Identification of tumor antigens and immune subtypes in lower grade gliomas for mRNA vaccine development

The therapeutic effect of mRNA vaccines in glioma: a comprehensive review

INTRODUCTION

Glioma is the most common primary brain tumor, with glioblastoma being the most lethal type due to its heterogeneous and invasive nature of the cancer. Current therapies have low curative success and are limited to surgery, radiotherapy, and chemotherapy. More than 50% of patients become resistant to chemotherapy, and tumor recurrence occurs in most patients following an initial course of therapy. Therefore, developing novel, effective strategies for glioma treatment is essential. Cancer vaccines are novel therapies that demonstrate advantages over conventional methods and, therefore, may be promising options for treating glioma.

AREAS COVERED

This article provided a critical review of pre-clinical and clinical studies that explored appropriate tumor antigen candidates for developing mRNA vaccines and discussed their clinical application in glioma patients. Medline database, PubMed, and ClinicalTrials.gov were searched for glioma vaccine studies published before 2025 using related keywords.

EXPERT OPINION

mRNA vaccines are promising strategies for treating glioma because they are efficient, cost-beneficial, and have lower side effects than other types such as peptide or DNA-based vaccines.

Current mRNA-based vaccine strategies for glioma treatment

Gliomas are one of the most aggressive types of brain tumors and are associated with high morbidity and mortality rates. Currently, conventional treatments for gliomas such as surgical resection, radiotherapy, and chemotherapy have limited effectiveness, and new approaches are needed to improve patient outcomes. mRNA-based vaccines represent a promising therapeutic strategy for cancer treatment, including gliomas. Recent advances in immunotherapy using mRNA-based dendritic cell vaccines have shown great potential in preclinical and clinical trials. Dendritic cells are professional antigen-presenting cells that play a crucial role in initiating and regulating immune responses. In this review, we summarize the current progress of mRNA-based vaccines for gliomas, with a focus on recent advances in dendritic cell-based mRNA vaccines. We also discuss the feasibility and safety of mRNA-based clinical applications for gliomas.

Advancing Cancer Immunotherapy: The Potential of mRNA Vaccines As a Promising Therapeutic Approach

mRNA vaccines have long been recognized for their ability to induce robust immune responses. The discovery that mRNA vaccines may also contribute to antitumor immunity has made them a promising therapeutic approach against cancer. Recent advances in understanding of immune system are precious in developing therapeutic strategies that target pathways involved in tumor survival and progression, leading to the most reliable therapeutic strategies in cancer treatment history. Among all traditional cancer treatments, cancer immunotherapies are less toxic and more effective, even in advanced or recurrent stages of cancer. Recent advancements in genomics and machine learning algorithms give new insight into vaccine development. mRNA vaccines are designed to interfere with stimulator of interferon genes (STING) and tumor‐infiltrating lymphocytes pathways, activating more CD8+ T‐cells involved in destroying tumor cells and inhibiting tumor growth. A stronger immune response can be achieved by incorporating immunological adjuvants alongside mRNA. Nonformulated or vehicle‐based mRNA vaccines, when combined with adjuvants, efficiently express tumor antigens through antigen‐presenting cells and stimulate both innate and adaptive immune responses. Codelivery with additional immunotherapeutic agents, such as checkpoint inhibitors, further enhances the efficacy of mRNA vaccines. This article focuses on the current clinical approaches and challenges to consider when developing mRNA‐based vaccine technology for cancer treatment.

Glioma stem cells remodel immunotolerant microenvironment in GBM and are associated with therapeutic advancements

Glioma is the most common primary tumor of the central nervous system (CNS). Glioblastoma (GBM) is incurable with current treatment strategies. Additionally, the treatment of recurrent GBM (rGBM) is often referred to as terminal treatment, necessitating hospice-level care and management. The presence of the blood-brain barrier (BBB) gives GBM a more challenging or "cold" tumor microenvironment (TME) than that of other cancers and gloma stem cells (GSCs) play an important role in the TME remodeling, occurrence, development and recurrence of giloma. In this review, our primary focus will be on discussing the following topics: niche-associated GSCs and macrophages, new theories regarding GSC and TME involving pyroptosis and ferroptosis in GBM, metabolic adaptations of GSCs, the influence of the cold environment in GBM on immunotherapy, potential strategies to transform the cold GBM TME into a hot one, and the advancement of GBM immunotherapy and GBM models.

