Immunotherapy is a rapidly advancing field of research in the treatment of conditions such as cancer and autoimmunity. Nanomaterials can be designed for immune system manipulation, with precise targeted delivery and improved immunomodulatory efficacy. Here, we elaborate on various strategies using nanomaterials, including liposomes, polymers, and inorganic NPs, and discuss their detailed design intricacies, mechanisms, and applications, including the current regulatory issues. This type of nanomaterial design for targeting specific immune cells or tissues and controlling release kinetics could push current technological frontiers and provide new and innovative solutions for immune-related disorders and diseases without off-target effects. These materials enable targeted interactions with immune cells, thereby enhancing the effectiveness of checkpoint inhibitors, cancer vaccines, and adoptive cell therapies. Moreover, they allow for fine-tuning of immune responses while minimizing side effects. At the intersection of nanotechnology and immunology, nanomaterial-based platforms have immense potential to revolutionize patient-centered immunotherapy and reshape disease management. By prioritizing safety, customization, and compliance with regulatory standards, these systems can make significant contributions to precision medicine, thereby significantly impacting the healthcare landscape.

Neoantigen peptides hold great potential as vaccine candidates for tumor immunotherapy. However, due to the limitation of antigen cellular uptake and cross-presentation, the progress with neoantigen peptide-based vaccines has obviously lagged in clinical trials. Here, a stapling peptide-based nano-vaccine is developed, comprising a self-assembly nanoparticle driven by the nucleic acid adjuvant-antigen conjugate. This nano-vaccine stimulates a strong tumor-specific T cell response by activating antigen presentation and toll-like receptor signaling pathways. By markedly improving the efficiency of antigen/adjuvant co-delivery to the draining lymph nodes, the nano-vaccine leads to 100% tumor prevention for up to 11 months and without tumor recurrence, heralding the generation of long-term anti-tumor memory. Moreover, the injection of nano-vaccine with signal neoantigen eliminates the established MC-38 tumor (a cell line of murine carcinoma of the colon without exogenous OVA protein expression) in 40% of the mice by inducing potent cytotoxic T lymphocyte infiltration in the tumor microenvironment without substantial systemic toxicity. These findings represent that stapling peptide-based nano-vaccine may serve as a facile, general, and safe strategy to stimulate a strong anti-tumor immune response for the neoantigen peptide-based personalized tumor immunotherapy.

Despite advancements in the successful use of immunotherapy in treating a variety of solid tumors, applications in treating brain tumors have lagged considerably. This is due, at least in part, to the lack of well-characterized antigens expressed within brain tumors that can mediate tumor rejection; the low mutational burden of these tumors that limits the abundance of targetable neoantigens; and the immunologically \"cold\" tumor microenvironment that hampers the generation of sustained and productive immunologic responses. The field of mRNA-based therapeutics has experienced a boon following the universal approval of COVID-19 mRNA vaccines. mRNA-based immunotherapeutics have also garnered widespread interest for their potential to revolutionize cancer treatment. In this study, we developed a novel and scalable approach for the production of personalized mRNA-based therapeutics that target multiple tumor rejection antigens in a single therapy for the treatment of refractory brain tumors.
Tumor-specific neoantigens and aberrantly overexpressed tumor-associated antigens were identified for glioblastoma and medulloblastoma tumors using our cancer immunogenomics pipeline called Open Reading Frame Antigen Network (O.R.A.N). Personalized tumor antigen-specific mRNA vaccine was developed for each individual tumor model using selective gene capture and enrichment strategy. The immunogenicity and efficacy of the personalized mRNA vaccines was evaluated in combination with anti-PD-1 immune checkpoint blockade therapy or adoptive cellular therapy with ex vivo expanded tumor antigen-specific lymphocytes in highly aggressive murine GBM models.
Our results demonstrate the effectiveness of the antigen-specific mRNA vaccines in eliciting robust anti-tumor immune responses in GBM hosts. Our findings substantiate an increase in tumor-infiltrating lymphocytes characterized by enhanced effector function, both intratumorally and systemically, after antigen-specific mRNA-directed immunotherapy, resulting in a favorable shift in the tumor microenvironment from immunologically cold to hot. Capacity to generate personalized mRNA vaccines targeting human GBM antigens was also demonstrated.
We have established a personalized and customizable mRNA-therapeutic approach that effectively targets a plurality of tumor antigens and demonstrated potent anti-tumor response in preclinical brain tumor models. This platform mRNA technology uniquely addresses the challenge of tumor heterogeneity and low antigen burden, two key deficiencies in targeting the classically immunotherapy-resistant CNS malignancies, and possibly other cold tumor types.

