As an important part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against lower grade glioma (LGG) remains undefined. Immunophenotyping of tumors is an essential tool to evaluate the immune function of patients with immunodeficiency or autoimmunity. Therefore, this study aims to find the potential tumor antigen of LGG and identify the suitable population for cancer vaccination based on the immune landscape. The genomic and clinical data of 529 patients with LGG were obtained from TCGA, the mRNA_seq data of normal brain tissue were downloaded from GTEx. Differential expression gene and mutation analysis were performed to screen out potential antigens, K-M curves were carried out to investigate the correlation between the level of potential antigens and OS and DFS of patients. TIMER dataset was used to explore the correlation between genes and immune infiltrating cells. Immunophenotyping of 529 tumor samples was based on the single-sample gene sets enrichment analysis. Cibersort and Estimate algorithm were used to explore the tumor immune microenvironment characteristics in each immune subtype. Weighted gene co-expression network analysis (WGCNA) clustered immune-related genes and screened the hub genes, and pathway enrichment analyses were performed on the hub modules related to immune subtype in the WGCNA. Selecting for the mutated, up-regulated, prognosis- and immune-related genes, four potential tumor antigens were identified in LGG. They were also significantly positively associated with the antigen-presenting immune cells (APCs). Three robust immune subtypes, IS1, IS2 and IS3, represented immune status "desert", "immune inhibition", and "inflamed" respectively, which might serve as a predictive parameter. Subsequently, clinicopathological features, including the codeletion status of 1p19q, IDH mutation status, tumor mutation burden, tumor stemness, etc., were significantly different among subtypes. FCGBP, FLNC, TLR7, and CSF2RA were potential antigens for developing cancer vaccination, and the patients in IS3 were considered the most suitable for vaccination in LGG.

中文翻译：

---

鉴定低级别胶质瘤中的肿瘤抗原和免疫亚型用于 mRNA 疫苗开发

作为肿瘤辅助免疫治疗的重要组成部分，治疗性肿瘤疫苗已对多种实体瘤有效，但其对低级别胶质瘤（LGG）的疗效仍不清楚。肿瘤的免疫表型分析是评估免疫缺陷或自身免疫患者免疫功能的重要工具。因此，本研究旨在寻找LGG的潜在肿瘤抗原，并根据免疫状况确定适合癌症疫苗接种的人群。从TCGA获得529例LGG患者的基因组和临床数据，从GTEx下载正常脑组织的mRNA_seq数据。通过差异表达基因和突变分析筛选出潜在抗原，并通过KM曲线探讨潜在抗原水平与患者OS和DFS的相关性。TIMER数据集用于探索基因与免疫浸润细胞之间的相关性。529 个肿瘤样本的免疫表型分析基于单样本基因集富集分析。采用Cibersort和Estimate算法探索各免疫亚型的肿瘤免疫微环境特征。加权基因共表达网络分析（WGCNA）对免疫相关基因进行聚类并筛选枢纽基因，并对WGCNA中与免疫亚型相关的枢纽模块进行通路富集分析。通过筛选突变、上调、预后和免疫相关基因，在 LGG 中鉴定出四种潜在的肿瘤抗原。它们还与抗原呈递免疫细胞（APC）呈显着正相关。三种稳健的免疫亚型 IS1、IS2 和 IS3 分别代表免疫状态“沙漠”、“免疫抑制”和“发炎”，这可以作为预测参数。随后，临床病理特征，包括1p19q的共缺失状态、IDH突变状态、肿瘤突变负荷、肿瘤干性等，在亚型之间存在显着差异。FCGBP、FLNC、TLR7和CSF2RA是开发癌症疫苗接种的潜在抗原，IS3中的患者被认为最适合LGG中的疫苗接种。