Tumor Mutational Burden as a Biomarker of Immunotherapy Response: An Immunogram Approach in Onco-immunology.

Immune checkpoint inhibitors have revolutionized cancer treatment by allowing T cells to reactivate. Tumor mutational burden (TMB) is a biomarker that has emerged as a viable diagnostic for locating patients who would benefit from immunotherapy in particular cancer types. Greater neo-antigens mean more opportunities for T cell identification, and TMB is clinically linked to better immune checkpoint inhibitors. Tumor foreignness is a cancer immunogram, and TMB can be used as a substitute for foreignness. The role of TMB analysis as an independent predictor of immunotherapy response in the context of immune checkpoint inhibitor medications is the subject of this mini-review.

mRNA-Based Cancer Vaccines: Advancements and Prospects.

The success of mRNA COVID-19 vaccines has reinvigorated research and interest in mRNA-based cancer vaccines. Despite promising results in clinical trials, therapeutic mRNA-based cancer vaccines have not yet been approved for human use. These vaccines are designed to trigger tumor regression, establish enduring antitumor memory, and mitigate adverse reactions. However, challenges such as tumor-induced immunosuppression and immunoresistance significantly hinder their application. Here, we provide an overview of the recent advances of neoantigen discovery and delivery systems for mRNA vaccines, focusing on improving clinical efficacy. Additionally, we summarize the recent clinical advances involving mRNA cancer vaccines and discuss prospective strategies for overcoming immuneresistance.

NitraTh epitope-based neoantigen vaccines for effective tumor immunotherapy.

Neoantigen vaccines represent an emerging and promising strategy in the field of tumor immunotherapy. Despite their potential, designing an effective neoantigen vaccine remains a challenge due to the current limitations in predicting CD4+ T cell epitopes with high accuracy. Here, we introduce a novel approach to neoantigen vaccine design that does not rely on computational prediction of CD4+ T cell epitopes. Utilizing nitrated helper T cell epitope containing p-nitrophenylalanine, termed "NitraTh epitope," we have successfully engineered a series of tumor neoantigen vaccines capable of eliciting robust neoantigen-specific immune responses. With the help of NitraTh epitope, even mutations with low predicted affinity for MHC class I molecules were successfully induced to elicit neoantigen-specific responses. In H22 cell allograft and patient-derived xenograft (PDX) liver cancer mouse models, the NitraTh epitope-based neoantigen vaccines significantly suppressed tumor progression. More strikingly, through single-cell sequencing we found that the NitraTh epitope-based neoantigen vaccines regulate macrophage reprogramming and modulate macrophages to decrease the levels of the immunosuppressive molecule prostaglandin E2 (PGE2), which in turn reshapes the tumor immunosuppressive microenvironment. In summary, NitraTh epitope-based neoantigen vaccines possess the dual effects of potently activating neoantigen-specific immunity and alleviating immunosuppression, potentially providing a new paradigm for the design of tumor neoantigen vaccines.

Molecular targets and strategies in the development of nucleic acid cancer vaccines: from shared to personalized antigens.

Recent breakthroughs in cancer immunotherapies have emphasized the importance of harnessing the immune system for treating cancer. Vaccines, which have traditionally been used to promote protective immunity against pathogens, are now being explored as a method to target cancer neoantigens. Over the past few years, extensive preclinical research and more than a hundred clinical trials have been dedicated to investigating various approaches to neoantigen discovery and vaccine formulations, encouraging development of personalized medicine. Nucleic acids (DNA and mRNA) have become particularly promising platform for the development of these cancer immunotherapies. This shift towards nucleic acid-based personalized vaccines has been facilitated by advancements in molecular techniques for identifying neoantigens, antigen prediction methodologies, and the development of new vaccine platforms. Generating these personalized vaccines involves a comprehensive pipeline that includes sequencing of patient tumor samples, data analysis for antigen prediction, and tailored vaccine manufacturing. In this review, we will discuss the various shared and personalized antigens used for cancer vaccine development and introduce strategies for identifying neoantigens through the characterization of gene mutation, transcription, translation and post translational modifications associated with oncogenesis. In addition, we will focus on the most up-to-date nucleic acid vaccine platforms, discuss the limitations of cancer vaccines as well as provide potential solutions, and raise key clinical and technical considerations in vaccine development.