Advancing personalized medicine in brain cancer: exploring the role of mRNA vaccines

Advancing personalized medicine in brain cancer relies on innovative strategies, with mRNA vaccines emerging as a promising avenue. While the initial use of mRNA vaccines was in oncology, their stunning success in COVID-19 resulted in widespread attention, both positive and negative. Regardless of politically biased opinions, which relate more to the antigenic source than form of delivery, we feel it is important to objectively review this modality as relates to brain cancer. This class of vaccines trigger robust immune responses through MHC-I and MHC-II pathways, in both prophylactic and therapeutic settings. The mRNA platform offers advantages of rapid development, high potency, cost-effectiveness, and safety. This review provides an overview of mRNA vaccine delivery technologies, tumor antigen identification, combination therapies, and recent therapeutic outcomes, with a particular focus on brain cancer. Combinatorial approaches are vital to maximizing mRNA cancer vaccine efficacy, with ongoing clinical trials exploring combinations with adjuvants and checkpoint inhibitors and even adoptive cell therapy. Efficient delivery, neoantigen identification, preclinical studies, and clinical trial results are highlighted, underscoring mRNA vaccines' potential in advancing personalized medicine for brain cancer. Synergistic combinatorial therapies play a crucial role, emphasizing the need for continued research and collaboration in this area.

The role of immune subtyping in glioma mRNA vaccine development

Studies on the development of mRNA vaccines for central nervous system tumors have used gene expression profiles, clinical data and RNA sequencing from sources such as The Cancer Genome Atlas and Chinese Glioma Genome Atlas to identify effective antigens. These studies revealed several immune subtypes of glioma, each one linked to unique prognoses and genetic/immune-modulatory changes. Potential antigens include ARPC1B, BRCA2, COL6A1, ITGB3, IDH1, LILRB2, TP53 and KDR, among others. Patients with immune-active and immune-suppressive phenotypes were found to respond better to mRNA vaccines. While these findings indicate the potential of mRNA vaccines in cancer therapy, further research is required to optimize administration and adjuvant selection, and precisely identify target antigens.

Classification of Brainstem Gliomas Based on Tumor Microenvironment Status

The inter-tumor heterogeneity of the tumor microenvironment (TME) and how it correlates with clinical profiles and biological characteristics in brainstem gliomas (BSGs) remain unknown, dampening the development of novel therapeutics against BSGs. The TME status was determined with a list of pan-cancer conserved gene expression signatures using a single-sample gene set enrichment analysis (ssGSEA) and was subsequently clustered via consensus clustering. BSGs exhibited a high inter-tumor TME heterogeneity and were classified into four clusters: "immune-enriched, fibrotic", "immune-enriched, non-fibrotic", "fibrotic", and "depleted". The "fibrotic" cluster had a higher proportion of diffuse intrinsic pontine gliomas (p = 0.041), and "PA-like" tumors were more likely to be "immune-enriched, fibrotic" (p = 0.044). The four TME clusters exhibited distinct overall survival (p < 0.001) and independently impacted BSG outcomes. A four-gene panel as well as a radiomics approach were constructed to identify the TME clusters and achieved high accuracy for determining the classification. Together, BSGs exhibited high inter-tumor heterogeneity in the TME and were classified into four clusters with distinct clinical outcomes and tumor biological properties. The TME classification was accurately identified using a four-gene panel that can potentially be examined with the immunohistochemical method and a non-invasive radiomics method, facilitating its clinical application.

Dissection of tumor antigens and immune landscape in clear cell renal cell carcinoma: Preconditions for development and precision medicine of mRNA vaccine

