Mathews Journal of Immunology & Allergy

2575-9523

Current Issue Volume 7, Issue 2 - 2023

Importance of Cancer Vaccines: Progress and Future Developments

Nemat Khansari*

Tehran University of Medical Sciences, School of Medicine, Department of Immunology, Tehran Iran

*Corresponding Author: Nemat Khansari, Tehran University of Medical Sciences, School of Medicine, Department of Immunology, Tehran Iran; Email: [email protected]

Received Date: October 09, 2023

Publication Date: October 25, 2023

Citation: Khansari N. (2023). Importance of Cancer Vaccines: Progress and Future Developments. Mathews J Immunol Allergy. 7(2):21.

Copyright: Khansari N. © (2023)

ABSTRACT

Cancer vaccines have the potential to revolutionize cancer treatment, offering an effective and long-lasting solution to many types of cancer. In recent years, significant progress has been made in the development of cancer vaccines, with a number of promising clinical trials showing positive results. As research progresses, it is hoped that these vaccines will play a pivotal role in transforming cancer from a deadly disease to a manageable condition. However, continued research and development are needed to further improve the efficacy and safety of cancer vaccines, and to develop new vaccines for other types of cancer. With the right investments and support, cancer vaccines could become an important part of cancer treatment in the near future. This review highlights some of the strategies for the future development of more efficient specific and/or personalized vaccines.

Keywords: Cancer, Vaccine, Neoantigen, Personalized medicine, Immunotherapy

INTRODUCTION

Cancer, one of the leading causes of health worldwide, has seen significant advances in its treatment modalities over the past few decades. Among these advancements, the cancer vaccine has emerged as a promising therapeutic approach. Cancer vaccines offer a promising avenue for treating cancer because they harness the power of the immune system to target and destroy cancer cells. Unlike traditional cancer treatments, such as chemotherapy or radiation therapy, which can harm healthy cells along with cancerous ones, cancer vaccines are designed to specifically target tumor cells. Moreover, cancer vaccines have shown great potential in preventing cancer from recurring after initial treatment. By training the immune system to recognize and attack cancer cells, these vaccines can help prevent new tumors from forming. Another advantage of cancer vaccines is their potential for use in combination with other treatments like chemotherapy or radiation therapy. As we look to the future, working in several key directions could shape the landscape of cancer vaccine development:

Enhancing Immune Response to Tumor Antigens: While the identification of suitable tumor antigens is crucial in developing an effective cancer vaccine, researchers should also explore innovative approaches to enhance the immune response to these antigens. One approach gaining traction is the use of new adjuvants, which are substances that can stimulate and enhance the immune response [1]. Adjuvants can be added to cancer vaccines to boost the activation of immune cells and improve their ability to recognize and target cancer cells. Another promising approach is the use of combination therapies that pair cancer vaccines with other immunotherapies [2]. For example, combining a vaccine with a PD-1 (program cell death protein-1) inhibitor can enhance the immune response and improve treatment outcomes [3]. One attempt to explore the enhancement of immune response against cancer is to explore novel delivery methods for tumor antigens, like nanoparticles or exosomes [4]. These delivery systems can help protect the antigens from degradation and improve their uptake by immune cells, leading to a stronger and more targeted immune response [5].

Developing Cancer Vaccines Effective Against Multiple Tumor Types: Developing cancer vaccines that can target multiple tumor types presents a significant challenge for researchers. However, there are several strategies that may hold promise in overcoming this hurdle. One approach involves targeting shared antigens that are present across multiple tumor types. For example, neoantigens, are unique proteins produced by tumor cells due to genetic mutations [6]. While neoantigens are specific to individual tumors, they may be present in multiple tumor types and could potentially form the basis for a vaccine that targets several different cancers. Another strategy involves targeting antigens expressed at high levels in multiple tumor types.  Protein human epidermal growth factor receptor 2 (HER2), which is over-expressed in several types of cancer, including breast and ovarian cancer, is a good example of these kinds of antigens.

