Neoantigen-based immunotherapies represent a promising frontier in cancer treatment, leveraging the body’s immune system to target TSAs [131]. These therapies encompass a variety of approaches, including vaccines, TIL therapy, TCR-T therapy, and CAR-T cells, each designed to stimulate or enhance immune responses against tumor neoantigens [132] (Figure 2). The breadth of neoantigen-targeted strategies underscores the potential for personalized cancer treatments [133, 134], emphasizing the importance of tailoring interventions to the unique antigenic landscape of individual tumors.

Neoantigen vaccines, for instance, aim to stimulate T cells by presenting neoantigen peptides or mRNA to the immune system, primarily targeting tumors such as melanoma, glioma, and lung cancer [131]. These vaccines offer advantages like non-toxicity and the ability to customize treatment for individual patients. However, challenges remain, including limited neoantigen identification and immune evasion by tumors. Despite these hurdles, studies have demonstrated the high therapeutic potential of neoantigen vaccines, particularly when combined with immune checkpoint inhibitors, leading to improved survival rates and tumor shrinkage [135, 136].

TIL therapy involves isolation, expansion, and reinfusion of TILs from the patient’s tumor to enhance antitumor activity. This approach has shown effectiveness in cancers with high TIL burden, such as melanoma and NSCLC [137, 138]. TIL therapy’s advantages include its ability to target multiple tumor mutations simultaneously and its direct engagement with the TME. However, invasive procedures for TIL harvesting and challenges related to tumor heterogeneity pose significant limitations [138]. Nonetheless, TIL therapy remains a powerful option, especially in immune-permissive tumors, with notable results in metastatic colorectal cancer [139, 140].

Combination therapies, including the use of neoantigen vaccines with TILs or immune checkpoint inhibitors, have gained attention for their synergistic effects in overcoming immune resistance [141]. As shown in Figure 2, combining these therapies can enhance the immune response by targeting multiple pathways simultaneously, particularly in cancers with high mutational burdens like melanoma and NSCLC [142, 143]. However, complex logistics, regulatory hurdles, and the risk of excessive immune activation remain barriers to widespread clinical adoption [144]. Still, the potential for achieving complete remission in refractory cancers underscores the promise of these multimodal strategies in advancing cancer immunotherapy.

Neoantigen-based therapeutic strategies represent a transformative advancement in cancer immunotherapy. These neoantigens are absent in normal tissues, allowing for precise tumor targeting with minimal risk to healthy cells [133, 145]. By focusing on these highly specific antigens, neoantigen therapies aim to harness and amplify the immune system’s natural ability to recognize and destroy malignant cells, thereby reducing the likelihood of off-target cytotoxicity and enhancing the therapeutic index [146, 147]. This precision is particularly advantageous in cancers with high mutational burdens, where the diversity of neoantigens increases the likelihood of effective immune responses [11, 148].

The principal neoantigen-based strategies include TCR-T therapy, CAR-T cell therapy, bispecific antibodies, neoantigen vaccines, TIL therapy, oncolytic virus therapies, cancer peptide vaccines, dendritic cell (DC) vaccines, and personalized multi-epitope vaccines [149]. TCR-T therapy involves the genetic engineering of autologous T cells to express TCRs capable of recognizing neoantigens presented by MHC-I molecules on the tumor cell surface [150]. CAR-T therapy modifies T cells to express synthetic antigen-binding receptors that can directly recognize tumor surface antigens without the need for MHC presentation, broadening their applicability to tumors with low MHC expression [151]. Bispecific antibodies act as immune engagers by simultaneously binding TSAs and CD3 on T cells, physically linking effector cells to tumor cells for targeted cytotoxicity [152, 153]. Neoantigen vaccines, including RNA, DNA, peptide, and DC-based platforms, work by introducing TSAs into the host to prime and expand tumor-reactive T cells [131, 154]. TIL therapy involves isolating and expanding TILs directly from the patient’s tumor, which are then reinfused into the patient to boost anti-tumor immunity [140, 155, 156]. Oncolytic virus therapies use genetically modified viruses that selectively infect and lyse tumor cells while also stimulating a systemic immune response against neoantigens released during tumor cell lysis [126]. Cancer peptide vaccines use synthetic peptides corresponding to TSAs to stimulate T cell responses, while DC vaccines involve loading patient-derived DCs with tumor neoantigens ex vivo before reinfusion [157–159]. Personalized multi-epitope vaccines combine multiple tumor neoantigens tailored to an individual’s tumor mutation profile, maximizing immune coverage [160, 161].

