Considerations for personalized neoantigen vaccination in Malignant glioma

Current Progress in Vaccines against Merkel Cell Carcinoma: A Narrative Review and Update

Merkel cell carcinoma is a rare, aggressive skin cancer that mainly occurs in elderly and immunocompromised patients. Due to the success of immune checkpoint inhibition in MCC, the importance of immunotherapy and vaccines in MCC has increased in recent years. In this article, we aim to present the current progress and perspectives in the development of vaccines for this disease. Here, we summarize and discuss the current literature and ongoing clinical trials investigating vaccines against MCC. We identified 10 articles through a PubMed search investigating a vaccine against MCC. From the international clinical trial database Clinical.Trials.gov, we identified nine studies on vaccines for the management of MCC, of which seven are actively recruiting. Most of the identified studies investigating a vaccine against MCC are preclinical or phase 1/2 trials. The vaccine principles mainly included DNA- and (synthetic) peptide-based vaccines, but RNA-based vaccines, oncolytic viruses, and the combination of vaccines and immunotherapy are also under investigation for the treatment of MCC. Although the management of MCC is changing, when compared to times before the approval of immune checkpoint inhibitors, it will still take some time before the first MCC vaccine is ready for approval.

Immunotherapy for Brain Tumors: Where We Have Been, and Where Do We Go From Here?

OPINION STATEMENT

Immunotherapy for glioblastoma (GBM) remains an intensive area of investigation. Given the seismic impact of cancer immunotherapy across a range of malignancies, there is optimism that harnessing the power of immunity will influence GBM as well. However, despite several phase 3 studies, there are still no FDA-approved immunotherapies for GBM. Importantly, the field has learned a great deal from the randomized studies to date. Today, we are continuing to better understand the disease-specific features of the microenvironment in GBM-as well as the exploitable antigenic characteristic of the tumor cells themselves-that are informing the next generation of immune-based therapeutic strategies. The coming phase of next-generation immunotherapies is thus poised to bring us closer to treatments that will improve the lives of patients with GBM.

Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy

Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.

Dendritic cell vaccine trials in gliomas: Untangling the lines

Glioblastoma is a deadly brain tumor without any significantly successful treatments to date. Tumor antigen-targeted immunotherapy platforms including peptide and dendritic cell (DC) vaccines, have extended survival in hematologic malignancies. The relatively "cold" tumor immune microenvironment and heterogenous nature of glioblastoma have proven to be major limitations to translational application and efficacy of DC vaccines. Furthermore, many DC vaccine trials in glioblastoma are difficult to interpret due to a lack of contemporaneous controls, absence of any control comparison, or inconsistent patient populations. Here we review glioblastoma immunobiology aspects that are relevant to DC vaccines, review the clinical experience with DC vaccines targeting glioblastoma, discuss challenges in clinical trial design, and summarize conclusions and directions for future research for the development of effective DC vaccines for patients.

Unraveling tumor specific neoantigen immunogenicity prediction: a comprehensive analysis

Introduction

Identification of tumor specific neoantigen (TSN) immunogenicity is crucial to develop peptide/mRNA based anti-tumoral vaccines and/or adoptive T-cell immunotherapies; thus, accurate in-silico classification/prioritization proves critical for cost-effective clinical applications. Several methods were proposed as TSNs immunogenicity predictors; however, comprehensive performance comparison is still lacking due to the absence of well documented and adequate TSN databases.

Methods

Here, by developing a new curated database having 199 TSNs with experimentally-validated MHC-I presentation and positive/negative immune response (ITSNdb), sixteen metrics were evaluated as immunogenicity predictors. In addition, by using a dataset emulating patient derived TSNs and immunotherapy cohorts containing predicted TSNs for tumor neoantigen burden (TNB) with outcome association, the metrics were evaluated as TSNs prioritizers and as immunotherapy response biomarkers.

Results

Our results show high performance variability among methods, highlighting the need for substantial improvement. Deep learning predictors were top ranked on ITSNdb but show discrepancy on validation databases. In overall, current predicted TNB did not outperform existing biomarkers.

Conclusion

Recommendations for their clinical application and the ITSNdb are presented to promote development and comparison of computational TSNs immunogenicity predictors.

Advances in computational and translational approaches for malignant glioma

Gliomas are the most common primary brain tumors in adults and carry a dismal prognosis for patients. Current standard-of-care for gliomas is comprised of maximal safe surgical resection following by a combination of chemotherapy and radiation therapy depending on the grade and type of tumor. Despite decades of research efforts directed towards identifying effective therapies, curative treatments have been largely elusive in the majority of cases. The development and refinement of novel methodologies over recent years that integrate computational techniques with translational paradigms have begun to shed light on features of glioma, previously difficult to study. These methodologies have enabled a number of point-of-care approaches that can provide real-time, patient-specific and tumor-specific diagnostics that may guide the selection and development of therapies including decision-making surrounding surgical resection. Novel methodologies have also demonstrated utility in characterizing glioma-brain network dynamics and in turn early investigations into glioma plasticity and influence on surgical planning at a systems level. Similarly, application of such techniques in the laboratory setting have enhanced the ability to accurately model glioma disease processes and interrogate mechanisms of resistance to therapy. In this review, we highlight representative trends in the integration of computational methodologies including artificial intelligence and modeling with translational approaches in the study and treatment of malignant gliomas both at the point-of-care and outside the operative theater in silico as well as in the laboratory setting.

