognition and killing [171,172]. Recent preclinical advances have benefitted from the using nanoparticles to advance and improve T-cell therapy in various tumors. Magnetic nanoparticles and nanoengagers formulated with phenylboronic acid and IgG and nanoparticle-mediated delivery of CAR and NK-1 have enhanced adoptive cell therapy against solid cancers and melanomas [173].

9. Nanoparticle-Aided Personalized Skin Cancer Immunotherapy

Skin cancers can be broadly classified as nonmelanoma and melanoma, each having diverse subtypes. However, at the patient level, every cancer has a unique set of genetic and epigenetic mutations. Furthermore, additional changes are incorporated as cancer proliferates, accumulating different mutations in the different cells within the same cancer microenvironment. Hence, there is a need for effectively tailored therapies suitable for each patient. Though malignant and non-malignant skin cancers have demonstrated sensitivity towards an advanced immunotherapeutic substantiating prospective immunologic cure of skin cancers, many patients develop primary or adaptive resistance. Resistance mechanisms against immunotherapy are generated by a complex interplay of TME, T- cells, cytokines, and existing co-morbidities, which are variable among patients. Hence, personalized immunotherapeutic approaches are considered to hold promise against skin cancers. Adoptive cell therapy, as a customized approach targeting exclusive somatic mutations against melanoma, has resulted in long-lasting regression in patients [174]. With the current tools, genetically engineered T-lymphocytes expressing chimeric antigens can be used as personalized adoptive cell therapy. mRNA-based personalized vaccines that activate T-cell responses specific to a patient’s tumor can amplify the endogenous tumor-specific T-cells’ repertoire. Predicated on neoantigens and TAA-based designs, therapeutic cancer vaccines can be personalized as safe and effective immunogens to drive anticancer immune response [175]. With the effective integration of nanotools in skin cancer immunotherapy, several immunotherapeutic modalities such as vaccines, adoptive cell therapy, immunomodulators, and immune checkpoint inhibitors can be modeled as precision medicines. Nanomaterials facilitate the effective use of personalized cancer immunotherapy by enhancing the immunogenicity of tailored antigens, improving antigen presentation, and stabilizing antigens. Nanoparticles effectively deliver immune agents in stabilized native forms to the target site with high accuracy, facilitating a potent anti-tumor response. Many nanovaccines approved by the FDA are now in clinical trials. A range of advanced immunotherapeutic methodologies can be explored for delivering precision medicine with enhanced outcomes.

10. Conclusions and Perspective

Diagnostic and therapeutic modalities for skin cancers have shown promise through immunotherapy. However, immunotherapeutics have also reached their response limit in nonmelanomas and melanomas. This article discusses the current knowledge of the integration of nanoplatforms with the immunotherapeutics regimes that are already in practice and sheds light on how immunotherapy against skin cancers can be enhanced. Coordinated efforts to amalgamate current therapy and diagnosis with nanotechnology to enable robust and sustained responses of skin cancer immunotherapy have proven successful in sporadic studies and clinical trials. Compared to the traditional procedure, immunotherapeutic targeting through nanoparticles or nanoencapsulation allows for better targeting, improved epithelial permeability, specific tumor targeting, enhanced bioavailability, and minimized side effects. Emerging nanosystem-based approaches preclude the importance of integrating nano-immunotherapeutics in skin cancer treatment to accelerate diagnosis and therapy.

11. Challenges and Future Directions

Even though nontherapeutic regimes have proven successful in many cancers, incorporating nanoplatforms against skin cancers is nominal. Nanomaterials are expected to greatly improve current skin cancer detection, tumor imaging, and therapy methods while reducing toxicity compared to traditional treatments. Nanomaterial-based immunotherapeutic strategies are expected to enhance the efficacy of immunotherapy as well, obviating the need to explore nano-based precision medicine against skin cancer.
Nevertheless, the inherent modular nature of nanomaterials can result in both beneficial and detrimental effects based on the targeted environment. Recently, studies have reported tissue accumulation, nuclear infiltration, increased oxidative stress, hepato- and nephron-toxicity, tissue-specific inflammation, etc., which are linked to nanomaterial-based therapies. The use of nanomaterials in cancers necessitates the need for nanotoxicology studies before their therapeutic or diagnostic use. Urgent attention to identifying and bridging the gap in the beneficial use of nanomaterials-based therapies and associated toxicities is fundamental to overcoming the current challenges. In sum, numerous nanosystems and strategies have been conceptualized to boost the efficacy of skin cancer immuno-theranostics. Recent years have observed significant advances at the nano–immuno interface in the preclinical settings with encouraging proofs-of-concept attained in the clinical settings.

Funding

This research was funded by the Deanship of Scientific Research at Jouf University, grant number DSR-2021-01-0218.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Arnold, M.; Singh, D.; Laversanne, M.; Vignat, J.; Vaccarella, S.; Meheus, F.; Cust, A.E.; de Vries, E.; Whiteman, D.C.; Bray, F. Global Burden of Cutaneous Melanoma in 2020 and Projections to 2040. JAMA Dermatol. 2022, 158, 495. [Google Scholar] [CrossRef] [PubMed]
  2. Li, Z.; Fang, Y.; Chen, H.; Zhang, T.; Yin, X.; Man, J.; Yang, X.; Lu, M. Spatiotemporal trends of the global burden of melanoma in 204 countries and territories from 1990 to 2019: Results from the 2019 global burden of disease study. Neoplasia 2021, 24, 12–21. [Google Scholar] [CrossRef] [PubMed]
  3. Chen, M.K.; Sebaratnam, D.F. A non-healing ulcer: Amelanotic melanoma. Med. J. Aust. 2021, 215, 405. [Google Scholar] [PubMed]
  4. Chuchvara, N.; Farabi, B.; Milgraum, D.; Lee, Y.; Chamorro, P.; Pappert, A.; Rao, B. Amelanotic melanoma with features of keratinocytic tumor on reflectance confocal microscopy. J. Cutan. Pathol. 2021, 49, 317–320. [Google Scholar] [CrossRef] [PubMed]
  5. Li, D.; Humayun, L.; Vienneau, E.; Vu, T.; Yao, J. Seeing through the Skin: Photoacoustic Tomography of Skin Vasculature and Beyond. JID Innov. 2021, 1, 100039. [Google Scholar] [CrossRef]
  6. Rasmussen, S.M.; Nielsen, T.; Hody, S.; Hager, H.; Schousboe, L.P. Photoplethysmography for demarcation of cutaneous squamous cell carcinoma. Sci. Rep. 2021, 11, 1–7. [Google Scholar] [CrossRef]
