Introduction
Gliomas were the most common human primary central nervous tumor, and lower grade gliomas (LGG), including World Health Organization (WHO) II, III grade, compose the largest subgroup in all gliomas [
1,
2]. At present, the primary available treatment for LGG is still surgical resection. However, due to the silent clinical characteristics of LGG, most patients miss the suitable opportunity to for surgery [
3]. Besides, the combination of radiotherapy and temozolomide chemotherapy is the first-line adjuvant strategy that could increase the patients'' survival time by 2.5 months [
4] but still with a high risk of acquired primary resistance [
3]. Hence, novel strategies are needed to improve the therapeutic condition of LGG. Nowadays, as an important part of tumor immunotherapy, therapeutic tumor vaccines were recently reported to be effective against multiple solid cancers and have attracted extensive attention [
5], while its efficacy against LGG remains undefined. Moreover, identifying a growing number of potentially unique immunoreactive tumor-associated antigens expressed by human gliomas makes cancer vaccines an exciting strategy [
6].
Tumor antigen with or without adjuvant is the main component of a typical cancer vaccine, assisting immune cells in recognizing and eliminating cancer cells [
7]. The advantages were minimal non-specific effect, non-toxic, long-term immune memory and wide treatment window for tumor vaccine treatment which could overcome the limits of drug resistance, high costs, limited therapeutic effects and other possible adverse reactions associated with traditional immunotherapy and chemotherapy [
8]. The form of antigens for tumor vaccine could be peptide, tumor cell, dendritic cell, DNA, and RNA type [
9]. However, when applied in clinical treatment, there were several prominent advantages for mRNA type compared with the first four types. First of all, the mRNA sequence can be easily modified to encode the protein we need [
10]. Second, genetic analysis of cancer was required in the traditional peptide vaccine which needs a relatively high cost, while mRNA vaccine does not need [
11]. Third, to ensure safety, the half-life of mRNA could be regulated through RNA sequence modification or a delivery system [
12]. Fourth, preventing gene deletion and insertional mutagenesis, mRNA has no risk of irrelevant sequence exclusion and gene integration which often happen to DNA type [
13]. In addition, increasing its in-vivo immunogenicity, the adjuvant properties of mRNA vaccine could induce an intense and persistent immune response [
14]. As a result, mRNA vaccines are highly feasible for targeting tumor-specific antigens and promising immunotherapy strategies. Several studies have proved the effectiveness of the possibility of mRNA tumor vaccines in clinical trials, Sebastian et al. [
15] reported that the RNActive® vaccine CV9201 could improve the specific immune response rate and survival time of a part of patients with non-small cell lung cancer. Similarly, the study of Kübler et al. [
16] showed that CV9103 can maintain well immunogenicity and tolerance in a large part of prostate cancer patients, enhancing the immune response of patients and prolong the overall survival time ultimately. However, for patients with LGG, no specific mRNA vaccine against tumor has been developed and no study have identified suitable patients for cancer vaccination based on immunophenotyping.
In our study, four candidates identified for developing mRNA vaccines were associated with clinical outcomes and positively correlated to the infiltration of antigen-presenting cells (APCs). Based on the clustering of immune-related differently expressed genes (IRDEGs), three robust immune subtypes were identified based on the features of TIME in each subtype. We then screened three functional modules closely related to subtypes through WGCNA. These findings provided a theoretical basis for developing mRNA cancer vaccine against LGG, described an immune landscape and identified candidate population for mRNA cancer vaccination.
Methods
Data acquisition
The normalized gene expression and corresponding clinical follow-up data of 529 LGG patients were downloaded from The Cancer Genome Atlas (TCGA). Furthermore, the mRNA data of 940 normal brain tissue samples were obtained from Genotype-Tissue Expression (GTEx) project. Then the mRNA data in TCGA and GTEx were merged and normalized as one cohort by R package "limma".
The data of simple nucleotide variation, including somatic mutation according to the VarScan2 [
17] platform, were acquired from TCGA.
Patient samples
The Institutional Ethics Committee approved this study of the Faculty of Medicine at our hospital. Informed consent was obtained from all patients whose tissues were used. In total, 6 control samples from patients with cerebral hemorrhage and 24 lower-grade glioma samples (WHO grade II-III) were collected during May 2019 and June 2021. All patients were not treated with chemotherapy or radiotherapy before surgery.
