TLS does not exist in human tissues under normal physiological conditions. It is caused by pathological conditions such as chronic inflammation or tumors, which trigger a series of complex molecular and cellular signaling pathway changes, disrupt the normal homeostasis of tissues, and lead to the formation of ectopic lymphoid structures in non-lymphoid tissues [31]. TLS shares structural features with secondary lymphoid organs, such as lymph nodes, typically including germinal centers, T cell zones, B cell zones, and high endothelial venules. However, its organizational structure is relatively looser and less mature compared to that of secondary lymphoid organs [32]. In the tumor tissue, TLS consists of B cells, T cells, DC, high endothelial venules (HEV), and a network of fibroblasts, encompassing both T cell areas and follicular B cell areas [33]. In TLS, HEVs serve a critical role as a “transportation hub.” They possess a unique structure where endothelial cells express adhesion molecules, including lymphocyte homing receptor ligands such as Mad-CAM-1, which guide lymphocytes (both B cells and T cells) from the circulation to the TLS. The presence and function of HEVs are crucial for the dynamic renewal of immune cells within the TLS and for maintaining an appropriate number of immune cells in the TLS [34]. Researchers believe that the formation of TLS may be initiated by antigen stimulation within the TME. In addition to the chemotactic role of Mad-CAM-1, chemokines such as CXCL13 and CCL21 secreted by various cells within the TME also serve as “road markers” to guide immune cells to accumulate in the tumor tissue. For instance, CXCR5-positive B and T cells are able to migrate into the tumor along a concentration gradient of CXCL13 [35]. Upon local aggregation, immune cells, particularly T cells, become fully activated in response to antigen stimulation and costimulatory signals. Activated T cells then secrete a range of cytokines, including IL-2 and IFN-γ. These cytokines, on the one hand, can enhance the activity of other immune cells, such as additional T cells and natural killer cells, thereby further amplifying the immune response; On the other hand, they can also exert a direct inhibitory effect on tumor cells, such as IFN-γ, which can inhibit tumor cell proliferation and angiogenesis [36,37]. B cells experience somatic hypermutation and undergo antibody affinity maturation in response to antigen stimulation and with the assistance of T cells. They are capable of producing high-affinity antibodies directed against tumor antigens, which can bind to antigens on the surface of tumor cells and eliminate them by activating the complement system or through antibody-dependent cell-mediated cytotoxicity (ADCC) [38]. The activation process of these immune cells is the key force behind the formation of TLS. As immune cells continuously accumulate and become activated, they interact with one another and begin to construct the cellular network structure of TLS, thereby forming a relatively mature and organized tertiary lymphoid structure. This structure plays a more effective local immune defense role and continuously attacks and monitors tumor cells [39]. In the field of medical research, TLS has been identified in various types of tumors, including lung cancer, breast cancer, and melanoma, among others [33]. The occurrence of TLS is often closely related to a better prognosis and a positive response to immunotherapy. The presence and maturity of TLS can serve as prognostic markers for certain diseases [40]. For instance, in various types of cancer, the density and maturity of intratumoral TLS are closely correlated with the patient’s survival time, treatment response, and other prognostic indicators, aiding doctors in evaluating the patient’s condition and prognosis [41].

In cold tumors, a series of intrinsic and extrinsic factors hinder the formation of TLS. These factors are intertwined and interact with each other, making the effective formation of TLS in cold tumors difficult. The overall status of the host immune system plays a crucial role in the formation of TLS within cold tumors. Cold tumor hosts are typically in a state of immunosuppression, often due to long-term radiotherapy and chemotherapy, immunodeficiency diseases, or the use of immunosuppressive drugs. This makes it challenging to form effective TLS even in the presence of tumors [42]. There is a significant presence of immunosuppressive cells, such as Treg and MDSC, within cold tumors. These cells secrete immunosuppressive factors, including TGF-β and IL-10, which inhibit the activity and proliferation of immune effector cells, thereby impeding the formation of TLS. Additionally, the reduced expression or imbalance of certain cytokines, such as IL-6 and IL-21, and chemokines like CXCL13 and CCL21, which are responsible for guiding immune cells to cluster at tumor sites, can also hinder the construction of TLS [35]. Cold tumor cells inherently possess low immunogenicity or the ability to evade the immune system. They express fewer antigens or produce immunosuppressive molecules, such as PD-L1, CTLA-4 ligand, CD73, and IDO, which complicates the immune system’s recognition and attack on tumor cells and hampers the formation of TLS [3]. The accumulation of tumor cell metabolites, such as lactic, can alter the local microenvironment, suppress immune cell function, and impede the formation of TLS [43]. Due to the plasticity of effector immune cells, they experience functional exhaustion in the cold tumor microenvironment. This affects the infiltration and organization of immune cells in cold tumors, thereby hindering the formation of TLS [44]. Similar to hot tumors, cold tumors also exhibit significant heterogeneity, with tumor cells in various regions displaying diverse gene expression, phenotypes, and functions. Despite the seemingly inconsistent tumor response to immune responses due to this heterogeneity, generally, all regions of the cold tumor manifest a relatively uniform state of immunosuppression, which hampers the formation of cold tumor TLS [1]. Additionally, the abnormal structure of tumor blood vessels and the accumulation of matrix components create a physical barrier that hinders immune cells from infiltrating the tumor, thus presenting obstacles to the generation of TLS [45].

In conclusion, intrinsic factors that hinder the formation of TLS in cold tumors encompass characteristics of tumor cells, expression of immunosuppressive molecules, and metabolic characteristics. Extrinsic factors include inadequate infiltration of immune cells, the presence of immunosuppressive cells, and specific cytokines such as IL-7, IL-15, IL-21, and CXCL13, which are required for the formation of TLS in the cytokine environment. These adverse factors intertwine and interact, creating a vicious cycle that permeates various stages of TLS formation, such as the recruitment, migration, activation, and proliferation of immune cells, as well as the maturation and maintenance of TLS. In cold tumors, the disorder in TLS formation results in a compromised tumor immune microenvironment, reduced treatment efficacy, a higher risk of recurrence and metastasis, a lower survival rate, and a poor prognosis. On the other hand, if we can intervene and regulate these factors using innovative methods, it is anticipated that we can promote the formation of TLS in cold tumors, thereby improving the efficacy of immunotherapy.

Metabolomics is a scientific discipline that concentrates on the study of all metabolites and their alterations within organisms. In recent years, it has been extensively applied in cancer research. During the growth, proliferation, and invasion of tumor cells, they exhibit a comprehensive and complex phenomenon of metabolic reprogramming that is markedly different from that of normal cells. This metabolic reprogramming not only aids tumor cells in adapting to the harsh microenvironment but also holds significant implications for tumor development and treatment.