DEMINING: A deep learning model embedded framework to distinguish RNA editing from DNA mutations in RNA sequencing data.

Precise calling of promiscuous adenosine-to-inosine RNA editing sites from transcriptomic datasets is hindered by DNA mutations and sequencing/mapping errors. Here, we present a stepwise computational framework, called DEMINING, to distinguish RNA editing and DNA mutations directly from RNA sequencing datasets, with an embedded deep learning model named DeepDDR. After transfer learning, DEMINING can also classify RNA editing sites and DNA mutations from non-primate sequencing samples. When applied in samples from acute myeloid leukemia patients, DEMINING uncovers previously underappreciated DNA mutation and RNA editing sites; some associated with the upregulated expression of host genes or the production of neoantigens.

Neoantigen sequestrated autophagosomes as therapeutic cancer vaccines.

Neoantigens serve as ideal personalized cancer vaccines because of their high immunogenicity, ability to evade central thymic tolerance, and minimal risk of eliciting autoimmune responses. Herein, we describe a genetically engineered autophagosome-based neoantigen vaccine (APNV) in combination with an immune checkpoint inhibitor (anti-PD-1 antibody) for cancer immunotherapy. The APNV was derived from engineered NIH 3T3 cells, which co-express melanoma neoantigens and autophagosome maker microtubule-associated proteins 1 A/1B light chain 3B (LC3), from which the LC3-labeled neoantigen-autophagosomes were isolated. These purified autophagosomes, in conjunction with vaccine adjuvants high-mobility group box 1 (HMGB1) and granulocyte-macrophage colony-stimulating factor (GM-CSF), were integrated into a hydrogel to create an APNV. The APNV effectively activated dendritic cells both in vitro and in vivo. Moreover, APNV, in combination with checkpoint blockade therapy, significantly hampered post-surgical tumor recurrence in a subcutaneous melanoma tumor model and effectively impeded metastatic progression in a melanoma lung metastasis model. This APNV may be conducive to making personalized therapeutic neoantigen vaccines for cancer immunotherapy.

RNA splicing junction landscape reveals abundant tumor-specific transcripts in human cancer.

RNA splicing is a critical process governing gene expression and transcriptomic diversity. Despite its importance, a detailed examination of transcript variation at the splicing junction level remains scarce. Here, we perform a thorough analysis of RNA splicing junctions in 34,775 samples across multiple sample types. We identified 29,051 tumor-specific transcripts (TSTs) in pan-cancer, with a majority of these TSTs being unannotated. Our findings show that TSTs are positively correlated with tumor stemness and linked to unfavorable outcomes in cancer patients. Additionally, TSTs display mutual exclusivity with somatic mutations and are overrepresented in transposable-element-derived transcripts possessing oncogenic functions. Importantly, TSTs can generate putative neoantigens for immunotherapy. Moreover, TSTs can be detected in blood extracellular vesicles from cancer patients. Our results shed light on the intricacies of RNA splicing and offer promising avenues for cancer diagnosis and therapy.

Harnessing the power of AI in precision medicine: NGS-based therapeutic insights for colorectal cancer cohort.