  7. Hawkes, J.E.; Truong, A.; Meyer, L.J. Genetic predisposition to melanoma. Semin. Oncol. 2016, 43, 591–597. [Google Scholar] [CrossRef]
  8. Hansson, J. Familial Cutaneous Melanoma. Dis. DNA Repair 2010, 685, 134–145. [Google Scholar] [CrossRef]
  9. Hawkes, J.E.; Campbell, J.; Garvin, D.; Cannon-Albright, L.; Cassidy, P.; Leachman, S.A. Lack of GNAQ and GNA11 Germ-Line Mutations in Familial Melanoma Pedigrees with Uveal Melanoma or Blue Nevi. Front. Oncol. 2013, 3, 160. [Google Scholar] [CrossRef]
  10. Ashida, A.; Takata, M.; Murata, H.; Kido, K.; Saida, T. Pathological activation of KIT in metastatic tumors of acral and mucosal melanomas. Int. J. Cancer 2008, 124, 862–868. [Google Scholar] [CrossRef] [Green Version]
  11. Kwak, G.; Kim, D.; Nam, G.-H.; Wang, S.Y.; Kim, I.-S.; Kim, S.H.; Kwon, I.-C.; Yeo, Y. Programmed Cell Death Protein Ligand-1 Silencing with Polyethylenimine–Dermatan Sulfate Complex for Dual Inhibition of Melanoma Growth. ACS Nano 2017, 11, 10135–10146. [Google Scholar] [CrossRef] [PubMed]
  12. Cretella, D.; Digiacomo, G.; Giovannetti, E.; Cavazzoni, A. PTEN alterations as a potential mechanism for tumor cell escape from PD-1/PD-L1 inhibition. Cancers 2019, 11, 1318. [Google Scholar] [CrossRef] [PubMed]
  13. Sabir, F.; Barani, M.; Rahdar, A.; Bilal, M.; Nadeem, M. How to face skin cancer with nanomaterials: A review. Biointerface Res. Appl. Chem. 2021, 11, 11931–11955. [Google Scholar]
  14. Attrill, G.H.; Ferguson, P.M.; Palendira, U.; Long, G.V.; Wilmott, J.S.; Scolyer, R.A. The tumour immune landscape and its implications in cutaneous melanoma. Pigment. Cell Melanoma Res. 2020, 34, 529–549. [Google Scholar] [CrossRef]
  15. Fujimura, T.; Kambayashi, Y.; Fujisawa, Y.; Hidaka, T.; Aiba, S. Tumor-Associated Macrophages: Therapeutic Targets for Skin Cancer. Front. Oncol. 2018, 8, 8. [Google Scholar] [CrossRef]
  16. Fujimura, T.; Aiba, S. Significance of Immunosuppressive Cells as a Target for Immunotherapies in Melanoma and Non-Melanoma Skin Cancers. Biomolecules 2020, 10, 1087. [Google Scholar] [CrossRef]
  17. Marzagalli, M.; Ebelt, N.; Manuel, E.R. Unraveling the crosstalk between melanoma and immune cells in the tumor microenvironment. Semin. Cancer Biol. 2019, 59, 236–250. [Google Scholar] [CrossRef]
  18. Wang, Y.; Yao, C.; Ding, L.; Li, C.; Wang, J.; Wu, M.; Lei, Y. Enhancement of the immune function by titanium dioxide nanorods and their application in cancer immu-notherapy. J. Biomed. Nanotechnol. 2017, 13, 367–380. [Google Scholar] [CrossRef]
  19. Hall, E.T.; Fernandez-Lopez, E.; Silk, A.W.; Dummer, R.; Bhatia, S. Immunologic Characteristics of Nonmelanoma Skin Cancers: Implications for Immunotherapy. Am. Soc. Clin. Oncol. Educ. Book 2020, 40, 398–407. [Google Scholar] [CrossRef]
  20. Tucci, M.; Passarelli, A.; Mannavola, F.; Felici, C.; Stucci, L.S.; Cives, M.; Silvestris, F. Immune System Evasion as Hallmark of Melanoma Progression: The Role of Dendritic Cells. Front. Oncol. 2019, 9, 1148. [Google Scholar] [CrossRef]
  21. Hemmi, H.; Akira, S. TLR Signalling and the Function of Dendritic Cells. Mech. Epithel. Def. 2005, 86, 120–135. [Google Scholar] [CrossRef]
  22. Falcone, I.; Conciatori, F.; Bazzichetto, C.; Ferretti, G.; Cognetti, F.; Ciuffreda, L.; Milella, M. Tumor Microenvironment: Implications in Melanoma Resistance to Targeted Therapy and Immunotherapy. Cancers 2020, 12, 2870. [Google Scholar] [CrossRef]
  23. Heibel, H.D.; Hooey, L.; Cockerell, C.J. A Review of Noninvasive Techniques for Skin Cancer Detection in Dermatology. Am. J. Clin. Dermatol. 2020, 21, 513–524. [Google Scholar] [CrossRef]
  24. Dorrell, D.N.; Strowd, L.C. Skin Cancer Detection Technology. Dermatol. Clin. 2019, 37, 527–536. [Google Scholar] [CrossRef]
  25. Stiegel, E.; Lam, C.; Schowalter, M.; Somani, A.-K.; Lucas, J.; Poblete-Lopez, C. Correlation Between Original Biopsy Pathology and Mohs Intraoperative Pathology. Dermatol. Surg. 2018, 44, 193–197. [Google Scholar] [CrossRef]
  26. Narayanamurthy, V.; Padmapriya, P.; Noorasafrin, A.; Pooja, B.; Hema, K.; Khan, A.Y.F.; Nithyakalyani, K.; Samsuri, F. Skin cancer detection using non-invasive techniques. RSC Adv. 2018, 8, 28095–28130. [Google Scholar] [CrossRef]
  27. Oh, B.H.; Kim, K.H.; Chung, K.Y. Skin Imaging Using Ultrasound Imaging, Optical Coherence Tomography, Confocal Microscopy, and Two-Photon Microscopy in Cutaneous Oncology. Front. Med. 2019, 6, 274. [Google Scholar] [CrossRef]
  28. Kato, J.; Horimoto, K.; Sato, S.; Minowa, T.; Uhara, H. Dermoscopy of Melanoma and Non-melanoma Skin Cancers. Front. Med. 2019, 6, 180. [Google Scholar] [CrossRef]
  29. Di Matteo, E.; Pampena, R.; Pizzichetta, M.A.; Cinotti, E.; Chester, J.; Kaleci, S.; Manfredini, M.; Guida, S.; Dika, E.; Moscarella, E.; et al. Unusual dermoscopic patterns of basal cell carcinoma mimicking melanoma. Exp. Dermatol. 2022, 31, 890–898. [Google Scholar] [CrossRef]
  30. Javed, R.; Rahim, M.S.M.; Saba, T.; Rehman, A. A comparative study of features selection for skin lesion detection from dermoscopic images. Netw. Model. Anal. Heal. Inform. Bioinform. 2019, 9, 4. [Google Scholar] [CrossRef]
  31. Rodríguez-Lomba, E.; García-Piqueras, P.; Lozano-Masdemont, B.; Nieto-Benito, L.M.; Hernández de la Torre, E.; Parra-Blanco, V.; Suárez-Fernández, R.; Lázaro-Ochaita, P.; Avilés-Izquierdo, J.A. ‘Rainbow pattern’: A dermoscopic sign of invasive melanoma. Clin. Exp. Dermatol. 2022, 47, 529–533. [Google Scholar]
  32. Pellacani, G.; Scope, A.; Gonzalez, S.; Guitera, P.; Farnetani, F.; Malvehy, J.; Witkowski, A.; De Carvalho, N.; Lupi, O.; Longo, C. Reflectance confocal microscopy made easy: The 4 must-know key features for the diagnosis of mela-noma and nonmelanoma skin cancers. J. Am. Acad. Dermatol. 2019, 81, 520–526. [Google Scholar] [CrossRef]
  33. Longo, C.; Mazzeo, M.; Raucci, M.; Cornacchia, L.; Lai, M.; Bianchi, L.; Peris, K.; Pampena, R.; Pellacani, G. Dark pigmented lesions: Diagnostic accuracy of dermoscopy and reflectance confocal microscopy in a ter-tiary referral center for skin cancer diagnosis. J. Am. Acad. Dermatol. 2021, 84, 1568–1574. [Google Scholar] [CrossRef]
  34. Rajabi-Estarabadi, A.; Bittar, J.M.; Zheng, C.; Nascimento, V.; Camacho, I.; Feun, L.G.; Nasiriavanaki, M.; Kunz, M.; Nouri, K. Optical coherence tomography imaging of melanoma skin cancer. Lasers Med Sci. 2018, 34, 411–420. [Google Scholar] [CrossRef]
  35. Wan, B.; Ganier, C.; Du-Harpur, X.; Harun, N.; Watt, F.; Patalay, R.; Lynch, M. Applications and future directions for optical coherence tomography in dermatology. Br. J. Dermatol. 2020, 184, 1014–1022. [Google Scholar] [CrossRef]
  36. Shinoda, Y.; Kato, D.; Ando, R.; Endo, H.; Takahashi, T.; Tsuneoka, Y.; Fujiwara, Y. Systematic Review and Meta-Analysis of In Vitro Anti-Human Cancer Experiments Investigating the Use of 5-Aminolevulinic Acid (5-ALA) for Photodynamic Therapy. Pharmaceuticals 2021, 14, 229. [Google Scholar] [CrossRef]