There are numerous differences in metabolomics between cold tumors and hot tumors, reflecting the distinct characteristics of these tumor types in energy metabolism and immune microenvironment, among other aspects. These differences are outlined below: A. Glucose metabolism. The Warburg effect in tumor cells is described in Section 2.1. Due to the reduced infiltration of immune cells in cold tumors, the uptake and utilization of glucose by these tumor cells is relatively more pronounced. Consequently, cold tumors often exhibit a higher rate of glycolysis. B. Fatty Acid Metabolism. Cold tumor cells exhibit increased uptake and oxidation of fatty acids. Within the hypoxic tumor microenvironment, these cells utilize fatty acid oxidation to generate energy by up-regulating proteins associated with fatty acid uptake. Additionally, fatty acid metabolites can function as signaling molecules, regulating the proliferation and survival of tumor cells [46]. Fatty acid utilization by immune cells is relatively high in hot tumors, which may limit fatty acid metabolism in tumor cells. Cold tumors and hot tumors exhibit different characteristics in the composition and properties of fatty acids. Cold tumors may contain a higher proportion of unsaturated fatty acids, which can alter the fluidity and function of the cell membrane, thereby affecting the signaling and immune escape ability of tumor cells. In contrast, the fatty acid composition of hot tumors is more “healthy,” which is more conducive to the normal function of immune cells [47]. C. Amino Acid Metabolism. Glutamine Metabolism: Glutamine metabolism is pivotal as it serves as a key energy source and biosynthetic precursor for tumor cells. Typically, cold tumor cells exhibit high expression of glutaminase, enabling them to uptake and metabolize glutamine in substantial amounts to support their rapid proliferation. This aberrant glutamine metabolic activity disrupts the amino acid equilibrium within the tumor microenvironment, subsequently impacting the function of immune cells. In contrast, hot tumors have tumor cells that are less reliant on glutamine, permitting immune cells to utilize glutamine more effectively to sustain their activity and function [48]. Beyond abnormal glutamine metabolism, cold tumors also exhibit other amino acid metabolism disorders, including imbalances in arginine and tryptophan metabolism. Regulatory T cells deplete arginine by increasing arginase activity, thereby suppressing the function of effector T cells and enhancing the immunosuppressive microenvironment. In contrast, such occurrences are less common in hot tumors, where the amino acid microenvironment surrounding immune cells is more conducive to their immune surveillance and cytotoxic functions [49]. Key enzymes such as IDO1 and tryptophan 2,3-dioxygenase (TDO), which are responsible for catalyzing the conversion of tryptophan to kynurenine (Kyn) and other metabolites, are upregulated in a variety of cold tumors. Kyn and its derivatives can bind to aryl hydrocarbon receptor (AhR) and activate AhR signaling pathway, thereby inhibiting the function of effector T cells, enhancing the stability and immunosuppressive ability of regulatory T cells, creating an immunosuppressive microenvironment conducive to tumor growth, and making cold tumors easier to escape immune surveillance and attack [50]. D. Nucleotide Metabolism. The rapid proliferation of cold tumors necessitates substantial quantities of nucleotides for DNA and RNA synthesis; thus, their nucleotide synthesis pathways are typically highly active [51]. Tumor cells supply the essential material for cell proliferation by enhancing nucleotide synthesis pathways. In the tumor microenvironment, the activation and proliferation of immune cells also consume a significant amount of nucleotides. Consequently, the nucleotide metabolism of tumor cells may be regulated by factors secreted by immune cells, potentially leading to a relatively “normal” nucleotide metabolism. Certain nucleotide metabolism products play immunomodulatory roles within the tumor microenvironment. For instance, adenosine accumulates in the cold tumor microenvironment and binds to adenosine receptors on immune cell surfaces, inhibiting their activity and thereby promoting immune tolerance [52]. Adenosine levels in hot tumors are relatively low, and their immunosuppressive effects are weak.

The application of metabolomics techniques, including nuclear magnetic resonance spectroscopy and mass spectrometry, has revealed significant differences in the metabolite profiles of cold tumors compared to hot tumors. In addition to metabolites from glycolysis, fatty acid metabolism, amino acid metabolism, and other pathways, cold tumors also contain specific metabolites related to tumor proliferation and invasion, such as matrix metalloproteinases (MMPs) and microRNAs (miRNAs). Among these specific metabolites, miR-21 is highly expressed in various cold tumors. It can regulate several biological behaviors, including cell proliferation, apoptosis, and invasion, and by binding to target genes, it inhibits their expression, thereby promoting tumor development [53,54]. Metabolites associated with immune activation and inflammation, such as IFN-γ and IL-6, were highly enriched in hot tumors. Metabolic pathway analysis revealed that cold tumors were primarily enriched in pathways closely related to tumor cell proliferation and survival, including glycolysis/gluconeogenesis, fatty acid synthesis, and amino acid biosynthesis. Conversely, hot tumors exhibited greater enrichment in pathways related to immune response, such as purine metabolism, unsaturated fatty acid metabolism, and amino acid, sugar, and ribose metabolism.

These metabolic abnormalities not only provide the energy and material foundation for the growth and proliferation of tumor cells but also further impair the anti-tumor immune response by affecting the metabolic state and function of immune cells. Through metabolomics studies, metabolic markers associated with cold tumor formation and immunotherapy efficacy can be identified, offering a new perspective for the development of personalized treatment strategies.

Multidimensional omics refers to a research approach that integrates multi-level data, such as genomics, transcriptomics, proteomics, and metabolomics, to systematically analyze biological characteristics [55]. With the continuous advancement of high-throughput sequencing technology and bioinformatics, multidimensional omics research has garnered increasing attention in the field of oncology. This approach can comprehensively unveil the molecular mechanisms underlying tumorigenesis and development. In the field of cold tumor research, multi-dimensional omics analysis plays a crucial role in uncovering key molecules and signaling pathways associated with tumor immune escape, the development of immunosuppressive microenvironments, and the efficacy of immunotherapy. By integrating multi-dimensional omics data, researchers can construct a more precise molecular classification system for cold tumors, thus offering a robust scientific foundation for the formulation of personalized treatment strategies. In addition to the metabolomic approaches mentioned above, the application of genomics can also assist us in identifying mutations in tumor driver genes [55]. Utilizing advanced technologies such as whole-genome sequencing or targeted sequencing, we are able to uncover key gene mutations in cold tumors. For instance, in breast cancer studies, certain cold tumors have been found to harbor specific genetic mutations that may cause tumor cells to evade effective recognition and attack by the immune system [56]. Genomics can also uncover genetic differences within a cold tumor, or between various tumor cell clones, known as tumor heterogeneity. This heterogeneity might result in varied responses of tumors to immunotherapy, potentially influencing the overall treatment efficacy [57].

