Introduction
Messenger RNA (mRNA) vaccines have evolved from a laboratory theory into a cornerstone of global health, propelled by breakthroughs in critical technological bottlenecks—particularly the optimization of mRNA modifications and delivery systems—and accelerated by the global pandemic. During the novel coronavirus (COVID‐19) pandemic, mRNA vaccines were developed with unprecedented speed and demonstrated remarkable efficacy. This not only showcased the platform's significant advantage in rapidly responding to infectious disease threats but also served as a global “proof of concept,” underscored by its exceptional effectiveness and safety profile [ 1 ]. This success has fundamentally transformed the research and development paradigm in the field of vaccines and has drawn worldwide attention to the broader applications of mRNA technology, among which cancer immunotherapy is considered one of the most promising directions.
Despite marking a milestone in infectious disease control, mRNA vaccines present a unique set of opportunities and challenges when applied to oncology. Unlike traditional vaccines that aim to prevent infectious diseases, therapeutic cancer vaccines are designed to precisely target tumor‐associated or tumor‐specific antigens (TAAs and TSAs) [ 2 ]. By selectively attacking and eliminating tumor cells expressing these antigens, such vaccines can establish long‐term efficacy through the induction of immune memory. Cancer vaccines are generally categorized into four types: tumor or immune cell vaccines, peptide vaccines, viral vector vaccines, and mRNA vaccines. Compared with other immunotherapies, cancer vaccines offer high tolerability and safety, as well as the ability to encode multiple antigens simultaneously, effectively reducing the risk of resistance during biological therapy. At present, numerous clinical trials are actively investigating the combination of personalized cancer vaccines with immune checkpoint inhibitors (ICIs) or cytokine therapies to enhance efficacy and overcome resistance to immunotherapy. These innovative combination strategies hold significant promise for the treatment of various solid tumors and metastatic cancers [ 3 , 4 , 5 , 6 , 7 , 8 ].
mRNA vaccines deliver multiple TAAs or neoantigens to efficiently express target proteins in vivo, thereby activating cytotoxic T cells for precise tumor targeting [ 9 , 10 ]. Their inherent advantages—including rapid development cycles, high flexibility, no risk of genomic integration, and robust activation of cellular immunity—make them an ideal platform for personalized cancer immunotherapy [ 11 , 12 , 13 , 14 ]. Advancements in chemical modifications, codon optimization [ 15 ], and delivery systems such as lipid nanoparticles (LNPs) and polymeric carriers have significantly enhanced their translational potential [ 16 ]. During the COVID‐19 pandemic, mRNA vaccines further demonstrated their capacity for multitarget antigen expression, strong immune activation, and durable protection, accelerating their transition into cutting‐edge tumor vaccines [ 17 , 18 ]. This progress holds promise for patients who have developed resistance to traditional immunotherapies.
However, seamlessly transitioning mRNA technology from infectious disease prevention to cancer treatment is not a straightforward matter of technology transfer [ 19 , 20 ]. Key obstacles in current research include the immunosuppressive nature of the tumor microenvironment (TME), the identification and validation of ideal target antigens, the in vivo targeting efficiency of delivery systems, and the cost and timeliness of personalized vaccines [ 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Researchers worldwide are actively working to address these challenges. Early‐stage clinical trials have demonstrated encouraging antitumor activity and favorable safety profiles, but they have also revealed limitations in efficacy and highlighted substantial room for optimization [ 28 , 29 ]. Therefore, it is both urgent and necessary to systematically review the latest advances in this field, clarify the core principles of key technologies, and thoroughly explore the bottlenecks and future directions of ongoing research.
This review aims to comprehensively elucidate the evolving applications of mRNA technology, ranging from infectious disease prevention to cancer therapy. We will begin by outlining the fundamental principles and advantages of mRNA vaccines, as well as their current applications in both tumor immunotherapy and infectious disease control. Next, we will examine the phenomena of immune escape and their underlying mechanisms in tumor immunotherapy, exploring strategies to overcome resistance. Finally, we will discuss future directions for mRNA cancer vaccines, including sequence design, chemical modifications, and LNP delivery systems, while emphasizing the broad application prospects of this technology in cancer therapy. This review seeks to provide researchers with an in‐depth reference on the development landscape, core challenges, and future opportunities in this rapidly advancing field.
The Basic Principles and Advantages of mRNA Vaccines
An mRNA vaccine is a synthetic immunization strategy that delivers mRNA encoding specific antigens to host cells. This approach enables host cells to express proteins from external sources, thereby eliciting targeted immune responses within the body. The mechanism not only mimics the immune response induced by natural viral infection but also offers substantial flexibility and safety. The basic principle involves the use of synthetic mRNA molecules, which typically comprise a 5′ cap structure, untranslated regions (UTRs), open reading frames (ORFs) encoding the antigen, and a poly(A) tail at the 3′ end [ 30 , 31 , 32 , 33 ]. When mRNA is introduced into cells—usually via LNPs or other delivery systems—it is translated in the cytoplasm into the target antigen. The resulting antigen is then processed and presented through either the MHC class I or class II pathway, subsequently activating cytotoxic T lymphocytes (CTLs) (CD8⁺ T cells) and helper T lymphocytes (CD4⁺ T cells). This process ultimately generates a highly targeted and robust immune response [ 34 , 35 ].
Compared with other types of vaccine platforms, mRNA vaccines offer several advantages [ 10 , 18 ]. Unlike DNA vaccines or viral vector vaccines, mRNA vaccines are noninfectious and nonintegrating, thereby eliminating the potential risks of infection or insertional mutagenesis [ 36 , 37 ].
In contrast to peptide vaccines, nucleic acid vaccines can encode complete tumor antigens, enabling antigen‐presenting cells (APCs) to present multiple epitopes simultaneously via both class I and class II HLA molecules. This feature allows nucleic acid vaccines to counteract tumor cell mechanisms that evade the immune system by modulating antigen expression. mRNA degradation occurs through normal cellular processes, and its half‐life in vivo can be regulated by various modifications and delivery [ 37 , 38 , 39 ]. mRNA vaccines are capable of delivering multiple TAAs or somatic mutations simultaneously, thereby reducing the likelihood of drug resistance during treatment [ 40 ]. The stability and translational efficiency of mRNA can be further improved through specific modifications [ 15 ]. Furthermore, the preparation cycle for mRNA vaccines is extremely [ 41 , 42 ], mRNAs can be rapidly synthesized by in vitro transcription (IVT) for any target protein with a known sequence, providing valuable therapeutic windows for patients [ 43 , 44 ]. While template pDNA for mRNA vaccines must be prepared via a cell culture step, this process is neither costly nor time consuming. The flexibility of mRNA vaccines is also reflected in their production process, which often allows for the rapid manufacture of variant or multivalent vaccines without significant alteration to the workflow. Additionally, mRNA vaccines possess an inherent adjuvant effect, activating immune cells to release cytokines such as tumor necrosis factor‐α and interferon‐α, thereby enhancing the immune response to antigen expression [ 45 ]. Owing to these considerable advantages, mRNAs are widely used not only in infectious disease control but also in tumor therapy, including strategies to overcome tumor immune resistance.
mRNA Vaccines are Being Used in the Field of Infectious Disease Control
In recent years, significant breakthroughs have been achieved in the development of mRNA vaccine technology for the prevention and control of infectious diseases, particularly during the COVID‐19 pandemic. This technology has demonstrated unprecedented speed and effectiveness. Compared with traditional vaccine platforms, mRNA vaccines offer several advantages, including rapid design, no requirement for cell culture, high immunogenicity, strong safety profiles, and adaptability to various pathogens. This paper reviews current research and applications of mRNA vaccines in major viral infectious diseases, including COVID‐19, influenza, respiratory syncytial virus (RSV), human immunodeficiency virus (HIV), and other pathogens.
COVID‐19 (SARS‐CoV‐2)
The mRNA vaccines were the first COVID‐19 vaccines to be authorized for emergency use and widely administered [ 46 , 47 ]. They encode the SARS‐CoV‐2 spike protein and have demonstrated up to 95% efficacy in preventing symptomatic infection in multiple large‐scale phase III clinical trials [ 48 ]. mRNA platforms also allow for therapid updating of vaccine sequences in response to emerging viral variants. As a result, bivalent or multivalent vaccines targeting variants such as Omicron have been introduced for use as booster shots. Although waning immunity over time and reduced protection against mild infections remain challenges, mRNA COVID‐19 vaccines continue to play a central role in the global fight against outbreaks.
Influenza
Influenza viruses require annual updates to the influenza vaccine to match prevalent strains due to their high antigenic variability [ 49 , 50 , 51 , 52 , 53 ]. mRNA vaccine platforms are considered ideal for influenza vaccines due to their rapid production and flexibility. These vaccines work by delivering mRNAs encoding antigens, such as the influenza virus haemagglutinin (HA), prompting recipient cells to synthesize these antigens and thereby inducing an immune response [ 54 ]. Moderna's mRNA‐1010 is a tetravalent influenza mRNA vaccine covering A/H1N1, A/H3N2, and two B strains, and has entered phase II/III clinical trials [ 55 ]. Preliminary data show that mRNA‐1010 induces neutralizing antibody levels comparable to or higher than those achieved with conventional vaccines and has a favorable safety profile. Similarly, GSK's mRNA influenza vaccines have demonstrated comparable immunity against both influenza A/H1N1, A/H3N2, and two strains of influenza B in phase II trials. mRNA influenza vaccines are expected to shorten production lead times and enhance protective efficacy. The industry has shown strong enthusiasm in this area; for example, GSK recently acquired CureVac's mRNA influenza vaccine program for $430 million and is using artificial intelligence (AI) to optimize antigen design. With further improvements in antigen and delivery system optimization, mRNA influenza vaccines are anticipated to provide broader and longer‐lasting protection.
Respiratory Syncytial Virus
RSV is the leading cause of acute lower respiratory tract infections in infants and young children, alongside influenza viruses. It poses a significant threat to both the elderly and infants, resulting in numerous serious complications each year [ 56 ]. The development of an effective RSV vaccine has proven challenging, as previous vaccine strategies have failed due to immune response imbalances and safety concerns. However, the emergence of mRNA vaccines offers promise in overcoming the limitations of traditional vaccines, such as the risk of antibody‐dependent enhancement. Domestic company AiBio has developed a freeze‐dried RSV mRNA vaccine that utilizes proprietary base modification technology and an LNP delivery system and has already received provisional clinical licensing. This vaccine can be stored at 2–8°C for several years. In animal studies, AiBio's vaccine candidate has demonstrated significantly higher RSV‐specific IgG and neutralizing antibody levels compared with internationally marketed control vaccines, indicating strong immunogenicity. Moderna's mRNA‐1345 vaccine, which encodes the RSV fusion protein in its preF conformation, has shown 83.7% efficacy in preventing RSV‐associated lower respiratory tract disease in the elderly in a phase III clinical trial [ 57 ]. This vaccine is currently eligible for priority review under the United States Food and Drug Administration's Biologics License Application and is expected to become the first RSV vaccine based on mRNA technology [ 58 ]. The RSV vaccine market is expanding rapidly, with mRNA vaccines offering significant advantages in meeting growing demand. With enhanced delivery systems and improved stability, mRNA‐based RSV vaccines are expected to provide broader protection for infants, children, and the elderly, effectively reducing the burden of RSV infection.
Human Immunodeficiency Virus (HIV)
HIV vaccine development has long been hindered by high viral mutation rates, latent infection, and immune escape mechanisms [ 59 ]. Despite ongoing efforts, no effective vaccine has been approved to date. However, the success of COVID‐19 mRNA vaccines has sparked renewed interest in utilizing mRNA technology for HIV vaccine design [ 60 , 61 , 62 , 63 , 64 ]. mRNA vaccines function by delivering genetic instructions for the expression of the Env spike glycoprotein found on the surface of HIV [ 62 ], thereby eliciting both antibody and T‐cell responses against the virus. Currently, several clinical trials are underway to assess the effectiveness and safety of mRNA‐based HIV vaccines. For example, Moderna has collaborated with the NIH to develop a series of mRNA vaccines, such as mRNA‐1644, designed to induce the production of broadly neutralizing antibodies [ 60 ]. These candidates are presently being evaluated in phase I clinical trials for their immunogenicity and safety. Additionally, IAVI's G002 trial, in partnership with Moderna, is investigating a sequential mRNA immunization strategy to guide the evolution of B cells for the production of broadly neutralizing antibodies [ 65 ]. The U.S. National Institute of Allergy and Infectious Diseases has also launched the HVTN 302 trial to assess the safety and immunogenicity of three different mRNA‐based HIV vaccines [ 66 ]. These promising developments have yielded positive results in animal models and are expected to progress to more advanced clinical stages in the near future. The versatility of mRNA technology allows for the rapid testing of various antigen combinations, opening new avenues for HIV vaccine research. By combining multiple Env variants with specific modifications, researchers aim to enhance the breadth of the neutralizing antibody response against HIV [ 64 ]. With the continuous accumulation of clinical data, mRNA vaccines are anticipated to play an increasingly crucial role in HIV prevention and treatment strategies in the coming years.
Other Viral Diseases
In recent years, the use of mRNA vaccines to combat various viral infections has been actively explored. Cytomegalovirus (CMV), a significant cause of congenital defects, is now targeted by Moderna's mRNA‐1647 vaccine, which has entered phase III clinical trials and shows promise for preventing CMV infection [ 67 ]. mRNA vaccines for Zika virus have demonstrated the ability to induce protective immunity in animal models and have progressed to clinical trials as well. Similarly, mRNA‐based rabies vaccines are currently under clinical investigation, offering the potential for more efficient and convenient pre‐ or postexposure prophylaxis [ 68 ]. Vaccine development is also underway for herpes simplex virus using mRNA technology [ 69 ]. Additionally, mRNA vaccines against other viruses such as Ebola [ 70 , 71 ] and Lassa fever [ 72 ] are in development, with researchers focusing on the genetic coding and design of key antigens. Given the lack of effective conventional vaccines for many of these viruses, mRNA technology offers the potential for rapid development of novel vaccines. mRNA platforms are highly flexible, allowing for the encoding of antigens from multiple pathogens within a single formulation, thereby enabling multivalent immunity and the creation of combination vaccines that can target multiple viruses simultaneously. The monkeypox outbreak in 2022 has further spurred research into the application of mRNA vaccines for such emerging threats [ 73 ]. With ongoing advancements in nano delivery systems and stabilizing formulation technologies—including self‐amplifying RNA and heat‐stabilized formulations—mRNA vaccines are expected to become a crucial tool in the fight against viral diseases.
mRNA Vaccines in Cancer Therapy
Among the various vaccine candidate platforms, the early application of mRNA was limited by instability, low efficiency, and excessive immunogenicity. However, the successful development of the SARS‐CoV‐2 mRNA vaccine overcame these technological bottlenecks in vaccine preparation. This breakthrough has enabled the rapid, economical production of tumor mRNA vaccines with improved stability and efficiency. In this context, we will discuss the application of mRNA vaccines in tumor immunotherapy, as well as current advances in targeted and personalized mRNA vaccines.
mRNA Vaccines in Tumor Immunotherapy
The application of mRNA vaccines in tumor immunotherapy primarily relies on encoding TAAs or TSAs to activate the immune system for targeted attacks on tumor cells. These vaccines efficiently stimulate APCs in vivo, promoting a synergistic effect between innate and adaptive immune responses. In clinical practice, mRNA vaccines are classified as either prophylactic or therapeutic: prophylactic vaccines aim to prevent tumor development in high‐risk populations by encoding tumor antigens, while therapeutic vaccines target patients with existing tumors, eliciting immune responses to attack and eliminate cancer cells [ 35 ]. In recent years, mRNA tumor vaccines have demonstrated significant promise in clinical trials for various cancer types. Sahin et al. [ 74 ] found that mRNA vaccines induced a strong immune response in patients with melanoma, which was notably enhanced when combined with ICIs. Similarly, Yuan et al. [ 75 ] showed that personalized vaccines targeting RNA mutations triggered multspecific and therapeutic immune responses against cancer. Furthermore, a review by Miao et al. [ 35 ] confirmed the promising application of mRNA vaccines in treating a range of aggressive solid tumors, such as non‐small cell lung cancer (NSCLC), colorectal cancer, and melanoma. mRNA vaccines are efficiently delivered to target cells using LNP‐based vectors. Once inside the cell, mRNA is internalized into endosomes. Protonation of ionizable lipids in the acidic endosomal environment promotes membrane fusion, leading to the release of mRNA into the cytoplasm, where it is translated into protein. These proteins are degraded by the proteasome into antigenic peptides, which are then presented on MHC molecules to CD8⁺ T cells, thereby activating cell‐mediated immune responses [ 76 ]. Pan et al. [ 77 ] demonstrated that nanomaterial‐based delivery systems significantly enhance the immunogenicity of mRNA vaccines and exert antitumor effects via the Toll‐like receptor 4 signaling pathway. mRNA vaccines activate APCs such as dendritic cells (DCs) and macrophages, enabling them to process exogenous antigens and present them through MHC molecules. Cells display exogenous antigens to CD4⁺ T cells via MHC‐II and facilitate cross‐presentation to CD8⁺ T cells via MHC‐I. Mature DCs secrete proinflammatory and immunostimulatory cytokines—including IL‐12, IL‐23, and IL‐1β and subsequently migrate to tumor‐draining lymph nodes [ 78 ]. Zhou et al. [ 79 ] reported that incorporating a STING agonist in mRNA vaccine design can substantially increase the effectiveness of cancer immunotherapy, promoting immune cell activation and antitumor responses through intelligently designed nanovaccines. Peptides presented on DC surface MHC molecules interact with T cell receptors (TCRs), activating naïve CD8⁺ T cells and differentiating them into CTLs under the combined influence of multiple receptors and cytokines. These CTLs can infiltrate tissues and target tumor cells, exerting potent antitumor effects [ 80 ]. A study by Melamed et al. [ 81 ] showed that mRNA delivered via ionizable LNPs can be efficiently targeted to pancreatic β‐cells to induce robust CTL responses. Importantly, mRNA vaccines are also capable of inducing memory T cell formation, enabling rapid and long‐lasting protection upon re‐exposure to the same antigen. He et al. [ 82 ] highlighted the potential of mRNA cancer vaccines in inducing durable immune memory. Figure 1 illustrates the mechanisms of mRNA vaccines in tumor immunotherapy.