  37. Walker, E.; Mann, M.; Honda, K.; Vidimos, A.; Schluchter, M.D.; Straight, B.; Bogyo, M.; Popkin, D.; Basilion, J.P. Rapid visualization of nonmelanoma skin cancer. J. Am. Acad. Dermatol. 2016, 76, 209–216.e9. [Google Scholar] [CrossRef]
  38. Maytin, E.V.; Hasan, T. Vitamin D and other differentiation-promoting agents as neoadjuvants for photodynamic thera-py of cancer. Photochem. Photobiol. 2020, 96, 529–538. [Google Scholar] [CrossRef]
  39. Kamiyanagi, M.; Taninaka, A.; Ugajin, S.; Nagoshi, Y.; Kurokawa, H.; Ochiai, T.; Arashida, Y.; Takeuchi, O.; Matsui, H.; Shigekawa, H. Cell-Level Analysis Visualizing Photodynamic Therapy with Porphylipoprotein and Talaporphyrin Sodium. Int. J. Mol. Sci. 2022, 23, 13140. [Google Scholar] [CrossRef]
  40. Meng, Z.; Xue, H.; Wang, T.; Chen, B.; Dong, X.; Yang, L.; Dai, J.; Lou, X.; Xia, F. Aggregation-induced emission photosensitizer-based photodynamic therapy in cancer: From chemical to clinical. J. Nanobiotechnol. 2022, 20, 1–35. [Google Scholar] [CrossRef]
  41. Wu, X.; Xu, M.; Wang, S.; Abbas, K.; Huang, X.; Zhang, R.; Tedesco, A.C.; Bi, H. F,N-Doped carbon dots as efficient Type I photosensitizers for photodynamic therapy. Dalton Trans. 2022, 51, 2296–2303. [Google Scholar] [CrossRef] [PubMed]
  42. Karges, J. Clinical Development of Metal Complexes as Photosensitizers for Photodynamic Therapy of Cancer. Angew. Chem. Int. Ed. 2021, 61. [Google Scholar] [CrossRef]
  43. Serda, M.; Szewczyk, G.; Krzysztyńska-Kuleta, O.; Korzuch, J.; Dulski, M.; Musioł, R.; Sarna, T. Developing [60] fullerene nanomaterials for better photodynamic treatment of non-melanoma skin can-cers. ACS Biomater. Sci. Eng. 2020, 6, 5930–5940. [Google Scholar] [CrossRef] [PubMed]
  44. Abd-El-Azim, H.; Tekko, I.A.; Ali, A.; Ramadan, A.; Nafee, N.; Khalafallah, N.; Rahman, T.; Mcdaid, W.; Aly, R.G.; Vora, L.K.; et al. Hollow microneedle assisted intradermal delivery of hypericin lipid nanocapsules with light ena-bled photodynamic therapy against skin cancer. J. Control. Release 2022, 348, 849–869. [Google Scholar] [CrossRef]
  45. Manghnani, P.N.; Wu, W.; Xu, S.; Hu, F.; Teh, C.; Liu, B. Visualizing photodynamic therapy in transgenic zebrafish using organic nanoparticles with aggre-gation-induced emission. Nano-Micro Lett. 2018, 10, 1–9. [Google Scholar] [CrossRef]
  46. Ishii, Y.; Mavligit, G.M. Immunodiagnosis of Human Melanoma: Characterization of Human Melanoma Antigens and Their Detection in Sera of Melanoma Patients by Radioimmunoassay. Oncology 1982, 39, 23–28. [Google Scholar] [CrossRef]
  47. Natali, P.; Bigotti, A.; Cavaliere, R.; Liao, S.K.; Taniguchi, M.; Matsui, M.; Ferrone, S. Heterogeneous expression of melanoma-associated antigens and HLA antigens by primary and multiple metastatic lesions removed from patients with melanoma. Cancer Res. 1985, 45, 2883–2889. [Google Scholar]
  48. Davis, L.E.; Shalin, S.C.; Tackett, A.J. Current state of melanoma diagnosis and treatment. Cancer Biol. Ther. 2019, 20, 1366–1379. [Google Scholar] [CrossRef]
  49. Singh, V.; Kesharwani, P. Recent advances in microneedles-based drug delivery device in the diagnosis and treatment of cancer. J. Control. Release 2021, 338, 394–409. [Google Scholar] [CrossRef]
  50. Moreira, A.F.; Rodrigues, C.F.; Jacinto, T.A.; Miguel, S.A.P.; Costa, E.C.; Correia, I.J. Microneedle-based delivery devices for cancer therapy: A review. Pharmacol. Res. 2019, 148, 104438. [Google Scholar] [CrossRef]
  51. Zhi, D.; Yang, T.; O’Hagan, J.; Zhang, S.; Donnelly, R.F. Corrigendum to “Microneedles for Photodynamic and Photothermal Therapy”. J. Control. Release 2020, 329, 1286. [Google Scholar] [CrossRef]
  52. Debele, T.A.; Yeh, C.-F.; Su, W.-P. Cancer Immunotherapy and Application of Nanoparticles in Cancers Immunotherapy as the Delivery of Immunotherapeutic Agents and as the Immunomodulators. Cancers 2020, 12, 3773. [Google Scholar] [CrossRef] [PubMed]
  53. Rodríguez-Cerdeira, C.; Gregorio, M.C.; López-Barcenas, A.; Sánchez-Blanco, E.; Sánchez-Blanco, B.; Fabbrocini, G.; Bardhi, B.; Sinani, A.; Guzman, R.A. Advances in Immunotherapy for Melanoma: A Comprehensive Review. Mediat. Inflamm. 2017, 2017, 1–14. [Google Scholar] [CrossRef] [Green Version]
  54. Patrinely, J.R.; Dewan, A.K.; Johnson, D.B. The role of anti-PD-1/PD-L1 in the treatment of skin cancer. BioDrugs 2020, 34, 495–503. [Google Scholar]
  55. Vaishampayan, P.; Curiel-Lewandrowski, C.; Dickinson, S.E. Review: PD-L1 as an emerging target in the treatment and prevention of keratinocytic skin cancer. Mol. Carcinog. 2022, 62, 52–61. [Google Scholar] [CrossRef]
  56. Sanlorenzo, M.; Vujic, I.; Carnevale-Schianca, F.; Quaglino, P.; Gammaitoni, L.; Fierro, M.T.; Aglietta, M.; Sangiolo, D. Role of interferon in melanoma: Old hopes and new perspectives. Expert Opin. Biol. Ther. 2017, 17, 475–483. [Google Scholar] [CrossRef]
  57. Eggermont, A.M.; Suciu, S.; Rutkowski, P.; Kruit, W.H.; Punt, C.J.; Dummer, R.; Salès, F.; Keilholz, U.; De Schaetzen, G.; Testori, A. Long term follow up of the EORTC 18952 trial of adjuvant therapy in resected stage IIB–III cutane-ous melanoma patients comparing intermediate doses of interferon-alpha-2b (IFN) with observation: Ulceration of primary is key determinant for IFN-sensitivity. Eur. J. Cancer 2016, 55, 111–121. [Google Scholar]
  58. Davar, D.; Ding, F.; Saul, M.; Sander, C.; Tarhini, A.A.; Kirkwood, J.M.; Tawbi, H.A. High-dose interleukin-2 (HD IL-2) for advanced melanoma: A single center experience from the University of Pittsburgh Cancer Institute. J. Immunother. Cancer 2017, 5, 74. [Google Scholar] [CrossRef]
  59. Jo, S.D.; Nam, G.-H.; Kwak, G.; Yang, Y.; Kwon, I.C. Harnessing designed nanoparticles: Current strategies and future perspectives in cancer immunotherapy. Nano Today 2017, 17, 23–37. [Google Scholar] [CrossRef]
  60. Wang, J.; Li, Y.; Nie, G. Multifunctional biomolecule nanostructures for cancer therapy. Nat. Rev. Mater. 2021, 6, 766–783. [Google Scholar] [CrossRef]
  61. Carnovale, C.; Bryant, G.; Shukla, R.; Bansal, V. Size, shape and surface chemistry of nano-gold dictate its cellular interactions, uptake and toxicity. Prog. Mater. Sci. 2016, 83, 152–190. [Google Scholar] [CrossRef]
  62. Yan, L.; Zhao, F.; Li, S.; Hu, Z.; Zhao, Y. Low-toxic and safe nanomaterials by surface-chemical design, carbon nanotubes, fullerenes, metallofullerenes, and graphenes. Nanoscale 2011, 3, 362–382. [Google Scholar] [CrossRef] [PubMed]
  63. Lenders, V.; Koutsoumpou, X.; Sargsian, A.; Manshian, B.B. Biomedical nanomaterials for immunological applications: Ongoing research and clinical trials. Nanoscale Adv. 2020, 2, 5046–5089. [Google Scholar] [CrossRef]
  64. Zhao, Y.-D.; Muhetaerjiang, M.; An, H.W.; Fang, X.; Zhao, Y.; Wang, H. Nanomedicine enables spatiotemporally regulating macrophage-based cancer immunotherapy. Bio-Mater. 2021, 268, 120552. [Google Scholar]