Transcriptomics enables the analysis of immune-related gene expression. Utilizing transcriptome sequencing technology, we can identify the expression levels of various immune-related genes in cold tumors, encompassing cytokines, chemokines, immune checkpoint molecules, and other categories. The low or high expression of specific immune-related genes may be closely associated with the immunosuppressive state of cold tumors, offering significant clues for the exploration of potential immunotherapy targets [58]. Additionally, transcriptomics can uncover novel immune cell subsets and molecular markers, aiding in the identification of unique immune cell subsets or molecular markers in cold tumors. These discoveries are crucial for a deeper comprehension of the complexity within the cold tumor immune microenvironment and offer a scientific foundation for the development of innovative immunotherapy strategies [59].

Proteomic techniques, such as mass spectrometry, facilitate the identification of immunomodulatory proteins. Through these methods, researchers can uncover the expression patterns of proteins in cold tumor tissues and their microenvironment, including immunomodulatory and signaling pathway-related proteins. These proteins are crucial for the activation, proliferation, migration, and functional regulation of immune cells. Abnormal expression levels of these proteins may be closely associated with the formation and maintenance of the cold tumor immune microenvironment [60]. By analyzing protein-protein interactions and constructing a network of these interactions, we can uncover the complex signal transduction pathways between immune cells and tumor cells in cold tumors, as well as the synergistic or antagonistic effects among immune cells. This provides a foundation for identifying key therapeutic targets and intervention pathways [60].

Single-cell omics technology enables the analysis of immune cell heterogeneity. Utilizing single-cell transcriptome sequencing, we have been able to analyze each cell in cold tumors with high precision, thereby revealing the heterogeneity and fine subpopulation classification of TME cells [61]. This offers insight into the functional status, differentiation processes, and interactions of various cell subsets within the cold tumor microenvironment, as well as their mechanisms of action in immune escape and tumor progression. Utilizing single-cell omics allows for the monitoring of dynamic changes in immune cells during the onset, development, and treatment of cold tumors in real-time, including alterations in cell numbers, subset proportions, functional statuses, and other aspects. This provides a crucial foundation for evaluating the efficacy of immunotherapy, predicting disease progression, and formulating personalized treatment strategies [62].

Spatial transcriptomics enables the mapping of the spatial distribution of immune cells within tissues, allowing researchers to simultaneously capture both the spatial location information of cells and gene expression data on tissue sections. This capability enables investigators to visually reveal the spatial distribution characteristics of immune cells in cold tumors. For instance, studies have identified that the distribution of immune cells in cold tumors is heterogeneous, with lower infiltration of immune cells in certain areas. Additionally, while there may be clusters of immune cells in other areas, these cells could be functionally suppressed [63]. This spatial distribution information is crucial for understanding the interaction between immune cells and tumor cells and for enhancing the precision of immunotherapy. The application of spatial transcriptomics helps to reveal the spatial association and interaction network among various cell types in the cold tumor microenvironment, including proximity effects and signal transmission between immune cells and tumor cells, stromal cells, vascular endothelial cells, etc. By constructing a tumor microenvironment map with high spatial resolution, the biological characteristics of cold tumors can be more deeply understood, and more accurate targets and basis for the development of targeted treatment strategies can be provided [64].

Multidimensional omics research will generate massive data, and its analysis process is extremely complex. Artificial intelligence-based data integration and analysis is undoubtedly a key development direction in the future research field. Through the use of machine learning algorithms, including support vector machine (SVM), random forest (RF), and deep learning, multi-omics data are trained and learned to construct prediction models. This enables a detailed analysis of the mechanisms of cold tumors and the prediction of their clinical outcomes and treatment responses. For instance, employing deep learning algorithms for feature learning and model building on integrated multi-omics data can enhance the diagnostic accuracy and prognosis prediction capabilities for cold tumors [65]. Utilizing the theories and methodologies of network pharmacology and systems biology, researchers have developed a multi-omics network model for cold tumors. This model encompasses a gene-protein-metabolite interaction network and a signaling pathway network. Through network analysis and simulation techniques, researchers have pinpointed key nodes and modules, offering novel insights for the discovery of therapeutic targets and the development of drugs for cold tumors [66].

In conclusion, by integrating multi-omics data for analysis, we can comprehensively delineate the characteristics of cold tumors. The integration of genomics, transcriptomics, proteomics, and other omics data can help to deeply describe the molecular characteristics, immune microenvironment characteristics, and biological behavior of cold tumors from multiple dimensions, and then construct a more comprehensive and accurate cold tumor disease model. This will lead to a deeper understanding of the pathogenesis of cold tumors, immune escape strategies, and mechanisms of response to therapy. The integrated analysis of multi-omics data can systematically reveal potential therapeutic targets and diagnostic markers, which may cover multiple levels such as genes, proteins, metabolism, and are closely related to the immune microenvironment and pathophysiological processes of cold tumors. This provides richer resources and more precise directions for the development of new therapeutic drugs and diagnostic methods. For summary information on multiomics in the analysis of different types of cold tumor studies, refer to Table 2.

Tumor vaccine technology has shown great potential in theory and research to elicit responses from “cold tumors.” In recent years, remarkable progress has been made at various stages of promoting tumor immune responses, significantly enhancing the effectiveness of tumor vaccine therapy. The innovations cover multiple aspects, including antigen design, antigen presentation mediated by MHC molecules, the activation and maturation of DCs, and the specific activation and expansion of T cells. The details are as follows:

(1) Innovative Antigen Design and Delivery: Optimizing antigen design and delivery in novel vaccines can break through the “invisible” barrier of tumors. However, Ma et al. [84] developed a Globo H hexosaccharide antigen via a comprehensive chemical-enzymatic synthesis process. This antigen was effectively conjugated with the non-toxic mutant CRM197 protein, resulting in the creation of the Globo H-CRM197 vaccine. Furthermore, they integrated a modular synthetic adjuvant, 3D-MPL (3-O-deacyl monophosphatidylcholine), into the formulation. This inclusion provided a structurally well-defined and controllable Toll like receptor 4 (TLR4) agonist adjuvant, enhancing the vaccine’s efficacy. This synergistic driving strategy successfully transformed the tumor antigen from a state of “immune escape” to one of “efficient activation”. Fu et al. [85] utilized the in vivo immune memory of known antigens to treat tumors. Unlike traditional antigen vaccines, the innovative mRNA vaccine does not directly encode intrinsic tumor antigens. Instead, it reprograms tumor tissue in situ to activate existing memory effector T cells. Firstly, an mRNA vaccine was constructed using egg white protein (cOVA) as the model antigen. In vitro and in vivo experiments demonstrated that the mRNA vaccine could effectively reprogram tumor cells, subsequently inducing effector T cells to specifically recognize and kill tumor cells in the mouse model with established immune memory. The study revealed that the vaccine demonstrated a robust anti-tumor effect in three mouse models of solid tumors—melanoma, breast cancer, and colon cancer—and was able to effectively enhance the infiltration and activation of Teff cells at the tumor sites. Upon combining bulk RNA-seq and single-cell RNA-seq analyses, it was discovered that the vaccine could reconfigure the TME to exhibit inflammatory characteristics and bolster the cytotoxic capabilities of effector memory T cell subsets [85]. Compared to traditional vaccine design strategies, the importance of selecting antigens with high specificity and high immunogenicity (TAA and TSA) has significantly diminished, focusing more on the in situ expression ability of immune memory antigens within the tumor. This provides a novel approach to the development of tumor vaccines.

(2) Promote DC Activation and Enhance Antigen Presentation Efficiency: The latest technical approaches to DC activation vaccines concentrate on enhancing targeting, immunogenicity, and combined therapeutic efficacy. Vaccines significantly enhance antigen presentation efficiency by directly targeting antigen-presenting cells (APCs) and streamlining the antigen recognition and processing mechanism. Lopez et al. [86] reported a DC-targeted mRNA delivery system that identifies up to 20 novel antigens by sequencing clinical patients’ blood and tumor tissues. These antigens are encoded into two mRNA molecules using a liposome nanoparticle (LNP) formulation designed to passively target APCs, particularly DCs, in lymphoid organs. The system activates DCs via the TLR7/8-mediated type I interferon pathway, thereby enhancing co-stimulatory signals and antigen presentation efficiency. This method efficiently delivers personalized neoantigens, thereby activating a potent and long-lasting T-cell immune response and inducing a new (de novo) CD8⁺ and CD4⁺ T-cell response. In some patients, the frequency of antigen-specific TCRs in peripheral blood CD8⁺ T cells can reach as high as 5%–20% [86]. Polyzoidis and Ashkan [87] reported on an autologous DC vaccine that utilizes pulsed DC cells derived from tumor lysates of patients. This method significantly improves the presentation efficiency of MHC class I and II-associated peptides (in a single sample, 4386 MHC class I-related peptides showed at least a 1.5-fold enrichment, while 7224 MHC class II-related peptides achieved at least a 1.5-fold enrichment). Furthermore, the DC vaccine expresses key co-stimulatory molecules such as CD40, CD80, CD86, and CD141, which effectively promote DC-T cell interaction, thereby enhancing antigen presentation and T cell activation. Currently, the project is conducting Phase III clinical trials for newly diagnosed patients [87]. Some nano-adsorbents also significantly improve the cross-presentation efficiency of MHC molecules by enhancing antigen uptake and processing. For instance, metal-organic framework (MOF) nanoparticles can efficiently load antigens and prevent the clearance of apoptotic cancer cells by blocking cellular phagocytosis. This leads to the accumulation of damage-associated molecular patterns (DAMPs) and promotes the presentation of antigen MHC class I molecules, thereby enhancing the anti-tumor immune response [88]. Furthermore, genetically engineered DCs have garnered significant attention, particularly through cytokine-armed dendritic cell progenitors (DCPs). By engineering these cells to express two immunostimulatory cytokines—IL-12 and fms-related tyrosine kinase 3 ligand (FLT3L)—DCPs can activate multiple immune cell types and significantly enhance therapeutic efficacy [89]; Vaccine design that targets specific DC subsets, when used in conjunction with immune checkpoint blockade therapy, can significantly enhance therapeutic efficacy. For instance, the combination of a cDC1 vaccine with PD-1 and CTLA-4 inhibitors can activate CD8⁺ T cells and induce long-lasting immune memory, effectively suppressing tumor recurrence [90].

(3) Strengthen Personalized Vaccine Research and Development for Tumor-Specific Neoantigens: Utilizing genomic sequencing technology and artificial intelligence algorithms, vaccines are designed with a focus on new epitopes generated by tumor-specific mutations. These serve as the core targets, allowing for the accurate prediction of their binding affinity with patients’ MHC molecules, thereby achieving individualized adaptation [91]. Braun et al. [91] conducted deep sequencing (with an average tumor sequencing depth of up to 200x) on tumors and normal tissues from each patient with clear cell renal cell carcinoma (RCC) to identify tumor-specific nonsynonymous mutations (SNV/Indel) and expression mutations as potential candidates for new antigen sources. “NetMHCpan 4.0,” an AI-driven algorithm for antigen prediction, forecasts the IC50 binding affinity between mutated peptides and patients’ HLA-A/B/C alleles. Utilizing an immunogenicity scoring model that evaluates various parameters comprehensively, such as peptide-MHC binding stability (NetMHCStabPan), proteasome cleavage (NetChop), TAP transport (NetCTLpan), and gene expression (TPM>10), it identifies the top 1% of high-confidence neoantigens to develop personalized neoantigen vaccines, known as “PCVs”. This study pioneers the establishment of a comprehensive closed-loop system encompassing “whole-genome analysis, AI prediction, and individualized vaccine development” within the field of renal cell carcinoma (RCC). It demonstrates that AI algorithms can accurately identify effective new antigens in tumors characterized by a low mutation load, offering a model for the clinical application transformation. The WT1-DC vaccine, developed by Nagai and Karube [92], utilizes tumor tissue samples from patients. Immunohistochemistry (IHC) confirmed high WT1 protein expression (≥3+) and peripheral blood HLA typing of A*24:02. The vaccine demonstrates high affinity binding to the WT1 peptide 235–243 (CYTWNQMNL), forming an “individualized antigen-target” that enhances the immune response and prolongs survival. The clinical transformation technology core of individualized mRNA cancer vaccines encompasses multiple professional fields, such as tumor immunology and bioinformatics. It includes rapid new epitope prediction based on high-throughput sequencing technology, precise identification of tumor-specific antigens through algorithm models; verification of MHC molecule binding using structural biology and molecular biology methods; and mRNA sequence optimization technology based on RNA chemistry and synthetic biology, which involves adjusting the primary and secondary structures of mRNA to enhance its stability and translation efficiency within cells. The comprehensive application of these technologies enables individualized mRNA cancer vaccines to precisely target a variety of cancer indications, offering cancer patients more personalized and efficient treatment options [93,94].