A comparative analysis of these neoantigen-based therapeutic strategies, evaluating critical parameters such as immune response potency, manufacturing complexity, scalability, and antigen breadth, is presented in Figure 3. TCR-T and CAR-T therapies exhibit robust immune responses but face challenges due to high manufacturing complexity and limited scalability, as they require patient-specific modifications [162, 163]. Bispecific antibodies provide a balance of moderate potency and manageable manufacturing demands, making them versatile, though still constrained by limited antigen breadth [164]. Neoantigen vaccines, while highly scalable and capable of broad antigen coverage, often elicit weaker immune responses and struggle to overcome immune suppression in advanced malignancies [146]. TIL therapy offers a potent and personalized response but relies on the availability of tumor-infiltrating cells and involves complex ex vivo expansion protocols [156]. Oncolytic viruses provide a dual mechanism of direct tumor lysis and immune activation but are often limited by pre-existing immunity against the viral vector [165, 166]. Peptide and DC vaccines offer moderate scalability and are less complex to produce but face challenges in generating sustained immune responses [167, 168]. Personalized multi-epitope vaccines maximize antigen breadth but require highly individualized tumor profiling, increasing complexity and cost [134, 141]. This comparative framework aids in selecting the optimal strategy based on clinical context and disease stage.

The development of neoantigen-based therapeutic strategies has heralded a transformative era in cancer immunotherapy, capitalizing on TSAs derived from somatic mutations [99, 169]. These neoantigens, exclusive to malignant cells and absent in normal tissues, facilitate precise tumor targeting while minimizing collateral damage to healthy tissues [11, 131, 170]. The convergence of precision medicine and immunotherapeutic innovations positions neoantigen-based therapies as a cornerstone of personalized cancer treatment [103, 169]. Their potential is particularly compelling in patients with high mutational burdens, where the presence of diverse neoantigens drives robust immune responses [171].

Technological advancements have significantly enhanced neoantigen identification and engineering, ensuring higher precision and efficacy in therapeutic development. The integration of AI and high-throughput sequencing has revolutionized neoantigen discovery [172, 173]. AI-driven algorithms analyze extensive genomic and proteomic datasets, expediting the identification of TSAs and enabling tailored treatments for individual tumor profiles [174]. Simultaneously, CRISPR/Cas9 gene-editing technology has expanded the therapeutic horizon by optimizing immune cells to improve neoantigen recognition [175]. The engineering of potent TCR-T and CAR-T cell therapies using CRISPR has been particularly impactful, overcoming challenges such as immune evasion and resistance and broadening the applicability of neoantigen-based strategies across diverse cancer types [175].

A pivotal milestone in advancing neoantigen-based immunotherapies lies in the integration of multi-omic data, including genomics, transcriptomics, proteomics, and metabolomics [176]. This comprehensive approach deepens our understanding of tumor biology, enabling the identification of a personalized, exhaustive set of neoantigens [177, 178]. Multi-omic profiling facilitates the design of immunotherapies that address both well-characterized and novel neoantigens [179, 180]. The advent of personalized multi-epitope vaccines, enriched by insights from multi-omic analyses, has demonstrated enhanced antigen selection and broadened immune coverage [181, 182]. These precision-driven vaccines underscore the transformative potential of combining molecular-level insights with immunotherapeutic strategies.

Despite their transformative promise, neoantigen-based therapies must overcome challenges such as immune evasion and tumor-mediated immunosuppression [147]. TMEs often suppress T-cell activation and proliferation, undermining therapeutic efficacy [183]. Innovative combination therapies that pair neoantigen-targeting strategies with immune checkpoint inhibitors, such as PD-1/PD-L1 or CTLA-4 blockers, show significant promise in mitigating these barriers [120, 184]. These synergistic approaches enhance immune persistence and activity, yielding improved therapeutic outcomes [185, 186]. Additionally, the use of personalized adjuvants targeting immunosuppressive pathways represents a strategic advancement. These adjuvants, when combined with neoantigen vaccines or adoptive T-cell therapies, amplify immune recognition and response, fostering a more effective anti-tumor immunity [134, 173, 187].

Emerging hybrid strategies that integrate multiple therapeutic modalities are gaining traction, addressing the inherent limitations of individual approaches. For example, combining CAR-T cell therapy with bispecific antibody treatments can overcome the antigen breadth constraints of standalone methods, providing broader tumor coverage and enhancing immune activation [188, 189]. Oncolytic viruses deliver dual benefits by directly targeting tumors and augmenting neoantigen presentation through tumor cell death and systemic immune stimulation [126]. Advances in stealth viral vectors and genetically modified oncolytic viruses address pre-existing immunity challenges, ensuring sustained therapeutic efficacy.

