Epitope-driven DNA vaccine design employing immunoinformatics against B-cell lymphoma: A biotech's challenge

Personalized cancer vaccine design using AI-powered technologies

Immunotherapy has ushered in a new era of cancer treatment, yet cancer remains a leading cause of global mortality. Among various therapeutic strategies, cancer vaccines have shown promise by activating the immune system to specifically target cancer cells. While current cancer vaccines are primarily prophylactic, advancements in targeting tumor-associated antigens (TAAs) and neoantigens have paved the way for therapeutic vaccines. The integration of artificial intelligence (AI) into cancer vaccine development is revolutionizing the field by enhancing various aspect of design and delivery. This review explores how AI facilitates precise epitope design, optimizes mRNA and DNA vaccine instructions, and enables personalized vaccine strategies by predicting patient responses. By utilizing AI technologies, researchers can navigate complex biological datasets and uncover novel therapeutic targets, thereby improving the precision and efficacy of cancer vaccines. Despite the promise of AI-powered cancer vaccines, significant challenges remain, such as tumor heterogeneity and genetic variability, which can limit the effectiveness of neoantigen prediction. Moreover, ethical and regulatory concerns surrounding data privacy and algorithmic bias must be addressed to ensure responsible AI deployment. The future of cancer vaccine development lies in the seamless integration of AI to create personalized immunotherapies that offer targeted and effective cancer treatments. This review underscores the importance of interdisciplinary collaboration and innovation in overcoming these challenges and advancing cancer vaccine development.

In silico epitope-based vaccine design against influenza a neuraminidase protein: Computational analysis established on B- and T-cell epitope predictions

Objective

Influenza A virus belongs to the most studied virus and its mutant initiates epidemic and pandemics outbreaks. Inoculation is the significant foundation to diminish the risk of infection. To prevent an incidence of influenza from the transmission, various practical approaches require more advancement and progress. More efforts and research must take in front to enhance vaccine efficacy.

Methods

The present research emphasizes the development and expansion of a universal vaccine for the influenza virus. Research focuses on vaccine design with high efficacy. In this study, numerous computational approaches were used, covering a wide range of elements and ideas in bioinformatics methodology. Various B and T-cell epitopic peptides derived from the Neuraminidase protein N1 are recognized by these approaches. With the implementation of numerous obtained databases and bioinformatics tools, the different immune framework methods of the conserved sequences of N1 neuraminidase were analyzed. NCBI databases were employed to retrieve amino acid sequences. The antigenic nature of the neuraminidase sequence was achieved by the VaxiJen server and Kolaskar and Tongaonkar method. After screening of various B and T cell epitopes, one efficient peptide each from B cell epitope and T cell epitopes was assessed for their antigenic determinant vaccine efficacy. Identical two B cell epitopes were recognized from the N1 protein when analyzed using B-cell epitope prediction servers. The detailed examination of amino acid sequences for interpretation of B and T cell epitopes was achieved with the help of the ABCPred and Immune Epitope Database.

Results

Computational immunology via immunoinformatic study exhibited RPNDKTG as having its high conservancy efficiency and demonstrated as a good antigenic, accessible surface hydrophilic B-cell epitope. Among T cell epitope analysis, YVNISNTNF was selected for being a conserved epitope. T cell epitope was also analyzed for its allergenicity and cytotoxicity evaluation. YVNISNTNF epitope was found to be a non-allergen and not toxic for cells as well. This T-cell epitope with maximum world populace coverages was scrutinized for its association with the HLA-DRB1*0401 molecule. Results from docking simulation analyses showed YVNISNTNF having lower binding energy, the radius of gyration (Rg), RMSD values, and RMSE values which make the protein structure more stable and increase its ability to become an epitopic peptide for influenza virus vaccination.

Conclusions

We propose that this epitope analysis may be successfully used as a measurement tool for the robustness of an antigen-antibody reaction between mutant strains in the annual design of the influenza vaccine.