ACT involves extracting immune-active cells from the body of a cancer patient, expanding and functionally modifying them in vitro. After rigorous identification and qualification, these cells are reintroduced into the patient’s body, aiming to directly eliminate tumor cells or activate the body’s anti-tumor immune response [95]. In recent years, significant progress has been made in the research of activating cold tumors through ACT Therapy. The following will elaborate from four perspectives.

Tumor Infiltrating Lymphocyte (TIL) Therapy: Breaking through the Immunoinfiltration Bottleneck of Cold Tumors

TIL therapy entails extracting lymphocytes from a patient’s tumor tissue, expanding them in a laboratory setting, and subsequently reintroducing them into the patient to enhance their ability to target and destroy the tumor. TIL therapy is particularly suitable for activating the immune response against cold tumors due to its natural ability to recognize a variety of tumor antigens. It is the first cell immunotherapy approved for the treatment of solid tumors, including metastatic melanoma. In patients with advanced metastatic melanoma, TIL therapy can achieve a “persistent complete response (CR)” and demonstrates potential curative effects, even for those previously unresponsive to immunotherapy. A randomized controlled trial (involving a Dutch/Danish cohort of 168 patients showed that the TIL group achieved an overall response rate (ORR) of 49% compared to 21% in the Ipilimumab group; a complete response rate (CR) of 20% vs. 7%; and a median progression-free survival (PFS) of 7.2 months vs. 3.1 months. Currently, this therapy has been approved by the FDA for use in patients resistant to immune checkpoint inhibitors, such as anti-PD-1 [96]. Furthermore, TIL therapy has demonstrated significant potential in treating solid tumors, including non-small cell lung cancer, colorectal cancer, and breast cancer [96–98]. Sim et al. [99] completely eliminated the tumor and maintained remission for 35 months by isolating TILs naturally present in the tumor of a metastatic colorectal cancer patient that could recognize the mutant KRAS (KRAS G12D) neoantigen, expanding them in vitro, and reinfusing them. According to the latest statistics from the Clinicaltrials.gov database (www.clinicaltrials.gov), as of May 2025, there were 128 clinical trials of TIL anti-tumor therapies in progress or planned to recruit participants worldwide, with 71 having completed recruitment. Additionally, three trials are in phase III, and one is in phase IV.

Cell Receptor Engineered T Cell Therapy-T Cell Receptor Engineered T Cell Therapy (TCR-T): Precisely Targeting Cold Tumor Antigens

Scientists are employing gene editing technology to introduce specific TCR genes into patients’ T cells, genes that can recognize specific cancer antigens. This process equips the T cells with the ability to specifically identify and eliminate tumor cells, thereby improving the recognition efficiency of low-expressing tumor antigens. Both TCR-T therapy and Chimeric antigen receptor-T (CAR-T) therapy are integral to ACT, yet they differ significantly. CAR-T cells are engineered by inserting a DNA sequence that encodes a chimeric antigen receptor into the patient’s own T cells. The CAR recognizes antigens via the single-chain variable fragment of an antibody. It can only recognize specific antigens on the surface of tumor cells. Traditional CAR T-cells require a relatively high concentration of target antigens to activate and possess rapid and continuous killing abilities, achieving remarkable results in the field of hematologic tumor treatment [100]. In contrast, TCR-T therapy demonstrates greater potential in combating solid tumors, as these tumors often lack distinct biomarkers on their cell surfaces [101]. TCR-T cells recognize tumor antigen peptides presented by MHC molecules through their T cell receptors (TCRs). These antigens, which may originate from intracellular proteins such as tumor-associated antigens, are processed by MHC class I (or II) molecules and presented on the cell surface. Unlike CAR-T cells, which specifically target surface antigens, TCR-T cells can identify antigens derived from both membrane-bound and intracellular proteins, thereby expanding the range of targets they can attack [102]. TCR-T cells only need a very small amount of target antigens to activate, and are more sensitive to low copy number antigens than CAR-T cells. Although their cytotoxicity is slower, it lasts longer [103,104]. In recent years, TCR-T therapy has made significant progress in technological innovation. Kuilman et al. [105] utilized tumor mutation and T-cell receptor (TCR) repertoire analysis, high-throughput DNA synthesis, and functional genetic screening to identify tumor neoantigen-specific TCRs, including those restricted by HLA class I and class II molecules, from inactive frozen tumor biopsy samples. The identified tumor-specific TCRs were transduced into the patient’s autologous T cells using bicistronic vectors, such as those with P2A-linked TCRα/β. After the quantity and function of these cells were enhanced, they were infused back into the patient for treatment. The breakthrough at the core of this innovative research, particularly applicable to solid tumors where tissue is scarce or the mutational burden is low, marks the beginning of translating previously deemed “infeasible” frozen-biopsy techniques into “personalized TCR-T therapy”. Neoantigen-driven TCR-T therapy offers a promising platform for precision immunotherapy of solid tumors. Nonetheless, optimizing antigen screening, enhancing the hit rate, establishing a standardized GMP process, and conducting larger clinical trials to verify its safety and efficacy are still necessary steps [106]. The development of allogeneic TCR-T cell therapy has also become one of the hotspots of current research. By simultaneously deleting the endogenous TCRα and TCRβ chains and inserting the transgenic TCR into the TRAC locus, the risk of graft-vs.-host disease can be avoided [107]. Combining gene editing technology, by engineering the induction of HLA-I molecule deletion and combining with NK cell inhibition, the host immune system’s rejection of allogeneic T cells can be further reduced, which is expected to achieve universal TCR-T cell therapy [105]. Switchable T cell Antigen Receptor (STAR)-T cell therapy is an innovative chimeric antigen receptor T cell therapy that combines the high affinity of antibodies with the high sensitivity of TCRs, aiming to enhance the recognition and killing ability of tumor cells. Through the carefully designed synthetic TCR and antigen receptor, STAR-T cell therapy can identify and target tumor neoantigens presented by HLA-I without relying on the CD8 co-receptor, thereby achieving a synergistic anti-tumor effect of CD8⁺ and CD4⁺ T cells [108]. Research findings that the combination of TCR-T therapy with PD-1 inhibitors or other therapies is expected to enhance the inhibitory effect of overcoming the cold tumor microenvironment, thus further improving the therapeutic effect of anti-cold tumors [102,109].

According to the latest statistics from the Clinicaltrials.gov database, there are a total of 99 ongoing or planned TCR-T anti-tumor clinical trials worldwide. These trials cover a range of solid tumor types, including but not limited to melanoma, lung cancer, liver cancer, and ovarian cancer. The development of these studies is expected to thoroughly verify the safety and efficacy of TCR-T therapy, and to further explore its potential in combination with other immunotherapies. This could provide new treatment options for patients with difficult-to-treat cancers and offer effective strategies for transforming “cold tumors” into “hot tumors”.

