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A dissected LMO2 functional analysis and clinical relevance in brain gliomas

Brain glioma is one of the cancer types with worst prognosis, and LMO2 has been reported to play oncogenic functions in brain gliomas. Herein, analysis of datasets from The Cancer Genome Atlas (TCGA) indicated that higher LMO2 level in patient samples indicated worse prognosis in lower grade gliomas...

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Detalles Bibliográficos
Autores principales: Yuan, Mei, Yu, Yanhong, Meng, Yingying, Wu, Huancheng, Sun, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9761381/
https://www.ncbi.nlm.nih.gov/pubmed/36545566
http://dx.doi.org/10.1016/j.bbrep.2022.101406
Descripción
Sumario:Brain glioma is one of the cancer types with worst prognosis, and LMO2 has been reported to play oncogenic functions in brain gliomas. Herein, analysis of datasets from The Cancer Genome Atlas (TCGA) indicated that higher LMO2 level in patient samples indicated worse prognosis in lower grade gliomas (LGG) but not glioblastoma multiforme (GBM). Further, in tumor tissues consisting of a variety of cell types, LMO2 level indicated intratumoral endothelium and pattern recognition receptor (PRR) response in both LGGs and GBMs, and additionally indicated cytotoxic T-lymphocyte, M2 macrophage infiltration and fibroblast specifically in LGGs. Moreover, only in LGGs these aspects were significantly associated with patient survival, in either risky or protective manner, and these dissected associations can give a better prediction on patient prognosis than LMO2 alone. This study not only provided more detailed understandings of LMO2 functional representatives in brain gliomas but also demonstrated that dealing with certain gene (LMO2 in this study) in transcriptome data with the Weighted Gene Co-Expression Network Analysis (WGCNA) method was a robust strategy for dissecting exact and reasonable gene functions/associations in a complicated tumor environment.