Accumulating evidence reveals that mRNA-type cancer vaccines could be exploited as cancer immunotherapies in various solid tumors. However, the use of mRNA-type cancer vaccines in clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to identify potential tumor antigens for the development of an anti-ccRCC mRNA vaccine. In addition, this study aimed to determine immune subtypes of ccRCC to guide the selection of patients to receive the vaccine. Raw sequencing and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Further, the cBioPortal website was used to visualize and compare genetic alterations. GEPIA2 was employed to evaluate the prognostic value of preliminary tumor antigens. Moreover, the TIMER web server was used to evaluate correlations between the expression of specific antigens and the abundance of infiltrated antigen-presenting cells (APCs). Single-cell RNA sequencing data of ccRCC was used to explore the expression of potential tumor antigens at single-cell resolution. The immune subtypes of patients were analyzed by the consensus clustering algorithm. Furthermore, the clinical and molecular discrepancies were further explored for a deep understanding of the immune subtypes. Weighted gene co-expression network analysis (WGCNA) was used to cluster the genes according to the immune subtypes. Finally, the sensitivity of drugs commonly used in ccRCC with diverse immune subtypes was investigated. The results revealed that the tumor antigen, LRP2, was associated with a good prognosis and enhanced the infiltration of APCs. ccRCC could be divided into two immune subtypes (IS1 and IS2) with distinct clinical and molecular characteristics. The IS1 group showed a poorer overall survival with an immune-suppressive phenotype than the IS2 group. Additionally, a large spectrum of differences in the expression of immune checkpoints and immunogenic cell death modulators were observed between the two subtypes. Lastly, the genes correlated with the immune subtypes were involved in multiple immune-related processes. Therefore, LRP2 is a potential tumor antigen that could be used to develop an mRNA-type cancer vaccine in ccRCC. Furthermore, patients in the IS2 group were more suitable for vaccination than those in the IS1 group.

A Novel Prognostic Marker and Therapeutic Target Associated with Glioma Progression in a Tumor Immune Microenvironment

Background

Immune microenvironment serves a vital role in glioma progression, and a large number of studies have found that tumor progression can be reduced to some extent by modulating the immune process in tumors.

Materials and Methods

ImmuneScore of each sample in CGGA datasets were calculated with Estimate R package, and samples were grouped by median ImmuneScore values for differential analysis to obtain immune microenvironment differential genes. We further conducted survival analysis, ROC curve analysis, independent prognostic analysis, and clinical correlation analysis on glioma sample genes in CGGA to obtain glioma prognostic genes, and then identified their intersection with immune microenvironment DEGs by Venn tool. The GEPIA and UALCAN databases were used to verify the differential expression of intersecting genes in the glioma and normal brain and to identify our target gene. After validation of their prognostic value, we constructed a nomogram to calculate the risk score and to estimate the accuracy of prognostic model. We mined co-expression genes, enriched functions and pathways, and correlations to immune cell infiltration of unigene with an online database. Finally, we verified the differential expression of FCGBP in glioma by immunohistochemical staining.

Results

We finally selected Fc fragment of IgG-binding protein (FCGBP) as our study gene. The prognostic values of FCGBP were validated by a series of analyses. Immunohistochemical staining showed that FCGBP expression increased in gliomas and was up-regulated with the progression of glioma grade.

Conclusion

As a key unigene in glioma progression, FCGBP contributes to the regulation of immune microenvironment and has the potential to be a prognostic biomarker and immune targets.

The integrative analysis based on super-enhancer related genes for predicting different subtypes and prognosis of patient with lower-grade glioma

Objective: Emerging evidence revealed that super-enhancer plays a crucial role in the transcriptional reprogramming for many cancers. The purpose aimed to explored how the super-enhancer related genes affects the prognosis and tumor immune microenvironment (TIME) of patients with low-grade glioma (LGG). Methods: In this study, the differentially expressed genes (DEGs) between LGG cohorts and normal brain tissue cohort were identified by the comprehensive analysis of the super-enhancer (SE) related genes. Then non-negative matrix factorization was performed to seek the optimal classification based on the DEGs, while investigating prognostic and clinical differences between different subtypes. Subsequently, a prognostic related signature (SERS) was constructed for the comprehensive evaluation in term of individualized prognosis, clinical characteristics, cancer markers, genomic alterations, and immune microenvironment of patients with LGG. Results: Based on the expression profiles of 170 DEGs, we identified three SE subtypes, and the three subtypes showed significant differences in prognostic, clinicopathological features. Then, nine optimal SE-related genes were selected to construct the SERS through the least absolute shrinkage and selection operator Cox regression analysis. Survival analysis showed that SERS had strong and stable predictive ability for the prognosis of LGG patients in the The Cancer Genome Atlas, China Glioma Genome Atlas, and Remdrandt cohorts, respectively. We also found that SERS was highly correlated with clinicopathological features, tumor immune microenvironment, cancer hallmarks, and genomic alterations in LGG patients. In addition, the predictive power of SERS for immune checkpoint inhibitor treatment is also superior. The qRT-PCR results and immunohistochemical results also confirmed the difference in the expression of four key genes in normal cells and tumors, as well as in normal tissues and tumor tissues. Conclusion: The SERS could be suitable to utilize individualized prognosis prediction and immunotherapy options for LGG patients in clinical application.