Targeted mRNA Vaccines
Tumor mRNA vaccines are highly valued for their precise target selection, as tumor antigens recognized by T lymphocytes are essential for the efficacy of cancer vaccines [ 83 ]. Ideal antigens for cancer vaccines should be highly immunogenic, expressed exclusively in cancer cells (but not in normal cells), and crucial for cancer cell survival [ 84 ]. Tumor antigens are generally categorized as TAAs and TSAs [ 85 , 86 ], also known as tumor‐sharing antigens [ 87 , 88 ]. Targeted mRNA vaccines offer advantages such as high specificity and low side effects, thereby minimizing damage to normal cells and reducing adverse reactions [ 77 ]. Mixtures of mRNA vaccines encoding multiple TAAs have been tested in several clinical trials for the treatment of metastatic melanoma. For example, BNT111, an mRNA vaccine encoding four TAAs (NY‐ESO‐1, MAGE‐A3, tyrosinase, and TPTE), has demonstrated efficacy as immunotherapy for patients with checkpoint inhibitor (CPI)‐refractory melanoma, highlighting the utility of nonmutated shared tumor antigens in cancer vaccination [ 74 ]. Researchers are also exploring targets that activate immune checkpoints to enhance the efficacy of mRNA vaccines. For instance, STING agonist‐enhanced mRNA vaccines improve antigen presentation and boost antitumor immune responses by activating the STING pathway in vivo [ 79 ]. Additionally, targeted mRNA vaccines can be combined with other immunotherapies, such as CPIs, to further enhance antitumor immune effects [ 89 ]. In clinical applications, targeted mRNA vaccines have shown promising efficacy across various malignancies. Although a study ( NCT02410733 ) did not observe increased patient responses with the combination of anti‐PD‐1 therapy and the TAA vaccine FixVac compared with FixVac alone, the potential for combining mRNA vaccines with ICIs in oncology cannot be excluded [ 75 ]. In melanoma patients, direct injection of a protective mRNA induced robust T‐cell responses and significantly reduced tumor burden. In prostate cancer patients, a self‐adjuvanted mRNA vaccine effectively activated the immune system and significantly prolonged patient survival [ 90 ]. Despite the great potential of targeted mRNA vaccines in tumor therapy, their development and application face several challenges. The heterogeneity and variability of tumor antigens complicate target selection, and the efficiency and stability of mRNA vaccine delivery systems require further improvement. To address these challenges, researchers are actively developing new antigen screening methods and delivery systems to improve the efficacy and safety of targeted mRNA vaccines [ 75 ]. Table 1 provides a summary of recent clinical trials involving targeted mRNA vaccines.
TABLE 1
Clinical trials of targeted mRNA vaccines.
| NCT number | Status | Disease | Sponsor | Phase | Start date | Last update posted |
| NCT05714748 | Recruiting | Malignant tumors | West China Hospital | Phase 1 | 2022/11/18 | 2023/02/06 |
| NCT05738447 | Recruiting | Liver cancer hepatocellular carcinoma | West China Hospital | Phase 1 | 2023/02/15 | 2023/02/22 |
| NCT03948763 | Completed | Neoplasms carcinoma non‐small cell lung pancreatic neoplasms colorectal neoplasms | Merck Sharp & Dohme LLC | Phase 1 | 2019/06/26 | 2022/09/07 |
| NCT03948763 | Completed | Neoplasms carcinoma non‐small cell lung pancreatic neoplasms | Merck Sharp & Dohme LLC | Phase 1 | 2019/06/26 | 2022/09/07 |
| NCT06019702 | Recruiting | Digestive system neoplasms | Sir Run Run Shaw Hospital | Phase 1 | 2023/09/08 | 2023/09/11 |
| NCT06026800 | Recruiting | Digestive system neoplasms | Sir Run Run Shaw Hospital | Phase 1 | 2023/09/08 | 2023/09/11 |
| NCT06026774 | Recruiting | Digestive system neoplasms | Sir Run Run Shaw Hospital | Phase 1 | 2023/09/08 | 2023/09/11 |
| NCT00890032 | Completed | Recurrent central nervous system neoplasm | John Sampson | Phase 1 | 2009/09/01 | 2016/10/17 |
| NCT00890032 | Completed | Recurrent central nervous system neoplasm | John Sampson | Phase 1 | 2009/09/01 | 2016/10/17 |
| NCT01278940 | Completed | Malignant melanoma | Oslo University Hospital | Phase 1/2 | 2002/03/01 | 2016/08/15 |
| NCT01278914 | Completed | Prostate cancer | Oslo University Hospital | Phase 1/2 | 2002/02/01 | 2023/05/08 |
| NCT03323398 | Terminated | Relapsed/refractory solid tumor malignancies or lymphoma ovarian cancer | ModernaTX, Inc. | Phase 1/2 | 2017/08/15 | 2024/07/31 |
| NCT03739931 | Active, not recruiting | Relapsed/refractory solid tumor malignancies or lymphoma triple negative breast cancer, HNSCC, non‐Hodgkins, urothelial cancer, immune checkpoint refractory melanoma, and NSCLC lymphoma | ModernaTX, Inc. | Phase 1 | 2018/11/27 | 2024/05/17 |
| NCT00890032 | Completed | Recurrent central nervous system neoplasm | John Sampson | Phase 1 | 2009/09/01 | 2016/10/17 |
| NCT00890032 | Completed | Recurrent central nervous system neoplasm | John Sampson | Phase 1 | 2009/09/01 | 2016/10/17 |
| NCT01278940 | Completed | Malignant melanoma | Oslo University Hospital | Phase 1/2 | 2002/03/01 | 2016/08/15 |
| NCT01278914 | Completed | Prostate cancer | Oslo University Hospital | Phase 1/2 | 2002/02/01 | 2023/05/08 |
| NCT03323398 | Terminated | Relapsed/refractory solid tumor malignancies or lymphoma ovarian cancer | ModernaTX, Inc. | Phase 1/2 | 2017/08/15 | 2024/07/31 |
| NCT03739931 | Active, not recruiting | Relapsed/refractory solid tumor malignancies or lymphoma triple negative breast cancer, HNSCC, non‐Hodgkins, urothelial cancer, immune checkpoint refractory melanoma, and NSCLC lymphoma | ModernaTX, Inc. | Phase 1 | 2018/11/27 | 2024/05/17 |
| NCT01066390 | Completed | Melanoma | Bart Neyns | Phase I | 2009/12/01 | 2014/05/06 |
| NCT05264974 | Recruiting | Melanoma | University of Florida | Phase 1 | 2024/11/01 | 2024/10/29 |
| NCT04932863 | Unknown | Neoplasms cancer, treatment‐related | Ente Ospedaliero Ospedali Galliera | Observational | 2021/03/15 | 2021/06/21 |
| NCT00961844 | Terminated | Metastatic malignant melanoma | Steinar Aamdal | Phase 1/2 | 2009/08/01 | 2021/02/26 |
| NCT00204516 | Completed | Malignant melanoma | University Hospital Tuebingen | Phase 1/2 | 2007/04/01 | 2013/01/16 |
| NCT00626483 | Completed | Malignant neoplasms brain | Gary Archer Ph.D. | Phase 1 | 2007/04/24 | 2021/03/09 |
| NCT05028374 | Completed | Multiple myeloma AL amyloidosis chronic lymphocytic leukemia | Barbara Ann Karmanos Cancer Institute | Phase 2 | 2021/08/17 | 2023/12/20 |
| NCT06156267 | Not yet recruiting | Pancreatic cancer | Fudan University | Early‐Phase 1 | 2024/01/01 | 2023/12/05 |
| NCT01153113 | Withdrawn | Metastatic prostate cancer | University of Florida | Phase 1/2 | 2008/01/01 | 2011/12/02 |
| NCT03164772 | Completed | Metastatic non‐small cell lung cancer NSCLC | Ludwig Institute for Cancer Research | Phase 1/2 | 2017/12/20 | 2022/10/10 |
| NCT05938387 | Recruiting | Glioblastoma | CureVac | Phase 1 | 2023/06/01 | 2024/08/15 |
| NCT04163094 | Terminated | Ovarian cancer | University Medical Center Groningen | Phase 1 | 2019/11/25 | 2023/06/29 |
| NCT04573140 | Recruiting | Adult glioblastoma high grade glioma WHO grade III or IV malignant glioma | University of Florida | Phase 1/2 | 2021/10/26 | 2024/09/25 |
| NCT04382898 | Terminated | Prostate cancer | BioNTech SE | Phase 1/2 | 2019/12/19 | 2024/05/17 |
| NCT03788083 | Recruiting | Breast cancer female early‐stage breast cancer | Universitair Ziekenhuis Brussel | Phase 1 | 2018/11/12 | 2022/05/19 |
Personalized mRNA Vaccines
Personalized mRNA cancer vaccines represent a cutting‐edge cancer therapy that works by stimulating the immune system to precisely target cancer cells using specific antigens found in a patient's tumor [ 91 ]. As cancer cells develop, they accumulate mutations that give rise to unique protein sequences—neoantigens—not present in normal cells [ 92 ]. These neoantigens are processed by the proteasome and displayed on the cell surface by MHC molecules, where they can be recognized by TCRs. Because these neoantigens are unique to each patient, they present both challenges and opportunities for personalized immunotherapy [ 93 ]. Clinical trials have demonstrated that personalized mRNA cancer vaccines are safe and well‐tolerated [ 94 , 95 ]. Companies like BioNTech and Moderna have made significant progress in this field, developing personalized mRNA vaccines that have shown promising antitumor effects in clinical trials [ 96 ]. For example, Moderna's mRNA‐4157 vaccine, which can encode up to 34 neoantigens within LNPs, has demonstrated positive effects in phase I trials for solid tumors, both as a monotherapy and in combination with pembrolizumab, and is currently in phase II trials. Similarly, BioNTech's BNT122 vaccine encodes up to 20 patient‐specific neoantigens using its mRNA personalized cancer vaccine platform. This vaccine has been shown to induce neoantigen‐specific T cell responses and clinically meaningful responses in a phase 1a/1b trial and is currently being evaluated in a phase II clinical trial for colorectal cancer ( NCT04486378 ). Sahin et al. [ 74 ] further elucidated how personalized RNA mutant vaccines can stimulate multispecific therapeutic immune responses to effectively combat cancer. These vaccines successfully activated patients’ immune systems by encoding individualized tumor neoantigens. Meanwhile, C. Pollard et al. highlighted the importance of predicting and identifying neoantigens using advanced technologies such as whole exome sequencing, RNA sequencing, and mass spectrometry. These technologies have not only streamlined vaccine production but have also improved the potential effectiveness of such vaccines [ 97 ]. One of the main challenges of personalized mRNA cancer vaccines lies in the prediction and identification of neoantigens. Currently, many neoantigen prediction methods rely on machine learning‐based algorithms [ 98 ]. mRNA vaccines are generated after candidate neoantigens are identified from tumor tissue by sequencing‐based prediction algorithms or microfluidic chip experiments (Figure 2 ). Personalized mRNA vaccines can also be combined with other treatments, such as chemotherapy and radiotherapy, to achieve synergistically enhanced therapeutic effects [ 99 , 100 ]. In clinical practice, personalized mRNA vaccines have shown encouraging results in the treatment of various malignancies. For instance, in a clinical trial involving patients with gastrointestinal cancers, personalized mRNA vaccines successfully induced specific T cell responses and significantly reduced tumor burden [ 94 ]. In studies on melanoma patients, these vaccines effectively activated the immune system and significantly prolonged patient survival [ 74 ]. Although personalized mRNA vaccines show great potential in oncology, there are still several challenges in their development and application. The process of preparing personalized vaccines is complex and costly. In addition, the delivery efficiency and stability of mRNA vaccines need to be further optimized. To overcome these obstacles, researchers are actively exploring new antigen screening methods and novel delivery systems, with the aim of improving the efficacy and safety of personalized mRNA vaccines [ 101 , 102 , 103 ]. Table 2 summarizes the clinical trials of personalized mRNA vaccines in recent years.