Vaccinomic approach for novel multi epitopes vaccine against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)

BACKGROUND

The spread of a novel coronavirus termed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in China and other countries is of great concern worldwide with no effective vaccine. This study aimed to design a novel vaccine construct against SARS-CoV-2 from the spike S protein and orf1ab polyprotein using immunoinformatics tools. The vaccine was designed from conserved epitopes interacted against B and T lymphocytes by the combination of highly immunogenic epitopes with suitable adjuvant and linkers.

RESULTS

The proposed vaccine composed of 526 amino acids and was shown to be antigenic in Vaxigen server (0.6194) and nonallergenic in Allertop server. The physiochemical properties of the vaccine showed isoelectric point of 10.19. The instability index (II) was 31.25 classifying the vaccine as stable. Aliphatic index was 84.39 and the grand average of hydropathicity (GRAVY) was - 0.049 classifying the vaccine as hydrophilic. Vaccine tertiary structure was predicted, refined and validated to assess the stability of the vaccine via Ramachandran plot and ProSA-web servers. Moreover, solubility of the vaccine construct was greater than the average solubility provided by protein sol and SOLpro servers indicating the solubility of the vaccine construct. Disulfide engineering was performed to reduce the high mobile regions in the vaccine to enhance stability. Docking of the vaccine construct with TLR4 demonstrated efficient binding energy with attractive binding energy of - 338.68 kcal/mol and - 346.89 kcal/mol for TLR4 chain A and chain B respectively. Immune simulation significantly provided high levels of immunoglobulins, T-helper cells, T-cytotoxic cells and INF-γ. Upon cloning, the vaccine protein was reverse transcribed into DNA sequence and cloned into pET28a(+) vector to ensure translational potency and microbial expression.

CONCLUSION

A unique vaccine construct from spike S protein and orf1ab polyprotein against B and T lymphocytes was generated with potential protection against the pandemic. The present study might assist in developing a suitable therapeutics protocol to combat SARSCoV-2 infection.

Immunoinformatics Approach for Multiepitope Vaccine Prediction from H, M, F, and N Proteins of Peste des Petits Ruminants Virus

Background

Small ruminant morbillivirus or peste des petits ruminants virus (PPRV) is an acute and highly contagious viral disease of goats, sheep, and other livestock. This study aimed at predicting an effective multiepitope vaccine against PPRV from the immunogenic proteins haemagglutinin (H), matrix (M), fusion (F), and nucleoprotein (N) using immunoinformatics tools.

Materials and Methods

The sequences of the immunogenic proteins were retrieved from GenBank of the National Center for Biotechnology Information (NCBI). BioEdit software was used to align each protein from the retrieved sequences for conservancy. Immune Epitope Database (IEDB) analysis resources were used to predict B and T cell epitopes. For B cells, the criteria for electing epitopes depend on the epitope linearity, surface accessibility, and antigenicity.

Results

Nine epitopes from the H protein, eight epitopes from the M protein, and ten epitopes from each of the F and N proteins were predicted as linear epitopes. The surface accessibility method proposed seven surface epitopes from each of the H and F proteins in addition to six and four epitopes from the M and N proteins, respectively. For antigenicity, only two epitopes ₁₄₂PPERV₁₄₆ and ₆₃DPLSP₆₇ were predicted as antigenic from H and M, respectively. For T cells, MHC-I binding prediction tools showed multiple epitopes that interacted strongly with BoLA alleles. For instance, the epitope ₄₅MFLSLIGLL₅₃ from the H protein interacted with four BoLA alleles, while ₂₇₆FKKILCYPL₂₈₄ predicted from the M protein interacted with two alleles. Although F and N proteins demonstrated no favorable interaction with B cells, they strongly interacted with T cells. For instance, ₃₅₈STKSCARTL₃₆₆ from the F protein interacted with five alleles, followed by ₃₄₀SQNALYPMS₃₄₈ and ₄₄₂IDLGPAISL₄₅₀ that interacted with three alleles each. The epitopes from the N protein displayed strong interaction with BoLA alleles such as ₄₉₀RSAEALFRL₄₉₈ that interacted with five alleles, followed by two epitopes ₂ATLLKSLAL₁₀ and ₃₀₄QQLGEVAPY₃₁₂ that interacted with four alleles each. In addition to that, four epitopes ₃TLLKSLALF₁₁, ₃₅₆YFDPAYFRL₃₆₄, ₃₆₀AYFRLGQEM₃₆₈, and ₄₁₂PRQAQVSFL₄₂₀ interacted with three alleles each.