Purpose: Developing innovative precision and personalized cancer therapeutics is essential to enhance cancer survivability, particularly for prevalent cancer types such as colorectal cancer. This study aims to demonstrate various approaches for discovering new targets for precision therapies using artificial intelligence (AI) on a Polish cohort of colorectal cancer patients. Methods: We analyzed 71 patients with histopathologically confirmed advanced resectional colorectal adenocarcinoma. Whole exome sequencing was performed on tumor and peripheral blood samples, while RNA sequencing (RNAseq) was conducted on tumor samples. We employed three approaches to identify potential targets for personalized and precision therapies. First, using our in-house neoantigen calling pipeline, ARDentify, combined with an AI-based model trained on immunopeptidomics mass spectrometry data (ARDisplay), we identified neoepitopes in the cohort. Second, based on recurrent mutations found in our patient cohort, we selected corresponding cancer cell lines and utilized knock-out gene dependency scores to identify synthetic lethality genes. Third, an AI-based model trained on cancer cell line data was employed to identify cell lines with genomic profiles similar to selected patients. Copy number variants and recurrent single nucleotide variants in these cell lines, along with gene dependency data, were used to find personalized synthetic lethality pairs. Results: We identified approximately 8,700 unique neoepitopes, but none were shared by more than two patients, indicating limited potential for shared neoantigenic targets across our cohort. Additionally, we identified three synthetic lethality pairs: the well-known APC-CTNNB1 and BRAF-DUSP4 pairs, along with the recently described APC-TCF7L2 pair, which could be significant for patients with APC and BRAF variants. Furthermore, by leveraging the identification of similar cancer cell lines, we uncovered a potential gene pair, VPS4A and VPS4B, with therapeutic implications. Conclusion: Our study highlights three distinct approaches for identifying potential therapeutic targets in cancer patients. Each approach yielded valuable insights into our cohort, underscoring the relevance and utility of these methodologies in the development of precision and personalized cancer therapies. Importantly, we developed a novel AI model that aligns tumors with representative cell lines using RNAseq and methylation data. This model enables us to identify cell lines closely resembling patient tumors, facilitating accurate selection of models needed for in vitro validation.

Developing Vaccines in Pancreatic Adenocarcinoma: Trials and Tribulations.

Pancreatic adenocarcinoma represents one of the most challenging malignancies to treat, with dismal survival rates despite advances in therapeutic modalities. Immunotherapy, particularly vaccines, has emerged as a promising strategy to harness the body's immune system in combating this aggressive cancer. This abstract reviews the trials and tribulations encountered in the development of vaccines targeting pancreatic adenocarcinoma. Key challenges include the immunosuppressive tumor microenvironment, the heterogeneity of tumor antigens, and a limited understanding of immune evasion mechanisms employed by pancreatic cancer cells. Various vaccine platforms, including peptide-based, dendritic cell-based, and viral vector-based vaccines, have been explored in preclinical and clinical settings. However, translating promising results from preclinical models to clinical efficacy has proven elusive. In recent years, mRNA vaccines have emerged as a promising immunotherapeutic strategy in the fight against various cancers, including pancreatic adenocarcinoma. We will discuss the potential applications, opportunities, and challenges associated with mRNA vaccines in pancreatic cancer treatment.

Advancements and Challenges in Personalized Therapy for BRAF-Mutant Melanoma: A Comprehensive Review.

Over the past several decades, advancements in the treatment of BRAF-mutant melanoma have led to the development of BRAF inhibitors, BRAF/MEK inhibitor combinations, anti-PD-1 therapy, and anti-CTLA4 therapy. Although these therapies have shown substantial efficacy in clinical trials, their sustained effectiveness is often challenged by the tumor microenvironment, which is a highly heterogeneous and complex milieu of immunosuppressive cells that affect tumor progression. The era of personalized medicine holds substantial promise for the tailoring of treatments to individual genetic profiles. However, tumor heterogeneity and immune evasion mechanisms contribute to the resistance to immunotherapy. Despite these challenges, tumor-infiltrating lymphocyte (TIL) therapy, as exemplified by lifileucel, has demonstrated notable efficacy against BRAF V600-mutant melanoma. Additionally, early response biomarkers, such as COX-2 and MMP2, along with FDG-PET imaging, offer the potential to improve personalized immunotherapy by predicting patient responses and determining the optimal treatment duration. Future efforts should focus on reducing the T-cell harvesting periods and costs associated with TIL therapy to enhance efficiency and accessibility.

Nine Human Leukocyte Antigen (HLA) Class I Alleles are Omnipotent Against 11 Antigens Expressed in Melanoma Tumors.