Some researchers have explored the potential for viral vectors to deliver multiple antigens simultaneously. By engineering viruses to express multiple tumor antigens, these vectors can potentially elicit an immune response against several different tumors simultaneously [7,8]. Others have focused on developing vaccines that target immunosuppressive cells or molecules within the tumor microenvironment. By inhibiting these immune-suppressing factors and promoting an anti-tumor immune response, these vaccines may be effective against multiple tumor types with varying molecular profiles [9].

The Use of Nanotechnology in Developing More Targeted and Efficient Cancer Vaccines: Nanotechnology represents a promising approach to developing more targeted and efficient cancer vaccines. By engineering nanoparticles to carry tumor-specific antigens, researchers can potentially enhance the immune response against cancer cells while minimizing off-target effects. It has been shown that nanoparticles can selectively bind to and enter cancer cells, delivering antigens directly to the immune system within the tumor microenvironment [10]. Thus, one advantage of using nanoparticles for cancer vaccine delivery is their ability to target specific cells or tissues. Moreover, nanoparticles can be engineered to release antigens over time, potentially providing sustained stimulation of the immune system. This sustained release may help overcome the challenge of immune tolerance seen in some types of cancer, where the immune system fails to recognize tumor cells as foreign. Nanotechnology also offers potential advantages in terms of vaccine formulation and stability, by encapsulating antigen within nanoparticles to protect it from degradation or denaturation during storage or transport.

The Potential of Using Gene Editing Technologies to Enhance the Efficacy of Cancer Vaccines: Gene editing technologies such as CRISPR-Cas9 offer promising possibilities for enhancing the efficacy of cancer vaccines [11]. By using these tools to modify immune cells, researchers can potentially improve their ability to recognize and eliminate tumor cells. One approach involves gene editing to knock out genes that encode immune checkpoint proteins, such as PD-1 or CTLA-4. These proteins play a critical role in regulating the immune response, and their inhibition has been shown to enhance anti-tumor immunity in some cases [12]. Moreover, gene editing can be used to introduce chimeric antigen receptors (CARs) into T cells [13]. These receptors are engineered to recognize specific tumor antigens and can help T cells more effectively target and kill cancer cells. Recently, Osorio-Rodrigues group [14] applied a second generation of CAR-T cells. They engineered an autologous T cell expressing a ROR1-specific chimeric antigen receptor (ROR1 CAR-T cells), which is a personalized therapeutic option for patients with recurrence tumors. In addition, gene editing offers potential advantages in terms of vaccine development and manufacturing by introducing genetic modifications into vaccine-producing cell lines. This technology also potentializes the use of "universal" cancer vaccines that can be effective against multiple tumor types. While there is still much research needed in this area, the use of gene editing technologies to enhance the efficacy of cancer vaccines offers exciting possibilities for improving treatment outcomes for patients with cancer Exploring the Role of Epigenetic Modifications in Modulating Immune Response to Cancer Vaccines. Epigenetic modifications, which refer to changes in gene expression that do not involve alterations to the underlying DNA sequence, but have been shown to play a critical role in regulating immune function [15]. This finding suggests that these epigenetic modifications may also influence the efficacy of cancer vaccines by modulating immune responses. Studies have shown that certain epigenetic changes can impact the expression of genes involved in immune cell activation and differentiation [16]. In addition, changes in epigenetic marks, such as DNA methylation or histone modification, have been associated with altered vaccine response rates. Researchers have explored the potential for epigenetic modifiers to enhance vaccine efficacy. Preclinical studies have suggested that inhibitors of histone deacetylases (HDACs), which are enzymes that regulate chromatin structure and gene expression, can improve anti-tumor immunity and increase response rates to cancer vaccines [17].