The scalability and accessibility of neoantigen-based therapies are critical for their global adoption. Automated, large-scale manufacturing processes are being developed to reduce production costs and streamline therapy distribution [131, 190]. These efforts aim to democratize access to advanced cancer treatments, ensuring that the benefits of precision immunotherapy reach diverse populations worldwide.

The integration of cutting-edge technologies, multi-omic approaches, and scalable production systems is driving the evolution of neoantigen-based cancer therapies [13, 191, 192]. By addressing existing challenges and harnessing emerging opportunities, the field is on the cusp of delivering highly personalized, effective, and accessible cancer treatments. These advancements mark a paradigm shift in cancer immunotherapy, offering renewed hope for improved patient outcomes across a broad spectrum of malignancies.

In personalized cancer immunotherapy, the identification and targeting of neoantigens are critical for developing tailored therapeutic strategies [13, 193]. The process begins with mutation calling, which involves the detection of genetic alterations, such as SNVs, INDELs, gene fusions, and alternative splice variants, all of which are potential sources of neoantigens [84]. Tools like INTEGRATE-neo, PAVIS, and Cancer Genome Interpreter leverage NGS data and machine learning integration to identify these mutations with high sensitivity [194–196] (Figure 4). However, challenges such as false positives from sequencing errors or low variant allele frequencies can complicate mutation detection, highlighting the need for robust validation methods in the neoantigen discovery pipeline [197].

Once mutations are identified, the next crucial step is human leukocyte antigen (HLA) typing, which determines the MHC alleles expressed by the individual. This is vital for predicting the potential presentation of peptides on the surface of tumor cells [198–200]. High-resolution genotyping tools like Polysolver and OptiType use sequence-based typing and Bayesian inference to accurately determine an individual’s HLA haplotype [201–203] (Figure 4). The accurate matching of peptides to specific MHCs is essential for the subsequent prediction of antigen presentation [17, 204, 205]. However, challenges arise in cases of low-coverage sequencing data, where the performance of HLA typing tools may be limited, necessitating further refinement of these methods for clinical applications.

HLA binding prediction is the next step, focusing on the prediction of peptide-MHC binding affinity and stability. The ability of peptides derived from mutations to bind to MHC molecules plays a pivotal role in eliciting a T-cell-mediated immune response [206, 207]. Tools such as NetMHCpan and pVAC-Seq employ advanced algorithms, including neural networks and position-specific scoring matrices, to predict the binding of peptides to MHC class I molecules (for CD8+ T cells) and class II molecules (for CD4+ T cells) [57, 172, 208] (Figure 4). These tools provide reliable predictions for peptide-MHC affinity, although they may overlook complex, non-linear binding patterns or peptide stability, which could affect the immune response. As a result, the integration of multiple prediction tools and experimental validation becomes necessary for optimizing neoantigen identification and ensuring effective immunogenicity [209].

To further refine neoantigen candidates, T cell recognition analysis assesses the likelihood of TCR binding to peptide-MHC complexes. Tools such as NetCTL and TCRMatch utilize structural modeling and TCR-peptide docking models to predict TCR interaction and immune activation [210, 211]. Despite their usefulness, these models are often complex and face challenges due to limited experimental validation data. Additionally, neoantigen ranking and prioritization tools like Neopepsee and MuPeXI evaluate immunogenicity and expression levels to prioritize the most promising neoantigens for therapeutic development [172, 212, 213]. Finally, the validation of computational predictions through experimental tools like ELISpot and MHC Tetramer assays is essential to confirm the immunogenicity of neoantigens [41, 214, 215]. While these experimental methods provide the gold standard for validation, they are labor-intensive and require specialized expertise and reagents. The integration of computational tools with experimental validation creates a comprehensive approach to neoantigen prediction, ultimately enabling the development of personalized cancer immunotherapies that target specific tumor mutations.

In the rapidly advancing field of immunogenomics, computational tools have become indispensable for neoantigen identification and immunogenicity prediction. These tools assist in pinpointing potential therapeutic targets, especially in the context of cancer immunotherapy, by predicting the ability of tumor mutations to be presented on MHC molecules and recognized by the immune system [173, 216]. Table 3 compares several prominent computational tools in this domain, each with specific functions, strengths, and limitations. These tools vary in their approach, from mutation calling and HLA typing to peptide binding prediction and T-cell recognition [217]. Despite their distinct methodologies, all these tools aim to provide accurate predictions that can aid in the development of personalized vaccines or other immunotherapies.