Conclusion

Fourteen epitopes were predicted as promising vaccine candidates against PPRV from four immunogenic proteins. These epitopes should be validated experimentally through in vitro and in vivo studies.

Heterogeneity and coexistence of oncogenic mechanisms involved in HCV-associated B-cell lymphomas

The association of HCV-infection with B-lymphomas is supported by the regression of most indolent/low-grade lymphomas following anti-viral therapy. Studies on direct and indirect oncogenic mechanisms have elucidated the pathogenesis of HCV-associated B-lymphoma subtypes. These include B-lymphocyte proliferation and sustained clonal expansion by HCV-envelope protein stimulation of B-cell receptors, and prolonged HCV-infected B-cell growth by overexpression of an anti-apoptotic BCL-2 oncogene caused by the increased frequency of t(14;18) chromosomal translocations in follicular lymphomas. HCV has been implicated in lymphomagenesis by a "hit-and-run" mechanism, inducing enhanced mutation rate in immunoglobulins and anti-oncogenes favoring immune escape, due to permanent genetic damage by double-strand DNA-breaks. More direct oncogenic mechanisms have been identified in cytokines and chemokines in relation to NS3 and Core expression, particularly in diffuse large B-cell lymphoma. By reviewing genetic alterations and disrupted signaling pathways, we intend to highlight how mutually non-contrasting mechanisms cooperate with environmental factors toward progression of HCV-lymphoma.

Analysis of Apical Membrane Antigen (AMA)-1 characteristics using bioinformatics tools in order to vaccine design against Plasmodium vivax

Plasmodium vivax, an intracellular protozoan, causes malaria which is characterized by fever, anemia, respiratory distress, liver and spleen enlargement. In spite of attempts to design an efficient vaccine, there is not a vaccine against P. vivax. Notable advances have recently achieved in the development of malaria vaccines targeting the surface antigens such as Apical Membrane Antigens (AMA)-1. AMA-1 is a micronemal protein synthesized during the erythrocyte-stage of Plasmodium species and plays a significant role in the invasion process of the parasite into host cells. P. vivax AMA-1 (PvAMA-1) can induce strong cellular and humoral responses, indicating that it can be an ideal candidate of vaccine against malaria. Identification and prediction of proteins characteristics increase our knowledge about them and leads to develop vaccine and diagnostic studies. In the present study several valid bioinformatics tools were applied to analyze the various characteristics of AMA-1 such as physical and chemical properties, secondary and tertiary structures, B- cell and T-cell prediction and other important features in order to introduce potential epitopes for designing a high-efficient vaccine. The results demonstrated that this protein had 57 potential PTM sites and only one transmembrane domain on its sequence. Also, multiple hydrophilic regions and classical high hydrophilic domains were predicted. Secondary structure prediction revealed that the proportions of random coil, alpha-helix and extended strand in the AMA-1 sequence were 53.74%, 27.22%, and 19.4%, respectively. Moreover, 5 disulfide bonds were predicted at positions 14-21aa, 162-192aa, 208-220aa, 247-265aa and 354-363aa. The data obtained from B-cell and T-cell epitopes prediction showed that there were several potential epitopes on AMA-1 that can be proper targets for diagnostic and vaccine studies. The current study presented interesting basic and theoretical information regarding PvAMA-1, being important for further studies in order to design a high-efficiency vaccine against malaria.