Developing Strategies for Targeting Cancer Stem Cells with Vaccines: Cancer stem cells (CSCs) represent a unique challenge in the development of effective cancer vaccines. Some of these cells are thought to be responsible for tumor initiation and progression, and they possess several features that make them resistant to traditional cancer therapies. However, recent research has suggested that CSCs may also be an important target for cancer vaccines [18]. By developing strategies that specifically target these cells, researchers may be able to elicit an immune response that is more effective at eliminating tumors. One approach involves targeting antigens specifically expressed on CSCs, like the CD133, a marker protein that is over-expressed on CSCs in several types of cancer. Researchers may explore the potential of using dendritic cell-based vaccines to target CSCs. By using dendritic cells to present tumor-specific antigens to T cells, these vaccines can potentially overcome the immune-suppressive effects of CSCs and stimulate an anti-tumor immune response. It should be noted that preclinical studies have suggested that targeting the Notch signaling pathway or inhibiting the expression of certain microRNAs can reduce CSC populations and enhance vaccine efficacy [19]. Targeting CSCs represents an exciting area of cancer research.  Even though, early results from preclinical studies and clinical trials suggest targeting CSCs may offer a new way to improve outcomes for patients with cancer. More work needs to be done to fully understand the biology of these cells and develop effective therapies and/or vaccines.

Developing Universal Vaccines: This is an active area of research that aims to create vaccines that can provide long-lasting protection against multiple strains or types of infectious agents. This approach differs from traditional vaccines, which are designed to protect against a specific strain or type of infectious agent. Currently, there is no universal vaccine for cancer therapy approved for clinical use. However, there are several ongoing clinical trials for universal cancer vaccines that target shared antigens or mutations found in many types of cancer cells. One example is a vaccine called GV1001, which targets a protein called telomerase found in many types of cancer cells. Telomerase is an enzyme that helps cancer cells maintain their ability to divide and grow uncontrollably [20]. The GV1001 vaccine stimulates the immune system to recognize and attack cells that express telomerase. Another example is a vaccine called MUC1, which targets a protein called mucin-1 that is over-expressed in many types of cancer cells. The MUC1 vaccine stimulates the immune system to recognize and attack cells that express mucin-1 [21]. While these vaccines are still in development and have not yet been approved for clinical use, early results from clinical trials have been promising.  A phase II clinical trial of the GV1001 vaccine in patients with pancreatic cancer showed a significant improvement in survival compared to patients who received standard chemotherapy alone.

Developing personalized vaccines: The process of developing a personalized vaccine typically involves analyzing the patient's tumor tissue to identify unique antigens (proteins) that are present on the surface of the cancer cells and preferentially not present on normal cells. Once these antigens are identified, researchers can use them to develop a vaccine that stimulates the patient's immune system to recognize and attack the cancer cells.

One advantage of personalized vaccines is that they can potentially be more effective than traditional chemotherapy or radiation therapy, which would have significant side effects and may not be effective against all types of cancer. Personalized vaccines, on the other hand, are specifically tailored to the patient's individual cancer, so they may be better at targeting and destroying cancer cells while leaving healthy cells unharmed. There have been promising results from early clinical trials of personalized cancer vaccines. For example, a study published in Nature in 2017 found that a personalized vaccine stimulated an immune response in patients with advanced melanoma, leading to tumor shrinkage and improved survival rates [22]. However, developing personalized vaccines is still a relatively new and complex process, and there are many challenges that need to be overcome. For example, it can be difficult to identify unique antigens that are present only in cancer cells, not in healthy cells. Additionally, there are logistical challenges in producing customized vaccines for each individual patient.

Despite these challenges, personalized vaccines represent an exciting avenue for future cancer research. As technology continues to advance and we learn more about the genetics and biology of different types of cancer, it may become possible to develop even more effective personalized vaccines that can help improve outcomes for cancer patients.