One of the most prominent tools is INTEGRATE-neo, which focuses on mutation calling through whole exome/genome sequencing. It employs graph-based detection, offering high sensitivity for detecting complex mutations and insertions [219]. However, its major limitation is that it is confined to specific types of mutation and may miss smaller variants. Similarly, Polysolver is a robust tool for HLA typing using Bayesian inference, which is known for its high accuracy, even with low-coverage data [201–203]. Despite its effectiveness, it is computationally intensive and demands significant processing power.

Tools such as NetMHCpan and NetMHCIIpan, which focus on HLA binding prediction, rely on neural network algorithms to predict peptide binding across various MHC alleles. While NetMHCpan offers broad allele coverage, it is constrained by sequence length limitations and may fail to predict certain peptides [221, 222]. Meanwhile, NetMHCIIpan is highly sensitive for MHC class II binding predictions, but its coverage is limited, particularly for rare alleles [241–243].

In addition to mutation calling and peptide binding prediction, several tools aim to predict T-cell recognition. NetCTL, based on machine learning, provides specific scoring for CD8+ T-cell recognition; however, it does not account for TCR structure or interactions, which can be a critical factor in immune response [41, 221, 244]. Similarly, NeoepitopePred integrates a hybrid model using support vector machines (SVM) and neural networks to predict T-cell responses, but it requires large training datasets and may overestimate some immune responses [236, 237, 245]. VAXign, a statistical modeling tool for epitope validation, can handle large peptide datasets efficiently but necessitates substantial experimental validation [230–232]. Meanwhile, the Immune Epitope Database (IEDB) is a widely recognized and extensively supported database query tool for epitope validation, although its performance may be hindered by the availability and specificity of datasets [233–235].

Together, these tools provide complementary insights into the complex process of neoantigen identification, each offering unique advantages but also facing significant challenges in terms of data coverage, computational power, and the need for experimental validation.

Neoantigens have catalyzed the development of advanced immunotherapeutic strategies for GBM. These strategies encompass a spectrum of approaches aimed at enhancing the immune system’s ability to recognize and destroy tumor cells. Personalized cancer vaccines, for instance, utilize patient-specific neoantigens to activate CD8+ and helper T cells, initiating a robust immune response [141]. However, tumor heterogeneity and immune evasion mechanisms remain significant barriers to efficacy (Table 4). To address these challenges, research has integrated vaccines with checkpoint inhibitors, demonstrating improved immune activation in GBM [263]. Future directions involve expanding vaccine applications to other tumor types and refining neoantigen identification processes to enhance immunogenicity.

Adoptive T cell therapies and TCR-engineered lymphocytes represent another pivotal class of neoantigen-focused therapies. Adoptive T cell therapies bolster tumor-specific cytotoxicity by infusing patients with expanded T cells targeting GBM-specific neoantigens (Table 4) [149]. However, sustaining T cell activity in GBM’s immunosuppressive environment is challenging [267]. Advances in cytokine supplementation, such as interleukin-2 (IL-2), have shown promise in enhancing T cell persistence and efficacy [268, 269]. Similarly, TCR-engineered lymphocytes improve tumor targeting by expressing receptors specific to neoantigens. Innovations in TCR optimization have minimized off-target effects and expanded the range of neoantigens targeted in GBM [150]. Emerging techniques aim to refine TCR engineering, leveraging combination therapies to further enhance treatment efficacy [270, 271].

CAR-T cells and oncolytic virus therapies highlight the potential of engineered and biologically driven approaches to target neoantigens (Table 4) [272]. CAR-T cells are equipped with receptors that specifically recognize GBM antigens, significantly enhancing tumor cell recognition and destruction [273, 274]. However, antigen escape and tumor heterogeneity present significant obstacles. Advanced CAR designs targeting multiple neoantigens and incorporating genetic modifications to sustain T cell activity are under investigation [275, 276]. Oncolytic virus therapies, meanwhile, employ modified viruses to selectively kill tumor cells and stimulate immune responses [123, 165]. Recent advancements in viral engineering and combinatory use with checkpoint inhibitors have demonstrated enhanced efficacy, particularly in preclinical models, underscoring the potential of synergistic therapeutic combinations [277, 278].