Predicting Promiscuous T Cell Epitopes for Designing a Vaccine Against Streptococcus pyogenes

One of the most dangerous human pathogens with high prevalence worldwide is Streptococcus pyogenes, which has major impacts on global morbidity and mortality. A major challenge for S. pyogenes vaccine development is the detection of epitopes that confer protection from infection by multiple S. pyogenes types. Our aim was to identify the most conserved and immunogenic antigens of S. pyogenes, which can be a potential candidate for vaccine design in the future. Eight important surface proteins were analyzed. Using different prediction servers, strongest epitopes were selected. They had the ability to stimulate the humoral and cell-mediated immune system. Molecular docking was performed for measuring free-binding energy of selected epitopes. Seven epitopes from three surface proteins were selected as potential candidates for vaccine development. Conservation of selected epitopes among different Streptococcus types was checked. Further in vitro and in vivo tests are required to validate the suitability of the epitopes for vaccine design.

Epitope design of L1 protein for vaccine production against Human Papilloma Virus types 16 and 18

Cervical cancer accounts for about two-thirds of all cancer cases linked etiologically to Human Papilloma Virus (HPV). 15 oncogenic HPV types can cause cervical cancer, of which HPV16 and HPV18 combinedly account for about 70% of it. So, effective epitope design for the clinically relevant HPV types 16 and 18 would be of major medical benefit. Here, a comprehensive analysis is carried out to predict the epitopes against HPV types 16 and 18 through "reverse vaccinology" approach. We attempted to identify the evolutionarily conserved regions of major capsid protein (L1) as well as minor capsid protein (L2) of HPV and designed epitopes within these regions. In this study, we analyzed about 49 and 27 sequences of HPV L2 and L1 proteins respectively. Since we found that the intertype variability of L2 is higher than for L1 proteins, our analysis was emphasized on epitopes of L1 of HPV types 16 and 18. We had selected HLA-A*0201, DRB1*1501, DQB1*0602, DRB1*0401 and DQB1*0301 alleles for the prediction of T cell epitopes of L1 of HPV 16 and 18. Finally, we reported that predicted epitope sequences EEYDLQFIFQLCKITLTA, and RHGEEYDLQFIFQLCKITLTA of L1 protein of HPV 16, and LPDPNKF, PETQRLVWAC, PVPGQYDA, YNPETQRLVWAC, DTGYGAMD, PVPGQYDATK, KQDIPKVSAYQYRVFRV, RDNVSVDYKQTQLCI and YSRHVEEYDLQFIF of L1 protein of HPV 18 could be therapeutic tools for vaccine design against HPV.

Epitope mapping and identification of amino acids critical for mouse IgG-binding to linear epitopes on Gly m Bd 28K

Gly m Bd 28K is one of the major allergens in soybeans, but there is limited information on its IgG-binding epitopes. Thirty-four overlapping peptides that covered the entire sequence of Gly m Bd 28K were synthesized, and 3 monoclonal antibodies against Gly m Bd 28K were utilized to identify the IgG-binding regions of Gly m Bd 28K. Three dominant peptides corresponding to (28)GDKKSPKSLFLMSNS(42)(G28-S42), (56)LKSHGGRIFYRHMHI(70)(L56-I70), and (154)ETFQSFYIGGGANSH(168)(E154-H168) were recognized. L56-I70 is the most important epitope, and a competitive ELISA indicated that it could inhibit the binding of monoclonal antibody to Gly m Bd 28K protein. Alanine scanning of L56-I70 documented that F64, Y65, and R66 were the critical amino acids of this epitope. Two bioinformatics tools, ABCpred and BepiPred, were used to predict the epitopes of Gly m Bd 28K, and the predictions were compared with the epitopes that we had located by monoclonal antibodies.

