Jiang Li, Liwei Qin, Kailong Xu, Jie Liu, Anren Xu, Yunlong Qu, XiaoLu Fu, Peng Wang, Yang Wang
{"title":"Cellular heterogeneity and inflammatory profiles in gliomas: Single-cell transcriptomic insights","authors":"Jiang Li, Liwei Qin, Kailong Xu, Jie Liu, Anren Xu, Yunlong Qu, XiaoLu Fu, Peng Wang, Yang Wang","doi":"10.1002/brx2.70013","DOIUrl":null,"url":null,"abstract":"<p>This study investigates the transcriptional profiles of gliomas across different grades (WHO II-IV) and clinical states (primary vs. recurrent). Utilizing RNA-seq data from public databases (e.g., GEO), we analyzed low-grade gliomas and high-grade gliomas, including oligodendrogliomas, glioblastomas, and other glioma subtypes. Key analyses encompassed differential gene expression, glioma subpopulation characterization (e.g., glioma-associated microglia/macrophages), regulatory network construction (WGCNA and transcription factor activity), and cell state analysis comparing primary and recurrent gliomas. Our findings reveal distinct transcriptional signatures and identify potential biomarkers associated with glioma progression and recurrence.\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70013","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain-X","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/brx2.70013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates the transcriptional profiles of gliomas across different grades (WHO II-IV) and clinical states (primary vs. recurrent). Utilizing RNA-seq data from public databases (e.g., GEO), we analyzed low-grade gliomas and high-grade gliomas, including oligodendrogliomas, glioblastomas, and other glioma subtypes. Key analyses encompassed differential gene expression, glioma subpopulation characterization (e.g., glioma-associated microglia/macrophages), regulatory network construction (WGCNA and transcription factor activity), and cell state analysis comparing primary and recurrent gliomas. Our findings reveal distinct transcriptional signatures and identify potential biomarkers associated with glioma progression and recurrence.