China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Department of Neurosurgery, China-Japan Friendship Hospital, Beijing, China.
CNS Neurosci Ther. 2024 Nov;30(11):e70083. doi: 10.1111/cns.70083.
Numerous diseases are associated with the interplay of mitochondrial and macrophage polarization. However, the correlation of mitochondria-related genes (MRGs) and macrophage polarization-related genes (MPRGs) with the prognosis of glioma remains unclear. This study aimed to examine this relationship based on bioinformatic analysis.
Glioma-related datasets (TCGA-GBMLGG, mRNA-seq-325, mRNA-seq-693, GSE16011, GSE4290, and GSE138794) were included in this study. The intersection genes were obtained by overlapping differentially expressed genes (DEGs) from differential expression analysis in GSE16011, key module genes from WGCNA, and MRGs. Subsequently, the intersection genes were further screened to obtain prognostic genes. Following this, a risk model was developed and verified. After that, independent prognostic factors were identified, followed by the construction of a nomogram and subsequent evaluation of its predictive ability. Furthermore, immune microenvironment analysis and expression validation were implemented. The GSE138794 dataset was utilized to evaluate the expression of prognostic genes at a cellular level, followed by conducting an analysis on cell-to-cell communication. Finally, the results were validated in different datasets and tissue samples from patients.
ECI2, MCCC2, OXCT1, SUCLG2, and CPT2 were identified as prognostic genes for glioma. The risk model constructed based on these genes in TCGA-GBMLGG demonstrated certain accuracy in predicting the occurrence of glioma. Additionally, the nomogram constructed based on risk score and grade exhibited strong performance in predicting patient survival. Significant differences were observed in the proportion of 27 immune cell types (e.g., activated B cells and macrophages) and the expression of 32 immune checkpoints (e.g., CD70, CD200, and CD48) between the two risk groups. Single-cell RNA sequencing showed that CPT2, ECI2, and SUCLG2 were highly expressed in oligodendrocytes, neural progenitor cells, and BMDMs, respectively. The results of cell-cell communication analysis revealed that both oligodendrocytes and BMDMs exhibited a substantial number of interactions with high strength.
This study revealed five genes associated with the prognosis of glioma (ECI2, MCCC2, OXCT1, SUCLG2, and CPT2), providing novel insights into individualized treatment and prognosis.
许多疾病都与线粒体和巨噬细胞极化的相互作用有关。然而，线粒体相关基因（MRGs）和巨噬细胞极化相关基因（MPRGs）与胶质瘤的预后之间的相关性尚不清楚。本研究旨在通过生物信息学分析来研究这种相关性。
本研究纳入了胶质瘤相关数据集（TCGA-GBMLGG、mRNA-seq-325、mRNA-seq-693、GSE16011、GSE4290 和 GSE138794）。通过重叠 GSE16011 中的差异表达基因（DEGs）、WGCNA 的关键模块基因和 MRGs，获得交集基因。然后，进一步筛选交集基因，获得预后基因。之后，建立风险模型并进行验证。然后，确定独立的预后因素，构建列线图并评估其预测能力。此外，进行免疫微环境分析和表达验证。利用 GSE138794 数据集在细胞水平上评估预后基因的表达，然后进行细胞间通讯分析。最后，在不同数据集和患者组织样本中进行验证。
确定 ECI2、MCCC2、OXCT1、SUCLG2 和 CPT2 为胶质瘤的预后基因。基于 TCGA-GBMLGG 中这些基因构建的风险模型在预测胶质瘤的发生方面具有一定的准确性。此外，基于风险评分和分级构建的列线图在预测患者生存方面表现出较强的性能。在两个风险组之间，观察到 27 种免疫细胞类型（如激活的 B 细胞和巨噬细胞）的比例和 32 种免疫检查点（如 CD70、CD200 和 CD48）的表达存在显著差异。单细胞 RNA 测序显示，CPT2、ECI2 和 SUCLG2 在少突胶质细胞、神经祖细胞和 BMDM 中分别高表达。细胞间通讯分析的结果表明，少突胶质细胞和 BMDM 之间都存在大量的高强度相互作用。
本研究揭示了与胶质瘤预后相关的五个基因（ECI2、MCCC2、OXCT1、SUCLG2 和 CPT2），为个体化治疗和预后提供了新的见解。