Identification of personalized neoantigen-based vaccines and immune subtype characteristic analysis of glioblastoma based on abnormal alternative splicing

The development of personalized neoantigen-based vaccines in cancer immunotherapy has shown promise. In this study, a large-scale bioinformatics analysis was performed to identify potential GBM-associated neoantigens based on abnormal alternative splicing, and then screen suitable patients for vaccination. Gene expression profiles and clinical information were collected from TCGA. We filtered the percent-spliced-in (PSI) spectrum of alternative splicing events in the dataset to identify abnormal alternative splicing events. MAF package was used to identify and analyse tumour mutation burden (TMB) in cancer samples. Tumour Immune Estimation Resource (TIMER) was used to calculate and visualize the infiltration of antigen presenting cells (APCs). In addition, consistent clustering algorithm utilized to identify immune subtypes of GBM. Five potential tumour neoantigens (LRP1, TCF12, DERL3, WIPI2, and TSHZ3) were identified in GBM by selecting genes both with abnormal alternative splicing (upregulated) and gene frameshift mutations, in which LRP1 was significantly associated with APCs. According to the expressions of five potential tumour neoantigens, 160 patients with GBM were divided into three immune subtypes. Patients in cluster3 exhibited good prognoses. Furthermore, the characteristics, including TMB, abnormal alternative splicing events, immune activity, immune cells proportion, and association with tumour biomarkers, were unique in each immune subtypes. The characteristics of cluster3 illustrated that cluster3 participants were more suitable candidates for vaccination. LRP1 was identified as a potential neoantigen for immunotherapy against GBM, and patients in cluster3 were more suitable for vaccination. Our findings provide important guidance for the development of novel neoantigens and therapeutic targets in patients with GBM.

Role of the mucin-like glycoprotein FCGBP in mucosal immunity and cancer

IgGFc-binding protein (FCGBP) is a mucin first detected in the intestinal epithelium. It plays an important role in innate mucosal epithelial defense, tumor metastasis, and tumor immunity. FCGBP forms disulfide-linked heterodimers with mucin-2 and members of the trefoil factor family. These formed complexes inhibit bacterial attachment to mucosal surfaces, affect the motility of pathogens, and support their clearance. Altered FCGBP expression levels may be important in the pathologic processes of Crohn’s disease and ulcerative colitis. FCGBP is also involved in regulating the infiltration of immune cells into tumor microenvironments. Thus, the molecule is a valuable marker of tumor prognosis. This review summarizes the functional relevance and role of FCGBP in immune responses and disease development, and highlights the potential role in diagnosis and predicting tumor prognosis.

Identification of tumor antigens and immune subtypes of glioma for mRNA vaccine development

Recent evidence suggested that the mRNA vaccine has been effective for many tumors, but its progress in gliomas was slow. In this study, we screened potential tumor antigens and suitable populations for mRNA vaccine to develop mRNA vaccine for glioma. We integrated the normalized RNA sequencing expression data and somatic mutation data from TCGA-GBM, TCGA-LGG, and CGGA datasets. Putative antigens in glioma were identified by selecting highly mutated genes with intimate correlation with clinical survival and immune infiltration. An unsupervised partition around medoids algorithm was utilized to stably cluster the patients into five different immune subtypes. Among them, IS1/2 was cold tumor with low tumor mutation burden (TMB), immunogenic cell death (ICDs), and immune checkpoints (ICPs), and IS4/5 was hot tumor with high TMB, ICDs, and ICPs. Monocle3 package was used to evaluate the immune status similarity and evolution in glioma, which identified cluster IS2A/2B within IS2 subtype to be more suitable vaccination receivers. Weighted gene co-expression network analysis identified five hub immune genes as the biomarkers of patients' immune status in glioma. In conclusion, NAT1, FRRS1, GTF2H2C, BRCA2, GRAP, NR5A2, ABCB4, ZNF90, ERCC6L, and ZNF813 are potential antigens suitable for glioma mRNA vaccine. IS1/2A/2B are suitable for mRNA vaccination.