TABLE 2
Clinical trials of personalized mRNA vaccines.
| NCT number | Status | Disease | Sponsor | Phase | Start date | Last update posted |
| NCT06496373 | Recruiting | Pancreatic cancer recurrent | Ruijin Hospital | Phase 1 | 2024/04/01 | 2024/07/11 |
| NCT05916248 | Recruiting | Advanced solid tumor | Ruijin Hospital | Phase 1 | 2023/05/18 | 2023/10/10 |
| NCT05916261 | Recruiting | Advanced pancreatic cancer | Ruijin Hospital | Early phase 1 | 2023/04/26 | 2023/10/26 |
| NCT02709616 | Completed | Glioblastoma | Guangdong 999 Brain Hospital | Phase 1 | 2016/03/01 | 2022/05/27 |
| NCT02808416 | Completed | Brain cancer neoplasm metastases | Guangdong 999 Brain Hospital | Phase 1 | 2016/03/01 | 2022/05/27 |
| NCT02808364 | Completed | Glioblastoma | Guangdong 999 Brain Hospital | Phase 1 | 2016/03/01 | 2022/05/27 |
| NCT05761717 | Not yet recruiting | Postoperative hepatocellular carcinoma | Shanghai Zhong shan Hospital | Not applicable | 2023/04/20 | 2023/03/09 |
| NCT03480152 | Terminated | Melanoma colon cancer gastrointestinal cancer genitourinary cancer hepatocellular cancer | National Cancer Institute (NCI) | Phase 1/2 | 2018/05/18 | 2020/06/02 |
| NCT06141369 | Recruiting | Adrenal cortical carcinoma medullary thyroid cancer thymic neuroendocrine carcinoma pancreatic neuroendocrine tumor | Shanghai Jiao Tong University School of Medicine | Not applicable | 2024/01/13 | 2024/01/26 |
| NCT05359354 | Recruiting | Solid tumor | YueJuan Cheng | Not applicable | 2022/09/01 | 2023/05/16 |
| NCT02035956 | Completed | Melanoma | BioNTech RNA Pharmaceuticals GmbH | Phase 1 | 2013/12/01 | 2020/01/18 |
| NCT03897881 | Recruiting | Melanoma | ModernaTX, Inc. | Phase 2 | 2019/07/18 | 2024/06/03 |
| NCT03380871 | Completed | Carcinoma, non‐small cell lung cancer, non‐squamous non‐small cell neoplasm of lung | BioNTech US Inc. | Phase 1 | 2018/05/04 | 2021/02/26 |
| NCT06026774 | Recruiting | Digestive system neoplasms | Sir Run Run Shaw Hospital | Phase 1 | 2023/09/08 | 2023/09/11 |
| NCT06026800 | Recruiting | Digestive system neoplasms | Sir Run Run Shaw Hospital | Phase 1 | 2023/09/08 | 2023/09/11 |
| NCT06497010 | Recruiting | Advanced solid tumor | The Affiliated Hospital of Guizhou Medical University | Early phase 1 | 2024/08/01 | 2024/08/01 |
| NCT05227378 | Not yet recruiting | Gastric cancer | Shen Lin | Not applicable | 2022/03/01 | 2022/02/07 |
| NCT05981066 | Recruiting | Advanced hepatocellular carcinoma | Peking Union Medical College Hospital | Not applicable | 2023/07/10 | 2023/08/08 |
| NCT03164772 | Completed | Metastatic non‐small cell lung cancer NSCLC | Ludwig Institute for Cancer Research | Phase 1/2 | 2017/12/20 | 2022/10/10 |
| NCT06326736 | Recruiting | Pancreatic cancer | Jinling Hospital, China | Early phase 1 | 2024/04/01 | 2024/03/22 |
| NCT03908671 | Recruiting | Esophageal cancer non‐small cell lung cancer | Stemirna Therapeutics | Not applicable | 2019/10/18 | 2023/04/13 |
| NCT05949775 | Not yet recruiting | Advanced malignant solid tumors | Stemirna Therapeutics | Not applicable | 2023/07/20 | 2023/07/18 |
| NCT05198752 | Unknown | Solid tumor | Stemirna Therapeutics | Phase 1 | 2022/03/18 | 2022/10/17 |
| NCT03468244 | Recruiting | Advanced esophageal squamous carcinoma gastric adenocarcinoma pancreatic adenocarcinoma colorectal adenocarcinoma | Changhai Hospital | Not applicable | 2018/05/01 | 2019/02/26 |
| NCT06195384 | Recruiting | Solid tumor | Second Affiliated Hospital of Guangzhou Medical University | Phase 1 | 2024/05/08 | 2024/06/26 |
| NCT05192460 | Recruiting | Gastric cancer esophageal cancer liver cancer | Jianming Xu | Not applicable | 2022/03/28 | 2023/03/07 |
| NCT06295809 | Active, not recruiting | Carcinoma, squamous cell skin neoplasms | Merck Sharp & Dohme LLC | Phase 2 | 2024/04/18 | 2026/03/05 |
| NCT06307431 | Active, not recruiting | Renal cell carcinoma | Merck Sharp & Dohme LLC | Phase 3 | 2024/04/10 | 2032/06/08 |
| NCT05933577 | Active, not recruiting | Melanoma | Merck Sharp & Dohme LLC | Phase 2 | 2023/07/19 | 2030/09/26 |
| NCT06961006 | Not yet recruiting | Malignant melanoma | Merck Sharp & Dohme LLC | Phase 3 | 2025/06/10 | 2031/09/05 |
| NCT06077760 | Recruiting | Non‐small cell lung cancer | Merck Sharp & Dohme LLC | Phase 2 | 2023/12/06 | 2035/12/21 |
The Potential for mRNA Vaccines to Overcome Tumor Immune Resistance
The issue of drug resistance in tumor cells has long posed a significant challenge in cancer treatment. Drug resistance not only diminishes the effectiveness of existing therapies but also increases the complexity and difficulty of disease management. In recent years, mRNA vaccines have shown promising advancements in tumor therapy, particularly in addressing immune escape and drug resistance. These vaccines work by delivering mRNAs encoding tumor antigens into cells, thereby activating APCs and stimulating specific T and B cell responses. This technology can be tailored to target tumor neoantigens and overcome drug resistance by modulating the immune microenvironment. In this discussion, we will explore the current challenges of immunotherapeutic resistance, the mechanisms underlying immune escape in tumor immunotherapy, and the potential of mRNA vaccines to overcome these barriers.
The Challenge of Immunotherapy Resistance
The phenomenon of drug resistance in tumor immunotherapy can be classified into three types: primary, adaptive, and acquired resistance [ 104 , 105 ]. Primary resistance occurs when the initial treatment is ineffective. Acquired resistance develops when tumor cells regain a survival advantage after treatment, often through genetic mutations [ 4 ]. Adaptive resistance involves tumor cells evading immune attack, with one well‐known mechanism being the expression of B7‐H1 in response to IFN‐γ released by T cells within the TME [ 106 ]. Recent studies have reported various immune resistance phenomena, such as an initial favorable response to ICI therapy that becomes difficult to sustain, resulting in reduced therapeutic effectiveness over time [ 107 ]. For example, research by He et al. [ 27 ] demonstrated that, in hepatocellular carcinoma, serum amyloid A promotes glycolysis in neutrophils, rendering them resistant to anti‐PD‐1 blockade therapy. This finding underscores the critical role of specific factors within the TME in the mechanisms underlying ICI resistance, highlighting the need to focus on modulating the TME when developing strategies to overcome drug resistance. In addition to the TME, intrinsic factors within tumor cells themselves also play a significant role in resistance [ 108 ]. Furthermore, drug resistance to CAR‐T cell therapy is closely associated with immunosuppression in the TME. Tumors can evade immune attack by modulating cellular and signaling components in their environment, such as downregulating MHC molecule expression to escape CAR‐T cell recognition, ultimately leading to treatment failure [ 109 ]. Tumor heterogeneity is strongly linked to acquired drug resistance, affecting the recognition and cytotoxic ability of CAR‐T cells [ 6 ]. In contrast, resistance to NK cell therapy is mainly attributed to immunosuppression within the TME and adaptive alterations in tumor cells. Weber et al. [ 110 ] discovered that myeloid‐derived suppressor cells (MDSCs) inhibit NK cell activity in the TME and promote the generation of regulatory T cells (Tregs), resulting in resistance to ICIs. Additionally, genetic mutations and upregulation of metabolic pathways in tumor cells—such as the activation of oxidative phosphorylation and DNA repair pathways as investigated by Memon et al. [ 6 ] allow these cells to survive and proliferate under immune stress. Sharma et al. [ 4 ] further noted that tumor cells can evade NK cell recognition by modulating their surface antigen expression, for instance, by downregulating activating receptor ligands or upregulating inhibitory receptor ligands. Finally, DCs play a key role in tumor immunotherapy by activating T cell responses. However, drug resistance may reduce the effectiveness of DC‐based therapies. Tumor cells can escape immune surveillance by decreasing antigen presentation, altering tumor antigens, or modulating the expression of immune checkpoint molecules, thereby influencing the efficacy of DC therapy. To counter drug resistance, researchers have explored combination strategies, such as pairing DC therapy with anti‐PD‐1 or anti‐CTLA‐4 antibodies, to enhance antitumor immune responses and reduce resistance [ 111 ].
Mechanisms Associated with Immune Evasion in Tumor Immunotherapy
Tumor cells can evade immune system recognition by decreasing the expression of tumor antigens. These antigens, which include TSAs and TAAs, play a crucial role in enabling the immune system to detect and attack tumor cells. Tumor cells employ various strategies to downregulate the expression of these antigens, thereby reducing their chances of being identified and targeted by T cells. One such strategy involves acquiring genetic mutations that inactivate or alter the genes encoding tumor antigens. These mutations can result in the complete loss or structural modification of tumor antigens, making them less recognizable to TCRs. Additionally, mutations in the coding regions of tumor antigen genes may cause changes or truncations in protein sequences, further hindering recognition by T cells. Such mechanisms contribute to immune evasion and present significant challenges to the effectiveness of immunotherapy [ 112 ]. Understanding these processes offers valuable insight into the development of resistance to immune‐based treatments.
Altering MHC I Molecular Expression
MHC class I molecules play a crucial role in the tumor immune response by displaying intracellular antigenic peptides on the surface of tumor cells, thereby providing targets for T cells to recognize and bind to, which stimulates an immune reaction. Unfortunately, tumor cells often adopt the strategy of downregulating MHC class I molecule expression to evade immune surveillance; this has become a common method by which tumors escape immune attack. Kalbasi and Ribas [ 108 ] revealed a mechanism whereby tumor cells resist cancer immunotherapy by reducing the expression of HLA molecules. In addition, mutations affecting MHC class I molecules represent another mechanism for tumors to evade immune recognition. Using advanced computational tools, McGranahan et al. [ 113 ] identified loss of heterozygosity in HLA genes among patients with NSCLC and found that approximately 40% of patients exhibited this phenomenon, resulting in diminished neoantigen presentation and further facilitating immune escape. Mutations in the β2‐microglobulin (β2m) gene constitute another key immune evasion mechanism. In studies of lung cancer patients resistant to PD‐1 therapy, Gettinger et al. [ 114 ] found that certain tumors exhibited loss of heterozygosity for β2m, resulting in a lack of HLA class I molecule expression on the cell surface, while others showed downregulation of β2m expression. These mutations not only render MHC‐I molecules unstable, but also prevent efficient presentation of neoantigens to tumor‐infiltrating lymphocytes, thereby allowing tumor cells to evade immune surveillance. Furthermore, activation of the β‐catenin signaling pathway in tumor cells can also alter MHC molecule expression and suppress the antitumor immune response [ 115 , 116 ]. The activation of this signaling pathway not only inhibits the function of effector T cells but also promotes the accumulation of immunosuppressive cells, thereby enhancing the tumor's ability to evade the immune system. D'Urso et al. [ 117 ] have further indicated that certain melanoma cells are deficient in the expression of the β2m gene, resulting in the loss of HLA class I antigens and allowing these cells to escape immune recognition.
Reduced Immunogenicity
Tumor cells can reduce their immunogenicity by secreting immunosuppressive factors such as TGF‐β and IL‐10. These factors inhibit T cell activity and promote the proliferation of Tregs, thereby suppressing the immune response. Additionally, cells within the TME—such as tumor‐associated macrophages (TAMs) and MDSCs—further facilitate immune evasion by secreting these same immunosuppressive factors. The resulting immunosuppressive microenvironment restricts antitumor immunity through the combined action of factors secreted by tumor cells, immune cells, and stromal cells. For example, elevated levels of IL‐8 may reflect a particularly unfavorable TME that impedes antitumor immunity in preclinical models as well as certain human cancers [ 118 ]. According to Vesely and colleagues [ 3 ], tumor cells inhibit the function of effector T cells and promote the accumulation of immunosuppressive cells by secreting factors such as TGF‐β and IL‐10, a strategy that enables tumors to grow and metastasize while escaping immune surveillance. Furthermore, B cell‐derived IL‐35 mediates the exclusion of CD8+ T cells in pancreatic cancer, promoting immune escape through a STAT3‐dependent mechanism [ 119 ]. Cytokine secretion not only impairs effector T cell function but also encourages the accumulation of other immunosuppressive cells, thereby intensifying tumor immune escape. Tregs [ 120 ], MDSCs [ 121 ], and TAMs [ 122 ], all suppress antitumor immune responses in preclinical cancer models. Notably, infiltration of Tregs into the TME has been observed in various cancer types [ 123 , 124 , 125 , 126 ]. It has been suggested that the modulation of the immune response by anti‐CTLA‐4 therapies may be attributed to their targeting of Tregs [ 127 , 128 , 129 , 130 , 131 ], Sharma et al. [ 4 ] have demonstrated that Tregs directly inhibit effector T cell activity by secreting inhibitory cytokines such as IL‐10 and IL‐35, thereby perpetuating tumor immune escape. High levels of Treg infiltration in many tumors are closely associated with immune evasion [ 4 ]. MDSCs are heterogeneous myeloid cells recruited to the TME that possess immunosuppressive functions [ 121 ]. Weber et al. [ 110 ] suggested that MDSCs accumulate in the TME and suppress the activity of effector T cells through the secretion of immunosuppressive factors such as IL‐10 and TGF‐β. Additionally, MDSCs can further impair the immune response by inducing T cell apoptosis and inhibiting T cell proliferation [ 110 ]. TAMs are considered predictors of patient prognosis, and targeting these cells remains a prominent area of clinical research [ 122 ]. Leal and John [ 8 ] have suggested that TAMs promote tumor growth and immune escape by secreting cytokines and chemokines such as IL‐10 and CCL2. They also indicated that TAMs support tumor progression and metastasis by promoting angiogenesis and suppressing antitumor immune responses [ 8 ].
Lack of Costimulatory Molecular Expression
Although tumor cells can directly present tumor antigens to T cells via MHC molecules on their surface, the absence of costimulatory signals prevents T cell activation, thereby inhibiting the effective recognition and elimination of tumor cells. This ultimately enables tumor cells to evade the immune system. For example, tumor cells may impede T cell activation and proliferation by downregulating the expression of B7 family costimulatory molecules (such as B7‐1 and B7‐2), allowing them to escape immune detection [ 7 ]. Clinically, tumors lacking costimulatory molecule expression often exhibit resistance to ICI therapy. Furthermore, some tumors evade immune responses by decreasing the expression of immune checkpoint molecules such as PD‐L1 and CTLA‐4, which can lead to immunotherapy failure [ 3 ]. This evasion mechanism enables tumor cells to continue growing and spreading even in the presence of ICIs. Additionally, a study by George et al. [ 132 ] suggests that PTEN deficiency is associated with resistance to PD‐1 checkpoint blockade therapy, likely due to its effect on costimulatory molecule expression. In the context of immune checkpoint blockade therapy, tumor cells can evade immune surveillance by reducing the expression of costimulatory molecules. Peng et al. [ 133 ] have also demonstrated that PTEN deletion enhances tumor cell resistance to T cell‐mediated immunotherapy, possibly by regulating the expression of costimulatory molecules. Figure 3 illustrates the mechanisms underlying immune evasion in tumor immunotherapy.