Objective: Host immunogenetics (Human Leukocyte Antigen, HLA) play a critical role in the human immune response to melanoma, influencing both melanoma prevalence and immunotherapy outcomes. Beneficial outcomes hinge on the successful binding of epitopes of melanoma antigens to HLA Class I molecules for an effective engagement of cytotoxic CD8+ lymphocytes and subsequent elimination of the cancerous cell. This study evaluated the binding affinity and immunogenicity of HLA Class I to melanoma tumor antigens to identify alleles best suited to facilitate elimination of melanoma antigens. Methods: In this study, we used freely available software tools to determine in silico the binding affinity and immunogenicity of 2462 reported HLA Class I alleles to all linear nonamer epitopes of 11 known antigens expressed in melanoma tumors (TRP2, S100, Tyrosinase, TRP1, PMEL(17), MAGE1, MAGE4, CTA, BAGE, GAGE/SSX2, Melan). Results: We identified the following 9 HLA Class I alleles with very high immunogenicity and binding affinity against all 11 melanoma antigens: A*02:14, B*07:10, B*35:10, B*40:10, B*40:12, B*44:10, C*07:11, and C*07:13, and C*07:14. Conclusion: These 9 HLA alleles possess the potential to aid in the elimination of melanoma both by themselves and by enhancing the beneficial effect of immune checkpoint inhibitors.

[Antitumor Study of Neoantigen-reactive T Cells Co-expressing IL-7 and CCL19 
in Mouse Lung Cancer].

BACKGROUND: Neoantigen reactive T cell (NRT) has the ability to inhibit the growth of tumors expressing specific neoantigens. However, due to the difficult immune infiltration and the inhibition of tumor microenvironment, the therapeutic effect of NRT in solid tumors is limited. In this study, we designed NRT cells (7×19 NRT) that can express both interleukin-7 (IL-7) and chemokine C-C motif ligand 19 (CCL19) in mouse lung cancer cells, and evaluated the difference in anti-tumor effect between 7×19 NRT cells and conventional NRT cells. METHODS: We performed next-generation sequencing and neoantigen prediction for mouse Lewis lung carcinoma (LLC), prepared RNA vaccine, cultured NRT cells, constructed retroviral vectors encoding IL-7 and CCL19, transduced NRT cells and IL-7 and CCL19 were successfully expressed, and 7×19 NRT was successfully obtained. The anti-tumor effect was evaluated in vivo and in vitro in mice. RESULTS: The 7×19 NRT cells significantly enhanced the proliferation and invasion ability of T cells by secreting IL-7 and CCL19, achieved significant tumor inhibition in the mouse lung cancer and extended the survival period of mice. The T cell infiltration into tumor tissue and the necrosis of tumor tissue increased significantly after 7×19 NRT treatment. In addition, both 7×19 NRT treatment and conventional NRT treatment were safe. CONCLUSIONS: The anti-solid tumor ability of NRT cells is significantly enhanced by the arming of IL-7 and CCL19, which is a safe and effective genetic modification of NRT.

Revamping Hepatocellular Carcinoma Immunotherapy: The Advent of Microbial Neoantigen Vaccines.

Immunotherapy has revolutionized the treatment paradigm for hepatocellular carcinoma (HCC). However, its efficacy varies significantly with each patient's genetic composition and the complex interactions with their microbiome, both of which are pivotal in shaping anti-tumor immunity. The emergence of microbial neoantigens, a novel class of tumor vaccines, heralds a transformative shift in HCC therapy. This review explores the untapped potential of microbial neoantigens as innovative tumor vaccines, poised to redefine current HCC treatment modalities. For instance, neoantigens derived from the microbiome have demonstrated the capacity to enhance anti-tumor immunity in colorectal cancer, suggesting similar applications in HCC. By harnessing these unique neoantigens, we propose a framework for a personalized immunotherapeutic response, aiming to deliver a more precise and potent treatment strategy for HCC. Leveraging these neoantigens could significantly advance personalized medicine, potentially revolutionizing patient outcomes in HCC therapy.