Memory T Cell Therapy: Enhancing Immune Persistence

Autologous memory T cell therapy for cancer is an advanced immunotherapy approach that has shown great potential in the field of cancer treatment in recent years. Memory T cells, encompassing central memory T cells (TCMs) and tissue-resident memory T cells (TRM cells), have become an important strategy for enhancing the efficacy of cold tumor treatments due to their long-term persistence, rapid response, and self-renewal capabilities. Particularly, TRM cells can survive for extended periods within tissues or tumor microenvironments, continuously patrol and monitor tumor cells, respond rapidly to antigen stimulation, and enhance the infiltration of immune cells in cold tumors. Fu et al. [110] utilized CRISPR-Cas9 gene editing technology to examine the precise effects of IL-2-induced T cell kinase (ITK) deletion on the therapeutic efficacy of CD19-CAR-T cells. ITK deficiency has been found to decrease the expression of co-inhibitory molecules associated with T-cell exhaustion, including PD-1, TIM-3, LAG-3, TIGIT, and CTLA4. CAR-T cells with an ITK gene knockout exhibit a reduced proportion of exhausted cells and an increased proportion of memory cells in animal models, effectively eliminating tumors and enhancing survival rates [110]. Mai et al. [111] utilized CRISPR-Cas9 RNP electroporation to effectively knock out Regnase-1 and Roquin-1, which are genes that regulate T cell inflammation. T cells with a double knockout (DKO) of Regnase-1 and Roquin-1, when engineered into CAR-T or TCR-T cells, demonstrated a significant increase in central memory T cell (TCM) and stem cell-like memory T cell (TSCM) phenotypes both in vitro and in vivo. These memory subsets possess greater self-renewal capabilities, such as increased expansion following secondary stimulation, and exhibit prolonged survival. Consequently, they display more potent antitumor activity and achieve more durable efficacy in solid tumor models. As of now, the Clinicaltrials database (www.clinicaltrials.gov) indicates that there are 12 clinical trials involving autologous memory T cells for cancer treatment worldwide, all of which are interventional studies. Currently, these trials are primarily concentrated on Phase I and Phase II early clinical trials and are anticipated to achieve breakthroughs in safety and efficacy evaluations.

Exploration of Novel Cell Therapy: CAR-NK and CAR-M

CAR-NK Therapy: NK cells are a type of innate immune cell that exhibits broad and unique anti-tumor activity. They possess chemotaxis and can be attracted by specific chemokines in the tumor microenvironment, subsequently infiltrating the tumor tissue [112]. Due to the relatively limited amplification in vivo, this precisely reduces the risk of serious adverse reactions such as cytokine release syndrome [113]. They have been genetically modified to express a CAR that specifically recognizes and kills tumor cells expressing the corresponding antigen, eliminating the need for strict HLA matching [114]. In the process of resisting immune checkpoint molecules expressed by tumor cells, due to the relatively small number of inhibitory receptors on the surface of NK cells, CAR-NK cells can still maintain a certain degree of activity even in the immunosuppressive microenvironment, thus showing significant advantages over CAR-T cells [115,116]. Studies have shown that CAR-NK cells can penetrate the immunosuppressive microenvironment of solid tumors and may become a complementary regimen for treating cold tumors [117,118]. In the field of solid tumor treatment, numerous clinical studies have been conducted to assess the feasibility of CAR-NK cell therapy for various types of solid tumors, such as pancreatic cancer, glioblastoma, lung cancer, breast cancer, hepatocellular carcinoma, colorectal cancer, and ovarian cancer [119–121]. Li et al. [120] reported a case study involving the use of Robo1-CAR-NK cells to treat liver metastasis from pancreatic ductal adenocarcinoma (PDAC). During treatment, the pancreatic lesions and liver metastases were controlled within five months. The patient experienced only a transient moderate fever, reaching 38.5°C, and no cytokine release syndrome (CRS) or other serious adverse reactions were observed. Although CAR-NK cell therapy is considered safer than CAR-T cell therapy, it still encounters numerous challenges, including limited durability and long-term efficacy, tumor antigen escape, and issues with manufacturing and scalability. It is essential to further refine the structure of the CAR to minimize off-target effects and enhance efficacy, while also addressing the problem of autophagy that arises from NK cell activation [122]. With the official release of various norms and standards for CAR-NK therapy, the industry will enter a new stage of increased normalization and standardization, indicating the beginning of a new era in the development of CAR-NK therapy.

CAR-M Therapy. A large number of TAMs are distributed in cold tumors, exhibiting an immunosuppressive (M2) phenotype, which is one of the key factors in the formation of an immunosuppressive microenvironment. Macrophages engineered with CARs exhibit antigen-dependent cytotoxicity, directly activate phagocytosis, release ROS to kill adjacent antigen-negative or positive tumor cells, and activate T cell responses [123]. Zheng et al. [124] discovered that CAR-M-c-Met significantly inhibited the progression of pancreatic cancer in a mouse model and enhanced the therapeutic effect when combined with chemotherapy drugs. CAR-M activates the TME by secreting proinflammatory cytokines, such as TNF-αand IL-6, promoting the infiltration of CD8⁺ T cells, and inhibiting the immunosuppressive functions of M2 macrophages and Tregs [125]. At the same time, CAR-M can also activate T cells via its antigen presentation function and induce “Epitope Spreading,” thereby enhancing the overall anti-tumor immune response [125]. Early clinical studies conducted by Reiss et al. [125] indicated that circulating tumor DNA (ctDNA) levels temporarily decreased following CAR-M treatment, suggesting systemic immune activation. Currently, research into solid tumor-specific targets for CAR-M technology includes HER2 (associated with breast and gastric cancers), c-MET (related to pancreatic cancer), GPC3 (linked to liver cancer), MSLN (associated with mesothelioma), and other prevalent clinical targets for cold tumors [125]. Although previous studies have shown a bright prospect for CAR-M in treatment, it still faces many challenges, including difficulties in preparation and expansion, unsatisfactory migration and distribution in vivo, low transfection efficiency, tumor heterogeneity, uncertainty of efficacy, off-target toxicity, and safety concerns. Innovative dual-target and multifunctional CAR designs could enhance therapeutic efficacy and assist in overcoming tumor heterogeneity, such as targeting HER2 and MSLN, or by integrating costimulatory signaling domains, like CD3ζ and FcεRIγ, to boost macrophage activity and persistence [126]. Since autologous monocyte-derived macrophages are currently the primary cell source, the expansion of these cells in vitro presents a significant challenge. Induced pluripotent stem cell (iPSC)-derived macrophages have garnered extensive attention as an alternative approach and strategy, anticipated to enable standardized production and large-scale application [126]. CAR-M therapy is currently in early clinical trials, and its efficacy and safety require further evaluation. Nevertheless, CAR-M therapy transforms the TME of cold tumors, activates T cells, triggers systemic immunity, and offers a breakthrough treatment approach for cold tumors. CAR-M therapy is particularly suitable for treating cold solid tumors that do not respond to traditional immunotherapy.