Potential Mechanisms for mRNA Vaccines to Overcome Drug Resistance
mRNA vaccines activate the immune system by encoding TAAs and expressing them directly within the body. Unlike conventional targeted drugs and antibody therapies, mRNA vaccines are capable of inducing a broader immune response. Targeted drugs are typically directed against specific molecular targets, while antibody therapies rely on antigen‐antibody specific binding. In contrast, mRNA vaccines can simultaneously activate multiple immune cells by encoding multiple tumor antigens, resulting in a stronger and more comprehensive immune response [ 134 ]. mRNA vaccines can also address drug resistance through several mechanisms. First, they offer rapid adaptability to drug‐resistant mutations. When drug‐resistant mutations arise in pathogens or tumor cells, researchers can quickly analyze the mutation sites and design new mRNA sequences accordingly. This flexibility enables mRNA vaccines to adapt rapidly to new mutations, thereby overcoming resistance and immune evasion issues in immunotherapy [ 135 ]. Xu et al. [ 136 ] demonstrated that mRNA vaccines could enhance T cell activity by encoding specific tumor antigens, thereby improving the immune system's ability to combat tumors. As new drug‐resistant mutations develop in tumor cells, mRNA sequences can be rapidly adjusted to maintain vaccine efficacy. Another study showed that by analyzing tumor cell mutations using whole genome sequencing and adapting mRNA sequences accordingly, therapeutic efficacy could be improved [ 137 ]. This rapid response mechanism, guided by genomic data, allows mRNA vaccines to retain high therapeutic efficiency in the face of complex tumor mutations. Second, broad‐spectrum antigen design involves engineering mRNA sequences to encode antigens that stimulate immune responses against multiple pathogens or tumor cell mutations. The key to this approach lies in identifying and selecting antigens that cover a wide range of tumor variants, thereby enhancing the effectiveness and adaptability of the vaccine. Broad‐spectrum antigen design can leverage high‐throughput sequencing to identify unique mutations within individual tumor samples, known as mutant cohorts, thus enabling personalized and comprehensive immune responses. This approach enables the rational design of tumor neoepitope vaccines tailored to individual patients, offering the advantage of specificity for nonself‐antigens that are not eliminated by central tolerance mechanisms. Nonsynonymous cancer mutations delivered via mRNA are largely immunogenic and are primarily recognized by CD4+ T cells. This personalized vaccine strategy has shown potential in controlling tumor growth in mouse models of melanoma and colon cancer. Second, mRNA vaccines can encode multiple TAAs, thereby eliciting a broader immune response. In a study by Xu et al. [ 136 ], an mRNA vaccine was synthesized containing a mixture of multiple TAAs combined with the immune‐enhancing adjuvant ImmunER, with the aim of inducing a potent antitumor immune response. This combination not only promotes DC maturation and migration but also enhances antigen presentation, thereby improving T cell proliferation and activation and ultimately leading to efficient tumor cell killing. Additionally, mRNA vaccines can overcome tumor immune escape mechanisms by encoding specific neoepitopes. Sahin et al. [ 96 ] developed personalized neoepitope mRNA vaccines and conducted clinical trials in melanoma patients. In these trials, CD4 + T‐cell responses to most of the neoepitopes were detected, and there was a low incidence of metastatic disease after several months of follow‐up [ 96 ]. This approach increases vaccine specificity and reduces the likelihood of tumor escape. Third, mRNA vaccines demonstrate remarkable potential for inducing robust and long‐lasting immune memory. By encoding specific antigens, mRNA vaccines effectively activate the immune system, generating memory B and T cells that provide sustained protection. For example, Zhuang et al. [ 138 ] showed that mRNA vaccines delivering H1N1 influenza virus HA proteins via cationic LNPs could induce a protective immune response in mice. This mechanism is also applicable to tumor vaccines, which deliver tumor antigens to activate DCs and elicit specific T‐cell responses. Furthermore, mRNA vaccines are capable of inducing diverse CD8 + T‐cell responses. Zhang et al. [ 134 ]. reported that approximately 30% of peripheral CD8 + T cells exhibited diverse TCR clonotypes, a diversity that persisted for at least 6 months after concluding vaccination. This heterogeneity is crucial for overcoming tumor immune evasion, as it enables recognition and targeting of various tumor antigenic epitopes. Moreover, mRNA vaccines can enhance antitumor immunity by improving the function of memory T cells, which play a significant role in optimizing tumor immunotherapy strategies, as demonstrated by Liu et al. [ 139 ]. Through mRNA vaccination, memory T cell function can be strengthened, thereby increasing the capability to eliminate tumor cells. In summary, mRNA vaccines are effective at inducing memory B and T cells by activating DCs, eliciting diverse CD8 + T cell responses, and enhancing memory T cell function. These memory cells are essential for long‐term protection and for overcoming tumor immune evasion. The potential mechanisms by which mRNA vaccines combat drug resistance are outlined in Figure 4 .

Optimizing the Delivery and Structure of mRNA Vaccines
As an emerging nucleic acid vaccine technology, mRNA vaccines have demonstrated great potential during the COVID‐19 pandemic, owing to their advantages of rapid development, programmability, and safety. However, mRNA molecules are inherently susceptible to degradation by nucleases in vivo and exhibit poor stability during delivery and expression, as well as low translational efficiency and immunogenicity. These limitations hinder their broader application across a wider range of diseases. Therefore, optimizing both mRNA structural design and delivery systems is crucial for enhancing their efficacy and safety. In this article, we discuss recent advances in the optimization of mRNA structures and delivery systems.
Strategies for Optimizing mRNA Structure
5′Cap Optimization
The cap structure is located at the 5′ end of mRNA and consists of methylated guanosine (m7G) pyro phosphorylated to the nucleotide at the 5′ terminus. During in vivo transcription, three common cap structures are observed: Cap0 (m7GpppXpYp), Cap1 (m7GpppXmpYp), and Cap2 (m7GpppXmpYmp). These cap structures significantly increase translation efficiency and enhance intracellular mRNA stability, primarily through their interaction with the eukaryotic translation initiation factor 4E [ 140 , 141 , 142 ]. Additionally, the absence of a terminal free phosphate group at the 5′ end after capping makes the mRNA less susceptible to degradation by alkaline phosphatase, thereby providing further protection [ 143 , 144 , 145 ]. Furthermore, methylated nucleotides found in Cap1 and Cap2 structures can block the free 2′‐OH group on the phosphate bond, conferring resistance to degradation by RNA enzymes. To prevent the loss of translation efficiency caused by reverse incorporation of the cap structure during IVT, researchers have developed an “antireverse” cap analogue (ARCA). By introducing 3′‐O‐methylation to the guanosine of the cap structure, ARCA ensures that the cap is incorporated in the correct orientation, thereby increasing mRNA stability and improving translation efficiency [ 25 ]. Over the years, scientists have continued to optimize ARCA, with the “CleanCap” analogue—developed by TriLink Biotechnologies in San Diego, CA, USA—now widely regarded as the most popular choice in the mRNA field [ 146 ]. Therefore, optimization of the 5' cap structure is crucial for enhancing the efficiency of mRNA vaccines and gene therapies.
Optimization of UTRs
Optimization of UTRs is essential for effective mRNA vaccine design, as the 5′ and 3′ UTRs can significantly influence both transcription rate and mRNA half‐life [ 147 , 148 , 149 ]. Currently, 5' UTR sequences are often derived from genes such as β‐globin and Hsp70, or are designed de novo using big data and machine learning approaches [ 150 , 151 , 152 ]. To minimize ribosomal scanning and enhance translation, it is advisable to use a short 5′ UTR of at least 20 nucleotides. Potential upstream start codons, especially AUG, should be avoided to prevent the formation of upstream ORFs, which can inhibit translation. In addition, avoiding both canonical (AUG) and noncanonical (e.g., CUG) initiation codons can further optimize the 5′ UTR and prevent interference with translation initiation [ 153 ]. It is also critical to prevent the formation of stable secondary structures within the UTRs, as these can impede ribosome recruitment and codon recognition. Notably, short 5′ UTRs have been shown to enhance mRNA translation efficiency [ 154 , 155 , 156 ]. Bioinformatics tools can predict the translational efficiency of 5' UTR candidates, providing valuable guidance for mRNA design. Furthermore, research indicates that specific stem‐loop structures within 5′ UTRs can facilitate ribosome loading and improve translational efficiency [ 157 ]. For the 3′ UTR, novel sequence motifs have been identified that confer stronger therapeutic effects than the traditional β‐globin 3′ UTR [ 158 , 159 , 160 ]. In addition, incorporating AU‐ and GU‐rich elements can improve RNA stability [ 161 , 162 ], while tandem repeats of the 3′ UTR can increase transcription efficiency [ 160 ]. In summary, careful optimization of UTRs is vital for maximizing translational efficiency and mRNA stability, particularly in the context of mRNA vaccines for tumor immunotherapy.
Codon Optimization
Codons within the ORF significantly influence translation efficiency and mRNA stability. The concept of codon optimality has been introduced to address this, as the ribosome decodes different codons at varying rates, which plays a crucial role in both translation efficiency and mRNA stability [ 75 ]. Substituting nonoptimal codons with optimal ones can greatly enhance mRNA stability, accelerate the translation process, and boost protein production [ 163 ]. Additionally, codon usage frequency is closely linked to the abundance of corresponding tRNAs in host cells; optimizing codon usage can therefore improve translation efficiency and increase protein expression. Miao et al. [ 35 ] demonstrated that adjusting the guanine (G) to cytosine (C) ratio within ORFs can regulate the rate of translation elongation and reduce uracil‐rich regions, which might otherwise be recognized by RIG‐I and subsequently hinder protein expression. Codon optimization can also expedite translation by replacing rare codons and preventing the formation of stable secondary structures and hairpin loops in the ORF, which could otherwise impede proper protein folding [ 164 , 165 , 166 , 167 ]. Moreover, Thess et al. [ 38 , 168 ] found that sequence‐engineered, chemically unmodified mRNAs exhibit higher protein expression levels compared with chemically modified but noncodon‐optimized mRNAs, highlighting the importance of codon optimization in enhancing mRNA expression efficiency. In conclusion, codon optimization not only enhances the efficiency and stability of vaccine expression but also offers a promising strategy in the field of tumor immunotherapy.
Poly(A) Tail Optimization
The poly(A) tail is a critical component of the mRNA molecule, playing a protective role in the cytoplasm by preventing degradation by exonucleases. It facilitates the assembly of the translation initiation complex through interactions with poly(A)‐binding proteins (PABPs), thereby enhancing translation efficiency [ 169 ]. Additionally, the binding of the poly(A) tail to PABPs enables efficient transport of mRNA from the nucleus to the cytoplasm. The length of the poly(A) tail significantly influences mRNA stability and translation efficiency; generally, longer poly(A) tails increase mRNA stability, although they may also affect delivery and intracellular processing in vivo. Different poly(A) tail lengths exert distinct regulatory effects on mRNA function, underscoring the importance of optimizing poly(A) tail length in mRNA design [ 169 ]. Furthermore, 2′‐O‐methylation of adenosine residues within the poly(A) tail can enhance mRNA stability and reduce immunogenicity. The function of the poly(A) tail can also be modulated by engineering specific secondary structures, such as hairpins, to further optimize mRNA performance. These strategies are essential for improving mRNA stability, translational efficiency, and therapeutic efficacy in applications such as tumor immunotherapy.
Development and Optimization of Delivery Systems
Lipid Nanoparticles
Originally designed for siRNA delivery, ionizable LNPs have become the most widely used mRNA delivery system today [ 170 , 171 , 172 ]. Since the feasibility of in vivo translation of mRNA‐LNPs was demonstrated in 2015 [ 173 ], numerous vaccine studies have utilized both unmodified and nucleoside‐modified mRNAs encapsulated in LNPs, resulting in the successful induction of long‐term protective immune responses against a wide range of infectious pathogens [ 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 ]. Additionally, mRNA‐LNPs have shown significant efficacy in the field of anticancer therapy [ 182 ]. Several clinical trials using mRNA‐LNPs are ongoing, and published data from two phase I influenza virus vaccine trials ( NCT03076385 and NCT03345043 ) are already available [ 54 , 174 ]. LNPs are primarily composed of three main components: ionizable lipids (40–50%), cholesterol (38–45%), and auxiliary phospholipids (10–12%). In some cases, a fourth component, such as polyethylene glycol (PEG)‐conjugated lipids (1–2%), is included [ 183 , 184 ]. These components together encapsulate and protect the naked mRNAs [ 185 ]. LNPs not only shield mRNAs from degradation in vivo but also promote their efficient intracellular delivery and expression. The choice of lipid type is a key strategy for optimizing LNP performance, as different lipid materials can greatly influence particle stability and delivery efficiency. For instance, several studies have shown that the use of unsaturated lipids improves mRNA transfection efficiency in vivo [ 186 ]. Additionally, certain lipid combinations can activate STING‐mediated immune responses, thereby enhancing antitumor effects [ 187 ]. The control of particle size is equally important for optimizing LNP performance. Studies have demonstrated that LNP particle size directly affects their in vivo distribution and cellular uptake efficiency. Smaller nanoparticles are more readily endocytosed by cells, which increases mRNA delivery efficiency [ 188 ]. Furthermore, the particle size of LNPs influences their biodistribution across different tissues and thus their therapeutic outcomes. For example, adjusting LNP particle size can facilitate targeted delivery to specific organs [ 189 ]. To further enhance LNP performance, researchers have explored various chemical modification strategies. For example, surface modification with PEG can significantly prolong LNP circulation time in vivo and improve stability [ 35 ]. In addition, novel amino lipid materials have been developed to promote endosomal escape, thereby improving both the efficiency and safety of mRNA delivery [ 154 ]. The use of these strategies offers great promise for advancing LNPs in mRNA vaccine delivery.
Polymer Carriers
Cationic polymers offer significant flexibility for structural modification and development, enabling the condensation of negatively charged mRNAs through electrostatic interactions. This protects mRNA from nuclease degradation and ultimately enhances delivery efficiency. Currently, cationic polymers such as polyethyleneimine (PEI), poly(β‐amino esters) (PBAE), chitosan, and others are commonly employed for mRNA delivery; these often require further modification to boost transfection efficiency and stability [ 190 , 191 , 192 ]. Recent research has focused on optimizing polymeric carriers to improve the efficacy of mRNA vaccines through various strategies [ 193 ]. First, the choice of polymer type is crucial for effective mRNA delivery. For example, combining low molecular weight PEI with cyclodextrins has been shown to be a safe and efficient method for mRNA delivery, yielding differing antibody responses depending on the route of administration [ 194 , 195 ]. Additionally, researchers have developed libraries of poly(amino esters) for structure–function studies, highlighting their potential for pulmonary mRNA delivery [ 196 , 197 ]. Surface modification is another key factor in optimizing polymeric carriers. For instance, the hydrogen bonding between PEGylated oligonucleotides and mRNA can significantly improve both stability and delivery efficiency [ 186 ]. Furthermore, the charge density and molecular weight of polymer carriers impact their delivery effectiveness, often necessitating modifications to further enhance transfection efficiency [ 198 , 199 , 200 , 201 , 202 , 203 , 204 ]. Moreover, pH‐responsive polymers—which degrade in response to cytoplasmic pH changes—have been explored to facilitate intracellular mRNA release [ 205 ]. Amphiphilic polymers containing cationic or amphiphilic amine groups have also demonstrated promise for forming nanocomplexes with mRNA, thereby improving delivery efficiency [ 187 ]. A summary of sequence and vector optimization strategies for tumor mRNA vaccines is provided in Figure 5 .

Conclusions and Future Prospects
As an emerging immunotherapeutic tool, mRNA vaccines have demonstrated great potential in controlling the COVID‐19 outbreak. Compared with conventional vaccines, mRNA vaccines offer several advantages, including rapid development, high production flexibility, and the ability to target multiple antigens. They also exhibit a favorable safety profile, with side effects generally limited to transient local reactions or mild systemic symptoms. Furthermore, mRNA vaccines do not require the use of viral vectors or intact viruses, thereby reducing the risks associated with viral components. However, despite the remarkable success of mRNA vaccines in the field of antiviral therapy, several challenges remain before their widespread adoption can be fully realized. Issues such as vaccine stability, delivery efficiency, durability of the immune response, and cost still require further optimization, particularly regarding the molecular structure of mRNA and the development of effective delivery vectors. Recent studies have shown that the efficacy of mRNA vaccines depends not only on the encoded antigen but also on the structure of the mRNA and the delivery system employed. Structural optimization of mRNA molecules can enhance their stability and immunogenicity in vivo. Additionally, the choice and refinement of delivery vehicles are critical to the success of mRNA vaccines, as appropriate delivery systems can ensure efficient mRNA transport to target cells and boost the overall effectiveness of the immune response
Currently, research on the molecular pharmacological mechanisms of mRNA vaccines remains limited. It is hoped that future studies will focus on how mRNA vaccines affect various immune cell populations including DCs, B cells, and T cells particularly regarding their roles in regulating innate and adaptive immune responses. Furthermore, investigations into the immune tolerance and immune escape mechanisms associated with mRNA vaccines should also be prioritized, especially with the aim of enhancing the broad‐spectrum protective effects of these vaccines against mutated viruses.
Looking ahead, mRNA tumor vaccines are expected to become an integral component of comprehensive cancer therapy, complementing traditional approaches such as surgery, chemotherapy, radiotherapy, and ICIs. These vaccines promise to offer patients more diverse and effective treatment options. With the ongoing advancement of personalized medicine, mRNA tumor vaccines have the potential to revolutionize cancer care, significantly improving patient survival rates and quality of life. In the future, research should focus on the integrated use of advanced technologies such as machine learning, AI, and deep learning algorithms to analyze and predict the performance of various delivery vehicles including lipids, polymers, and inorganic nanoparticles. This approach will help identify their immunological effects and optimize their stability and targeting within the body. Moreover, these technologies will enable researchers to rapidly design mRNA molecules with enhanced stability, higher translational efficiency, and reduced degradation in vivo. It is anticipated that, through the persistent efforts of researchers, mRNA cancer vaccines will continue to be optimized, bringing greater hope to cancer patients and becoming a powerful tool in the fight against cancer.