Rational Design of a Multi-epitope Vaccine Using Neoantigen Against Colorectal Cancer Through Structural Immunoinformatics and ML-Enabled Simulation Approach.

Colorectal cancer poses a substantial global health burden. Regarding WHO, the global burden of colorectal cancer will be about 3.2 million new cases by the year 2040. Simultaneously, it indicated that this cancer will cause 6 million deaths per year. Despite advancements in chemotherapy and monoclonal antibody therapy, the disease remains a significant challenge due to the resistance of cancer stem cells. This study endeavors to design a multi-epitopic peptide (9-mer epitopes) neoantigen-based vaccine targeting the TLR4/MD2 complex as a potential vaccine candidate. These tumor-specific neoantigens (TSA) are considered novel antigens that can be used for vaccine development against cancer. To develop the neoantigen vaccine candidate, we used the SPENCER database, and 140 lncRNA-derived epitopes were retrieved. From 140 epitopes, we selected seven neoantigens with high antigenic properties for the vaccine construct. A novel vaccine containing epitopes, linkers (EAAAK and CPCPG), and adjuvants (ribosomal [50S] protein L7L12) was formulated utilizing immunoinformatics tools. The vaccine's biophysical properties were evaluated, revealing its antigenicity (0.6469), stability (instability index: 37.05), and potential for immune system interaction. In-depth structural analyses, molecular docking studies, and ML-enabled immune simulation profiling underscored the vaccine's structural integrity, binding affinity with TLR4, and ability to elicit robust immune responses against colorectal cancer antigens. These findings suggest that the multi-epitopic vaccine holds promise as a next-generation approach to combat colorectal cancer. Our in silico studies exhibit potentiality of the vaccine candidate; however, further in vivo and in vitro investigations are crucial to validate immunogenicity, safety, and efficacy before clinical implementation. Our study developed a first-time lncRNA-derived neoantigen-based cancer vaccine.

Altered epitopes enhance macrophage-mediated anti-tumour immunity to low-immunogenic tumour mutations.

Personalized neoantigen therapy has shown long-term and stable efficacy in specific patient populations. However, not all patients have sufficient levels of neoantigens for treatment. Although somatic mutations are commonly found in tumours, a significant portion of these mutations do not trigger an immune response. Patients with low mutation burdens continue to exhibit unresponsiveness to this treatment. We propose a design paradigm for neoantigen vaccines by utilizing the highly immunogenic unnatural amino acid p-nitrophenylalanine (pNO2Phe) for sequence alteration of somatic mutations that failed to generate neoepitopes. This enhances the immunogenicity of the mutations and transforms it into a suitable candidate for immunotherapy. The nitrated altered epitope vaccines designed according to this paradigm is capable of activating circulating CD8+ T cells and inducing immune cross-reactivity against autologous mutated epitopes in different MHC backgrounds (H-2Kb, H-2Kd, and human HLA-A02:01), leading to the elimination of tumour cells carrying the mutation. After immunization with the altered epitopes, tumour growth was significantly inhibited. It is noteworthy that nitrated epitopes induce tumour-infiltrating macrophages to differentiate into the M1 phenotype, surprisingly enhancing the MHC II molecule presenting pathway of macrophages. Nitrated epitope-treated macrophages have the potential to cross-activate CD4+ and CD8+ T cells, which may explain why pNO2Phe can enhance the immunogenicity of epitopes. Meanwhile, the immunosuppressive microenvironment of the tumour is altered due to the activation of macrophages. The nitrated neoantigen vaccine strategy enables the design of vaccines targeting non-immunogenic tumour mutations, expanding the pool of potential peptides for personalized and shared novel antigen therapy. This approach provides treatment opportunities for patients previously ineligible for new antigen vaccine therapy.

Identification of tumor rejection antigens and the immunologic landscape of medulloblastoma.