Data processing
R package "maftools" was used to identify the mutant genes in LGG and the corresponding chromosome position of genes. Over-expressed genes in the tumor were identified in the merged cohort by "limma" package based on the criterion: the ABS of logFC > 1 and p value < 0.05. By "estimate" algorithm, the immune infiltration level of each tumor sample was calculated and quantified as stromal score and immune score. According to the median value of stromal and immune scores, respectively, the samples were divided into high and low score groups, genes differentially expressed in two groups were screened by "limma" package and defined as immune-related differentially expressed genes (IRDEGs). The intersection of mutant genes, overexpressed genes, and IRDEGs was considered the potential mRNA cancer antigens in LGG.
Prognostic analysis of potential antigens
Kaplan–Meier (K–M) survival analysis was performed to explore the relationship between potential antigens’ expression level and overall survival (OS) rate in patients. Then based on the Gene Expression Profiling Interactive Analysis (GEPIA) database, the relationship between genes and disease-free survival (DFS) of LGG patients was investigated, log-rank P-value < 0.05 was considered significant.
TIMER analysis
Tumor Immune Estimation Resource [
18] (TIMER) was used to analyze and visualize the association between the abundance of tumor immune infiltrating cells (TIICs) and prognosis-related antigens. Considering purity adjustment, the relationship between potential LGG antigens and antigen-presenting cells (APCs), including B cells, macrophages, and dendritic cells, was investigated through spearman's correlation analysis. P-value < 0.05 was significant.
Quantitative real-time PCR
The extraction of potential LGG antigens' RNA from tissues and cells was carried out by Trizol reagent (Invitrogen, Carlsbad, CA, USA). The PrimeScript RT Reagent Kit (RR047A, Takara, Japan) was used to synthesize cDNA. We used SYBR Premix Ex Taq II (RR820A, Takara, Kusatsu, Japan) and Bio-Rad CFX Manager 2.1 real-time PCR Systems (Bio-Rad, Hercules, CA, USA) to detect mRNA levels following the specifications provided by the manufacturers. Adopt the relative Ct method to compare the data of the experimental group and the control group, and GADPH was set as an internal control.
Development and validation of the immune subtypes
The 1113 IRDEGs were clustered based on their expression profiles, and a consistency matrix was constructed to identify corresponding immune subtypes. The partition around medoids algorithm using the "1-Pearson correlation" distance metric was applied, and 500 bootstraps were performed, each involving 80% patients in the discovery cohort. Cluster sets varied from 2 to 9, and the optimal partition was defined by evaluating the consensus matrix and the consensus cumulative distribution function. Besides, the correlation between immune subtypes and clinical features, molecular subtypes, tumor mutation burden (TMB), and tumor stemness indices were explored to describe the clinical and molecular pathological features among immune subtypes we defined.
The ssGSEA of immune subtypes
In the TCGA dataset, 29 immune signatures[
19] representing diverse immune cell types, functions, and pathways were quantified for their enrichment degrees within respective LGG samples using single sample gene set enrichment analysis (ssGSEA)[
20]. The ssGSEA score of each LGG sample was calculated and then compared among different immune subtypes.
TIICs profiles in different subtypes
Through "cibersort" [
21] algorithm, the abundance of TIICs in each LGG sample were evaluated and then compared among subgroups, exploring the features of tumor immune microenvironment (TIME) in each immune subtype.
Differential expression analysis of ICPs and ICDs
Immune checkpoints (ICPs)- and immunogenic cell death modulators (ICDs)-related genes were obtained from the previous studies[
7,
22]. Then the expression level of ICPs and ICDs were compared among different immune subtypes by Pairwise t-tests[
23].
Weight gene co-expression network analysis
The R package "WGCNA" was used to identify the co-expression modules of the IRDEGs. Highly variable genes of HPC population were detected by FindVariableGenes in Seurat. Gene modules were examined by dynamic hybrid cut. The relationship between module genes and immune subtypes was investigated (P-value < 0.05 were considered significant). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to annotate the functions of the modules correlated to immune subtypes.
Discussion
Immunotherapy is a rapidly growing field, and tumor vaccines are a promising immunotherapeutic treatment modality in cancer research [
28]. The ultimate goal of immunotherapy in cancer is eradicating tumors through vaccine strategies [
29]. Through inducing anti-tumor immunity, a peptide vaccine targeting mutant IDH1 had been proved to be a feasible new strategy for the treatment of IDH1 (R132H) mutant gliomas in recent days [
30,
31]. In this study, we identified four potential tumor antigens correlated to the immune infiltration level and screened out from mutant and up-regulated genes in LGG. Subsequently, the antigens’ association with prognosis and APCs were explored to assess their effectiveness and feasibility as antigens for mRNA tumor vaccines. Moreover, through the construction of robust immune subtypes, the characteristics of TIME and other clinical molecular characteristics of each subtype were investigated, and the population suitable for vaccination was identified on the basis of the immune landscape in three immune subtypes. Finally, the potential mechanisms and hub regulatory genes related to the immune subtype were then explored.