Author Contributions
Jianmei Li, Yixin Liu, and Jie Dai prepared the figures and the manuscript, including searching the literature and writing the original draft and editing. Li Yang, Feng Xiong, Jing Xia, and Jing Jin revised the details of this review. Yangping Wu and Xingchen Peng edited the manuscript. All authors have read and approved the final manuscript.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethics Statement
The authors have nothing to report.
Acknowledgments
The flowcharts of each figure were created with BioRender.com.
Data Availability Statement
The authors have nothing to report.
References
1 N. Dagan , N. Barda , E. Kepten , et al., “ BNT162b2 mRNA Covid‐19 Vaccine in a Nationwide Mass Vaccination Setting , ” New England Journal of Medicine 384 ( 2021 ): 1412 – 1423 . 33626250 10.1056/NEJMoa2101765 PMC7944975
2 L. W. Kwak , “ Cancer Vaccines: Moving Toward Prevention? , ” Cancer Prevention Research 4 ( 2011 ): 954 – 956 . 21733818 10.1158/1940-6207.CAPR-11-0236
3 M. D. Vesely , T. Zhang , and L. Chen , “ Resistance Mechanisms to Anti‐PD Cancer Immunotherapy , ” Annual Review of Immunology 40 ( 2022 ): 45 – 74 . 10.1146/annurev-immunol-070621-030155 35471840
4 P. Sharma , S. Hu‐Lieskovan , J. A. Wargo , and A. Ribas , “ Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy , ” Cell 168 ( 2017 ): 707 – 723 . 28187290 10.1016/j.cell.2017.01.017 PMC5391692
5 S. M. Ansell , A. M. Lesokhin , I. Borrello , et al., “ PD‐1 Blockade With Nivolumab in Relapsed or Refractory Hodgkin's Lymphoma , ” New England Journal of Medicine 372 ( 2015 ): 311 – 319 . 25482239 10.1056/NEJMoa1411087 PMC4348009
6 D. Memon , A. J. Schoenfeld , D. Ye , et al., “ Clinical and Molecular Features of Acquired Resistance to Immunotherapy in Non‐small Cell Lung Cancer , ” Cancer Cell 42 ( 2024 ): 209 – 224.e9 . 38215748 10.1016/j.ccell.2023.12.013 PMC11249385
7 D. Liu , R. W. Jenkins , and R. J. Sullivan , “ Mechanisms of Resistance to Immune Checkpoint Blockade , ” American Journal of Clinical Dermatology 20 ( 2019 ): 41 – 54 . 30259383 10.1007/s40257-018-0389-y PMC6358473
8 J. L. Leal and T. John , “ Immunotherapy in Advanced NSCLC without Driver Mutations: Available Therapeutic Alternatives after Progression and Future Treatment Options , ” Clinical Lung Cancer 23 ( 2022 ): 643 – 658 . 36130865 10.1016/j.cllc.2022.08.009
9 E. Dolgin , “ The Tangled History of mRNA Vaccines , ” Nature 597 ( 2021 ): 318 – 324 . 34522017 10.1038/d41586-021-02483-w
10 N. Pardi , M. J. Hogan , F. W. Porter , and D. Weissman , “ mRNA Vaccines‐a New Era in Vaccinology , ” Nature Reviews Drug Discovery 17 ( 2018 ): 261 – 279 . 29326426 10.1038/nrd.2017.243 PMC5906799
11 M. Diken , L. M. Kranz , S. Kreiter , and U. Sahin , “ mRNA: A Versatile Molecule for Cancer Vaccines , ” Current Issues in Molecular Biology 22 ( 2017 ): 113 – 128 . 27801664 10.21775/cimb.022.113
12 R. Yao , C. Xie , and X. Xia , “ Recent Progress in mRNA Cancer Vaccines , ” Human Vaccines and Immunotherapeutics 20 ( 2024 ): 2307187 . 38282471 10.1080/21645515.2024.2307187 PMC10826636
13 J. Maynard Smith and E. SzathmáRy , “ From the RNA World to the Modern World , ” The Origins of Life ( 2023 ): 37 – 46 , 10.1093/oso/9780198504931.003.0004 .
14 M. Saxena , S. H. van der Burg , C. J. M. Melief , and N. Bhardwaj , “ Therapeutic Cancer Vaccines , ” Nature Reviews Cancer 21 ( 2021 ): 360 – 378 . 33907315 10.1038/s41568-021-00346-0
15 K. Karikó , H. Muramatsu , J. Ludwig , and D. Weissman , “ Generating the Optimal mRNA for Therapy: HPLC Purification Eliminates Immune Activation and Improves Translation of Nucleoside‐modified, Protein‐encoding mRNA , ” Nucleic Acids Research 39 ( 2011 ): 1 – 10 . 21890902 10.1093/nar/gkr695 PMC3241667
16 Y. Jiang , M. Fan , Z. Yang , et al., “ Recent Advances in Nanotechnology Approaches for Non‐viral Gene Therapy , ” Biomaterials Science 10 ( 2022 ): 6862 – 6892 . 36222758 10.1039/d2bm01001a
17 R. Verbeke , M. J. Hogan , K. Loré , and N. Pardi , “ Innate Immune Mechanisms of mRNA Vaccines , ” Immunity 55 ( 2022 ): 1993 – 2005 . 36351374 10.1016/j.immuni.2022.10.014 PMC9641982
18 U. Sahin , K. Karikó , and Ö. Türeci , “ MRNA‐based Therapeutics‐developing a New Class of Drugs , ” Nature Reviews Drug Discovery 13 ( 2014 ): 759 – 780 . 25233993 10.1038/nrd4278
19 C. L. Lorentzen , J. B. Haanen , Ö. Met , and I. M. Svane , “ Clinical Advances and Ongoing Trials of mRNA Vaccines for Cancer Treatment , ” Lancet Oncology ( 2020 ): 19 – 21 . 10.1016/S1470-2045(22)00372-2 PMC9512276 36174631
20 L. S. Mbatha , J. Akinyelu , F. Maiyo , and T. Kudanga , “ Future Prospects in mRNA Vaccine Development , ” Biomedical Materials (Bristol) 18 ( 2023 ). 10.1088/1748-605X/aceceb 37589309
21 F. P. Polack , S. J. Thomas , N. Kitchin , et al., “ Safety and Efficacy of the BNT162b2 mRNA Covid‐19 Vaccine , ” New England Journal of Medicine 383 ( 2020 ): 2603 – 2615 . 33301246 10.1056/NEJMoa2034577 PMC7745181
22 B. Petsch , M. Schnee , A. B. Vogel , et al., “ Protective Efficacy of in Vitro Synthesized, Specific mRNA Vaccines Against influenza A Virus Infection , ” Nature Biotechnology 30 ( 2012 ): 1210 – 1216 . 10.1038/nbt.2436 23159882
23 A. J. Geall , A. Verma , G. R. Otten , et al., “ Nonviral Delivery of Self‐amplifying RNA Vaccines , ” Proceedings of the National Academy of Sciences of the United States of America 109 ( 2012 ): 14604 – 14609 . 22908294 10.1073/pnas.1209367109 PMC3437863
24 N. Pardi , M. J. Hogan , R. S. Pelc , et al., “ Zika Virus Protection by a Single Low‐dose Nucleoside‐modified mRNA Vaccination , ” Nature 543 ( 2017 ): 248 – 251 . 28151488 10.1038/nature21428 PMC5344708
25 Y. Cao and G. F. Gao , “ mRNA Vaccines: A Matter of Delivery , ” EClinicalMedicine 32 ( 2021 ): 100746 . 33644722 10.1016/j.eclinm.2021.100746 PMC7889829
26 Z. Kis , C. Kontoravdi , A. K. Dey , R. Shattock , and N. Shah , “ Rapid Development and Deployment of High‐volume Vaccines for Pandemic Response , ” Journal of Advanced Manufacturing and Processing 2 ( 2020 ): 1 – 10 . 10.1002/amp2.10060 PMC7361221 33977274
27 M. He , Y. Liu , S. Chen , et al., “ Serum Amyloid A Promotes Glycolysis of Neutrophils During PD‐1 Blockade Resistance in Hepatocellular Carcinoma , ” Nature Communications 15 ( 2024 ): 1 – 19 . 10.1038/s41467-024-46118-w PMC10897330 38409200
28 Z. N. Berneman , M. De Laere , P. Germonpré , et al., “ WT1‐mRNA Dendritic Cell Vaccination of Patients With Glioblastoma Multiforme, Malignant Pleural Mesothelioma, Metastatic Breast Cancer, and Other Solid Tumors: Type 1 T‐lymphocyte Responses Are Associated With Clinical Outcome , ” Journal of Hematology and Oncology 18 ( 2025 ): 4 – 9 . 39849594 10.1186/s13045-025-01661-x PMC11755790
29 C. Kurzeder , I. Bover , F. Marmé , et al., “ Double‐blind, Placebo‐controlled, Randomized Phase III Trial Evaluating pertuzumab Combined With Chemotherapy for Low Tumor human Epidermal Growth Factor Receptor 3 mRNA‐Expressing Platinum‐resistant Ovarian Cancer (PENELOPE) , ” Journal of Clinical Oncology 34 ( 2016 ): 2516 – 2525 . 27269942 10.1200/JCO.2015.66.0787
30 C. Bai , C. Wang , and Y. Lu , “ Novel Vectors and Administrations for mRNA Delivery , ” Small 19 ( 2023 ): 1 – 36 . 10.1002/smll.202303713 37475520
31 S. Kwon , M. Kwon , S. Im , K. Lee , and H. Lee , “ mRNA Vaccines: The Most Recent Clinical Applications of Synthetic mRNA , ” Archives of Pharmacal Research 45 ( 2022 ): 245 – 262 . 35426547 10.1007/s12272-022-01381-7 PMC9012156
32 A. M. Bourke , A. Schwarz , and E. M. Schuman , “ De‐centralizing the Central Dogma: MRNA Translation in Space and Time , ” Molecular Cell 83 ( 2023 ): 452 – 468 . 36669490 10.1016/j.molcel.2022.12.030
33 M. S. Attia , G. Kijanka , N. T. Nguyen , J. Zhang , and H. An , “ Advances and Prospects of RNA Delivery Nanoplatforms for Cancer Therapy , ” Acta Pharmaceutica Sinica B 15 ( 2025 ): 52 – 96 . 40041887 10.1016/j.apsb.2024.09.009 PMC11873661
34 Y. Omidi , M. M. Pourseif , R. A. Ansari , and J. Barar , “ Design and Development of mRNA and Self‐amplifying mRNA Vaccine Nanoformulations , ” Nanomedicine 19 , no. 30 ( 2024 ): 2699 – 2725 . 39535127 10.1080/17435889.2024.2419815
35 L. Miao , Y. Zhang , and L. Huang , “ mRNA Vaccine for Cancer Immunotherapy , ” Molecular Cancer 20 ( 2021 ): 1 – 23 . 33632261 10.1186/s12943-021-01335-5 PMC7905014
36 M. R. Bell and M. A. Kutzler , “ An Old Problem With New Solutions: Strategies to Improve Vaccine Efficacy in the Elderly , ” Advanced Drug Delivery Reviews 183 ( 2022 ): 114175 . 35202770 10.1016/j.addr.2022.114175
37 K. Karikó , H. Muramatsu , F. A. Welsh , et al., “ Incorporation of Pseudouridine Into mRNA Yields Superior Nonimmunogenic Vector With Increased Translational Capacity and Biological Stability , ” Molecular Therapy 16 ( 2008 ): 1833 – 1840 . 18797453 10.1038/mt.2008.200 PMC2775451
38 A. Thess , S. Grund , B. L. Mui , et al., “ Sequence‐engineered mRNA without Chemical Nucleoside Modifications Enables an Effective Protein Therapy in Large Animals , ” Molecular Therapy 23 ( 2015 ): 1456 – 1464 . 26050989 10.1038/mt.2015.103 PMC4817881
39 K. J. Kauffman , M. J. Webber , and D. G. Anderson , “ Materials for Non‐viral Intracellular Delivery of Messenger RNA Therapeutics , ” Journal of Controlled Release 240 ( 2016 ): 227 – 234 . 26718856 10.1016/j.jconrel.2015.12.032
40 Y. K. Kim , “ RNA Therapy: Rich History, Various Applications and Unlimited Future Prospects , ” Experimental and Molecular Medicine 54 ( 2022 ): 455 – 465 . 35440755 10.1038/s12276-022-00757-5 PMC9016686
41 Y. Qu , J. Xu , T. Zhang , Q. Chen , T. Sun , and C. Jiang , “ Advanced Nano‐based Strategies for mRNA Tumor Vaccine , ” Acta Pharmaceutica Sinica B 14 ( 2024 ): 170 – 189 . 38239240 10.1016/j.apsb.2023.07.025 PMC10792970
42 Y. Fan , R. Feng , X. Zhang , et al., “ Encoding and Display Technologies for Combinatorial Libraries in Drug Discovery: The Coming of Age From Biology to Therapy , ” Acta Pharmaceutica Sinica B 14 ( 2024 ): 3362 – 3384 . 39220863 10.1016/j.apsb.2024.04.006 PMC11365444
43 A. J. Pollard and E. M. Bijker , “ A Guide to Vaccinology: From Basic Principles to New Developments , ” Nature Reviews Immunology 21 ( 2021 ): 83 – 100 . 10.1038/s41577-020-00479-7 PMC7754704 33353987
44 Y. Wang , Z. Zhang , J. Luo , X. Han , Y. Wei , and X. Wei , “ mRNA Vaccine: A Potential Therapeutic Strategy , ” Molecular Cancer 20 ( 2021 ): 1 – 23 . 33593376 10.1186/s12943-021-01311-z PMC7884263
45 M. A. Liu , “ A Comparison of Plasmid DNA and mRNA as Vaccine Technologies , ” Vaccines 7 ( 2019 ): 37 . 31022829 10.3390/vaccines7020037 PMC6631684
46 R. Reindl‐Schwaighofer , A. Heinzel , M. Mayrdorfer , et al., “ Comparison of SARS‐CoV‐2 Antibody Response 4 Weeks after Homologous vs Heterologous Third Vaccine Dose in Kidney Transplant Recipients: A Randomized Clinical Trial , ” JAMA Internal Medicine 182 ( 2022 ): 165 – 171 . 34928302 10.1001/jamainternmed.2021.7372 PMC8689434
47 E. E. Walsh , R. W. Frenck , A. R. Falsey , et al., “ Safety and Immunogenicity of Two RNA‐Based Covid‐19 Vaccine Candidates , ” New England Journal of Medicine 383 ( 2020 ): 2439 – 2450 . 33053279 10.1056/NEJMoa2027906 PMC7583697
48 L. R. Baden , H. M. El Sahly , B. Essink , et al., “ Efficacy and Safety of the mRNA‐1273 SARS‐CoV‐2 Vaccine , ” New England Journal of Medicine 384 ( 2021 ): 403 – 416 . 33378609 10.1056/NEJMoa2035389 PMC7787219
49 A. W. Freyn , J. Ramos da Silva , V. C. Rosado , et al., “ A Multi‐Targeting, Nucleoside‐Modified mRNA Influenza Virus Vaccine Provides Broad Protection in Mice , ” Molecular Therapy 28 ( 2020 ): 1569 – 1584 . 32359470 10.1016/j.ymthe.2020.04.018 PMC7335735
50 M. McMahon , G. O'Dell , J. Tan , et al., “ Assessment of a Quadrivalent Nucleoside‐modified mRNA Vaccine That Protects Against Group 2 Influenza Viruses , ” Proceedings of the National Academy of Sciences of the United States of America 119 ( 2022 ): 1 – 11 . 10.1073/pnas.2206333119 PMC9659346 36322769