A critical challenge of existing cancer vaccines is to orchestrate the demands of antigen-enriched furnishment and optimal antigen-presentation functionality within antigen-presenting cells (APCs). Here, a complementary immunotherapeutic strategy is developed using dendritic cell (DC)-tumor hybrid cell-derived chimeric exosomes loaded with stimulator of interferon genes (STING) agonists (DT-Exo-STING) for maximized tumor-specific T-cell immunity. These chimeric carriers are furnished with broad-spectrum antigen complexes to elicit a robust T-cell-mediated inflammatory program through direct self-presentation and indirect DC-to-T immunostimulatory pathway. This chimeric exosome-assisted delivery strategy possesses the merits versus off-the-shelf cyclic dinucleotide (CDN) delivery techniques in both the brilliant tissue-homing capacity, even across the intractable blood-brain barrier (BBB), and the desired cytosolic entry for enhanced STING-activating signaling. The improved antigen-presentation performance with this nanovaccine-driven STING activation further enhances tumor-specific T-cell immunoresponse. Thus, DT-Exo-STING reverses immunosuppressive glioblastoma microenvironments to pro-inflammatory, tumoricidal states, leading to an almost obliteration of intracranial primary lesions. Significantly, an upscaling option that harnesses autologous tumor tissues for personalized DT-Exo-STING vaccines increases sensitivity to immune checkpoint blockade (ICB) therapy and exerts systemic immune memory against post-operative glioma recrudesce. These findings represent an emerging method for glioblastoma immunotherapy, warranting further exploratory development in the clinical realm.

Over 100 innovative in vitro transcribed (IVT)-mRNAs are presently undergoing clinical trials, with a projected substantial impact on the pharmaceutical market in the near future. Τhe idea behind this is that after the successful cellular internalization of IVT-mRNAs, they are subsequently translated into proteins with therapeutic or prophylactic relevance. Simultaneously, cancer immunotherapy employs diverse strategies to mobilize the immune system in the battle against cancer. Therefore, in this review, the fundamental principles of IVT-mRNA to its recruitment in cancer immunotherapy, are discussed and analyzed. More specifically, this review paper focuses on the development of mRNA vaccines, the exploitation of neoantigens, as well as Chimeric Antigen Receptor (CAR) T-Cells, showcasing their clinical applications and the ongoing trials for the development of next-generation immunotherapeutics. Furthermore, this study investigates the synergistic potential of combining the CAR immunotherapy and the IVT-mRNAs by introducing our research group novel, patented delivery method that utilizes the Protein Transduction Domain (PTD) technology to transduce the IVT-mRNAs encoding the CAR of interest into the Natural Killer (NK)-92 cells, highlighting the potential for enhancing the CAR NK cell potency, efficiency, and bioenergetics. While IVT-mRNA technology brings exciting progress to cancer immunotherapy, several challenges and limitations must be acknowledged, such as safety, toxicity, and delivery issues. This comprehensive exploration of IVT-mRNA technology, in line with its applications in cancer therapeutics, offers valuable insights into the opportunities and challenges in the evolving landscape of cancer immunotherapy, setting the stage for future advancements in the field.

Neoantigen-based cancer vaccines are emerging as promising tumor therapies, but enhancement of immunogenicity can further improve therapeutic outcomes. Here, we demonstrate that anchoring different peptide neoantigens on subcutaneously administered serum exosomes promote lymph node homing and dendritic cell uptake, resulting in significantly enhanced antigenicity in vitro and in vivo. Exosomes anchoring of melanoma peptide neoantigens augmented the magnitude and breadth of T cell response in vitro and in vivo, to a greater extent with CD8+ T cell responses. Simultaneous decoration of different peptide neoantigens on serum exosomes induced potent tumor suppression and neoantigen-specific immune responses in mice with melanoma and colon cancer. Complete tumor eradication and sustainable immunological memory were achieved with neoantigen-painted serum exosome vaccines in combination with programmed cell death protein 1 (PD-1) antibodies in mice with colon cancer. Importantly, human serum exosomes loaded with peptide neoantigens elicited significant tumor growth retardation and immune responses in human colon cancer 3-dimensional (3D) multicellular spheroids. Our study demonstrates that serum exosomes direct in vivo localization, increase dendritic cell uptake, and enhance the immunogenicity of antigenic peptides and thus provides a general delivery tool for peptide antigen-based personalized immunotherapy.