Reversing T Cell Dysfunction to Boost Glioblastoma Immunotherapy by Paroxetine-Mediated GRK2 Inhibition and Blockade of Multiple Checkpoints through Biomimetic Nanoparticles

T cell dysfunction-induced tumor immune escape is particularly severe in glioblastoma (GBM), and significantly affects the efficacy of immunotherapy. It is crucial to innovatively reverse the T cell dysfunction for improving GBM immunotherapy. Herein, T cell dysfunction is remarkably reversed and immunotherapy of GBM is boosted by repurposing the U. S. Food and Drug Administration-approved antidepressant paroxetine (PX) with biomimetic nanoparticles (CS-J@CM/6 NPs). The PX is successfully applied to abrogate T cell sequestration in the bone marrow of GBM-bearing mice and increase their infiltration in tumor. The biomimetic NPs are composed of ultrasmall Cu_{2- x} Se NPs, JQ1, and tumor cell membrane modified with CD6, and are efficiently delivered into tumor through the specific interactions between CD6 and activated leukocyte cell adhesion molecule. They ameliorate the T cell dysfunction through the double roles of loaded JQ1, which simultaneously decreases the expression of PD-1 and TIM-3 on T cells, and the expression of PD-L1 on tumor cells. The NP also induces the immunogenic cell death of tumor cells to activate immune response. The synergistic roles of PX and biomimetic CS-J@CM/6 NPs notably enhance the survival of GBM-bearing mice. This work provides new insights into tumor immunotherapy by repurposing "old drugs" with advanced NPs.

Neoantigens: promising targets for cancer therapy

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

Development of therapeutic vaccines for the treatment of diseases

Vaccines are one of the most effective medical interventions to combat newly emerging and re-emerging diseases. Prophylactic vaccines against rabies, measles, etc., have excellent effectiveness in preventing viral infection and associated diseases. However, the host immune response is unable to inhibit virus replication or eradicate established diseases in most infected people. Therapeutic vaccines, expressing specific endogenous or exogenous antigens, mainly induce or boost cell-mediated immunity via provoking cytotoxic T cells or elicit humoral immunity via activating B cells to produce specific antibodies. The ultimate aim of a therapeutic vaccine is to reshape the host immunity for eradicating a disease and establishing lasting memory. Therefore, therapeutic vaccines have been developed for the treatment of some infectious diseases and chronic noncommunicable diseases. Various technological strategies have been implemented for the development of therapeutic vaccines, including molecular-based vaccines (peptide/protein, DNA and mRNA vaccines), vector-based vaccines (bacterial vector vaccines, viral vector vaccines and yeast-based vaccines) and cell-based vaccines (dendritic cell vaccines and genetically modified cell vaccines) as well as combinatorial approaches. This review mainly summarizes therapeutic vaccine-induced immunity and describes the development and status of multiple types of therapeutic vaccines against infectious diseases, such as those caused by HPV, HBV, HIV, HCV, and SARS-CoV-2, and chronic noncommunicable diseases, including cancer, hypertension, Alzheimer's disease, amyotrophic lateral sclerosis, diabetes, and dyslipidemia, that have been evaluated in recent preclinical and clinical studies.

Scoring model based on the signature of non-m6A-related neoantigen-coding lncRNAs assists in immune microenvironment analysis and TCR-neoantigen pair selection in gliomas

Background

Small peptides encoded by long non-coding RNAs (lncRNAs) have attracted attention for their various functions. Recent studies indicate that these small peptides participate in immune responses and antigen presentation. However, the significance of RNA modifications remains unclear.

Methods

Thirteen non-m6A-related neoantigen-coding lncRNAs were selected for analysis from the TransLnc database. Next, a neoantigen activation score (NAS) model was established based on the characteristics of the lncRNAs. Machine learning was employed to expand the model to two additional RNA-seq and two single-cell sequencing datasets for further validation. The DLpTCR algorithm was used to predict T cell receptor (TCR)-peptide binding probability.

Results

The non-m6A-related NAS model predicted patients’ overall survival outcomes more precisely than the m6A-related NAS model. Furthermore, the non-m6A-related NAS was positively correlated with tumor cells’ evolutionary level, immune infiltration, and antigen presentation. However, high NAS gliomas also showed more PD-L1 expression and high mutation frequencies of T-cell positive regulators. Interestingly, results of intercellular communication analysis suggest that T cell-high neoplastic cell interaction is weaker in both of the NAS groups which might arise from decreased IFNGR1 expression. Moreover, we identified unique TCR-peptide pairs present in all glioma samples based on peptides encoded by the 13 selected lncRNAs. And increased levels of neoantigen-active TCR patterns were found in high NAS gliomas.

Conclusions

Our work suggests that non-m6A-related neoantigen-coding lncRNAs play an essential role in glioma progression and that screened TCR clonotypes might provide potential avenues for chimeric antigen receptor T cell (CAR-T) therapy for gliomas.