51 N. Pardi , J. M. Carreño , G. O'Dell , et al., “ Development of a Pentavalent Broadly Protective Nucleoside‐modified mRNA Vaccine Against Influenza B Viruses , ” Nature Communications 13 ( 2022 ): 1 – 14 . 10.1038/s41467-022-32149-8 PMC9362976 35945226
52 J. A. Flynn , T. Weber , P. J. Cejas , et al., “ Characterization of Humoral and Cell‐mediated Immunity Induced by mRNA Vaccines Expressing Influenza Hemagglutinin Stem and Nucleoprotein in Mice and Nonhuman Primates , ” Vaccine 40 ( 2022 ): 4412 – 4423 . 35680500 10.1016/j.vaccine.2022.03.063
53 C. P. Arevalo , M. J. Bolton , V. Le Sage , et al., “ A Multivalent Nucleoside‐modified mRNA Vaccine Against all Known Influenza Virus Subtypes , ” Science 378 ( 2022 ): 899 – 904 . 36423275 10.1126/science.abm0271 PMC10790309
54 R. A. Feldman , R. Fuhr , I. Smolenov , et al., “ mRNA Vaccines Against H10N8 and H7N9 Influenza Viruses of Pandemic Potential Are Immunogenic and Well Tolerated in Healthy Adults in Phase 1 Randomized Clinical Trials , ” Vaccine 37 ( 2019 ): 3326 – 3334 . 31079849 10.1016/j.vaccine.2019.04.074
55 I. T. Lee , R. Nachbagauer , D. Ensz , et al., “ Safety and Immunogenicity of a Phase 1/2 Randomized Clinical Trial of a Quadrivalent, mRNA‐based Seasonal Influenza Vaccine (mRNA‐1010) in Healthy Adults: Interim Analysis , ” Nature Communications 14 ( 2023 ): 9 – 11 . 10.1038/s41467-023-39376-7 PMC10279702 37336877
56 A. C. Langedijk and L. J. Bont , “ Respiratory Syncytial Virus Infection and Novel Interventions , ” Nature Reviews Microbiology 21 ( 2023 ): 734 – 749 . 37438492 10.1038/s41579-023-00919-w
57 E. Wilson , J. Goswami , A. H. Baqui , et al., “ Efficacy and Safety of an mRNA‐Based RSV PreF Vaccine in Older Adults , ” New England Journal of Medicine 389 ( 2023 ): 2233 – 2244 . 38091530 10.1056/NEJMoa2307079
58 A. Mullard , “ FDA Approves mRNA‐based RSV Vaccine , ” Nat Rev Drug Discovery 23 ( 2024 ): 487 . 10.1038/d41573-024-00095-3 38849520
59 B. F. Haynes , K. Wiehe , P. Borrow , et al., “ Strategies for HIV‐1 Vaccines That Induce Broadly Neutralizing Antibodies , ” Nature Reviews Immunology 23 ( 2023 ): 142 – 158 . 10.1038/s41577-022-00753-w PMC9372928 35962033
60 M. Melo , E. Porter , Y. Zhang , et al., “ Immunogenicity of RNA Replicons Encoding HIV Env Immunogens Designed for Self‐Assembly Into Nanoparticles , ” Molecular Therapy 27 ( 2019 ): 2080 – 2090 . 31515132 10.1016/j.ymthe.2019.08.007 PMC6904793
61 E. Melzi , J. R. Willis , K. M. Ma , et al., “ Membrane‐bound mRNA Immunogens Lower the Threshold to Activate HIV Env V2 Apex‐directed Broadly Neutralizing B Cell Precursors in Humanized Mice , ” Immunity 55 ( 2022 ): 2168 – 2186.e6 . 36179690 10.1016/j.immuni.2022.09.003 PMC9671093
62 N. Moyo , E. Wee , B. Korber , et al., “ Tetravalent Immunogen Assembled From Conserved Regions of HIV‐1 and Delivered as mRNA Demonstrates Potent Preclinical T‐cell Immunogenicity and Breadth , ” Vaccines 8 ( 2020 ): 1 – 10 . 10.3390/vaccines8030360 PMC7563622 32640600
63 K. O. Saunders , N. Pardi , R. Parks , et al., “ Lipid Nanoparticle Encapsulated Nucleoside‐modified mRNA Vaccines Elicit Polyfunctional HIV‐1 Antibodies Comparable to Proteins in Nonhuman Primates , ” Npj Vaccines 6 ( 2021 ): 1 – 14 . 33837212 10.1038/s41541-021-00307-6 PMC8035178
64 P. Zhang , E. Narayanan , Q. Liu , et al., “ A Multiclade Env–gag VLP mRNA Vaccine Elicits Tier‐2 HIV‐1‐neutralizing Antibodies and Reduces the Risk of Heterologous SHIV Infection in Macaques , ” Nature Medicine 27 ( 2021 ): 2234 – 2245 . 10.1038/s41591-021-01574-5 34887575
65 J. R. Willis , M. Prabhakaran , M. Muthui , et al., “ Vaccination With mRNA‐encoded Nanoparticles Drives Early Maturation of HIV bnAb Precursors in Humans , ” Science 8382 ( 2025 ): 1 – 36 . 10.1126/science.adr8382 PMC13164876 40373112
66 S. A. Riddler , Z. Moodie , J. Clark , et al., “ High Frequency of Chronic Urticaria Following an Investigational HIV‐1 BG505 MD39.3 Trimer mRNA Vaccine in a Phase 1, Randomized, Open‐Label Clinical Trial (HVTN 302) , ” Annals of Internal Medicine 178 ( 2025 ), 10.7326/ANNALS-24-02701 . PMC12404031 40294415
67 X. Hu , K. P. Karthigeyan , S. Herbek , et al., “ Human Cytomegalovirus mRNA‐1647 Vaccine Candidate Elicits Potent and Broad Neutralization and Higher Antibody‐Dependent Cellular Cytotoxicity Responses than the gB/MF59 Vaccine , ” Journal of Infectious Diseases 230 ( 2024 ): 455 – 466 . 38324766 10.1093/infdis/jiad593 PMC11326847
68 M. Alberer , U. Gnad‐Vogt , H. S. Hong , et al., “ Safety and Immunogenicity of a mRNA Rabies Vaccine in Healthy Adults: An Open‐label, Non‐randomised, Prospective, First‐in‐human Phase 1 Clinical Trial , ” The Lancet 390 ( 2017 ): 1511 – 1520 . 10.1016/S0140-6736(17)31665-3 28754494
69 S. Awasthi , L. M. Hook , N. Pardi , et al., “ Nucleoside‐modified mRNA Encoding HSV‐2 Glycoproteins C, D, and E Prevents Clinical and Subclinical Genital herpes , ” Science Immunology 4 ( 2019 ): eaaw7083 . 31541030 10.1126/sciimmunol.aaw7083 PMC6822172
70 J. S. Chahal , O. F. Khan , C. L. Cooper , et al., “ Dendrimer‐RNA Nanoparticles Generate Protective Immunity Against Lethal Ebola, H1N1 Influenza, and Toxoplasma Gondii Challenges With a Single Dose , ” Proceedings of the National Academy of Sciences of the United States of America 113 ( 2016 ): E4133 – E4142 . 27382155 10.1073/pnas.1600299113 PMC4961123
71 M. Meyer , E. Huang , O. Yuzhakov , P. Ramanathan , G. Ciaramella , and A. Bukreyev , “ Modified mRNA‐Based Vaccines Elicit Robust Immune Responses and Protect Guinea Pigs From Ebola Virus Disease , ” Journal of Infectious Diseases 217 ( 2018 ): 451 – 455 . 29281112 10.1093/infdis/jix592 PMC5853918
72 A. J. Ronk , N. M. Lloyd , M. Zhang , et al., “ A Lassa Virus mRNA Vaccine Confers Protection but Does Not Require Neutralizing Antibody in a guinea Pig Model of Infection , ” Nature Communications 14 ( 2023 ): 1 – 13 . 10.1038/s41467-023-41376-6 PMC10497546 37699929
73 A. W. Freyn , C. Atyeo , P. L. Earl , et al., “ An Mpox Virus mRNA‐lipid Nanoparticle Vaccine Confers Protection Against Lethal Orthopoxviral Challenge , ” Science Translational Medicine 15 ( 2023 ). 10.1126/scitranslmed.adg3540 37792954
74 U. Sahin , P. Oehm , E. Derhovanessian , et al., “ An RNA Vaccine Drives Immunity in Checkpoint‐inhibitor‐treated Melanoma , ” Nature 585 ( 2020 ): 107 – 112 . 32728218 10.1038/s41586-020-2537-9
75 Y. Yuan , F. Gao , Y. Chang , Q. Zhao , and X. He , “ Advances of mRNA Vaccine in Tumor: A Maze of Opportunities and Challenges , ” Biomarker Research 11 ( 2023 ). 10.1186/s40364-023-00449-w PMC9845107 36650562
76 B. E. Ferdows , D. N. Patel , W. Chen , X. Huang , N. Kong , and W. Tao , “ RNA Cancer Nanomedicine: Nanotechnology‐mediated RNA Therapy , ” Nanoscale 14 ( 2022 ): 4448 – 4455 . 35080555 10.1039/d1nr06991h
77 S. Pan , R. Fan , B. Han , A. Tong , and G. Guo , “ The Potential of mRNA Vaccines in Cancer Nanomedicine and Immunotherapy , ” Trends in Immunology 45 ( 2024 ): 20 – 31 . 38142147 10.1016/j.it.2023.11.003
78 A. M. Dudek , S. Martin , A. D. Garg , and P. Agostinis , “ Immature, Semi‐mature, and Fully Mature Dendritic Cells: Toward a DC‐cancer Cells Interface That Augments Anticancer Immunity , ” Frontiers in Immunology 4 ( 2013 ): 1 – 14 . 24376443 10.3389/fimmu.2013.00438 PMC3858649
79 L. Zhou , W. Yi , Z. Zhang , et al., “ STING Agonist‐boosted mRNA Immunization via Intelligent Design of Nanovaccines for Enhancing Cancer Immunotherapy , ” National Science Review 10 ( 2023 ): nwad214 . 37693123 10.1093/nsr/nwad214 PMC10484175
80 N. Prokhnevska , M. A. Cardenas , R. M. Valanparambil , et al., “ CD8+ T Cell Activation in Cancer Comprises an Initial Activation Phase in Lymph Nodes Followed by Effector Differentiation Within the Tumor , ” Immunity 56 ( 2023 ): 107 – 124.e5 . 36580918 10.1016/j.immuni.2022.12.002 PMC10266440
81 J. R. Melamed , S. S. Yerneni , M. L. Arral , et al., “ Ionizable Lipid Nanoparticles Deliver mRNA to Pancreatic β Cells via Macrophage‐mediated Gene Transfer , ” Science Advances 9 ( 2023 ): eade1444 . 36706177 10.1126/sciadv.ade1444 PMC9882987
82 Q. He , H. Gao , D. Tan , H. Zhang , and J. Z. Wang , “ mRNA Cancer Vaccines: Advances, Trends and Challenges , ” Annals of Oncology ( 2020 ): 19 – 21 . 10.1016/j.apsb.2022.03.011 PMC8942458 35345451
83 P. G. Coulie , B. J. Van Den Eynde , P. Van Der Bruggen , and T. Boon , “ Tumour Antigens Recognized by T Lymphocytes: At the Core of Cancer Immunotherapy , ” Nature Reviews Cancer 14 ( 2014 ): 135 – 146 . 24457417 10.1038/nrc3670
84 R. E. Hollingsworth and K. Jansen , “ Turning the Corner on Therapeutic Cancer Vaccines , ” Npj Vaccines 4 ( 2019 ): 1 – 10 . 30774998 10.1038/s41541-019-0103-y PMC6368616
85 N. O. Alarcon , M. Jaramillo , H. M. Mansour , and B. Sun , “ Therapeutic Cancer Vaccines—Antigen Discovery and Adjuvant Delivery Platforms , ” Pharmaceutics 14 ( 2022 ): 1448 . 35890342 10.3390/pharmaceutics14071448 PMC9325128
86 R. A. Hernandez‐Lopez , W. Yu , K. A. Cabral , et al., “ T Cell Circuits That Sense Antigen Density With an Ultrasensitive Threshold , ” Pharmacognosy Magazine 75 ( 2021 ): 399 – 405 . 10.1126/science.abc1855 PMC8025675 33632893
87 Z. A. Gibbs and A. W. Whitehurst , “ Emerging Contributions of Cancer/Testis Antigens to Neoplastic Behaviors , ” Trends in Cancer 4 ( 2018 ): 701 – 712 . 30292353 10.1016/j.trecan.2018.08.005 PMC6366644
88 J. Liu , M. Fu , M. Wang , D. Wan , Y. Wei , and X. Wei , “ Cancer Vaccines as Promising Immuno‐therapeutics: Platforms and Current Progress , ” Journal of Hematology and Oncology 15 ( 2022 ): 1 – 26 . 35303904 10.1186/s13045-022-01247-x PMC8931585
89 Y. N. Diep , T. J. Kim , H. Cho , and L. P. Lee , “ Nanomedicine for Advanced Cancer Immunotherapy , ” Journal of Controlled Release 351 ( 2022 ): 1017 – 1037 . 36220487 10.1016/j.jconrel.2022.10.004
90 A. J. Barbier , A. Y. Jiang , P. Zhang , R. Wooster , and D. G. Anderson , “ The Clinical Progress of mRNA Vaccines and Immunotherapies , ” Nature Biotechnology 40 ( 2022 ): 840 – 854 . 10.1038/s41587-022-01294-2 35534554
91 Y. Guo , K. Lei , and L. Tang , “ Neoantigen Vaccine Delivery for Personalized Anticancer Immunotherapy , ” Frontiers in Immunology 9 ( 2018 ): 1 – 8 . 30013560 10.3389/fimmu.2018.01499 PMC6036114
92 D. K. Wells , M. M. van Buuren , K. K. Dang , et al., “ Key Parameters of Tumor Epitope Immunogenicity Revealed through a Consortium Approach Improve Neoantigen Prediction , ” Cell 183 ( 2020 ): 818 – 834.e13 . 33038342 10.1016/j.cell.2020.09.015 PMC7652061
93 E. Blass and P. A. Ott , “ Advances in the Development of Personalized Neoantigen‐based Therapeutic Cancer Vaccines , ” Nature Reviews Clinical Oncology 18 ( 2021 ): 215 – 229 . 10.1038/s41571-020-00460-2 PMC7816749 33473220
94 G. Cafri , J. J. Gartner , T. Zaks , et al., “ mRNA Vaccine–induced Neoantigen‐specific T Cell Immunity in Patients With Gastrointestinal Cancer , ” Journal of Clinical Investigation 130 ( 2020 ): 5976 – 5988 . 33016924 10.1172/JCI134915 PMC7598064
95 A. Esprit , W. de Mey , R. Bahadur Shahi , K. Thielemans , L. Franceschini , and K. Breckpot , “ Neo‐antigen mRNA Vaccines , ” Vaccines 8 ( 2020 ): 1 – 24 . 10.3390/vaccines8040776 PMC7766040 33353155
96 U. Sahin , E. Derhovanessian , M. Miller , et al., “ Personalized RNA Mutanome Vaccines Mobilize Poly‐specific Therapeutic Immunity Against Cancer , ” Nature 547 ( 2017 ): 222 – 226 . 28678784 10.1038/nature23003
97 C. Pollard , S. De Koker , X. Saelens , G. Vanham , and J. Grooten , “ Challenges and Advances towards the Rational Design of mRNA Vaccines , ” Trends in Molecular Medicine 19 ( 2013 ): 705 – 713 . 24138818 10.1016/j.molmed.2013.09.002
98 P. A. Ott , Z. Hu , D. B. Keskin , et al., “ An Immunogenic Personal Neoantigen Vaccine for Melanoma Patients , ” Nature Medicine 10 ( 2018 ): 1 – 13 .
