Identification of Tumor Antigens and Immune Landscape in Glioblastoma for mRNA Vaccine Development

Abstract

Background: Clinical benefits from standard therapies against glioblastoma (GBM) are limited in part due to the intrinsic radio- and chemo-resistance. As an essential part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against GBM remains undefined. Therefore, this study aims to find the possible tumor antigens of GBM and identify the suitable population for cancer vaccination through immunophenotyping.Method: The genomic and responding clinical data of 169 GBM samples and five normal brain samples were obtained from The Cancer Genome Atlas (TCGA). The mRNA_seq data of 940 normal brain tissue were downloaded from Genotype-Tissue Expression (GTEx). Potential GBM mRNA antigens were screened out by differential expression, copy number variant (CNV), and mutation analysis. K-M survival and Cox analysis were carried out to investigate the prognostic association of potential tumor antigens. Tumor Immune Estimation Resource (TIMER) was used to explore the association between the antigens and tumor immune infiltrating cells (TIICs). Immunophenotyping of 169 samples was performed through consensus clustering based on the abundance of 22 kinds of immune cells. The characteristics of the tumor immune microenvironment (TIME) in each cluster were explored through single-sample gene set enrichment analysis based on 29 kinds of immune-related hallmarks and pathways. Weighted gene co-expression network analysis (WGCNA) was performed to cluster the genes related to immune subtypes. Finally, pathway enrichment analyses were performed to annotate the potential function of modules screened through WGCNA.Results: Two potential tumor antigens selected were significantly positively associated with the antigen-presenting immune cells (APCs) in GBM. Furthermore, the expression of antigens was verified at the protein level by Immunohistochemistry. Two robust immune subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2), representing immune status “immune inhibition” and “immune inflamed”, respectively, had distinct clinical outcomes in GBM.Conclusion: ARPC1B and HK3 were potential mRNA antigens for developing GBM mRNA vaccination, and the patients in IS2 were considered the most suitable population for vaccination in GBM.

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

“…Immune subtypes can reflect the current tumor microenvironment status of patients and the patient’s current immune status correlates with the effect of immune-related therapy ( Ye et al, 2021a ). Hence, we used immune-related genes in the TCGA-LUAD cohort to identify different patient populations and to assess their suitability for mRNA vaccination.…”

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

“…However, hub genes of immune gene co‐expression modules were not studied. Another study also used similar methods to identify tumor antigens and immune subtypes in GBM, but they did not construct the immune landscape 23 . Compared with these studies, we took a further step in the branch point analysis and identified cellular pathways that might impact on the immune status of glioma patients.…”

“…Unfortunately, there are few studies on mRNA vaccines for glioma, and most of them only focused on finding tumor‐specific antigens and immunizing patients against subtypes 21–23 . Based on these findings, we further investigated mRNA vaccines for glioma.…”

Identification of Candidate Antigens and Immune Subtypes in Colon Cancer for mRNA Vaccine Development

“…Currently, the development of mRNA vaccines is a hotspot in cancer immunotherapy. [33][34][35][36][37][38] We systematically analyzed gene expression and mutation in patients with CC and selected COQ2, BGN, CASP6, and FAP as potential antigens for CC mRNA vaccines. These potential antigen genes were overexpressed in tumor tissue, could encode proteins, were significantly related to prognosis, and were highly associated with APCs.…”