Tumor antigens and immune subtypes of glioblastoma: the fundamentals of mRNA vaccine and individualized immunotherapy development

Abstract

Purpose Glioblastoma (GBM) is the most common primary brain tumor in adults and is notorious for its lethality. Given its limited therapeutic measures and high heterogeneity, the development of new individualized therapies is important. mRNA vaccines have exhibited promising performance in a variety of solid tumors, those designed for glioblastoma (GBM) need further development. The aim of this study is to explore tumor antigens for the development of mRNA vaccines against GBM and to identify potential immune subtypes of GBM to identify the patients suitable for different immunotherapies. Methods RNA-seq data and the clinical information of 143 GBM patients was extracted from the TCGA database; microarray data and the clinical information of 181 GBM patients was obtained from the REMBRANDT cohort. A GBM immunotherapy cohort of 17 patients was obtained from a previous literature. GEPIA2, cBioPortal, and TIMER2 were used to identify the potential tumor antigens. Immune subtypes and gene modules were identified using consensus clustering; immune landscape was constructed using graph-learning-based dimensionality reduction analysis. Results Nine potential tumor antigens associated with poor prognosis and infiltration of antigen-presenting cells were identified in GBM: ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1. Four robust immune subtypes and seven functional gene modules were identified and validated in an independent cohort. Immune subtypes had different cellular and molecular characteristics, with IS1, an immune cold phenotype; IS2, an immune hot and immunosuppressive phenotype; IS3, a relatively immune cold phenotype, second only to IS1; IS4, having a moderate tumor immune microenvironment. Immune landscape revealed the immune distribution of the GBM patients. Additionally, the potential value of immune subtypes for individualized immunotherapy was demonstrated in a GBM immunotherapy cohort. Conclusions ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1 are the candidate tumor antigens for mRNA vaccine development in GBM, and IS1 GBM patients are best suited for mRNA vaccination, IS2 patients are best suited for immune checkpoint inhibitor. This study provides a theoretical framework for GBM mRNA vaccine development and individualized immunotherapy strategies.

Proneural – Mesenchymal antagonism dominates the patterns of phenotypic heterogeneity in Glioblastoma

“…Our meta-analysis suggests that mesenchymal subtype is relatively enriched in glycolytic traits, a behaviour validated in metabolic differences between proneural and mesenchymal tumor-initiating cells (Mao et al, 2013; Seliger et al, 2022). The observed association of PD-L1 with mesenchymal subgroup in GBM (Nduom et al, 2015; Ricklefs et al, 2018; Wu et al, 2022) also reinforces our analysis; functionally, PD-L1 can trigger more aggressive GBM behaviour through the downstream Ras/Erk signaling. The independent association of both PD-L1 and glycolysis with worse patient outcomes in GBM (Nduom et al, 2015; Z.…”

Liquid biopsy-based identification of prognostic and immunotherapeutically relevant gene signatures in lower grade glioma

“…Based on the gene expression profiles of the identified 43 RRGs in 54 PBMC samples, robust LGG PBMC clusters were identified using unsupervised clustering based on the partition around medoids (PAM) algorithm. As we described previously, a total of 1000 bootstraps were executed, and each bootstrap resampled 80% of samples [31,32]. The maximum number of clusters was 10, and K values were evaluated using a consensus cumulative distribution function and consensus heatmap [33].…”

mRNA—From COVID-19 Treatment to Cancer Immunotherapy

“…Bladder cancer AP2S1, P3H4, and RAC3 [174] Melanoma PTPRC, SIGLEC10, CARD11, LILRB1, and ADAMDEC1 [175] Colorectal, NSCLC, and pancreatic cancers KRAS [176] Esophageal squamous cell carcinoma (ESCC) NLRC5, FCRL4, TMEM229B, and LCP2 [177] Soft tissue sarcoma HLTF, ITGA10, PLCG1, and TTC3 [178] Glioblastoma ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1 [179] Glioma NAT1, FRRS1, GTF2H2C, BRCA2, GRAP, NR5A2, ABCB4, ZNF90, ERCC6L, and ZNF813 [180] Malignant mesothelioma FAM134B, ALDH3A2, SAV1, RORC, and FN1 [181] Stomach adenocarcinoma ADAMTS18, COL10A1, PPEF1, and STRA6 [182] Mesothelioma AUNIP, FANCI, LASP1, PSMD8, and XPO5 [183] Dosing of mRNA can be achieved by titrating up or down, depending on the need, weight, and disease state of the patient. The duration of action is intrinsically limited by mRNA degradation, reducing the likelihood of irreversible side effects, and enabling the treatment of acute indications [184,185].…”