99 S. Wilgenhof , A. Van Nuffel , D. Benteyn , et al., “ A Phase IB Study on Intravenous Synthetic mRNA Electroporated Dendritic Cell Immunotherapy in Pretreated Advanced Melanoma Patients , ” Annals of Oncology 24 ( 2013 ): 2686 – 2693 . 23904461 10.1093/annonc/mdt245
100 D. J. Chung , R. D. Carvajal , M. A. Postow , et al., “ Langerhans‐type Dendritic Cells Electroporated With TRP‐2 mRNA Stimulate Cellular Immunity Against Melanoma: Results of a Phase I Vaccine Trial , ” OncoImmunology 7 ( 2018 ): 0–36. 10.1080/2162402X.2017.1372081 PMC5739582 29296525
101 R. Tenchov , R. Bird , A. E. Curtze , and Q. Zhou , “ Lipid Nanoparticles From Liposomes to mRNA Vaccine Delivery, a Landscape of Research Diversity and Advancement , ” ACS Nano 15 ( 2021 ): 16982 – 17015 . 34181394 10.1021/acsnano.1c04996
102 Z. Hu , P. A. Ott , and C. J. Wu , “ Towards Personalized, Tumour‐specific, Therapeutic Vaccines for Cancer , ” Nature Reviews Immunology 18 ( 2018 ): 168 – 182 . 10.1038/nri.2017.131 PMC6508552 29226910
103 T. N. Schumacher , W. Scheper , and P. Kvistborg , “ Cancer Neoantigens , ” Annual Review of Immunology 37 ( 2019 ): 173 – 200 . 10.1146/annurev-immunol-042617-053402 30550719
104 T. K. Kim , R. S. Herbst , and L. Chen , “ Defining and Understanding Adaptive Resistance in Cancer Immunotherapy , ” Trends in Immunology 39 ( 2018 ): 624 – 631 . 29802087 10.1016/j.it.2018.05.001 PMC6066429
105 S. L. Topalian , C. G. Drake , and D. M. Pardoll , “ Immune Checkpoint Blockade: A Common Denominator Approach to Cancer Therapy , ” Cancer Cell 27 ( 2015 ): 450 – 461 . 25858804 10.1016/j.ccell.2015.03.001 PMC4400238
106 J. M. Taube , R. A. Anders , G. D. Young , et al., “ Colocalization of Inflammatory Response With B7‐H1 Expression in human Melanocytic Lesions Supports an Adaptive Resistance Mechanism of Immune Escape , ” Science Translational Medicine 4 ( 2012 ). 10.1126/scitranslmed.3003689 PMC3568523 22461641
107 J. L. Benci , B. Xu , Y. Qiu , et al., “ Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade , ” Cell 167 ( 2016 ): 1540 – 1554.e12 . 27912061 10.1016/j.cell.2016.11.022 PMC5385895
108 A. Kalbasi and A. Ribas , “ Tumour‐intrinsic Resistance to Immune Checkpoint Blockade , ” Nature Reviews Immunology 20 ( 2020 ): 25 – 39 . 10.1038/s41577-019-0218-4 PMC8499690 31570880
109 M. J. Hogan and N. Pardi , “ MRNA Vaccines in the COVID‐19 Pandemic and Beyond , ” Annual Review of Medicine 73 ( 2022 ): 17 – 39 . 10.1146/annurev-med-042420-112725 34669432
110 R. Weber , V. Fleming , X. Hu , et al., “ Myeloid‐derived Suppressor Cells Hinder the Anti‐cancer Activity of Immune Checkpoint Inhibitors , ” Frontiers in Immunology 9 ( 2018 ): 1 – 9 . 29942309 10.3389/fimmu.2018.01310 PMC6004385
111 D. R. Leach , M. F. Krummel , and J. P. Allison , “ Enhancement of Antitumor Immunity by CTLA‐4 Blockade , ” Science 271 ( 1996 ): 1734 – 1736 . 8596936 10.1126/science.271.5256.1734
112 D. B. Page , M. A. Postow , and M. K. Callahan , J. P. Allison , and J. D. Wolchok , “ Immune Modulation in Cancer With Antibodies , ” Annual Review of Medicine 65 ( 2014 ): 185 – 202 . 10.1146/annurev-med-092012-112807 24188664
113 N. McGranahan , A. J. S. Furness , R. Rosenthal , et al., “ Clonal Neoantigens Elicit T Cell Immunoreactivity and Sensitivity to Immune Checkpoint Blockade , ” Science 351 ( 2016 ): 1463 – 1469 . 26940869 10.1126/science.aaf1490 PMC4984254
114 S. Gettinger , J. Choi , K. Hastings , et al., “ Impaired HLA Class I Antigen Processing and Presentation as a Mechanism of Acquired Resistance to Immune Checkpoint Inhibitors in Lung Cancer , ” Cancer Discovery 7 ( 2017 ): 1420 – 1435 . 29025772 10.1158/2159-8290.CD-17-0593 PMC5718941
115 S. Spranger , D. Dai , B. Horton , and T. F. Gajewski , “ Tumor‐Residing Batf3 Dendritic Cells Are Required for Effector T Cell Trafficking and Adoptive T Cell Therapy , ” Cancer Cell 31 ( 2017 ): 711 – 723.e4 . 28486109 10.1016/j.ccell.2017.04.003 PMC5650691
116 S. Spranger , R. Bao , and T. F. Gajewski , “ Melanoma‐intrinsic β‐catenin Signalling Prevents Anti‐tumour Immunity , ” Nature 523 ( 2015 ): 231 – 235 . 25970248 10.1038/nature14404
117 C. M. D'Urso , Z. G. Wang , Y. Cao , R. Tatake , R. A. Zeff , and S. Ferrone , “ Lack of HLA Class I Antigen Expression by Cultured Melanoma Cells FO‐1 due to a Defect in B2M Gene Expression , ” Journal of Clinical Investigation 87 ( 1991 ): 284 – 292 . 1898655 10.1172/JCI114984 PMC295046
118 K. A. Schalper , M. Carleton , M. Zhou , et al., “ Elevated Serum Interleukin‐8 Is Associated With Enhanced Intratumor Neutrophils and Reduced Clinical Benefit of Immune‐checkpoint Inhibitors , ” Nature Medicine 26 ( 2020 ): 688 – 692 . 10.1038/s41591-020-0856-x PMC8127102 32405062
119 B. Mirlekar , D. Michaud , S. J. Lee , et al., “ Bcell‐derived IL35 Drives STAT3‐DependentCD8+ T‐cell Exclusion in Pancreatic Cancer , ” Cancer Immunology Research 8 ( 2020 ): 292 – 308 . 32024640 10.1158/2326-6066.CIR-19-0349 PMC7056532
120 F. Arce Vargas , A. J. Furness , I. Solomon , et al., “ Fc‐Optimized Anti‐CD25 Depletes Tumor‐Infiltrating Regulatory T Cells and Synergizes With PD‐1 Blockade to Eradicate Established Tumors , ” Immunity 46 ( 2017 ): 577 – 586 . 28410988 10.1016/j.immuni.2017.03.013 PMC5437702
121 F. Veglia , M. Perego , and D. Gabrilovich , “ Myeloid‐derived Suppressor Cells Coming of Age , ” Nature Immunology 19 ( 2018 ): 108 – 119 . 29348500 10.1038/s41590-017-0022-x PMC5854158
122 A. Mantovani , F. Marchesi , A. Malesci , L. Laghi , and P. Allavena , “ Tumour‐associated Macrophages as Treatment Targets in Oncology , ” Nature Reviews Clinical Oncology 14 ( 2017 ): 399 – 416 . 10.1038/nrclinonc.2016.217 PMC5480600 28117416
123 B. Shang , Y. Liu , S. J. Jiang , and Y. Liu , “ Prognostic Value of Tumor‐infiltrating FoxP3+ Regulatory T Cells in Cancers: A Systematic Review and Meta‐analysis , ” Scientific Reports 5 ( 2015 ): 1 – 9 . 10.1038/srep15179 PMC4604472 26462617
124 F. Ichihara , K. Kono , A. Takahashi , et al., “ Increased Populations of Regulatory T Cells in Peripheral Blood and Tumor‐infiltrating Lymphocytes in Patients With Gastric and Esophageal Cancers , ” Clinical Cancer Research 9 ( 2003 ): 4404 – 4408 . 14555512
125 T. J. Curiel , G. Coukos , L. Zou , et al., “ Specific Recruitment of Regulatory T Cells in Ovarian Carcinoma Fosters Immune Privilege and Predicts Reduced Survival , ” Nature Medicine 10 ( 2004 ): 942 – 949 . 10.1038/nm1093 15322536
126 N. Hiraoka , K. Onozato , T. Kosuge , and S. Hirohashi , “ Prevalence of FOXP3+ Regulatory T Cells Increases During the Progression of Pancreatic Ductal Adenocarcinoma and Its Premalignant Lesions , ” Clinical Cancer Research 12 ( 2006 ): 5423 – 5434 . 17000676 10.1158/1078-0432.CCR-06-0369
127 K. Wing , Y. Onishi , P. Prieto‐Martin , et al., “ CTLA‐4 Control Over Foxp3+Regulatory T Cell Function , ” Science 322 ( 2008 ): 271 – 275 . 18845758 10.1126/science.1160062
128 H. S. Kuehn , W. Ouyang , B. Lo , et al., “ Immune Dysregulation in human Subjects With Heterozygous Germline Mutations in CTLA4 , ” Science 345 ( 2014 ): 1623 – 1627 . 25213377 10.1126/science.1255904 PMC4371526
129 X. Du , F. Tang , M. Liu , et al., “ A Reappraisal of CTLA‐4 Checkpoint Blockade in Cancer Immunotherapy , ” Cell Research 28 ( 2018 ): 416 – 432 . 29472691 10.1038/s41422-018-0011-0 PMC5939050
130 T. R. Simpson , F. Li , W. Montalvo‐Ortiz , et al., “ Fc‐dependent Depletion of Tumor‐infiltrating Regulatory T Cells co‐defines the Efficacy of Anti‐CTLA‐4 Therapy Against Melanoma , ” Journal of Experimental Medicine 210 ( 2013 ): 1695 – 1710 . 23897981 10.1084/jem.20130579 PMC3754863
131 E. Romano , M. Kusio‐Kobialka , P. G. Foukas , et al., “ Ipilimumab‐dependent Cell‐mediated Cytotoxicity of Regulatory T Cells Ex Vivo by Nonclassical Monocytes in Melanoma Patients , ” Proceedings of the National Academy of Sciences of the United States of America 112 ( 2015 ): 6140 – 6145 . 25918390 10.1073/pnas.1417320112 PMC4434760
132 S. George , D. Miao , G. D. Demetri , et al., “ Loss of PTEN Is Associated With Resistance to Anti‐PD‐1 Checkpoint Blockade Therapy in Metastatic Uterine Leiomyosarcoma , ” Immunity 46 ( 2017 ): 197 – 204 . 28228279 10.1016/j.immuni.2017.02.001 PMC5408320
133 W. Peng , J. Q. Chen , C. Liu , et al., “ Loss of PTEN Promotes Resistance to T Cell–mediated Immunotherapy , ” Cancer Discovery 6 ( 2016 ): 202 – 216 . 26645196 10.1158/2159-8290.CD-15-0283 PMC4744499
134 G. Zhang , T. Tang , Y. Chen , X. Huang , and T. Liang , “ mRNA Vaccines in Disease Prevention and Treatment , ” Signal Transduction and Targeted Therapy 8 ( 2023 ). 10.1038/s41392-023-01579-1 PMC10509165 37726283
135 X. Wang , W. Wang , S. Zou , et al., “ Combination Therapy of KRAS G12V mRNA Vaccine and Pembrolizumab: Clinical Benefit in Patients With Advanced Solid Tumors , ” Cell Research 34 , no. 9 ( 2024 ): 661 – 664 . 38914844 10.1038/s41422-024-00990-9 PMC11369195
136 Z. Xu , Z. Xiao , J. Wang , et al., “ Novel mRNA Adjuvant ImmunER Enhances Prostate Cancer Tumor‐associated Antigen mRNA Therapy via Augmenting T Cell Activity , ” OncoImmunology 13 ( 2024 ): 1 – 15 . 10.1080/2162402X.2024.2373526 PMC11212567 38948931
137 R. Rosell , E. Jantus‐lewintre , P. Cao , et al., KRAS‐mutant non‐small cell lung cancer (NSCLC) therapy based on tepotinib and omeprazole combination . 1 – 15 ( 2024 ). 10.1186/s12964-024-01667-x PMC11167791 38867255
138 X. Zhuang , Y. Qi , M. Wang , et al., “ MRNA Vaccines Encoding the HA Protein of Influenza a H1N1 Virus Delivered by Cationic Lipid Nanoparticles Induce Protective Immune Responses in Mice , ” Vaccines 8 ( 2020 ): 1 – 16 . 10.3390/vaccines8010123 PMC7157730 32164372
139 Q. Liu , Z. Sun , and L. Chen , “ Memory T Cells: Strategies for Optimizing Tumor Immunotherapy , ” Protein and Cell 11 ( 2020 ): 549 – 564 . 32221812 10.1007/s13238-020-00707-9 PMC7381543
140 M. Shanmugasundaram , A. Senthilvelan , and A. R. Kore , “ Recent Advances in Modified Cap Analogs: Synthesis, Biochemical Properties, and mRNA Based Vaccines , ” Chemical Record 22 ( 2022 ): e202200005 . 35420257 10.1002/tcr.202200005 PMC9111249
141 S. Xu , K. Yang , R. Li , and L. Zhang , “ mRNA Vaccine Era—mechanisms, Drug Platform and Clinical Prospection , ” International Journal of Molecular Sciences 21 ( 2020 ): 6582 . 32916818 10.3390/ijms21186582 PMC7554980
142 D. Weissman , “ mRNA Transcript Therapy , ” Expert Review of Vaccines 14 ( 2014 ): 265 – 281 . 25359562 10.1586/14760584.2015.973859
143 D. R. Gallie , “ The Cap and Poly(A) Tail Function Synergistically to Regulate mRNA Translational Efficiency , ” Genes and Development 5 ( 1991 ): 2108 – 2116 . 1682219 10.1101/gad.5.11.2108
144 J. Stepinski , C. Waddell , R. Stolarski , E. Darzynkiewicz , and R. E. Rhoads , “ Synthesis and Properties of mRNAs Containing the Novel ‘Anti‐reverse’ cap Analogs 7‐methyl(3′‐O‐methyl)GpppG and 7‐methyl(3′‐deoxy)GpppG , ” Rna 7 ( 2001 ): 1486 – 1495 . 11680853 PMC1370192
145 R. W. Malone , P. L. Felgner , and I. M. Verma , “ Cationic Liposome‐mediated RNA Transfection , ” Proceedings of the National Academy of Sciences of the United States of America 86 ( 1989 ): 6077 – 6081 . 2762315 10.1073/pnas.86.16.6077 PMC297778
146 S. Pascolo , “ Synthetic Messenger Rna‐based Vaccines: From Scorn to Hype , ” Viruses 13 ( 2021 ). 10.3390/v13020270 PMC7916233 33572452
147 K. H. Asrani , J. D. Farelli , M. R. Stahley , et al., “ Optimization of mRNA Untranslated Regions for Improved Expression of Therapeutic mRNA , ” RNA Biology 15 ( 2018 ): 756 – 762 . 29578372 10.1080/15476286.2018.1450054 PMC6152433
148 P. J. Sample , B. Wang , D. W. Reid , et al., “ Human 5′ UTR Design and Variant Effect Prediction From a Massively Parallel Translation Assay , ” Nature Biotechnology 37 ( 2019 ): 803 – 809 . 10.1038/s41587-019-0164-5 PMC7100133 31267113
149 Z. Trepotec , M. K. Aneja , J. Geiger , G. Hasenpusch , C. Plank , and C. Rudolph , “ Maximizing the Translational Yield of mRNA Therapeutics by Minimizing 5′‐UTRs , ” Tissue Engineering—Part A 25 ( 2019 ): 69 – 79 . 29638193 10.1089/ten.TEA.2017.0485
150 J. Carralot , J. Probst , I. Hoerr , et al., “ Polarization of Immunity Induced by Direct Injection of Naked Sequence‐stabilized mRNA Vaccines , ” Cellular and Molecular Life Sciences 61 ( 2004 ): 2418 – 2424 . 15378210 10.1007/s00018-004-4255-0 PMC7079797
151 Y. Weng , C. Li , T. Yang , et al., “ The Challenge and Prospect of mRNA Therapeutics Landscape , ” Biotechnology Advances 40 ( 2020 ). 10.1016/j.biotechadv.2020.107534 32088327
