Bulk and single-cell transcriptome revealed the metabolic heterogeneity in human glioma

作者：Yong Xiao, Mengjie Zhao, Ran Wang, Liang Liu, Chong Xiang, Taiping Li, Chunfa Qian, Hong Xiao, Hongyi Liu, Yuanjie Zou, Xianglong Tang, Kun Yang · 发表于：Heliyon · 年份：2024 · DOI：10.1016/j.heliyon.2024.e41241 · 被引用次数：5 · 研究领域：Glioma Diagnosis and Treatment、Single-cell and spatial transcriptomics、Ferroptosis and cancer prognosis

Background Emerging perspectives on tumor metabolism reveal its heterogeneity, a characteristic yet to be fully explored in gliomas. To advance therapies targeting metabolic processes, it is crucial to uncover metabolic differences and identify distinct metabolic subtypes. Therefore, we aimed to develop a classification system for gliomas based on the enrichment levels of four key metabolic pathways: glutaminolysis, glycolysis, the pentose phosphate pathway, and fatty acid oxidation. Methods Energy-related features of glioma were characterized through integrative analyses of multiple datasets, including bulk, single-cell, and spatial transcriptome profiling. The glioma energy metabolic subtypes were constructed using the R package ConsensusClusterPlus. Kaplan–Meier analysis was conducted to compare clinical outcomes between different metabolic groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to elucidate the biological functions of genes of interest. Cell-cell communication analysis was performed at single-cell resolution using the R package CellChat and at spatial resolution using the standard stLearn pipeline. Results Glioma samples were stratified into two prognostic subtypes. Group 1, enriched in the glutaminolysis pathway, had better clinical outcomes. In contrast, Group 2 exhibited high activities in glycolysis, the pentose phosphate pathway, and fatty acid oxidation, correlating with decreased survival time. Group 1 s...