Lymphoma Immunotherapy: Current Status

The rationale to treat lymphomas with immunotherapy comes from long-standing evidence on their distinctive immune responsiveness. Indolent B-cell non-Hodgkin lymphomas, in particular, establish key interactions with the immune microenvironment to ensure prosurvival signals and prevent antitumor immune activation. However, reports of spontaneous regressions indicate that, under certain circumstances, patients develop therapeutic antitumor immunity. Several immunotherapeutic approaches have been thus developed to boost these effects in all patients. To date, targeting CD20 on malignant B cells with the antibody rituximab has been the most clinically effective strategy. However, relapse and resistance prevent to cure approximately half of B-NHL patients, underscoring the need of more effective therapies. The recognition of B-cell receptor variable regions as B-NHL unique antigens promoted the development of specific vaccines to immunize patients against their own tumor. Despite initial promising results, this strategy has not yet demonstrated a sufficient clinical benefit to reach the regulatory approval. Several novel agents are now available to stimulate immune effector functions or counteract immunosuppressive mechanisms, such as engineered antitumor T cells, co-stimulatory receptor agonist, and immune checkpoint-blocking antibodies. Thus, multiple elements can now be exploited in more effective combinations to break the barriers for the induction of anti-lymphoma immunity.

Vaccination strategies in lymphoproliferative disorders: Failures and successes

Anti-tumor vaccines in lymphoproliferative disorders hold out the prospect of effective tumor therapies with minimal side effects. The addition of immunotherapy to old and new chemotherapy regimens has improved both response rates and disease-free survival, leading in many cases to an extended overall survival. Ideally, an antigen that is used for vaccination would be specifically expressed in the tumor; it must have an important, causal part in the multifactorial process that leads to cancer, and it must be expressed stably even after it is attacked by the immune system. Immunotherapies, which aim to activate the immune system to kill cancer cells, include strategies to increase the frequency or potency of antitumor T cells, to overcome suppressive factors in the tumor microenvironment, and to reduce T-cell suppression systemically. In this review, we focus on the results of clinical trials of vaccination in lymphoma, and discuss potential strategies to enhance the efficacy of immunotherapy in the future.

Evaluation of a multi-epitope subunit vaccine against avian leukosis virus subgroup J in chickens

The intricate sequence and antigenic variability of avian leukosis virus subgroup J (ALV-J) have led to unprecedented difficulties in the development of vaccines. Much experimental evidence demonstrates that ALV-J mutants have caused immune evasion and pose a challenge for traditional efforts to develop effective vaccines. To investigate the potential of a multi-epitope vaccination strategy to prevent chickens against ALV-J infections, a recombinant chimeric multi-epitope protein X (rCMEPX) containing both immunodominant B and T epitope concentrated domains selected from the major structural protein of ALV-J using bioinformatics approach was expressed in Escherichia coli Rosetta (DE3). Its immunogenicity and protective efficacy was studied in chickens. The results showed that rCMEPX could elicit neutralizing antibodies and cellular responses, and antibodies induced by rCMEPX could specifically recognize host cell naturally expressed ALV-J proteins, which indicated that the rCMEPX is a good immunogen. Challenge experiments showed 80% chickens that received rCMEPX were well protected against ALV-J challenge. This is the first report of a chimeric multi-epitope protein as a potential immunogen against ALV-J.

An overview of bioinformatics tools for epitope prediction: implications on vaccine development

Exploitation of recombinant DNA and sequencing technologies has led to a new concept in vaccination in which isolated epitopes, capable of stimulating a specific immune response, have been identified and used to achieve advanced vaccine formulations; replacing those constituted by whole pathogen-formulations. In this context, bioinformatics approaches play a critical role on analyzing multiple genomes to select the protective epitopes in silico. It is conceived that cocktails of defined epitopes or chimeric protein arrangements, including the target epitopes, may provide a rationale design capable to elicit convenient humoral or cellular immune responses. This review presents a comprehensive compilation of the most advantageous online immunological software and searchable, in order to facilitate the design and development of vaccines. An outlook on how these tools are supporting vaccine development is presented. HIV and influenza have been taken as examples of promising developments on vaccination against hypervariable viruses. Perspectives in this field are also envisioned.