Immune-cell therapy and targeting therapy are in rapid development to treat tumor diseases. However, current immune-cell therapy and targeting immunotherapy often face three challenges (three Ss): safety challenges such as cytokine releasing syndrome (C.R.S.); specificity targeting problems such as low efficacy caused by off-targeting tumor cells; unsatisfying payment are confounded to clinical patients and physicians. We have been studying immunotherapy for more than thirty years, and recently, personalized immunotherapy to treat tumor disease has been proposed. After we discovered quiescent genes from immune cells within the tumor microenvironment, we set up single-cell genomics analysis, studying heterogeneous immune responses from multiple tumor antigens (neo-antigen); here, we further introduce a new generation of immunotherapy module by using a machine-learning model to assess optimal immunotherapy. The machine-learning model combined with single-cell genomic analysis can predict optimal immune-cell (such as T-cells) and other optimal targeting drugs such as PD1 and CTLA4 inhibitors for the patient to use.

Immunotherapy, including immune cell therapy and targeted therapy, is gradually developed through the ongoing discovery of molecular compounds or immune cells. Choosing the best one or the best combination of target compounds and immune-cell therapy is a challenge for clinical scientists and clinicians. We have found variable efficacy individually after tumor-infiltrating lymphocyte (TIL) therapy, and now TILs have been discovered in a group of heterogeneous immune cells. To select the best immunotherapy for each patient, we started to study TIL genomics, including single-cell mRNA differential display from TIL published in 2007 and single-cell RNA-seq from TIL published in 2013, set up TIL quantitative network in 2015, researched machine-learning model for immune therapy in 2022. These manual reports single-cell RNA-seq data combined with machine learning to evaluate the optimal compounds and immune cells for individual patients. The machine-learning model, one of artificial intelligence, can estimate targeting genomic variance from single-cell RNA-seq so that they can cover thirteen kinds of immune cell therapies and ongoing FDA-approved targeted therapies such as PD1 inhibitors, PDL1 inhibitors, and CTLA4 inhibitors, as well as other different treatments such as HDACI or DNMT1 inhibitors, FDA-approved drugs. Moreover, also cover Phase-1, Phase-2, Phase-3, and Phase-4 of clinical trials, such as TIL, CAR T-cells, TCR T-cells. Single-cell RNA-seq with an Artificial intelligence estimation system is much better than our published models from microarrays or just cell therapy. The medical goal is to address three issues in clinical immunotherapy: the increase of efficacy; the decrease of adverse effects and the decrease of the cost in clinical applications.

Neoantigens are emerging as attractive targets to develop personalized cancer vaccines, but their immunization efficacy is severely hampered by their restricted accessibility to lymphoid tissues where immune responses are initiated. Leveraging the capability of red blood cells (RBCs) to capture and present pathogens in peripheral blood to the antigen-presenting cells (APCs) in spleen, we developed a RBC-driven spleen targeting strategy to deliver DNA vaccine encoding hepatocellular carcinoma (HCC) neoantigen. The DNA vaccine-encapsulating polymeric nanoparticles that were intentionally hitchhiked on the preisolated RBCs could preferentially accumulate in the spleen to promote the neoantigen expression by APCs, resulting in the burst of neoantigen-specific T-cell immunity to prevent tumorigenesis in a personalized manner, and slow down tumor growth in the established aggressively growing HCC. Remarkably, when combined with anti-PD-1, the vaccine achieved complete tumor regression and generated a robust systemic immune response with long-term tumor-specific immunological memory, which thoroughly prevented tumor recurrence and spontaneous lung metastasis. This study offers a prospective strategy to develop personalized neoantigen vaccines for augmenting cancer immunotherapy efficiency in immune \"cold\" HCC.

Cancer vaccine-based postsurgical immunotherapy is emerging as a promising approach in patients following surgical resection for inhibition of tumor recurrence. However, low immunogenicity and insufficient cancer antigens limit the widespread application of postoperative cancer vaccines. Here, we propose a \"trash to treasure\" cancer vaccine strategy to enhance postsurgical personalized immunotherapy, in which antigenicity and adjuvanticity of purified surgically exfoliated autologous tumors (with whole antigen repertoire) were co-reinforced. In the antigenicity and adjuvanticity co-reinforced personalized vaccine (Angel-Vax), polyriboinosinic: polyribocytidylic acid (pIC) and tumor cells that have undergone immunogenic death are encapsulated in a self-adjuvanted hydrogel formed by cross-linking of mannan and polyethyleneimine. Angel-Vax exhibits an enhanced capacity on antigen-presenting cells stimulation and maturation compared to its individual components in vitro. Immunization with Angel-Vax provokes an efficient systemic cytotoxic T-cell immune response, contributing to the satisfied prophylactic and therapeutic efficacy in mice. Furthermore, when combined with immune checkpoint inhibitors (ICI), Angel-Vax effectively prevented postsurgical tumor recurrence, as evidenced by an increase in median survival of approximately 35% compared with ICI alone. Unlike the cumbersome preparation process of postoperative cancer vaccines, the simple and feasible approach herein may represent a general strategy for various kinds of tumor cell-based antigens in the inhibition of postsurgical tumor relapse by reinforced immunogenicity.