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<p>Gliomas, including both glioblastoma multiforme (GBM) and lower-grade glioma (LGG), present a substantial challenge in neuro-oncology because of genetic heterogeneity and unsatisfactory prognosis. This study aimed to conduct a comprehensive multi-omics analysis of gliomas using various bioinformatics approaches to identify potential therapeutic targets and prognostic markers. A comprehensive analysis was conducted on 1327 sequencing data samples alongside their relevant clinical information sourced from The Cancer Genome Atlas (TCGA) pertaining to glioblastoma (GBM), low-grade glioma (LGG), the Chinese Glioma Genome Atlas (CCGA) and University of California Santa Cruz Xena (UCSC Xena) datasets. These tools were employed for gene expression profiling, survival analysis, and cell communication mapping. Spatial transcriptomics revealed the localization of mesenchymal (MES)-like malignant tumors, and drug sensitivity analysis was performed to evaluate responses to quinpirole and meropenem. Additionally, the Tumor Immune Dysfunction and Exclusion (TIDE) framework was utilized to gauge the responsiveness to immunotherapy. The MES-like malignant and monocyte/macrophage (mono/macro) cell subsets showed high hallmark scores, playing key roles in the tumor microenvironment. MES-like malignant marker gene scores correlated with overall survival across datasets, whereas mono/macro marker gene scores were significant in the TCGA-LGG and CCGA datasets. Key interactions between these cell types were found, especially with <i>CD14-ITGB2, LGALS1-CD69</i>, and <i>APOE-TREM2</i>. The mono/macro cell subset demonstrated better immune therapy responsiveness, as indicated by lower TIDE scores. Spatial transcriptomics revealed that MES-like malignant tumors are predominantly localized in four distinct regions, with the marker genes <i>CHI3L1</i> and <i>ADM</i> confirming these locations. Drug sensitivity analysis revealed differential responses of the MES-like malignant cell subset to quinpirole and meropenem. Our results offer fresh perspectives on the differential roles of MES-like malignant and monocyte/macrophage cell subsets in tumor progression and immune modulation, providing novel insights into glioma biology.</p>

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A spatial transcriptomics study of MES-like and mono/macro cells in gliomas

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月13日

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  • Boyan Zhao,
  • Jianing Wu,
  • Tiehui Zhang,
  • Mingyang Han,
  • Cheng Zhang,
  • Xuan Rong,
  • Ruotian Zhang,
  • Xin Chen,
  • Fei Peng,
  • Jin Jin,
  • Shiya Liu,
  • Xingli Dong,
  • Shiguang Zhao

摘要

Gliomas, including both glioblastoma multiforme (GBM) and lower-grade glioma (LGG), present a substantial challenge in neuro-oncology because of genetic heterogeneity and unsatisfactory prognosis. This study aimed to conduct a comprehensive multi-omics analysis of gliomas using various bioinformatics approaches to identify potential therapeutic targets and prognostic markers. A comprehensive analysis was conducted on 1327 sequencing data samples alongside their relevant clinical information sourced from The Cancer Genome Atlas (TCGA) pertaining to glioblastoma (GBM), low-grade glioma (LGG), the Chinese Glioma Genome Atlas (CCGA) and University of California Santa Cruz Xena (UCSC Xena) datasets. These tools were employed for gene expression profiling, survival analysis, and cell communication mapping. Spatial transcriptomics revealed the localization of mesenchymal (MES)-like malignant tumors, and drug sensitivity analysis was performed to evaluate responses to quinpirole and meropenem. Additionally, the Tumor Immune Dysfunction and Exclusion (TIDE) framework was utilized to gauge the responsiveness to immunotherapy. The MES-like malignant and monocyte/macrophage (mono/macro) cell subsets showed high hallmark scores, playing key roles in the tumor microenvironment. MES-like malignant marker gene scores correlated with overall survival across datasets, whereas mono/macro marker gene scores were significant in the TCGA-LGG and CCGA datasets. Key interactions between these cell types were found, especially with CD14-ITGB2, LGALS1-CD69, and APOE-TREM2. The mono/macro cell subset demonstrated better immune therapy responsiveness, as indicated by lower TIDE scores. Spatial transcriptomics revealed that MES-like malignant tumors are predominantly localized in four distinct regions, with the marker genes CHI3L1 and ADM confirming these locations. Drug sensitivity analysis revealed differential responses of the MES-like malignant cell subset to quinpirole and meropenem. Our results offer fresh perspectives on the differential roles of MES-like malignant and monocyte/macrophage cell subsets in tumor progression and immune modulation, providing novel insights into glioma biology.