Immunogenicity evaluation of a rationally designed polytope construct encoding HLA-A*0201 restricted epitopes derived from Leishmania major related proteins in HLA-A2/DR1 transgenic mice: steps toward polytope vaccine

Background

There are several reports demonstrating the role of CD8 T cells against Leishmania species. Therefore peptide vaccine might represent an effective approach to control the infection. We developed a rational polytope-DNA construct encoding immunogenic HLA-A2 restricted peptides and validated the processing and presentation of encoded epitopes in a preclinical mouse model humanized for the MHC-class-I and II.

Methods and Findings

HLA-A*0201 restricted epitopes from LPG-3, LmSTI-1, CPB and CPC along with H-2Kd restricted peptides, were lined-up together as a polytope string in a DNA construct. Polytope string was rationally designed by harnessing advantages of ubiquitin, spacers and HLA-DR restricted Th1 epitope. Endotoxin free pcDNA plasmid expressing the polytope was inoculated into humanized HLA-DRB1*0101/HLA-A*0201 transgenic mice intramuscularly 4 days after Cardiotoxin priming followed by 2 boosters at one week interval. Mice were sacrificed 10 days after the last booster, and splenocytes were subjected to ex-vivo and in-vitro evaluation of specific IFN-γ production and in-vitro cytotoxicity against individual peptides by ELISpot and standard chromium-51(⁵¹Cr) release assay respectively. 4 H-2Kd and 5 HLA-A*0201 restricted peptides were able to induce specific CD8 T cell responses in BALB/C and HLA-A2/DR1 mice respectively. IFN-γ and cytolytic activity together discriminated LPG-3-P1 as dominant, LmSTI-1-P3 and LmSTI-1-P6 as subdominant with both cytolytic activity and IFN-γ production, LmSTI-1-P4 and LPG-3-P5 as subdominant with only IFN-γ production potential.

Conclusions

Here we described a new DNA-polytope construct for Leishmania vaccination encompassing immunogenic HLA-A2 restricted peptides. Immunogenicity evaluation in HLA-transgenic model confirmed CD8 T cell induction with expected affinities and avidities showing almost efficient processing and presentation of the peptides in relevant preclinical model. Further evaluation will determine the efficacy of this polytope construct protecting against infectious challenge of Leishmania. Fortunately HLA transgenic mice are promising preclinical models helping to speed up immunogenicity analysis in a human related mouse model.

pH-sensitive carbonate apatite nanoparticles as DNA vaccine carriers enhance humoral and cellular immunity

To demonstrate the potential of pH-sensitive carbonate apatite (CO₃Ap) nanoparticles as DNA vaccine carriers to enhance vaccination efficacy, we examined the humoral and cellular immune responses of C57BL/6 mice immunized with the plasmid expression vector pCI-neo encoding the full-length soluble ovalbumin (OVA) (pCI-neo-sOVA), pCI-neo-sOVA/CO₃Ap complexes, or pCI-neo/CO₃Ap complexes as a control. Mice immunized with a low dose of pCI-neo-sOVA-loaded CO₃Ap (10 μg) produced ex vivo splenocyte proliferation after stimulation with CD8 T-cell but not CD4 T-cell epitopes and a delayed-type-hypersensitivity reaction more efficiently than mice in the other groups. Furthermore, mice receiving this immunization generated the same levels of OVA-specific antibodies and interferon (IFN)-γ secretion after CD8 T-cell and CD4 T-cell epitope challenges as those in mice treated with 100 μg of free pCI-neo-sOVA, whereas mice injected with a high dose of pCI-neo-sOVA-loaded CO₃Ap (100 μg) or with control plasmids produced negligible levels of OVA-specific antibodies or IFN-γ. Therefore, our results showed that 10 μg of pCI-neo-sOVA delivered by CO₃Ap strongly elicited humoral and cellular immune responses. This study is the first to demonstrate the promising potential of CO₃Ap nanoparticles for DNA vaccine delivery.