  65. Liu, T.; Wan, Q.; Luo, Y.; Chen, M.; Zou, C.; Ma, M.; Liu, X.; Chen, H. On-Demand Detaching Nanosystem for the Spatiotemporal Control of Cancer Theranostics. ACS Appl. Mater. Interfaces 2019, 11, 16285–16295. [Google Scholar] [CrossRef]
  66. Thang, D.C.; Wang, Z.; Lu, X.; Xing, B. Precise cell behaviors manipulation through light-responsive nano-regulators: Recent advance and perspective. Theranostics 2019, 9, 3308–3340. [Google Scholar] [CrossRef]
  67. Ismail, T.; Shehata, T.; Mohamed, D.; Elsewedy, H.; Soliman, W. Quality by Design for Development, Optimization and Characterization of Brucine Ethosomal Gel for Skin Cancer Delivery. Molecules 2021, 26, 3454. [Google Scholar] [CrossRef]
  68. Mohapatra, P.K.; Srivastava, R.; Varshney, K.K.; Babu, S.H. Formulation and Evaluation of Isradipine Nanosuspension and Exploring its Role as a Potential An-ticancer Drug by Computational Approach. Anti-Cancer Agents Med. Chem. 2022, 22, 1984–2001. [Google Scholar]
  69. Sokol, M.; Gulyaev, I.; Mollaeva, M.; Kuznetsov, S.; Zenin, V.; Klimenko, M.; Yabbarov, N.; Chirkina, M.; Nikolskaya, E. Box-Behnken assisted development and validation of HPLC method for simultaneous determination of doxorubicin and vorinostat in polymeric nanoparticles. J. Sep. Sci. 2022. [Google Scholar] [CrossRef]
  70. Bonaccorso, A.; Russo, G.; Pappalardo, F.; Carbone, C.; Puglisi, G.; Pignatello, R.; Musumeci, T. Quality by design tools reducing the gap from bench to bedside for nanomedicine. Eur. J. Pharm. Biopharm. 2021, 169, 144–155. [Google Scholar] [CrossRef]
  71. Hathout, R.M.; Saharan, V.A. Computer-Aided Formulation Development, in Computer Aided Pharmaceutics and Drug Delivery; Springer: Berlin, Germany, 2022; pp. 73–98. [Google Scholar]
  72. Eftekhari, A.; Ahmadian, E.; Salatin, S.; Sharifi, S.; Dizaj, S.M.; Khalilov, R.; Hasanzadeh, M. Current analytical approaches in diagnosis of melanoma. TrAC Trends Anal. Chem. 2019, 116, 122–135. [Google Scholar] [CrossRef]
  73. Balaji, A.; Zhang, J. Electrochemical and optical biosensors for early-stage cancer diagnosis by using graphene and gra-phene oxide. Cancer Nanotechnol. 2017, 8, 1–12. [Google Scholar] [CrossRef] [PubMed]
  74. Lalan, M.; Shah, P.; Barve, K.; Parekh, K.; Mehta, T.; Patel, P. Skin cancer therapeutics: Nano-drug delivery vectors—present and beyond. Futur. J. Pharm. Sci. 2021, 7, 1–25. [Google Scholar] [CrossRef]
  75. Zhang, Y.; He, X.; Zhang, Y.; Zhao, Y.; Lu, S.; Peng, Y.; Lu, L.; Hu, X.; Zhan, M. Native Mitochondria-Targeting polymeric nanoparticles for mild photothermal therapy rationally poten-tiated with immune checkpoints blockade to inhibit tumor recurrence and metastasis. Chem. Eng. J. 2021, 424, 130171. [Google Scholar] [CrossRef]
  76. Teijeira, A.; Garasa, S.; Etxeberria, I.; Gato-Cañas, M.; Melero, I.; Delgoffe, G.M. Metabolic Consequences of T-cell Costimulation in Anticancer Immunity. Cancer Immunol. Res. 2019, 7, 1564–1569. [Google Scholar] [CrossRef]
  77. Chodari, L.; Aytemir, M.D.; Vahedi, P.; Alipour, M.; Vahed, S.Z.; Khatibi, S.M.H.; Ahmadian, E.; Ardalan, M.; Eftekhari, A. Targeting Mitochondrial Biogenesis with Polyphenol Compounds. Oxidative Med. Cell. Longev. 2021, 2021, 1–20. [Google Scholar] [CrossRef]
  78. Cilingir, E.K.; Seven, E.S.; Zhou, Y.; Walters, B.M.; Mintz, K.J.; Pandey, R.R.; Wikramanayake, A.H.; Chusuei, C.C.; Vanni, S.; Graham, R.M.; et al. Metformin derived carbon dots: Highly biocompatible fluorescent nanomaterials as mitochondrial targeting and blood-brain barrier penetrating biomarkers. J. Colloid Interface Sci. 2021, 592, 485–497. [Google Scholar] [CrossRef]
  79. Xu, J.; Shamul, J.G.; Kwizera, E.A.; He, X. Recent Advancements in Mitochondria-Targeted Nanoparticle Drug Delivery for Cancer Therapy. Nanomaterials 2022, 12, 743. [Google Scholar] [CrossRef]
  80. Saha, T.; Dash, C.; Jayabalan, R.; Khiste, S.; Kulkarni, A.; Kurmi, K.; Mondal, J.; Majumder, P.K.; Bardia, A.; Jang, H.L.; et al. Intercellular nanotubes mediate mitochondrial trafficking between cancer and immune cells. Nat. Nanotechnol. 2021, 17, 98–106. [Google Scholar] [CrossRef]
  81. Yoo, Y.J.; Lee, C.H.; Park, S.H.; Lim, Y.T. Nanoparticle-based delivery strategies of multifaceted immunomodulatory RNA for cancer immunotherapy. J. Control. Release 2022, 343, 564–583. [Google Scholar] [PubMed]
  82. Tewabe, A.; Lee, C.H.; Park, S.H.; Lim, Y.T. Targeted drug delivery—from magic bullet to nanomedicine: Principles, challenges, and future perspectives. J. Multidiscip. Healthc. 2021, 14, 1711. [Google Scholar] [CrossRef]
  83. Song, M.; Liu, C.; Chen, S.; Zhang, W. Nanocarrier-Based Drug Delivery for Melanoma Therapeutics. Int. J. Mol. Sci. 2021, 22, 1873. [Google Scholar] [CrossRef] [PubMed]
  84. Yan, W.; Leung, S.S.; To, K.K. Updates on the use of liposomes for active tumor targeting in cancer therapy. Nanomedicine 2020, 15, 303–318. [Google Scholar] [CrossRef] [PubMed]
  85. Wang, Z.; Li, J.; Lin, G.; He, Z.; Wang, Y. Metal complex-based liposomes: Applications and prospects in cancer diagnostics and therapeutics. J. Control. Release 2022, 348, 1066–1088. [Google Scholar] [CrossRef]
  86. Gu, Z.; Da Silva, C.; Van Der Maaden, K.; Ossendorp, F.; Cruz, L. Liposome-Based Drug Delivery Systems in Cancer Immunotherapy. Pharmaceutics 2020, 12, 1054. [Google Scholar] [CrossRef]
  87. Sun, Z.; Wang, W.; Wang, R.; Duan, J.; Hu, Y.; Ma, J.; Zhou, J.; Xie, S.; Lu, X.; Zhu, Z.; et al. Aluminum nanoparticles enhance anticancer immune response induced by tumor cell vaccine. Cancer Nanotechnol. 2010, 1, 63–69. [Google Scholar] [CrossRef]
  88. Chattopadhyay, S.; Dash, S.K.; Mandal, D.; Das, B.; Tripathy, S.; Dey, A.; Pramanik, P.; Roy, S. Metal based nanoparticles as cancer antigen delivery vehicles for macrophage based antitumor vaccine. Vaccine 2016, 34, 957–967. [Google Scholar] [CrossRef]
  89. Safwat, M.A.; Soliman, G.M.; Sayed, D.; Attia, M.A. Fluorouracil-Loaded Gold Nanoparticles for the Treatment of Skin Cancer: Development, in Vitro Characterization, and in Vivo Evaluation in a Mouse Skin Cancer Xenograft Model. Mol. Pharm. 2018, 15, 2194–2205. [Google Scholar] [CrossRef]
  90. Rallis, K.S.; Corrigan, A.E.; Dadah, H.; George, A.M.; Keshwara, S.M.; Sideris, M.; Szabados, B. Cytokine-based Cancer Immunotherapy: Challenges and Opportunities for IL-10. Anticancer. Res. 2021, 41, 3247–3252. [Google Scholar] [CrossRef]
  91. Lin, X.; Huang, R.; Huang, Y.; Wang, K.; Li, H.; Bao, Y.; Wu, C.; Zhang, Y.; Tian, X.; Wang, X. Nanosonosensitizer-augmented sonodynamic therapy combined with checkpoint blockade for cancer immu-notherapy. Int. J. Nanomed. 2021, 16, 1889. [Google Scholar]
  92. Kim, D.; Amatya, R.; Hwang, S.; Lee, S.; Min, K.; Shin, M. BSA-Silver Nanoparticles: A Potential Multimodal Therapeutics for Conventional and Photothermal Treatment of Skin Cancer. Pharmaceutics 2021, 13, 575. [Google Scholar] [CrossRef]
  93. Evans, E.R.; Bugga, P.; Asthana, V.; Drezek, R. Metallic nanoparticles for cancer immunotherapy. Mater. Today 2017, 21, 673–685. [Google Scholar] [CrossRef]