Identification of Tumor Antigens and Immune Subtypes of Esophageal Squamous Cell Carcinoma for mRNA Vaccine Development

Purpose: The applicability of mRNA vaccines against esophageal squamous cell carcinoma (ESCC) remains unclear. Here, we identified potential antigens for developing mRNA vaccines against ESCC and characterized immune subtypes to select appropriate patients for vaccination.

Methods: RNA-seq, genetic alteration data, and corresponding clinical information of ESCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The RNA-seq data of normal esophageal tissue were obtained from the Genotype-Tissue Expression (GTEx) database. Potential tumor antigens were screened by analyzing differentially expressed and mutated genes and potential antigens with significant differences in prognosis were screened using the Kaplan-Meier method. The proportion of immune cell infiltration in the tumor microenvironment was estimated using CIBERSORT and MCPcounter, and the correlation of potential antigens with antigen-presenting cells and major histocompatibility complex class II was analyzed. Subsequently, immune subtypes were constructed using consensus clustering analysis and characterized by single-sample gene set enrichment analysis and weighted gene co-expression network analysis (WGCNA). The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to analyze the drug sensitivity of different immune subtypes.

Results: Four overexpressed and mutated tumor antigens associated with antigen presentation and poor prognosis were identified in ESCC, including NLRC5, FCRL4, TMEM229B, and LCP2. By consensus clustering, we identified two immune-associated ESCC subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2); the prognosis of the two subtypes was statistically different. In addition, the two immune subtypes had distinctly different cellular, molecular, and clinical characteristics. IS1 patients have a distinct immune “hot” phenotype with strong immune tolerance, whereas patients with IS2 have an immune “cold” phenotype. Differential expression of immune checkpoints and immunogenic cell death modulators was observed between the different immune subtypes. Finally, we found that IS1 and IS2 patients showed different drug sensitivities to common anti-tumor drugs, possibly facilitating the development of individualized treatment regimens for patients.

Conclusion: NLRC5, LCP2, TMEM229B, and FCRL4 are potential antigens for ESCC mRNA vaccines, and such vaccines may be more suitable for IS2 patients. This study provides a theoretical basis for mRNA vaccines against ESCC, by identifying the critical characteristics to predict ESCC prognosis and select suitable patients for vaccination.

Identification of Tumor Antigens and Immune Subtypes in Lung Adenocarcinoma for mRNA Vaccine Development

Cancer vaccines are emerging as a viable strategy for cancer treatment. In the current study, we screened for genes associated with the prognosis of patients with lung adenocarcinoma and positively correlated with antigen-presenting cell infiltration and identified KLRG1 and CBFA2T3 as potential tumor antigens for mRNA vaccines in lung adenocarcinoma (LUAD). Further analyses of immune subtypes revealed that patients with early-stage LUAD, high immune cell infiltration, high immune checkpoint expression, and low tumor mutation burden might benefit from mRNA vaccination. Moreover, we identified four biomarkers that can be used to assess mRNA vaccination suitability. We also identified potentially sensitive anti-cancer drugs for populations not suitable for vaccination by means of anti-cancer drug susceptibility prediction. Overall, we provided a new perspective for mRNA vaccine treatment strategies for LUAD and emphasized the importance of precise and personalized treatments.

Definition of an Inflammatory Biomarker Signature in Plasma-Derived Extracellular Vesicles of Glioblastoma Patients

Glioblastoma (GB) is an aggressive type of tumour for which therapeutic options and biomarkers are limited. GB diagnosis mostly relies on symptomatic presentation of the tumour and, in turn, brain imaging and invasive biopsy that can delay its diagnosis. Description of easily accessible and effective biomarkers present in biofluids would thus prove invaluable in GB diagnosis. Extracellular vesicles (EVs) derived from both GB and stromal cells are essential to intercellular crosstalk in the tumour bulk, and circulating EVs have been described as a potential reservoir of GB biomarkers. Therefore, EV-based liquid biopsies have been suggested as a promising tool for GB diagnosis and follow up. To identify GB specific proteins, sEVs were isolated from plasma samples of GB patients as well as healthy volunteers using differential ultracentrifugation, and their content was characterised through mass spectrometry. Our data indicate the presence of an inflammatory biomarker signature comprising members of the complement and regulators of inflammation and coagulation including VWF, FCGBP, C3, PROS1, and SERPINA1. Overall, this study is a step forward in the development of a non-invasive liquid biopsy approach for the identification of valuable biomarkers that could significantly improve GB diagnosis and, consequently, patients’ prognosis and quality of life.