Current trends in cancer vaccines--a bioinformatics perspective

Cancer vaccine development is in the process of becoming reality in future, due to successful phase II/III clinical trials. However, there are still problems due to the specificity of tumor antigens and weakness of tumor associated antigens in eliciting an effective immune response. Computational models to assess the vaccine efficacy have helped to improve and understand what is necessary for personalized treatment. Further research is needed to elucidate the mechanisms of activation of antigen specific cytotoxic T lymphocytes, decreased TREG number functionality and antigen cascade, so that overall improvement in vaccine efficacy and disease free survival can be attained. T cell epitomic based in sillico approaches might be very effective for the design and development of novel cancer vaccines.

Strategies for improving DNA vaccine performance

The goal of active vaccination is to induce all the immune effector pathways and to establish immunological memory allowing prolonged surveillance against pathogens or cancer cells. DNA vaccination platform is an intriguing strategy owing to its ability to mobilize both branches of the immune system (i.e., innate immunity as well as adaptive immunity). Since plasmids offer several advantages for biotechnological applications due to their modular structure and easy manipulation, a wide range of strategies can be applied to improve DNA vaccine performance. This chapter discusses this topic in detail taking into account antigen/epitope selection and optimization, inclusion of intracellular targeting sequences and genetic adjuvants, and provision of T cell help.

Immunoinformatics: a brief review

A large volume of data relevant to immunology research has accumulated due to sequencing of genomes of the human and other model organisms. At the same time, huge amounts of clinical and epidemiologic data are being deposited in various scientific literature and clinical records. This accumulation of the information is like a goldmine for researchers looking for mechanisms of immune function and disease pathogenesis. Thus the need to handle this rapidly growing immunological resource has given rise to the field known as immunoinformatics. Immunoinformatics, otherwise known as computational immunology, is the interface between computer science and experimental immunology. It represents the use of computational methods and resources for the understanding of immunological information. It not only helps in dealing with huge amount of data but also plays a great role in defining new hypotheses related to immune responses. This chapter reviews classical immunology, different databases, and prediction tool. Further, it briefly describes applications of immunoinformatics in reverse vaccinology, immune system modeling, and cancer diagnosis and therapy. It also explores the idea of integrating immunoinformatics with systems biology for the development of personalized medicine. All these efforts save time and cost to a great extent.

Novel approaches in polyepitope T-cell vaccine development against HIV-1

RV144 clinical trial was modestly effective in preventing HIV infection. New alternative approaches are needed to design improved HIV-1 vaccines and their delivery strategies. One of these approaches is construction of synthetic polyepitope HIV-1 immunogen using protective T- and B-cell epitopes that can induce broadly neutralizing antibodies and responses of cytotoxic (CD8(+) CTL) and helpers (CD4(+) Th) T-lymphocytes. This approach seems to be promising for designing of new generation of vaccines against HIV-1, enables in theory to cope with HIV-1 antigenic variability, focuses immune responses on protective determinants and enables to exclude from the vaccine compound that can induce autoantibodies or antibodies enhancing HIV-1 infectivity. Herein, the authors will focus on construction and rational design of polyepitope T-cell HIV-1 immunogens and their delivery, including: advantages and disadvantages of existing T-cell epitope prediction methods; features of organization of polyepitope immunogens, which can generate high-level CD8(+) and CD4(+) T-lymphocyte responses; the strategies to optimize efficient processing, presentation and immunogenicity of polyepitope constructs; original software to design polyepitope immunogens; and delivery vectors as well as mucosal strategies of vaccination. This new knowledge may bring us a one step closer to developing an effective T-cell vaccine against HIV-1, other chronic viral infections and cancer.

Exhaustive proteome mining for functional MHC-I ligands

We present the development and application of a new machine-learning approach to exhaustively and reliably identify major histocompatibility complex class I (MHC-I) ligands among all 20(8) octapeptides and in genome-derived proteomes of Mus musculus , influenza A H3N8, and vesicular stomatitis virus (VSV). Focusing on murine H-2K(b), we identified potent octapeptides exhibiting direct MHC-I binding and stabilization on the surface of TAP-deficient RMA-S cells. Computationally identified VSV-derived peptides induced CD8(+) T-cell proliferation after VSV-infection of mice. The study demonstrates that high-level machine-learning models provide a unique access to rationally designed peptides and a promising approach toward "reverse vaccinology".