Personalized Cancer Vaccines Based on a Patient's Microbiome Composition: The human microbiome, which consists of trillions of microorganisms living within and on our bodies, plays a crucial role in regulating immune function. Recent research has also suggested that the microbiome may influence the efficacy of cancer vaccines by modulating immune responses. Other studies have explored the potential for using probiotics or other interventions to modulate the microbiome and enhance vaccine efficacy. Preclinical studies have suggested that supplementing with certain strains of bacteria can improve anti-tumor immunity and increase response rates to cancer vaccines [23].

While there is still much research needed in this area, understanding the role of the microbiome in modulating immune response to cancer vaccines offers exciting possibilities for developing more personalized and effective treatments. As researchers continue to explore this field further, we may see even more innovative approaches emerge that take advantage of these interactions between our bodies and their resident microorganisms. It may be possible that certain bacterial species or strains may promote anti-tumor immunity by stimulating specific immune cells or producing metabolites that enhance immune function. Studies have shown that certain types of bacteria within the gut microbiome can stimulate T cells, which are critical for effective anti-tumor immunity [24]. In addition, these bacteria can help activate dendritic cells, which are responsible for presenting tumor antigens to T cells and initiating an immune response against cancer cells. In addition, research has suggested that changes in the composition or diversity of the gut microbiome may impact vaccine response rates. It has also been shown that individuals with lower levels of certain types of enteric bacteria have reduced responses to some types of vaccines [25].

Exploring the Potential of Using Plant-Based Expression Systems for Producing Cancer Vaccines: While traditional methods of production of cancer vaccines involve using mammalian cells, some researchers are exploring the potential of using plant-based expression systems as an alternative. Plant-based systems offer several advantages over traditional methods, including lower cost and increased scalability. Plant-based expression systems can be easily scaled up to meet demand, making them an attractive option for producing cancer vaccines on a large scale. One approach involves using genetically modified plants to produce antigens that can be used in cancer vaccines. By introducing a gene encoding a tumor antigen into a plant's genome, researchers can use the plant's cellular machinery to produce large quantities of the antigen. This approach has been successfully used in producing antigens for other types of vaccines, such as those for hepatitis B [26,27]. Plant-based expression systems offer potential safety advantages over traditional methods. The risk of contamination with animal pathogens is eliminated when using plants to produce vaccines, reducing the risk of adverse events associated with these contaminants. In addition, plant-based expression systems may also offer benefits in terms of vaccine stability and storage. Some researchers are exploring the use of freeze-drying or other techniques to stabilize plant-produced antigens for long-term storage and transport [28]. In short, while there is still much research needed in this area, the potential for using plant-based expression systems to produce cancer vaccines offers exciting possibilities for improving vaccine accessibility and affordability.

The Use of Artificial Intelligence and Machine Learning to Identify Suitable Tumor Antigens for Personalized Cancer Vaccines: The identification of suitable tumor antigens is a critical step in the development of personalized cancer vaccines. However, this process can be time-consuming and labor-intensive, requiring extensive genomic sequencing and bioinformatic analysis. To address these challenges, researchers should explore the use of artificial intelligence (AI) and machine learning (ML) algorithms to streamline the identification of tumor antigens. These algorithms can analyze large datasets of genomic information and identify patterns or mutations that may be relevant for targeting cancer cells. Moreover, AI/ML algorithms can help predict which tumor antigens are most likely to elicit an immune response in individual patients. By analyzing data from multiple sources, such as electronic health records, imaging data, and gene expression profiles, these algorithms can develop personalized treatment plans tailored to an individual's unique tumor profile. In addition, AI/ML algorithms can help identify potential side effects or adverse events associated with personalized cancer vaccines. By analyzing data from clinical trials or post-market surveillance, these algorithms can help predict which patients may be at increased risk for adverse events and inform treatment decisions accordingly. It is clear that the use of AI/ML in identifying suitable tumor antigens for personalized cancer vaccines offers exciting possibilities for improving treatment outcomes and streamlining the drug development process. As research continues in this area, we may see even more personalized and effective treatment options available for patients around the world.