In summary, the key advancements in the field of cold tumor treatment with adoptive cell therapy are reflected in the gradual overcoming of the immunosuppressive microenvironment through specific cell modifications, the integration of immunomodulatory strategies, and the application of new cell types (such as memory T cells, CAR-NK cells). Looking forward, we anticipate more clinical data to verify its long-term safety and broad applicability.

Since its inception in 2001, the concept of PROTAC molecules has garnered widespread interest from both academic and industrial sectors. With ongoing advancements in PROTAC design and thorough evaluation in preclinical models, the first cohort of PROTAC molecules, ARV-110 and ARV-471, entered the clinical research phase in 2019. Presently, nearly 40 PROTAC molecules globally have been approved for clinical trials, with indications ranging from cancers to autoimmune diseases, among others. In numerous studies, the PROTAC molecule ARV-471 entered the clinical phase III trial stage at the end of 2022 [150]. According to the information provided by Clinicaltrials, ARV-471 is currently under in-depth study in 12 clinical trials for breast cancer, marking a new approach in the exploration of cancer treatment. PROTAC technology represents an innovative therapeutic approach that utilizes the cell’s own protein degradation mechanism—the Ubiquitin-Proteasome System (UPS)—to selectively degrade specific proteins associated with diseases through an “event-driven” approach. This may enable the modulation of “undruggable” targets that are challenging for traditional small molecule drugs to affect. Taking cold tumors as an example, the expression of HLA-I is suppressed due to epigenetic silencing (such as DNA methylation), which leads to a defect in neoantigen presentation. However, employing PROTAC technology to degrade epigenetic modification enzymes (such as EZH2) can restore antigen presentation function [150]. By designing delivery systems like nanoparticles and prodrug strategies, the solubility, targeting, and bioavailability of PROTAC can be improved, thereby reshaping the immune microenvironment of cold tumors [151]. Despite the potential of PROTACs in treating diseases such as cancer, their clinical development is constrained by challenges in pharmacokinetic optimization, the development of effective biomarkers, and the difficulty in targeting membrane or extracellular proteins. Regarding safety, there is a risk of the “on-target but off-tissue” effect, where the effective degradation of the target protein may also affect the same protein in normal tissues, potentially causing systemic toxicity [152]. The main reasons are related to the widespread expression of E3 ubiquitin ligases, the lack of tissue specificity of delivery systems, the amplification of Hook effect in specific tissues, and the non-specificity of target proteins [152]. In terms of their formulations, PROTACs typically have a large molecular weight (>700 Da), strong hydrophobicity, and high polarity. These characteristics result in poor water solubility, weak cell permeability, and suboptimal pharmacokinetic properties, which in turn limit their oral bioavailability and tissue permeability [153]. Therefore, to overcome these limitations, the structural design of PROTACs, the development of novel delivery systems (such as tissue-specific delivery), and the expansion of the E3 ligase library are necessary for clinical application.

In summary, PROTAC technology has shown great potential in overcoming tumor drug resistance with the ultimate goal of inducing protein degradation. In addition, the technology can also be used for precision treatment of targets that are difficult to become drugs, and effectively regulate the tumor microenvironment, which is expected to bring a revolutionary breakthrough in the treatment of cold tumors.

The term “engineered nanoplatform” refers to a collection of nanomaterials or nanostructures that have been designed and modified by humans specifically for certain biomedical applications. These platforms, which have been innovatively designed and modified, typically possess the following characteristics and functions: (1) Precision targeting. New engineered nanoplatforms can specifically recognize and bind to certain antigens or receptors on the surface of tumor cells through surface modifications, such as antibodies, peptides, and other targeting molecules, achieving precise delivery of drugs to tumor cells [154]. (2) Multi-functional integration. Engineered nanoplatforms can integrate multiple functions, such as drug delivery, diagnostic imaging, and therapy. For example, some nanoplatforms can simultaneously carry chemotherapeutic drugs and imaging agents, realizing the integration of diagnosis and treatment [155]. (3) Responsive design. Engineered nanoplatforms can be designed according to the characteristics of the tumor microenvironment, allowing them to release drugs under specific conditions. For example, some nanoplatforms can release drugs in the acidic environment within tumor cells or under the action of overexpressed glutathione (GSH) [154]. Therefore, nanomedicines based on new engineered nanoplatforms can intervene in the TME through various mechanisms, enhancing anti-tumor immune responses. For instance, by loading immune agonists (such as STING agonists, TLR ligands) or regulating immune suppressive factors (such as TGF-β, IL-10), precise intervention in TME can be achieved [156,157]. Currently, some new engineered nanoplatform anti-tumor drugs have entered the clinical research stage, including: the mRNA vaccine CV9103 designed by CureVac, which contains 4 TAAs and has shown significant efficacy in the treatment of prostate cancer, is currently in the clinical phase II stage [158]; BioNTech has developed a personalized mRNA vaccine BNT122 using liposomal complexes as carriers, which can encode 20 tumor neoantigens, and the treatment for melanoma and colorectal cancer has entered the clinical phase II stage [159]; a supramolecular therapeutic nanoplatform designed by the Chen, H team, based on the “AND” logic gate, is used to overcome resistance to non-small cell lung cancer. This drug delivery system provides a highly controlled and targeted treatment method, effectively inhibiting tumor growth, suppressing bypass signaling pathways, and overcoming EGFR-TKI resistance [160]. Although novel nanoimmunomodulators have shown great potential for converting “cold tumors” into “hot tumors” and enhancing the response to immunotherapy, they still encounter several key limitations during clinical translation. Inorganic nanomaterials, (uch as metal and silicon nanoparticles, or highly immunogenic carriers, may trigger a systemic inflammatory response or be rapidly cleared by macrophages, thereby reducing targeting efficiency [161]. Nanoplatforms coated with cell membranes can fail due to host immune recognition; thus, hybrid membranes, such as those combining red blood cell and cancer cell membranes, are required to reduce immunogenicity [162]. However, scaling up the production of nanocapsules with complex structures, (uch as multi-layer responsive particles, from the laboratory to the clinic presents challenges related to process stability and cost [161]. Additionally, it may involve numerous challenges, such as the absence of biomarkers, the complexity of combination therapy, the unknown pharmacokinetics (PK) and pharmacodynamics (PD), and the regulatory and standardization hurdles. Despite the clinical limitations nano-platforms still face in treating “cold tumors,” their prospects remain generally optimistic. Nano-platforms for treating cold tumors have evolved from a “scientific hypothesis” to “clinically accessible technology,” and their systemic immune remodeling capabilities are anticipated to overcome the bottleneck of traditional immunotherapy.