Active immunotherapy: current state of the art in vaccine approaches for NHL

Immune therapy of cancer is a rapidly evolving field, with long-deserved successes now finally achieved. As new pathways triggered by the immune synapsis are elucidated, and new molecules responsible for immune checkpoints are being discovered, it is becoming clear that vaccination against a single antigen aided by non-specific immune stimulation is not sufficient for an efficient, long term, immune response. Though lymphoma is a highly curable malignancy, there is still a subset of patients that is at very high risk of disease relapse even after successfully completing chemotherapy or a stem cell transplant. Patients with minimal residual disease are particularly suitable for vaccination. Over the past 3 decades, the classic model of lymphoma-specific idiotype vaccine has evolved and recent data on vaccination with nonspecific oligodeoxynucleotides has provided very encouraging results. Furthermore, the introduction of checkpoint blockade via agonist or antagonist monoclonal antibodies holds the promise of significant improvement in the efficacy of future vaccines. What follows is a brief summary of the historical highlights in lymphoma immunotherapy as well as an update on the most recently published clinical trials and a look at future developments.

Cancer vaccines: state of the art of the computational modeling approaches

Cancer vaccines are a real application of the extensive knowledge of immunology to the field of oncology. Tumors are dynamic complex systems in which several entities, events, and conditions interact among them resulting in growth, invasion, and metastases. The immune system includes many cells and molecules that cooperatively act to protect the host organism from foreign agents. Interactions between the immune system and the tumor mass include a huge number of biological factors. Testing of some cancer vaccine features, such as the best conditions for vaccine administration or the identification of candidate antigenic stimuli, can be very difficult or even impossible only through experiments with biological models simply because a high number of variables need to be considered at the same time. This is where computational models, and, to this extent, immunoinformatics, can prove handy as they have shown to be able to reproduce enough biological complexity to be of use in suggesting new experiments. Indeed, computational models can be used in addition to biological models. We now experience that biologists and medical doctors are progressively convinced that modeling can be of great help in understanding experimental results and planning new experiments. This will boost this research in the future.

Enhancement of DNA vaccine efficacy by targeting the xenogeneic human chorionic gonadotropin, survivin and vascular endothelial growth factor receptor 2 combined tumor antigen to the major histocompatibility complex class II pathway

BACKGROUND

A number of strategies have been used to improve the efficacy of the DNA vaccine for the treatment of tumors. These strategies, ranging from activating CD4+ T cell, manipulating antigen presentation and/or processing to anti-angiogenesis, focus on one certain aspect in the functioning of the vaccine. Therefore, their combination is necessary for rational DNA vaccines design by synergizing different regimens and overcoming the limitations of each strategy.

METHODS

A DNA fragment (HSV) encoding the C terminal 37 amino acids of human chorionic gonadotropin β chain (hCGβ), 5 different HLA-restricted cytotoxic T lymphocyte epitopes from human survivin and the third and fourth extracellular domains of vascular endothelial growth factor receptor 2 (VEGFR2) was inserted into the sequence between the luminal and transmembrane domain of human lysosome-associated membrane protein-1 cDNA for the construction of a novel DNA vaccine.

RESULTS

This novel vaccine, named p-L/HSV, has a potent antitumor effect on the LL/2 lung carcinoma model in syngeneic C57BL/6 mice. The immunologic mechanism involved in the antitumor effect referred to the activation of both cellular and humoral immune response. In addition, the tumor vasculature was abrogated as observed by immunohistochemistry in p-L/HSV immunized mice. Furthermore, the immunized mice received an additional boost with p-L/HSV 6 months later and showed a strong immune recall response.

CONCLUSIONS

The present study indicates that the strategies of combining antitumor with antiangiogenesis and targeting the tumor antigen to the major histocompatibility complex class II pathway cooperate well. Such a study may shed new light on designing vaccine for cancer in the future.