152 R. P. H. de Jongh , A. D. J. van Dijk , M. K. Julsing , P. J. Schaap , and D. de Ridder , “ Designing Eukaryotic Gene Expression Regulation Using Machine Learning , ” Trends in Biotechnology 38 ( 2020 ): 191 – 201 . 31431299 10.1016/j.tibtech.2019.07.007
153 P. R. Araujo , K. Yoon , D. Ko , et al., “ Before It Gets Started: Regulating Translation at the 5' UTR ,” Comparative and Functional Genomics 2012 ( 2012 ). 10.1155/2012/475731 PMC3368165 22693426
154 D. D. Kang , H. Li , and Y. Dong , “ Advancements of in Vitro Transcribed mRNA (IVT mRNA) to Enable Translation Into the Clinics , ” Advanced Drug Delivery Reviews 199 ( 2023 ): 114961 . 37321375 10.1016/j.addr.2023.114961 PMC10264168
155 M. Kozak , “ At Least Six Nucleotides Preceding the AUG Initiator Codon Enhance Translation in Mammalian Cells , ” Journal of Molecular Biology 196 ( 1987 ): 947 – 950 . 3681984 10.1016/0022-2836(87)90418-9
156 J. Pelletier and N. Sonenberg , “ Insertion Mutagenesis to Increase Secondary Structure Within the 5′ Noncoding Region of a Eukaryotic mRNA Reduces Translational Efficiency , ” Cell 40 ( 1985 ): 515 – 526 . 2982496 10.1016/0092-8674(85)90200-4
157 K. Leppek , G. W. Byeon , W. Kladwang , et al., “ Combinatorial Optimization of mRNA Structure, Stability, and Translation for RNA‐based Therapeutics , ” Nature Communications 13 ( 2022 ). 10.1038/s41467-022-28776-w PMC8940940 35318324
158 N. Pardi , M. J. Hogan , and D. Weissman , “ Recent Advances in mRNA Vaccine Technology , ” Current Opinion in Immunology 65 ( 2020 ): 14 – 20 . 32244193 10.1016/j.coi.2020.01.008
159 M. Ferizi , C. Leonhardt , C. Meggle , et al., “ Stability Analysis of Chemically Modified mRNA Using Micropattern‐based Single‐cell Arrays , ” Lab on a Chip 15 ( 2015 ): 3561 – 3571 . 26201602 10.1039/c5lc00749f
160 A. G. Orlandini von Niessen , M. A. Poleganov , C. Rechner , et al., “ Improving mRNA‐Based Therapeutic Gene Delivery by Expression‐Augmenting 3′ UTRs Identified by Cellular Library Screening , ” Molecular Therapy 27 ( 2019 ): 824 – 836 . 30638957 10.1016/j.ymthe.2018.12.011 PMC6453560
161 E. L. Murray and D. R. Schoenberg , “ A+U‐Rich Instability Elements Differentially Activate 5′‐3′ and 3′‐5′ mRNA Decay , ” Molecular and Cellular Biology 27 ( 2007 ): 2791 – 2799 . 17296726 10.1128/MCB.01445-06 PMC1899944
162 I. Vlasova‐St Louis and P. R. Bohjanen , “ Coordinate Regulation of mRNA Decay Networks by GU‐rich Elements and CELF1 , ” Current Opinion in Genetics and Development 21 ( 2011 ): 444 – 451 . 21497082 10.1016/j.gde.2011.03.002 PMC3146975
163 V. Presnyak , N. Alhusaini , Y. Chen , et al., “ Codon Optimality Is a Major Determinant of mRNA Stability , ” Cell 160 ( 2015 ): 1111 – 1124 . 25768907 10.1016/j.cell.2015.02.029 PMC4359748
164 S. Linares‐Fernández , C. Lacroix , J. Y. Exposito , and B. Verrier , “ Tailoring mRNA Vaccine to Balance Innate/Adaptive Immune Response , ” Trends in Molecular Medicine 26 ( 2020 ): 311 – 323 . 31699497 10.1016/j.molmed.2019.10.002
165 G. Kudla , A. W. Murray , D. Tollervey , and J. B. Plotkin , “ Coding‐sequence Determinants of Gene Expression in Escherichia coli , ” Bone 23 ( 2008 ): 1 – 7 . 10.1126/science.1170160 PMC3902468 19359587
166 F. Buhr , S. Jha , M. Thommen , et al., “ Synonymous Codons Direct Cotranslational Folding Toward Different Protein Conformations , ” Molecular Cell 61 ( 2016 ): 341 – 351 . 26849192 10.1016/j.molcel.2016.01.008 PMC4745992
167 C. Yu , Y. Dang , Z. Zhou , et al., “ Codon Usage Influences the Local Rate of Translation Elongation to Regulate Co‐translational Protein Folding , ” Molecular Cell 59 ( 2015 ): 744 – 754 . 26321254 10.1016/j.molcel.2015.07.018 PMC4561030
168 T. Schlake , A. Thess , M. Fotin‐mleczek , and K. Kallen , “ Developing mRNA‐vaccine Technologies , ” RNA Biol 9 ( 2012 ): 1319 – 1330 . 23064118 10.4161/rna.22269 PMC3597572
169 S. A. Lima , L. B. Chipman , A. L. Nicholson , et al., “ Short Poly(A) Tails Are a Conserved Feature of Highly Expressed Genes , ” Nature Structural and Molecular Biology 24 ( 2017 ): 1057 – 1063 . 10.1038/nsmb.3499 PMC5877826 29106412
170 S. C. Semple , A. Akinc , J. Chen , et al., “ Rational Design of Cationic Lipids for siRNA Delivery , ” Nature Biotechnology 28 ( 2010 ): 172 – 176 . 10.1038/nbt.1602 20081866
171 E. Samaridou , J. Heyes , and P. Lutwyche , “ Lipid Nanoparticles for Nucleic Acid Delivery: Current Perspectives , ” Advanced Drug Delivery Reviews 154–155 ( 2020 ): 37 – 63 . 10.1016/j.addr.2020.06.002 32526452
172 M. F. Bachmann and G. T. Jennings , “ Vaccine Delivery: A Matter of Size, Geometry, Kinetics and Molecular Patterns , ” Nature Reviews Immunology 10 ( 2010 ): 787 – 796 . 10.1038/nri2868 20948547
173 N. Pardi , S. Tuyishime , H. Muramatsu , et al., “ Expression Kinetics of Nucleoside‐modified mRNA Delivered in Lipid Nanoparticles to Mice by Various Routes , ” Journal of Controlled Release 217 ( 2015 ): 345 – 351 . 26264835 10.1016/j.jconrel.2015.08.007 PMC4624045
174 C. Roth , T. Cantaert , C. Colas , et al., “ A Modified mRNA Vaccine Targeting Immunodominant NS Epitopes Protects Against Dengue Virus Infection in HLA Class I Transgenic Mice , ” Frontiers in Immunology 10 ( 2019 ): 1 – 14 . 31293584 10.3389/fimmu.2019.01424 PMC6598640
175 K. Bahl , J. J. Senn , O. Yuzhakov , et al., “ Preclinical and Clinical Demonstration of Immunogenicity by mRNA Vaccines Against H10N8 and H7N9 Influenza Viruses , ” Molecular Therapy 25 ( 2017 ): 1316 – 1327 . 28457665 10.1016/j.ymthe.2017.03.035 PMC5475249
176 B. W. Jagger , K. A. Dowd , R. E. Chen , et al., “ Protective Efficacy of Nucleic Acid Vaccines against Transmission of Zika Virus during Pregnancy in Mice Brett , ” Nature Biotechnology 3 ( 2014 ): 1 – 16 . 10.1093/infdis/jiz338 PMC6782106 31260518
177 S. John , O. Yuzhakov , A. Woods , et al., “ Multi‐antigenic human cytomegalovirus mRNA Vaccines That Elicit Potent Humoral and Cell‐Mediated Immunity , ” Vaccine 36 ( 2018 ): 1689 – 1699 . 29456015 10.1016/j.vaccine.2018.01.029
178 J. Lutz , S. Lazzaro , M. Habbeddine , et al., “ Unmodified mRNA in LNPs Constitutes a Competitive Technology for Prophylactic Vaccines , ” Npj Vaccines 2 ( 2017 ): 1 – 9 . 29263884 10.1038/s41541-017-0032-6 PMC5648897
179 N. Pardi , M. J. Hogan , M. S. Naradikian , et al., “ Nucleoside‐modified mRNA Vaccines Induce Potent T Follicular Helper and Germinal Center B Cell Responses , ” Journal of Experimental Medicine 215 ( 2018 ): 1571 – 1588 . 29739835 10.1084/jem.20171450 PMC5987916
180 N. Pardi , K. Parkhouse , E. Kirkpatrick , et al., “ Nucleosidemodified mRNA Immunization Elicits Influenza Virus Hemagglutinin Stalk‐specific Antibodies , ” Nature Communications 9 ( 2018 ): 1 – 12 . 10.1038/s41467-018-05482-0 PMC6105651 30135514
181 J. M. Richner , S. Himansu , K. A. Dowd , et al., “ Modified mRNA Vaccines Protect Against Zika Virus Infection , ” Cell 169 ( 2017 ): 176 . 10.1016/j.cell.2017.03.016 28340344
182 S. L. Hewitt , A. Bai , D. Bailey , et al., “ Durable Anticancer Immunity From Intratumoral Administration of IL‐23, IL‐36γ, and OX40L mRNAs , ” Science Translational Medicine 11 ( 2019 ). 10.1126/scitranslmed.aat9143 30700577
183 J. Buck , P. Grossen , P. R. Cullis , J. Huwyler , and D. Witzigmann , “ Lipid‐based DNA Therapeutics: Hallmarks of Non‐viral Gene Delivery , ” ACS Nano 13 ( 2019 ): 3754 – 3782 . 30908008 10.1021/acsnano.8b07858
184 Y. Zong , Y. Lin , T. Wei , and Q. Cheng , “ Lipid Nanoparticle (LNP) Enables mRNA Delivery for Cancer Therapy , ” Advanced Materials 35 ( 2023 ): e2303261 . 0–2. 37196221 10.1002/adma.202303261
185 J. Kim , Y. Eygeris , M. Gupta , and G. Sahay , “ Self‐assembled mRNA Vaccines , ” Advanced Drug Delivery Reviews 170 ( 2021 ): 83 – 112 . 33400957 10.1016/j.addr.2020.12.014 PMC7837307
186 S. Qin , X. Tang , Y. Chen , et al., “ mRNA‐based Therapeutics: Powerful and Versatile Tools to Combat Diseases , ” Signal Transduction and Targeted Therapy 7 ( 2022 ). 10.1038/s41392-022-01007-w PMC9123296 35597779
187 N. Al Fayez , M. S. Nassar , A. A. Alshehri , et al., “ Recent Advancement in mRNA Vaccine Development and Applications , ” Pharmaceutics 15 ( 2023 ): 1 – 24 . 10.3390/pharmaceutics15071972 PMC10384963 37514158
188 C. Malburet , L. Leclercq , J. Cotte , et al., “ Taylor Dispersion Analysis to Support Lipid‐nanoparticle Formulations for mRNA Vaccines , ” Gene Therapy 30 ( 2023 ): 421 – 428 . 36316446 10.1038/s41434-022-00370-1 PMC9628342
189 E. Kon , U. Elia , and D. Peer Principles for designing an optimal mRNA lipid nanoparticle vaccine . ( 2020 ). 10.1016/j.copbio.2021.09.016 PMC8547895 34715546
190 H. Kang , S. Rho , W. R. Stiles , et al., “ Size‐Dependent EPR Effect of Polymeric Nanoparticles on Tumor Targeting , ” Advanced Healthcare Materials 9 ( 2020 ): 8 – 15 . 10.1002/adhm.201901223 PMC7224408 31794153
191 R. Simón‐Vázquez , M. Peleteiro , and Á. González‐Fernández , “ Polymeric Nanostructure Vaccines: Applications and Challenges , ” Expert Opinion on Drug Delivery 17 ( 2020 ): 1007 – 1023 . 32476491 10.1080/17425247.2020.1776259
192 A. Das and N. Ali , “ Nanovaccine: An Emerging Strategy , ” Expert Review of Vaccines 20 ( 2021 ): 1273 – 1290 . 34550859 10.1080/14760584.2021.1984890
193 P. Midoux and C. Pichon , “ Lipid‐based mRNA Vaccine Delivery Systems , ” Expert Review of Vaccines 14 ( 2014 ): 221 – 234 . 25540984 10.1586/14760584.2015.986104
194 J. A. Poliskey , S. T. Crowley , R. Ramanathan , C. W. White , B. Mathew , and K. G. Rice , “ Metabolically Stabilized Double‐stranded mRNA Polyplexes , ” Gene Therapy 25 ( 2018 ): 473 – 484 . 30154525 10.1038/s41434-018-0038-3 PMC6404535
195 L. Tan , T. Zheng , M. Li , et al., “ Optimization of an mRNA Vaccine Assisted With Cyclodextrin‐polyethyleneimine Conjugates , ” Drug Delivery and Translational Research 10 ( 2020 ): 678 – 689 . 32048201 10.1007/s13346-020-00725-4
196 J. C. Kaczmarek , K. J. Kauffman , O. S. Fenton , et al., “ Optimization of a Degradable Polymer‐Lipid Nanoparticle for Potent Systemic Delivery of mRNA to the Lung Endothelium and Immune Cells , ” Nano Letters 18 ( 2018 ): 6449 – 6454 . 30211557 10.1021/acs.nanolett.8b02917 PMC6415675
197 K. Zhou , L. H. Nguyen , J. B. Miller , et al., “ Modular Degradable Dendrimers Enable Small RNAs to Extend Survival in an Aggressive Liver Cancer Model , ” Proceedings of the National Academy of Sciences of the United States of America 113 ( 2016 ): 520 – 525 . 26729861 10.1073/pnas.1520756113 PMC4725465
198 R. Chintakunta , N. Buaron , N. Kahn , et al., “ Synthesis, Characterization, and Self‐assembly With Plasmid DNA of a Quaternary Ammonium Derivative of Pectic Galactan and Its Fluorescent Labeling for Bioimaging Applications , ” Carbohydrate Polymers 150 ( 2016 ): 308 – 318 . 27312642 10.1016/j.carbpol.2016.05.015
199 D. Wu , L. Zhu , Y. Li , et al., “ Chitosan‐based Colloidal Polyelectrolyte Complexes for Drug Delivery: A Review , ” Carbohydrate Polymers 238 ( 2020 ). 10.1016/j.carbpol.2020.116126 32299572
200 N. Butkovich , E. Li , A. Ramirez , A. M. Burkhardt , and S. W. Wang , “ Advancements in Protein Nanoparticle Vaccine Platforms to Combat Infectious Disease , ” Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology 13 ( 2021 ): 1 – 29 . 10.1002/wnan.1681 PMC8052270 33164326
201 J. I. Solomun , G. Cinar , P. Mapfumo , et al., “ Solely Aqueous Formulation of Hydrophobic Cationic Polymers for Efficient Gene Delivery , ” International Journal of Pharmaceutics 593 ( 2021 ): 120080 . 33246046 10.1016/j.ijpharm.2020.120080
202 M. Zhao , M. Li , Z. Zhang , T. Gong , and X. Sun , “ Induction of HIV‐1 Gag Specific Immune Responses by Cationic Micelles Mediated Delivery of Gag mRNA , ” Drug Delivery 23 ( 2016 ): 2596 – 2607 . 26024387 10.3109/10717544.2015.1038856
203 M. Li , M. Zhao , Y. Fu , et al., “ Enhanced Intranasal Delivery of mRNA Vaccine by Overcoming the Nasal Epithelial Barrier via Intra‐ A nd Paracellular Pathways , ” Journal of Controlled Release 228 ( 2016 ): 9 – 19 . 26941035 10.1016/j.jconrel.2016.02.043
204 H. Y. Choi , T. Lee , G. Yang , et al., “ Efficient mRNA Delivery With Graphene Oxide‐polyethylenimine for Generation of Footprint‐free human Induced Pluripotent Stem Cells , ” Journal of Controlled Release 235 ( 2016 ): 222 – 235 . 27266364 10.1016/j.jconrel.2016.06.007
205 J. Karlsson , H. J. Vaughan , and J. J. Green , “ Biodegradable Polymeric Nanoparticles for Therapeutic Cancer Treatments , ” Annual Review of Chemical and Biomolecular Engineering 9 ( 2018 ): 105 – 127 . 10.1146/annurev-chembioeng-060817-084055 PMC6215694 29579402