Tumor immune escape and drug resistance have long been intractable challenges in clinical treatment. CRISPR technology, by precisely locating and editing specific gene sequences, can identify genes related to the growth, proliferation, differentiation, invasion, and drug resistance of tumor cells, thereby simplifying research processes and efficiently advancing the understanding of tumor molecular mechanisms. The research team at New York University, including Chen, X, etc., revealed through CRISPR-Cas9 whole-genome screening that the SUSD6/TMEM127/WWP2 (STW) axis in leukemia degrades MHC-I through ubiquitination. Targeted inhibition of this axis can restore antigen presentation function and enhance the killing effect of T cells [179]. This discovery has opened new horizons for the application of gene editing technology in studying the mechanisms of cold tumor immune escape, and the formation mechanism of the suppressive microenvironment of solid tumors will be more deeply explained and understood. At the same time, the application of gene editing technology in clinical treatment has also shown unprecedented precision, capable of repairing or regulating specific genetic mutations, thereby reversing the state of immune suppression [180]. This technological breakthrough not only promises to promote the development of cold tumor treatment strategies but may also lead a revolution in the field of tumor treatment. By combining gene editing with immunotherapy, scientists can more precisely locate and intervene in the key links of tumor immune escape, thereby activating the patient’s immune system to more effectively identify and attack tumor cells.

The integration of AI with bioinformatics has provided robust support for researchers to deeply understand the immune microenvironment of cold tumors, which helps in uncovering potential immunotherapy targets. Using AI algorithms, researchers are able to conduct in-depth analysis of vast tumor genomic, transcriptomic, and proteomic data, revealing the unique immune escape mechanisms and immune suppression networks of cold tumors. Currently, some preliminary research results have emerged.

stKeep is an innovative heterogeneous graph learning method specifically developed for analyzing spatially resolved transcriptomics (SRT) data to precisely parse the TME. This method captures the complex relationships between cells, genes, and tissue regions through heterogeneous graph learning, integrating multimodal data and gene-gene interactions, and is capable of identifying cellular modules and gene modules within the TME, as well as cell-cell communication (CCC). In various cancer samples, including breast cancer, lung cancer, colorectal cancer, and liver metastatic cancer, stKeep outperforms other tools in accurately identifying cellular states within the TME, such as bipotent basal cell populations, tumorigenic myoepithelial cells, and metastatic cells. Additionally, stKeep can identify key transcription factors, ligands, and receptors related to disease progression, which have been further validated through functional and survival analyses of independent clinical data, highlighting its significant potential in clinical prognosis and immunotherapy applications [181]. Yang et al. [182] constructed the BEPH (BEiT-based model Pre-training on Histopathological images) model, using the BEiTv2 Transformer and employing Masked Image Modeling (MIM) for self-supervised pre-training. The training data scale covers 32 types of cancers, with approximately 11,760 full-field digital slices (WSI), which are divided into 11.77 million 224 × 224-pixel image blocks. The model was tested on 16 public datasets, and BEPH outperformed existing weakly-supervised and specialized models in multiple indicators, with an average improvement of 5%–15%. When the training data volume was reduced to 20%, the performance decreased by less than 3%, demonstrating good small-sample adaptability. The visualization heatmap shows that the model’s focused areas highly overlap with the tumor regions labeled by pathologists, demonstrating interpretability. BEPH achieved “one model for multiple uses” in the diagnosis and survival prediction tasks of 32 types of cancers through “large-scale self-supervised pre-training + lightweight fine-tuning”, significantly reducing data annotation requirements and improving cross-cancer generalization ability. The existing rich genomic, transcriptomic, Metabolomics and proteomic data in the field of bioinformatics provide valuable training materials for AI models, enabling them to more accurately identify tumor-related biomarkers. Therefore, we firmly believe that the deep integration of future AI technology and bioinformatics will certainly pave new ways for understanding the mechanisms of cold tumor development and optimizing immunotherapy strategies. Through deep learning and big data analysis, AI will be able to more accurately predict patients’ responses to immunotherapy, thereby formulating better personalized treatment plans, achieving personalized precision treatment, improving treatment outcomes, and reducing side effects.

The integration of nanotechnology and biotechnology has brought revolutionary advances to the field of cold tumor immunotherapy. Through nanomedicine delivery systems, drugs can achieve precise targeting and controlled release, significantly increasing the concentration of drugs in tumor tissues while minimizing damage to healthy tissues. At the same time, the application of biotechnological engineering makes the modification of immune cells possible, endowing them with stronger anti-tumor capabilities and higher safety. The utilization of nanotechnology platforms further promotes the development of synthetic biology. Nanotechnology plays a crucial role in gene regulation, enabling precise temporal and spatial control over gene expression. By combining nanoparticles with gene regulatory elements, the unique physical and chemical properties of nanoparticles, such as optical and magnetic characteristics, can be used to remotely manipulate gene expression. This gene regulation strategy based on nanotechnology provides innovative methods for the construction and regulation of complex gene networks in synthetic biology [183]. In turn, synthetic biology can expand the application scope of nanotechnology. Through techniques such as genetic engineering, synthetic biology can customize the modification of organisms, utilizing their metabolic pathways to synthesize bio-nanoparticles with specific structures and functions. For example, by genetically modifying bacteria, yeast, and other microorganisms, they can be made to produce exosomes, microvesicles, and other bio-nanoparticles that can carry drugs, nucleic acids, and other active ingredients for the treatment and diagnosis of diseases [183]. The fusion of synthetic biology and biomaterials science provides powerful tools for the development of new immunotherapies, such as synthetic biosensors for real-time monitoring of changes in the tumor microenvironment [184], and intelligent responsive materials for the on-demand release of therapeutic molecules [185].

The deep integration of these cutting-edge technologies with interdisciplinary fields will greatly advance the development of cold tumor immunotherapy and herald a new era of personalized precision medicine. In the future, as cutting-edge technologies continue to evolve and interdisciplinary fields become more deeply integrated, the cold tumor immunotherapy field is expected to see the emergence of more innovative technologies and treatment methods, offering increased hope and positive outcomes for patients with cold tumors.