The Role of Big Data and Analytics in Improving Clinical Trial Design and Patient Outcomes: Big data and analytics are increasingly being used to improve clinical trial design and patient outcomes. By analyzing large datasets of patient information, researchers can identify patterns or trends that may inform the development of more effective treatments. One way big data is being used in clinical trials is through electronic health records (EHRs) to collect patient data. EHRs can provide a wealth of information about patient demographics, medical history, and treatment outcomes, which can be used to inform trial design and recruitment strategies. It should be noted that big data analytics can help identify potential participants for clinical trials by analyzing large datasets of patient information. By identifying patients with specific characteristics or medical histories, researchers can target recruitment efforts more effectively and increase the likelihood of trial success. Moreover, big data analytics can be used to monitor patient safety during clinical trials. By analyzing real-time data from multiple sources, such as wearable devices or remote monitoring systems, researchers can quickly identify potential adverse events and take appropriate action. Big data analytics can also help improve treatment outcomes by identifying factors that may influence therapy. For example, researchers can analyze genetic or biomarker data from patients enrolled in a clinical trial. Researchers may identify subgroups of patients who are more likely to respond to a particular treatment.

CONCLUSION

Recent advancements in genomic sequencing and bioinformatics have greatly facilitated the identification of neoantigens. Additionally, high-throughput sequencing technologies allow for rapid and comprehensive analysis of tumor DNA, helping researchers pinpoint potential target antigens for the development of specific and efficient vaccines. By continuing to refine our understanding of tumor antigen selection and optimizing vaccine production processes, researchers aim to overcome these challenges and bring personalized cancer vaccines closer to becoming a viable treatment option for patients. It should be noted that the future of developing a cancer vaccine with sufficient efficiency and specificity is bright, with numerous innovative approaches on the horizon. As research progresses, it is hoped that these vaccines will play a pivotal role in transforming cancer from a deadly disease to a manageable condition.