  94. Gao, S.; Yang, X.; Xu, J.; Qiu, N.; Zhai, G. Nanotechnology for boosting cancer immunotherapy and remodeling tumor microenvironment: The hori-zons in cancer treatment. ACS Nano 2021, 15, 12567–12603. [Google Scholar] [CrossRef] [PubMed]
  95. López-Campos, F.; Candini, D.; Carrasco, E.; Francés, M.A.B.; Candini, D. Nanoparticles applied to cancer immunoregulation. Rep. Pract. Oncol. Radiother. 2019, 24, 47–55. [Google Scholar] [CrossRef] [PubMed]
  96. Singh, P.; Pandit, S.; Mokkapati, V.; Garg, A.; Ravikumar, V.; Mijakovic, I. Gold Nanoparticles in Diagnostics and Therapeutics for Human Cancer. Int. J. Mol. Sci. 2018, 19, 1979. [Google Scholar] [CrossRef] [PubMed]
  97. Chauhan, A.; Khan, T.; Omri, A. Design and Encapsulation of Immunomodulators onto Gold Nanoparticles in Cancer Immuno-therapy. Int. J. Mol. Sci. 2021, 22, 8037. [Google Scholar] [PubMed]
  98. Yoon, H.Y.; Selvan, S.T.; Yang, Y.; Kim, M.J.; Yi, D.K.; Kwon, I.C.; Kim, K. Engineering nanoparticle strategies for effective cancer immunotherapy. Biomaterials 2018, 178, 597–607. [Google Scholar] [CrossRef]
  99. Nejati, K.; Dadashpour, M.; Gharibi, T.; Mellatyar, H.; Akbarzadeh, A. Biomedical Applications of Functionalized Gold Nanoparticles: A Review. J. Clust. Sci. 2021, 33, 1–16. [Google Scholar] [CrossRef]
  100. Tamura, Y.; Ito, A.; Wakamatsu, K.; Kamiya, T.; Torigoe, T.; Honda, H.; Yamashita, T.; Uhara, H.; Ito, S.; Jimbow, K. Immunomodulation of Melanoma by Chemo-Thermo-Immunotherapy Using Conjugates of Melanogen-esis Substrate NPrCAP and Magnetite Nanoparticles: A Review. Int. J. Mol. Sci. 2022, 23, 6457. [Google Scholar] [CrossRef] [PubMed]
  101. Li, X.; Li, W.; Wang, M.; Liao, Z. Magnetic nanoparticles for cancer theranostics: Advances and prospects. J. Control. Release 2021, 335, 437–448. [Google Scholar] [CrossRef]
  102. Wu, D.; Shou, X.; Zhang, Y.; Li, Z.; Wu, G.; Wu, D.; Wu, J.; Shi, S.; Wang, S. Cell membrane-encapsulated magnetic nanoparticles for enhancing natural killer cell-mediated cancer im-munotherapy. Nanomed. Nanotechnol. Biol. Med. 2021, 32, 102333. [Google Scholar] [CrossRef] [PubMed]
  103. Farhana, A.; Koh, A.E.H.; Ling Mok, P.; Alsrhani, A.; Khan, Y.S.; Subbiah, S.K. Camptothecin Encapsulated in β-Cyclodextrin-EDTA-Fe3O4 Nanoparticles Induce Metabolic Repro-gramming Repair in HT29 Cancer Cells through Epigenetic Modulation: A Bioinformatics Approach. Nanomaterials 2021, 11, 3163. [Google Scholar] [CrossRef] [PubMed]
  104. Farhana, A.; Koh, A.E.-H.; Tong, J.B.; Alsrhani, A.; Subbiah, S.K.; Mok, P.L. Nanoparticle-Encapsulated Camptothecin: Epigenetic Modulation in DNA Repair Mechanisms in Colon Cancer Cells. Molecules 2021, 26, 5414. [Google Scholar] [CrossRef] [PubMed]
  105. Jabir, M.S.; Nayef, U.M.; Abdulkadhim, W.K.; Taqi, Z.J.; Sulaiman, G.M.; Sahib, U.I.; Al-Shammari, A.M.; Wu, Y.J.; El-Shazly, M.; Su, C.C. Fe3O4 nanoparticles capped with PEG induce apoptosis in breast cancer AMJ13 cells via mitochondrial damage and reduction of NF-κB translocation. J. Inorg. Organomet. Polym. Mater. 2021, 31, 1241–1259. [Google Scholar] [CrossRef]
  106. Volovat, S.R.; Negru, S.; Stolniceanu, C.R.; Volovat, C.; Lungulescu, C.; Scripcariu, D.; Cobzeanu, B.M.; Stefanescu, C.; Grigorescu, C.; Augustin, I.; et al. Nanomedicine to modulate immunotherapy in cutaneous melanoma (Review). Exp. Ther. Med. 2021, 21, 1–14. [Google Scholar] [CrossRef]
  107. Ahmadian, E.; Janas, D.; Eftekhari, A.; Zare, N. Application of carbon nanotubes in sensing/monitoring of pancreas and liver cancer. Chemosphere 2022, 302, 134826. [Google Scholar] [CrossRef]
  108. Hassan, H.A.; Smyth, L.; Wang, J.T.-W.; Costa, P.M.; Ratnasothy, K.; Diebold, S.S.; Lombardi, G.; Al-Jamal, K.T. Dual stimulation of antigen presenting cells using carbon nanotube-based vaccine delivery system for cancer immunotherapy. Biomaterials 2016, 104, 310–322. [Google Scholar] [CrossRef]
  109. Lima, E.N.D.C.; Piqueira, J.R.C.; Maria, D.A. Advances in Carbon Nanotubes for Malignant Melanoma: A Chance for Treatment. Mol. Diagn. Ther. 2018, 22, 703–715. [Google Scholar] [CrossRef]
  110. Behzadpour, N.; Ranjbar, A.; Azarpira, N.; Sattarahmady, N. Development of a composite of polypyrrole-coated carbon nanotubes as a sonosensitizer for treat-ment of melanoma cancer under multi-step ultrasound irradiation. Ultrasound Med. Biol. 2020, 46, 2322–2334. [Google Scholar]
  111. Wang, C.; Xu, L.; Liang, C.; Xiang, J.; Peng, R.; Liu, Z. Immunological Responses Triggered by Photothermal Therapy with Carbon Nanotubes in Combination with Anti-CTLA-4 Therapy to Inhibit Cancer Metastasis. Adv. Mater. 2014, 26, 8154–8162. [Google Scholar] [CrossRef]
  112. Dianzani, C.; Zara, G.P.; Maina, G.; Pettazzoni, P.; Pizzimenti, S.; Rossi, F.; Gigliotti, C.L.; Ciamporcero, E.S.; Daga, M.; Barrera, G. Drug delivery nanoparticles in skin cancers. Biomed. Res. Int. 2014, 2014, 895986. [Google Scholar] [CrossRef] [PubMed]
  113. Hu, J.K.; Suh, H.-W.; Qureshi, M.; Lewis, J.M.; Yaqoob, S.; Moscato, Z.M.; Griff, S.; Lee, A.K.; Yin, E.S.; Saltzman, W.M.; et al. Nonsurgical treatment of skin cancer with local delivery of bioadhesive nanoparticles. Proc. Natl. Acad. Sci. USA 2021, 118, 2020575118. [Google Scholar] [CrossRef]
  114. Xia, Y.; Wei, J.; Zhao, S.; Guo, B.; Meng, F.; Klumperman, B.; Zhong, Z. Systemic administration of polymersomal oncolytic peptide LTX-315 combining with CpG adjuvant and anti-PD-1 antibody boosts immunotherapy of melanoma. J. Control. Release 2021, 336, 262–273. [Google Scholar] [CrossRef] [PubMed]
  115. Kim, H.; Niu, L.; Larson, P.; Kucaba, T.A.; Murphy, K.A.; James, B.R.; Ferguson, D.M.; Griffith, T.S.; Panyam, J. Polymeric nanoparticles encapsulating novel TLR7/8 agonists as immunostimulatory adjuvants for enhanced cancer immunotherapy. Biomaterials 2018, 164, 38–53. [Google Scholar] [CrossRef]
  116. Todaro, B.; Achilli, S.; Liet, B.; Laigre, E.; Tiertant, C.; Goyard, D.; Berthet, N.; Renaudet, O. Structural influence of antibody recruiting glycodendrimers (ARGs) on antitumoral cytotoxicity. Biomater. Sci. 2021, 9, 4076–4085. [Google Scholar] [CrossRef]
  117. Su, L.; Feng, Y.; Wei, K.; Xu, X.; Liu, R.; Chen, G. Carbohydrate-Based Macromolecular Biomaterials. Chem. Rev. 2021, 121, 10950–11029. [Google Scholar] [CrossRef]
  118. Fruchon, S.; Poupot, M.; Martinet, L.; Turrin, C.-O.; Majoral, J.-P.; Fournié, J.-J.; Caminade, A.-M.; Poupot, R. Anti-inflammatory and immunosuppressive activation of human monocytes by a bioactive dendrimer. J. Leukoc. Biol. 2008, 85, 553–562. [Google Scholar] [CrossRef]
  119. Poupot, M.; Turrin, C.O.; Caminade, A.M.; Fournie, J.J.; Attal, M.; Poupot, R.; Fruchon, S. Poly (phosphorhydrazone) dendrimers: Yin and yang of monocyte activation for human NK cell amplification applied to immunotherapy against Multiple Myeloma. Nanomed. Nanotechnol. Biol. Med. 2016, 12, 2321–2330. [Google Scholar]