Tumor associated antigens (TAAs) are significantly over-expressed in cancer compared to normal cells [
32]. Nowadays, advances in next-generation sequencing (NGS), bioinformatics and peptidomics have enabled the identification of non-synonymous mutations and other alterations of the cancer cell genome (intron retention, indels, frameshifts, etc.), emerging as neo-antigens and resulting in the development of personalized vaccines [
33]. Neo-antigens could be recognized as non-self-epitopes and thereby enhance the immune reactivity against tumor cells [
34].FCGBP (Fc fragment of IgG binding protein), a key regulator of TGF-1-induced epithelial-mesenchymal transition (EMT), was reported to be associated with the progression and prognosis of gallbladder cancer [
35]. It reported that FLNC (filamin C) mutations cause myofibrillar myopathies [
36], and it was also associated with central nervous system disease such as Friedreich's ataxia, fragile X syndrome, and spinocerebellar atrophy [
37]. TLR7 (toll-like receptor 7) agonist MEDI9197 could modulate the tumor microenvironment leading to enhanced activity when combined with other immunotherapies [
38]. Furthermore, study reported that CSF2RA (colony-stimulating factor 2 receptor) produced in the tumor was an essential factor affecting the progression and metastasis of breast cancer [
39]. In this study, FCGBP, FLNC, TLR7, and CSF2RA were also correlated to the prognosis of LGG patients, which had not been reported before. Therefore, we considered these biomarkers with mutation possibility and up-regulated expression in LGG as potential TAAs, which provided a selection of tumor vaccine antigens and molecular targets of gliomas.
TIME plays a vital role in assisting anticancer vaccines to elicit therapeutically relevant tumor-specific immune responses [
40]. The subtyping criteria developed for solid tumors could be well applied for the characterization of their immune microenvironment [
41], Thorsson et al. identified six immune subtypes on the basis of a pan-cancer study in TCGA and revealed novel insights into the mechanisms and immunotherapy strategy across cancer types [
42]. However, due to the existence of the blood–brain barrier and the specificity of TIME of gliomas, the immunotyping of pan-cancer maybe not suitable enough to distinguish the subtypes of glioma and provide a guideline for immunotherapy strategies. Based on the expression patterns of genes related to immune infiltration level in LGG, we divided glioma immune subtypes into IS1, IS2, and IS3, and defined them as immune desert type, immunosuppressive type, and immune promoting type, respectively. The three immune subtypes had distinct molecular, cellular, and clinical characteristics. In addition, we found that the patients in IS3 showed a better prognosis than other subtypes, which suggested immunotyping was a prognostic indicator in LGG. Base on the stemness of the tumor (mRNAsi), immunophenotyping could also be used to evaluate the ability of tumor progression and metastasis. As samples in IS1 were with higher value of mRNAsi, tumors of IS1 may be more likely to progress and metastasize. In addition to prognostic prediction, immunophenotyping could also predict the response and efficacy of mRNA vaccine therapy. IS1 with a poor correlation to immune infiltration level accounts for the vast majority of LGG, which indicated patients in IS1 receiving tumor vaccine treatment or immune checkpoint inhibitors (ICIs) therapy may not receive a better response or curative effect. Therefore, improving the infiltration level of tumor-killing immune cells is the precondition for ICIs of patients in IS1. Chemokines are necessary in transporting peripheral immune cells across the blood–brain barrier and activating these immune cells [
43]. It may be a strategy to emphasize the critical role of chemokines in immune response for patients in IS1. Instead, patients in IS3 may be the most suitable candidates for tumor vaccination for its pro-inflammatory characteristics making mRNA cancer vaccine treatment more responsive and effective. However, as a subtype with moderate infiltration level and apparent immunosuppressive TIME, IS2 may lead to the difficulty in activating the activity of tumor-killing immune cells which played an anti-tumor role after receiving the mRNA tumor vaccine. Fortunately, the expression levels of PDCD1 (PD-1), CD274 (PD-L1), and CTLA4, the vital immune checkpoints in glioma, were significantly higher in IS2 than other subtypes, which indicated that patients receiving ICIs therapies might achieve a better curative effect [
44]. As a result, combined with ICIs and mRNA tumor vaccine cold be an effective treatment strategy for patients with LGG in IS2.
Biomarkers of immune subtypes are the hub of linkage mechanism research, population screening, and typing specificity [
45]. WGCNA revealed three key modules closely associated with each immune subtype and were of great significance to explore the potential biological mechanism of subtypes. KEGG and GO analysis showed that the red, brown, and blue modules had apparent differences in biology and involved pathways, which further suggested that the classification based on this study was of a high degree of discrimination.
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