REFERENCES

  1. Teshome M, Hunt KK. (2014). Neoadjuvant therapy in the treatment of breast cancer. Surg Oncol Clin America. 23: 505-523.
  2. Kalos M, Levine B, Porter D, Katz S, Grupp S, Bagg A, et al. (2011). T cells with chimeric antigen receptors with potent antitumor effects can establish memory in patients with advanced leukemia. Sice Tranl Med. 3: 95-105.
  3. Pardoll DM. (2012). The blockade of immune checkpoint in cancer immunotherapy. Nature Rev Cancer. 12:252-264.
  4. Walkley CD, Olsen JB, Guo H, Emili A, Chan WCW. (2012). Nanoparticle size and surface chemistry determine serum protein absorption and macrophage uptake. J Am Chem Soc. 134:2139-2147.
  5. Chan WCW. (2023). Principles of nanoparticles delivery to solid tumors. BME Frontier. 4:16-26.
  6. Schumacher TN, Schreiber RD. (2015). Neoantigens in cancer immunotherapy in cancer. Science. 348:6974.
  7. Kantoff PW, Higano CS, Shore ND, Berger ER, Small EJ, Penson DF, et al. (2010). Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N Engl J Med. 365:411-422.
  8. Le Tournea C, Delord JP, Cassier P, Loirat D, Tavernaro A, Bastien  B, et al. (2019). Phase Ib/II trial of TG4001 (Tipapkinogene sovacivec), a therapeutic HPV-vaccine, and Avelumab in patients with recurrent/metastatic (R/M) HPV-16 cancers. Ann Oncol. 30:121-127.
  9. Bulliard Y, Jolicoeur R, Windman M, Rue SM, et al. (2013). Activating Fcγ receptors contributing to the antitumor activities of immunoregulatory receptor targeting antibodies. J Exp Med. 210:1685-1693.
  10. Wang X, Li J, Wang Y, Cho KJ, Kim G, Gjyrezi A, et al. (2009). A target nanoparticle enhances specific delivery of paclitaxel to folate receptor positive tumor. ACS Nano. 3:3165-3174.
  11. Mout R, Ray M, Yesilbag TG, Lee YW, Sasak K, Rotello VM. (2017). Direct cytosolic delivery of CRISPR/Cas9-ribonucleoprotein for efficient gene editing. ACS Nano. 11:2452-2458.
  12. Pricerman S, Forman S, Brown C. (2015). Amart CARs for cancer immunotherapy. Cur Opin Oncol. 27:466-474.
  13. Kostyi P, Maker J, Arnold J. (2018). Perspective on chimeric antigen receptor T- cell immunotherapy for solid tumors. Frontier Immunol. 9: 1104-1110.
  14. Osorio-Rodriguez DA, Camacho BA, Ramirez-Segura C. (2023). Anti-ROR1 CAR-T cells: Architecture and performance. Frontier Med. 10:3389-3399.
  15. Lu LF, Rudensky AY. (2012). Regulatory T-cells: Mechanisms of differentiation and function. Ann Rev Immunol. 30:531-564.
  16. Russ BE, Olshanksy M, Smallwood HS, Li J, Denton AE, Prier JE, et al. (2014). Distinct epigenetic signatures delineate transcriptional programs during virus specific CD8+ T cell differentiation. Immunity. 41: 853-865.
  17. Bannister AJ, Kouzarides T. (2011). Regulation of chromatin by histone modifications. Cell Res. 21:381-395.
  18. Lytle NK, Barber AG, Reya T. (2018). Stem cell fate in cancer growth, progression and therapy resistance. Nature Rev Cancer. 18:669-680.
  19. Takebe N, Harris SP, Warren RQ, Ivy SP. (2011). Targeting cancer stem cells by inhibiting Wnt, Notch, and Hedghog pathways. Nature Rev Clin Oncol. 8:97-106.
  20. Brunsvig PF, Kyte JA, Kersten C, Sundstrøm S, Møller M, Nyakas M, et al. (2011). Telomerase pe[ptide vaccination in NSCLC: A phase II trial in stage III patients vaccinated after chemotherapy, and 8 years update on a phase I/II trial. Clinical Cancer Res. 17: 6847-6857.
  21. Ramanathan RK, Lee KM, McKolanis J, Hitbold E, Schraut W, Moser AJ, et al. (2005). Phase I study of MUC1 vaccine composed different doses of MUC1 peptide with SB-AS2 adjuvant in resected and locally advanced pancreatic cancer. Cancer Immunol Immunotherapy. 54:254-264.
  22. Ott PA, Hu Z, Keskin DB, Shukla SA, Sun J, Bozym DJ, et al. (2017). Immunological personal neoantigen vaccine for patients with melanoma. Nature. 547:217-221.
  23. Belhaid Y, Hand TW. (2014). Role of the microbiota in immunity and inflammation. Cell. 157: 121-141.
  24. Gopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC, Karpinets TV, et al. (2018). Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 359:97-103.
  25. Lynn DJ, Pulendran B. (2018). The potential of the microbiota to influence vaccine responses. J. Leukocyte Biol. 103:225-231.
  26. Mason HS, Lam DM, Arntzen CJ. (1992). Expression of hepatitis B surface antigen in transgenic plants. Proc Nat Acad Sci. 89:11745-11749.
  27. Kapusta J, Modelska A, Figlerowicz M, Pniewski T, Letellier M, Lisowa O, et al. (1999). A plant-derived edible vaccine against hepatitis B virus. The FASEB J. 13:1796-1799.
  28. Daniell H, Singh ND, Mason H, Streatfield SJ. (2009). Plant made vaccine antigen and pharmaceuticals. Trends Plant Sci. 14:669-679.

 

 


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