  120. Gao, Y.; Shen, M.; Shi, X. Interaction of dendrimers with the immune system: An insight into cancer nanotheranostics. View 2021, 2, 20200120. [Google Scholar]
  121. Wróbel, K.; Wołowiec, S.; Markowicz, J.; Wałajtys-Rode, E.; Uram, Ł. Synthesis of Biotinylated PAMAM G3 Dendrimers Substituted with R-Glycidol and Celecoxib/Simvastatin as Repurposed Drugs and Evaluation of Their Increased Additive Cytotoxicity for Cancer Cell Lines. Cancers 2022, 14, 714. [Google Scholar] [CrossRef] [PubMed]
  122. Inglut, C.T.; Sorrin, A.J.; Kuruppu, T.; Vig, S.; Cicalo, J.; Ahmad, H.; Huang, H.-C. Immunological and Toxicological Considerations for the Design of Liposomes. Nanomaterials 2020, 10, 190. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Gao, C.; Cheng, Q.; Li, J.; Chen, J.; Wang, Q.; Wei, J.; Huang, Q.; Lee, S.M.Y.; Gu, D.; Wang, R. Supramolecular Macrophage-Liposome Marriage for Cell-Hitchhiking Delivery and Immunotherapy of Acute Pneumonia and Melanoma. Adv. Funct. Mater. 2021, 31, 2102440. [Google Scholar] [CrossRef]
  124. Shiraishi, K.; Yokoyama, M. Toxicity and immunogenicity concerns related to PEGylated-micelle carrier systems: A review. Sci. Technol. Adv. Mater. 2019, 20, 324–336. [Google Scholar] [CrossRef] [PubMed]
  125. Ferrisse, T.M.; de Oliveira, A.B.; Surur, A.K.; Buzo, H.S.; Brighenti, F.L.; Fontana, C.R. Photodynamic therapy associated with nanomedicine strategies for treatment of human squamous cell carcinoma: A systematic review and meta-analysis. Nanomed. Nanotechnol. Biol. Med. 2021, 40, 102505. [Google Scholar] [CrossRef]
  126. Wilhelm, S.; Tavares, A.J.; Dai, Q.; Ohta, S.; Audet, J.; Dvorak, H.F.; Chan, W.C.W. Analysis of nanoparticle delivery to tumours. Nat. Rev. Mater. 2016, 1, 16014. [Google Scholar] [CrossRef]
  127. Gabizon, A.; Szebeni, J. Complement activation: A potential threat on the safety of poly (ethylene glycol)-coated nano-medicines. Acs Nano 2020, 14, 7682–7688. [Google Scholar]
  128. Stavnsbjerg, C.; Christensen, E.; Münter, R.; Henriksen, J.R.; Fach, M.; Parhamifar, L.; Christensen, C.; Kjaer, A.; Hansen, A.E.; Andresen, T.L. Accelerated blood clearance and hypersensitivity by PEGylated liposomes containing TLR agonists. J. Control. Release 2021, 342, 337–344. [Google Scholar] [CrossRef]
  129. Sharma, S.; Parveen, R.; Chatterji, B.P. Toxicology of Nanoparticles in Drug Delivery. Curr. Pathobiol. Rep. 2021, 9, 133–144. [Google Scholar] [CrossRef]
  130. Medici, S.; Peana, M.; Pelucelli, A.; Zoroddu, M.A. An updated overview on metal nanoparticles toxicity. Semin. Cancer Biol. 2021, 76, 17–26. [Google Scholar] [CrossRef]
  131. Singh, N.; Joshi, A.; Toor, A.P.; Verma, G. Drug delivery: Advancements and challenges. Nanostruct. Drug Deliv. 2017, 865–886. [Google Scholar] [CrossRef]
  132. Yan, H.; Xue, Z.; Xie, J.; Dong, Y.; Ma, Z.; Sun, X.; Kebebe Borga, D.; Liu, Z.; Li, J. Toxicity of Carbon Nanotubes as Anti-Tumor Drug Carriers. Int. J. Nanomed. 2019, 14, 10179–10194. [Google Scholar] [CrossRef]
  133. Sakamoto, Y.; Hojo, M.; Kosugi, Y.; Watanabe, K.; Hirose, A.; Inomata, A.; Suzuki, T.; Nakae, D. Comparative study for carcinogenicity of 7 different multi-wall carbon nanotubes with different physicochemical characteristics by a single intraperitoneal injection in male Fischer 344 rats. J. Toxicol. Sci.-Es 2018, 43, 587–600. [Google Scholar]
  134. Naha, P.C.; Mukherjee, S.P.; Byrne, H.J. Toxicology of Engineered Nanoparticles: Focus on Poly(amidoamine) Dendrimers. Int. J. Environ. Res. Public Health 2018, 15, 338. [Google Scholar] [CrossRef] [Green Version]
  135. Li, X.; Naeem, A.; Xiao, S.; Hu, L.; Zhang, J.; Zheng, Q. Safety Challenges and Application Strategies for the Use of Dendrimers in Medicine. Pharmaceutics 2022, 14, 1292. [Google Scholar] [CrossRef] [PubMed]
  136. Youden, B.; Jiang, R.; Carrier, A.J.; Servos, M.R.; Zhang, X. A Nanomedicine Structure–Activity Framework for Research, Development, and Regulation of Future Cancer Therapies. ACS Nano 2022, 16, 17497–17551. [Google Scholar]
  137. Sun, Y.; Guo, F.; Zou, Z.; Li, C.; Hong, X.; Zhao, Y.; Wang, C.; Wang, H.; Liu, H.; Yang, P.; et al. Cationic nanoparticles directly bind angiotensin-converting enzyme 2 and induce acute lung injury in mice. Part. Fibre Toxicol. 2015, 12, 1–13. [Google Scholar] [CrossRef]
  138. Bidram, M.; Zhao, Y.; Shebardina, N.G.; Baldin, A.V.; Bazhin, A.V.; Ganjalikhany, M.R.; Zamyatnin, A.A., Jr.; Ganjalikhani-Hakemi, M. mRNA-based cancer vaccines: A therapeutic strategy for the treatment of melanoma patients. Vaccines 2021, 9, 1060. [Google Scholar]
  139. Singh, A.; Gupta, A.; Chowdhary, M.; Brahmbhatt, H.D. Integrated analysis of miRNA-mRNA networks reveals a strong anti-skin cancer signature in vitiligo epi-dermis. Exp. Dermatol. 2021, 30, 1309–1319. [Google Scholar] [CrossRef] [PubMed]
  140. Kowalski, P.S.; Rudra, A.; Miao, L.; Anderson, D.G. Delivering the Messenger: Advances in Technologies for Therapeutic mRNA Delivery. Mol. Ther. 2019, 27, 710–728. [Google Scholar] [CrossRef]
  141. Weng, Y.; Li, C.; Yang, T.; Hu, B.; Zhang, M.; Guo, S.; Xiao, H.; Liang, X.-J.; Huang, Y. The challenge and prospect of mRNA therapeutics landscape. Biotechnol. Adv. 2020, 40, 107534. [Google Scholar] [CrossRef]
  142. Gebre, M.S.; Brito, L.A.; Tostanoski, L.H.; Edwards, D.K.; Carfi, A.; Barouch, D.H. Novel approaches for vaccine development. Cell 2021, 184, 1589–1603. [Google Scholar] [CrossRef] [PubMed]
  143. Midoux, P.; Pichon, C. Lipid-based mRNA vaccine delivery systems. Expert Rev. Vaccines 2014, 14, 221–234. [Google Scholar] [CrossRef] [PubMed]
  144. Knudson, C.J.; Alves-Peixoto, P.; Muramatsu, H.; Stotesbury, C.; Tang, L.; Lin, P.J.; Tam, Y.K.; Weissman, D.; Pardi, N.; Sigal, L.J. Lipid-nanoparticle-encapsulated mRNA vaccines induce protective memory CD8 T cells against a le-thal viral infection. Mol. Ther. 2021, 29, 2769–2781. [Google Scholar] [CrossRef] [PubMed]
  145. Chung, S.; Lee, C.M.; Zhang, M. Advances in nanoparticle-based mRNA delivery for liver cancer and liver-associated infectious diseases. Nanoscale Horizons 2022, 8, 10–28. [Google Scholar] [CrossRef] [PubMed]
  146. Miao, L.; Zhang, Y.; Huang, L. mRNA vaccine for cancer immunotherapy. Mol. Cancer 2021, 20, 1–23. [Google Scholar] [CrossRef] [PubMed]
  147. Zhang, Y.; Lin, S.; Wang, X.-Y.; Zhu, G. Nanovaccines for cancer immunotherapy. Wiley Interdiscip. Rev. Nanomed. Nanobiotech-Nology 2019, 11, 1559. [Google Scholar]
  148. Wang, Y.; Zhang, Z.; Luo, J.; Han, X.; Wei, Y.; Wei, X. mRNA vaccine: A potential therapeutic strategy. Mol. Cancer 2021, 20, 1–23. [Google Scholar] [CrossRef]
  149. Binnewies, M.; Roberts, E.W.; Kersten, K.; Chan, V.; Fearon, D.F.; Merad, M.; Coussens, L.M.; Gabrilovich, D.I.; Ostrand-Rosenberg, S.; Hedrick, C.C.; et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat. Med. 2018, 24, 541–550. [Google Scholar] [CrossRef]