Emerging technologies such as CRISPR-Cas9 gene editing and peptide-based immunotherapies provide further avenues for innovation in neoantigen-targeted strategies [175, 279]. CRISPR-Cas9 has enabled precise modifications in T cells, enhancing neoantigen recognition and therapeutic outcomes in early-phase studies (Table 4) [175, 280]. Future research aims to expand its applications while addressing concerns about off-target effects and long-term safety. Peptide-based immunotherapies utilize synthetic peptides to activate immune cells against GBM-specific neoantigens. However, effective delivery remains a challenge [281, 282]. Nanoparticle-mediated delivery systems have improved peptide stability and target preclinical models, paving the way for clinical translation. Additionally, neoantigen-based biomarkers emerge as tools for monitoring therapy efficacy and guiding personalized treatments (Table 4) [134]. Non-invasive liquid biopsy techniques show potential for tracking tumor progression and detecting resistance, signaling a paradigm shift in GBM management [283].

Neoantigen-based immunotherapies represent a promising frontier in the treatment of GBM, but their clinical application faces several significant challenges [131, 261]. Among the most formidable obstacles is tumor heterogeneity, a hallmark of GBM that manifests as profound genetic and phenotypic diversity [284, 285]. This heterogeneity enables tumors to adapt swiftly to therapeutic pressures, often leading to immune escape [286]. For instance, tumor cells may lose the expression of targeted neoantigens or develop resistance mechanisms that diminish immune surveillance, ultimately limiting the efficacy of neoantigen-targeted treatments [11, 133]. Such adaptability underscores the need for strategies that can address the dynamic and heterogeneous nature of GBM [287].

The immunosuppressive TME further complicates the application of neoantigen-based immunotherapies [11, 149]. Regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and immunosuppressive cytokines like TGF-β collectively create a microenvironment that inhibits immune cell activity [288, 289]. This suppression prevents immune cells from fully engaging with and eliminating tumor cells, thereby significantly reducing the effectiveness of therapeutic interventions [290, 291]. In addition, immune evasion mechanisms, such as those mediated by the PD-1/PD-L1 and CTLA-4 pathways, further enable tumors to escape immune detection and suppression [292, 293], presenting yet another barrier to successful treatment.

To overcome these challenges, researchers are exploring combination therapies designed to enhance the efficacy of neoantigen-based immunotherapies [294]. One promising approach involves the use of immune checkpoint inhibitors, such as anti-PD-1 or anti-CTLA-4 antibodies, which block tumor-mediated immune suppression [120, 295]. These inhibitors enhance the immune system’s ability to recognize and target neoantigen-expressing cells, thereby improving therapeutic outcomes [11, 296]. Concurrently, efforts to reprogram the immunosuppressive TME by targeting Tregs, MDSCs, and immunosuppressive cytokines aim to create a more supportive environment for immune-mediated tumor destruction [288, 297].

Personalized neoantigen vaccines have emerged as a particularly compelling therapeutic strategy. These vaccines, which focus on tumor-specific neoantigens, have demonstrated the ability to elicit robust T cell responses in GBM patients, providing evidence of their potential to stimulate tailored immune responses while sparing healthy tissues [131, 161, 261]. However, several critical aspects must be optimized to fully realize their therapeutic potential, including the selection of immunogenic neoantigens, the development of efficient vaccine delivery platforms, and the refinement of dosing strategies [173]. Ensuring that the selected neoantigens are both specific to the patient’s tumor and capable of eliciting strong immune responses is paramount for the success of these therapies.

TCR-engineered lymphocytes offer another promising avenue for advancing neoantigen-based immunotherapy. These modified T cells are engineered to exhibit enhanced specificity and potency, allowing them to selectively target and eliminate neoantigen-expressing GBM cells [149]. To further enhance their effectiveness, researchers are investigating the combination of TCR-engineered lymphocytes with immune checkpoint inhibitors [270, 298]. By blocking tumor-induced immune suppression, these combinations may sustain immune responses and reduce the likelihood of tumor immune escape [299, 300].

Clinical trials investigating neoantigen-targeted therapies in GBM have provided encouraging, though preliminary, results [260, 261]. Personalized neoantigen vaccines have demonstrated their ability to activate immune responses, offering valuable insights into their therapeutic potential [134, 136, 301]. However, long-term clinical outcomes, such as survival benefits, remain to be thoroughly evaluated. Early successes in integrating neoantigen vaccines with other immunotherapeutic approaches highlight the potential of combination strategies, but additional research is needed to refine these approaches and address the immunosuppressive elements of the TME [103, 302]. Overcoming the inhibitory effects of Tregs, MDSCs, and immunosuppressive cytokines like TGF-β will be critical for improving the efficacy of neoantigen-based therapies [303, 304].

By addressing these challenges and leveraging innovative combination strategies, neoantigen-based immunotherapies have the potential to transform GBM treatment and improve patient outcomes. Continued research and clinical investigation will be essential to unlock the full therapeutic promise of these approaches.