BACKGROUND: The current standard of care treatments for medulloblastoma are insufficient as these do not take tumor heterogeneity into account. Newer, safer, patient-specific treatment approaches are required to treat high-risk medulloblastoma patients who are not cured by the standard therapies. Immunotherapy is a promising treatment modality that could be key to improving survival and avoiding morbidity. For an effective immune response, appropriate tumor antigens must be targeted. While medulloblastoma patients with subgroup-specific genetic substitutions have been previously reported, the immunogenicity of these genetic alterations remains unknown. The aim of this study is to identify potential tumor rejection antigens for the development of antigen-directed cellular therapies for medulloblastoma. METHODS: We developed a cancer immunogenomics pipeline and performed a comprehensive analysis of medulloblastoma subgroup-specific transcription profiles (n = 170, 18 WNT, 46 SHH, 41 Group 3, and 65 Group 4 patient tumors) available through International Cancer Genome Consortium (ICGC) and European Genome-Phenome Archive (EGA). We performed in silico antigen prediction across a broad array of antigen classes including neoantigens, tumor-associated antigens (TAAs), and fusion proteins. Furthermore, we evaluated the antigen processing and presentation pathway in tumor cells and the immune infiltrating cell landscape using the latest computational deconvolution methods. RESULTS: Medulloblastoma patients were found to express multiple private and shared immunogenic antigens. The proportion of predicted TAAs was higher than neoantigens and gene fusions for all molecular subgroups, except for sonic hedgehog (SHH), which had a higher neoantigen burden. Importantly, cancer-testis antigens, as well as previously unappreciated neurodevelopmental antigens, were found to be expressed by most patients across all medulloblastoma subgroups. Despite being immunologically cold, medulloblastoma subgroups were found to have distinct immune cell gene signatures. CONCLUSIONS: Using a custom antigen prediction pipeline, we identified potential tumor rejection antigens with important implications for the development of immunotherapy for medulloblastoma.

Exploring the dynamic landscape of immunopeptidomics: Unravelling posttranslational modifications and navigating bioinformatics terrain.

Immunopeptidomics is becoming an increasingly important field of study. The capability to identify immunopeptides with pivotal roles in the human immune system is essential to shift the current curative medicine towards personalized medicine. Throughout the years, the field has matured, giving insight into the current pitfalls. Nowadays, it is commonly accepted that generalizing shotgun proteomics workflows is malpractice because immunopeptidomics faces numerous challenges. While many of these difficulties have been addressed, the road towards the ideal workflow remains complicated. Although the presence of Posttranslational modifications (PTMs) in the immunopeptidome has been demonstrated, their identification remains highly challenging despite their significance for immunotherapies. The large number of unpredictable modifications in the immunopeptidome plays a pivotal role in the functionality and these challenges. This review provides a comprehensive overview of the current advancements in immunopeptidomics. We delve into the challenges associated with identifying PTMs within the immunopeptidome, aiming to address the current state of the field.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives.

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

Neoantigen-specific T cell help outperforms non-specific help in multi-antigen DNA vaccination against cancer.

CD4+ T helper antigens are essential components of cancer vaccines, but the relevance of the source of these MHC class II-restricted antigens remains underexplored. To compare the effectiveness of tumor-specific versus tumor-unrelated helper antigens, we designed three DNA vaccines for the murine MC-38 colon carcinoma, encoding CD8+ T cell neoantigens alone (noHELP) or in combination with either "universal" helper antigens (uniHELP) or helper neoantigens (neoHELP). Both types of helped vaccines increased the frequency of vaccine-induced CD8+ T cells, and particularly uniHELP increased the fraction of KLRG1+ and PD-1low effector cells. However, when mice were subsequently injected with MC-38 cells, only neoHELP vaccination resulted in significantly better tumor control than noHELP. In contrast to uniHELP, neoHELP-induced tumor control was dependent on the presence of CD4+ T cells, while both vaccines relied on CD8+ T cells. In line with this, neoHELP variants containing wild-type counterparts of the CD4+ or CD8+ T cell neoantigens displayed reduced tumor control. These data indicate that optimal personalized cancer vaccines should include MHC class II-restricted neoantigens to elicit tumor-specific CD4+ T cell help.