  150. Feng, B.; Zhou, F.; Hou, B.; Wang, D.; Wang, T.; Fu, Y.; Ma, Y.; Yu, H.; Li, Y. Binary Cooperative Prodrug Nanoparticles Improve Immunotherapy by Synergistically Modulating Immune Tumor Microenvironment. Adv. Mater. 2018, 30, 1803001. [Google Scholar] [CrossRef]
  151. Wickström, S.L.; Lövgren, T.; Wolodarski, M.; Edbäck, U.; Martell, E.; Markland, K.; Nyström, M.; Lundqvist, A.; Jacobsson, H.; Hansson, J.; et al. Abstract CT032: Adoptive T cell transfer combined with DC vaccination in patients with metastatic melanoma. Cancer Res. 2018, 78, CT032. [Google Scholar] [CrossRef]
  152. Miki, K.; Nagaoka, K.; Harada, M.; Hayashi, T.; Jinguji, H.; Kato, Y.; Maekawa, R. Combination therapy with dendritic cell vaccine and IL-2 encapsulating polymeric micelles enhances intra-tumoral accumulation of antigen-specific CTLs. Int. Immunopharmacol. 2014, 23, 499–504. [Google Scholar] [CrossRef] [PubMed]
  153. Sabado, R.L.; Balan, S.; Bhardwaj, N. Dendritic cell-based immunotherapy. Cell Res. 2017, 27, 74–95. [Google Scholar] [CrossRef] [PubMed]
  154. Van der Waart, A.B.; Fredrix, H.; van der Voort, R.; Schaap, N.; Hobo, W.; Dolstra, H. siRNA silencing of PD-1 ligands on dendritic cell vaccines boosts the expansion of minor histo-compatibility antigen-specific CD8+ T cells in NOD/SCID/IL2Rg (null) mice. Cancer Immunol. Immunother. 2015, 64, 645–654. [Google Scholar] [CrossRef]
  155. Hobo, W.; Novobrantseva, T.I.; Fredrix, H.; Wong, J.; Milstein, S.; Epstein-Barash, H.; Liu, J.; Schaap, N.; van der Voort, R.; Dolstra, H. Improving dendritic cell vaccine immunogenicity by silencing PD-1 ligands using siRNA-lipid nanoparti-cles combined with antigen mRNA electroporation. Cancer Immunol. Immunother. 2013, 62, 285–297. [Google Scholar] [CrossRef]
  156. Ponsaerts, P.; VAN Tendeloo, V.F.I.; Berneman, Z.N. Cancer immunotherapy using RNA-loaded dendritic cells. Clin. Exp. Immunol. 2003, 134, 378–384. [Google Scholar] [CrossRef]
  157. Shadbad, M.A.; Hajiasgharzadeh, K.; Derakhshani, A.; Silvestris, N.; Baghbanzadeh, A.; Racanelli, V.; Baradaran, B. From Melanoma Development to RNA-Modified Dendritic Cell Vaccines: Highlighting the Lessons From the Past. Front. Immunol. 2021, 12, 623639. [Google Scholar] [CrossRef] [PubMed]
  158. Qian, C.; Yang, L.-J.; Cui, H. Recent Advances in Nanotechnology for Dendritic Cell-Based Immunotherapy. Front. Pharmacol. 2020, 11, 960. [Google Scholar] [CrossRef]
  159. Mohammadzadeh, Y.; De Palma, M. Boosting dendritic cell nanovaccines. Nat. Nanotechnol. 2022, 17, 442–444. [Google Scholar] [CrossRef]
  160. Achmad, H.; Ibrahim, Y.S.; Al-Taee, M.M.; Gabr, G.A.; Riaz, M.W.; Alshahrani, S.H.; Ramírez-Coronel, A.A.; Jalil, A.T.; Budi, H.S.; Sawitri, W.; et al. Nanovaccines in cancer immunotherapy: Focusing on dendritic cell targeting. Int. Immunopharmacol. 2022, 113, 109434. [Google Scholar] [CrossRef]
  161. Carlino, M.S.; Larkin, J.; Long, G.V. Immune checkpoint inhibitors in melanoma. Lancet 2021, 398, 1002–1014. [Google Scholar]
  162. Lamba, N.; Ott, P.A.; Iorgulescu, J.B. Use of First-Line Immune Checkpoint Inhibitors and Association With Overall Sur-vival Among Patients With Metastatic Melanoma in the Anti–PD-1 Era. JAMA Netw. Open 2022, 5, 2225459. [Google Scholar] [CrossRef]
  163. Chae, Y.K.; Arya, A.; Iams, W.; Cruz, M.R.; Chandra, S.; Choi, J.; Giles, F. Current landscape and future of dual anti-CTLA4 and PD-1/PD-L1 blockade immunotherapy in cancer; lessons learned from clinical trials with melanoma and non-small cell lung cancer (NSCLC). J. Immunother. Cancer 2018, 6, 1–27. [Google Scholar]
  164. Cremolini, C.; Vitale, E.; Rastaldo, R.; Giachino, C. Advanced Nanotechnology for Enhancing Immune Checkpoint Blockade Therapy. Nanomaterials 2021, 11, 661. [Google Scholar] [CrossRef] [PubMed]
  165. Nikpoor, A.R.; Tavakkol-Afshari, J.; Sadri, K.; Jalali, S.A.; Jaafari, M.R. Improved tumor accumulation and therapeutic efficacy of CTLA-4-blocking antibody using liposome-encapsulated antibody: In vitro and in vivo studies. Nanomed. Nanotechnol. Biol. Med. 2017, 13, 2671–2682. [Google Scholar] [CrossRef]
  166. Johann, K.; Bohn, T.; Shahneh, F.; Luther, N.; Birke, A.; Jaurich, H.; Helm, M.; Klein, M.; Raker, V.K.; Bopp, T.; et al. Therapeutic melanoma inhibition by local micelle-mediated cyclic nucleotide repression. Nat. Commun. 2021, 12, 1–9. [Google Scholar] [CrossRef]
  167. Zheng, C.; Zhang, J.; Chan, H.F.; Hu, H.; Lv, S.; Na, N.; Tao, Y.; Li, M. Engineering Nano-Therapeutics to Boost Adoptive Cell Therapy for Cancer Treatment. Small Methods 2021, 5, 2001191. [Google Scholar] [CrossRef]
  168. Curran, K.J.; Pegram, H.J.; Brentjens, R.J. Chimeric antigen receptors for T cell immunotherapy: Current understanding and fu-ture directions. J. Gene Med. 2012, 14, 405–415. [Google Scholar]
  169. Xu, J.; Zheng, B.; Zhang, S.; Liao, X.; Tong, Q.; Wei, G.; Yu, S.; Chen, G.; Wu, A.; Gao, S.; et al. Copper Sulfide Nanoparticle-Redirected Macrophages for Adoptive Transfer Therapy of Melanoma. Adv. Funct. Mater. 2021, 31. [Google Scholar] [CrossRef]
  170. Seitter, S.J.; Sherry, R.M.; Yang, J.C.; Robbins, P.F.; Shindorf, M.L.; Copeland, A.R.; McGowan, C.T.; Epstein, M.; Shelton, T.E.; Langhan, M.M.; et al. Impact of Prior Treatment on the Efficacy of Adoptive Transfer of Tumor-Infiltrating Lymphocytes in Pa-tients with Metastatic MelanomaImpact of Prior Treatment on TIL for Metastatic Melanoma. Clin. Cancer Res. 2021, 27, 5289–5298. [Google Scholar] [CrossRef]
  171. Liu, C.; Lai, H.; Chen, T. Boosting Natural Killer Cell-Based Cancer Immunotherapy with Selenocystine/Transforming Growth Factor-Beta Inhibitor-Encapsulated Nanoemulsion. ACS Nano 2020, 14, 11067–11082. [Google Scholar] [CrossRef]
  172. Wang, C.; Ye, Y.; Hu, Q.; Bellotti, A.; Gu, Z. Tailoring Biomaterials for Cancer Immunotherapy: Emerging Trends and Future Outlook. Adv. Mater. 2017, 29, 1606036. [Google Scholar] [CrossRef]
  173. Kim, K.-S.; Kim, D.-H.; Kim, D.-H. Recent Advances to Augment NK Cell Cancer Immunotherapy Using Nanoparticles. Pharmaceutics 2021, 13, 525. [Google Scholar]
  174. Rosenberg, S.A.; Restifo, N.P. Adoptive cell transfer as personalized immunotherapy for human cancer. Science 2015, 348, 62–68. [Google Scholar] [CrossRef] [PubMed]
  175. Blass, E.; Ott, P.A. Advances in the development of personalized neoantigen-based therapeutic cancer vaccines. Nat. Rev. Clin. Oncol. 2021, 18, 215–229. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Cancer Immune editing: Cancer cells develop and proliferate through a process of immune editing, a process based on three Es (E3), namely, elimination, equilibrium, and escape. The elimination phase is marked by the effective control of host immune surveillance and tumor removal. However, with a breach in immunosurveillance or ineffective host response, the tumor can undergo a dormant phase. Tumor dormancy is reversible and can become active in the presence of pro-tumor factors, leading to tumor proliferation and growth.
Figure 1. Cancer Immune editing: Cancer cells develop and proliferate through a process of immune editing, a process based on three Es (E3), namely, elimination, equilibrium, and escape. The elimination phase is marked by the effective control of host immune surveillance and tumor removal. However, with a breach in immunosurveillance or ineffective host response, the tumor can undergo a dormant phase. Tumor dormancy is reversible and can become active in the presence of pro-tumor factors, leading to tumor proliferation and growth.
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Figure 2. Mechanism of cancer diagnostics and therapeutics using nanosystems. (A) Nanomolecules can be functionalized with specific modulators (such as antibodies, nucleic acids, proteins, etc.) and targeted to specific cancer sites. Based on their ability to sense perturbations in pH, temperature and concentration changes, etc., signals can be generated and measured to precisely and accurately diagnose the type and stage of cancers (B) Nanosystems can be targeted to cancer microenvironment as a therapeutic modality to induce tumor regression.
Figure 2. Mechanism of cancer diagnostics and therapeutics using nanosystems. (A) Nanomolecules can be functionalized with specific modulators (such as antibodies, nucleic acids, proteins, etc.) and targeted to specific cancer sites. Based on their ability to sense perturbations in pH, temperature and concentration changes, etc., signals can be generated and measured to precisely and accurately diagnose the type and stage of cancers (B) Nanosystems can be targeted to cancer microenvironment as a therapeutic modality to induce tumor regression.
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Figure 3. Nanoimmunotherapy interface for cancers: Immunotherapeutics for cancers have used nanomaterials to boost the potential of various immunotherapy techniques such as DC vaccine, adoptive cell transfer, checkpoint inhibition, and RNA-based immunotherapeutics. The basic mechanisms are illustrated.
Figure 3. Nanoimmunotherapy interface for cancers: Immunotherapeutics for cancers have used nanomaterials to boost the potential of various immunotherapy techniques such as DC vaccine, adoptive cell transfer, checkpoint inhibition, and RNA-based immunotherapeutics. The basic mechanisms are illustrated.
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Table 1. The above table lists some types of nanoparticles commonly used in immunotherapeutic modules against various cancers. It lists the modes of surface functionalization (SF) and encapsulation (EN) with drugs, peptides, nucleic acids, etc. The immunotherapeutic and diagnostic functions of each type of nanomaterial are mentioned.
Table 1. The above table lists some types of nanoparticles commonly used in immunotherapeutic modules against various cancers. It lists the modes of surface functionalization (SF) and encapsulation (EN) with drugs, peptides, nucleic acids, etc. The immunotherapeutic and diagnostic functions of each type of nanomaterial are mentioned.
NanomaterialTypesSurface Functionalization (SF) and Encapsulation (EN)Immunotherapeutic and Diagnostic Function
LiposomesEthosomes, transfersomes, PEGylated liposomesSF: Aptamer, antibodies, proteins, peptides, small molecules, carbohydrates
EN: Hydrophobic drugs, mRNA, DNA, siRNA, imaging agents
Mechanical damage, receptor mediated targeting, vaccines, checkpoint blockers
Metallic NanoparticlesMagnetic iron (Fe3O4), Superparamagnetic iron oxide Nanoparticles (SPION), Gold (AuNP),Silver (AgNP), Glyco-gold NP, Nickle oxid (NiO), Aluminium, Titanium and Zinc oxide Al, TiO, ZnO, PallidiumSF: Antigens, adjuvants, antibodies,
EN: can be encapsulated in liposomes, dendrimers, carbon nanotubes
Photo thermal therapy, Photodynamic visualization
TME modulation (ROS generation, hypoxia relief, glutathione depletion, thermal ablation), photothermal editing, hyperthermia, sonodynamic therapy, TME reprogramming, T-cell activation
Carbon NanotubesSingle walled (SWCNTs), multiwalled (MWCNTs), fullerene encapsulated carbon nanotubesSF: shRNA, aptamers, mAb, immunotargeting short peptides, growth factors, intracellular targeting tags
EN: Fullerenes
Immunoactive compounds (genes and proteins), tumor imaging, photothermal therapy, drug and vaccine delivery, nanovaccines, antioxidants
subcellular targeting, biosensing
Polymeric NanoparticlesPoly(lactide) (PLA)
Poly(lactide-co-glycolide) (PLGA) copolymers,
Poly (ɛ-caprolactone) (PCL)
Poly(amino acids) –poly-L-lysine, poly-L-arginine
SF: Subcellular targeting chimeric proteins, pH sensitive hybrid membrane, antibodies
EN: Drugs, antigenic proteins, tumor associated antigens, aptamers and cellular receptors
Cancer vaccines, immune checkpoint inhibitors, drug targeting, TME targeting, biosensing, bioimaging,
antigen presentation, antigen internalization, TME modulation, fluorescence and photoacoustic imaging
DendrimersPolyamidoamine (PAMAM) dendrimers
Poly(propylene imine) (PPI) dendrimers
Citric acid dendrimers
Polyester dendrimer system
Polyether dendrimers.
Phosphorous dendrimers
Glycodendrimers
Carbosilane dendrimers.
SF: Imaging probes, drug, ligand, nucleic acid, cell anchors, controlled release substances, gene delivery; stimuli-response; targeted drug delivery
EN: drugs, genetic material, mRNA
Vaccines, antibodies and immunostimulation, imaging, adjuvant, antigen presentation, antigen internalization, TME manipulation, adoptive cell transfer, immunomodulation, checkpoint inhibitors
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Farhana, A. Enhancing Skin Cancer Immunotheranostics and Precision Medicine through Functionalized Nanomodulators and Nanosensors: Recent Development and Prospects. Int. J. Mol. Sci. 2023, 24, 3493. https://doi.org/10.3390/ijms24043493

AMA Style

Farhana A. Enhancing Skin Cancer Immunotheranostics and Precision Medicine through Functionalized Nanomodulators and Nanosensors: Recent Development and Prospects. International Journal of Molecular Sciences. 2023; 24(4):3493. https://doi.org/10.3390/ijms24043493

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Farhana, Aisha. 2023. "Enhancing Skin Cancer Immunotheranostics and Precision Medicine through Functionalized Nanomodulators and Nanosensors: Recent Development and Prospects" International Journal of Molecular Sciences 24, no. 4: 3493. https://doi.org/10.3390/ijms24043493

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