Han Myung-Hoon, Min Kyueng-Whan, Noh Yung-Kyun, Kim Jae Min, Cheong Jin Hwan, Ryu Je Il, Won Yu Deok, Koh Seong-Ho, Park Young Mi
Department of Neurosurgery, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, South Korea.
Department of Pathology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, South Korea.
Front Oncol. 2022 Aug 10;12:965638. doi: 10.3389/fonc.2022.965638. eCollection 2022.
Glioblastoma multiforme (GBM) is the most malignant brain tumor with an extremely poor prognosis. The Cancer Genome Atlas (TCGA) database has been used to confirm the roles played by 10 canonical oncogenic signaling pathways in various cancers. The purpose of this study was to evaluate the expression of genes in these 10 canonical oncogenic signaling pathways, which are significantly related to mortality and disease progression in GBM patients. Clinicopathological information and mRNA expression data of 525 patients with GBM were obtained from TCGA database. Gene sets related to the 10 oncogenic signaling pathways were investigated Gene Set Enrichment Analysis. Multivariate Cox regression analysis was performed for all the genes significantly associated with mortality and disease progression for each oncogenic signaling pathway in GBM patients. We found 12 independent genes from the 10 oncogenic signaling pathways that were significantly related to mortality and disease progression in GBM patients. Considering the roles of these 12 significant genes in cancer, we suggest possible mechanisms affecting the prognosis of GBM. We also observed that the expression of 6 of the genes significantly associated with a poor prognosis of GBM, showed negative correlations with CD8+ T-cells in GBM tissue. Using a large-scale open database, we identified 12 genes belonging to 10 well-known oncogenic canonical pathways, which were significantly associated with mortality and disease progression in patients with GBM. We believe that our findings will contribute to a better understanding of the mechanisms underlying the pathophysiology of GBM in the future.
多形性胶质母细胞瘤(GBM)是最恶性的脑肿瘤,预后极差。癌症基因组图谱(TCGA)数据库已被用于确认10条经典致癌信号通路在各种癌症中所起的作用。本研究的目的是评估这10条经典致癌信号通路中与GBM患者死亡率和疾病进展显著相关的基因的表达情况。从TCGA数据库中获取了525例GBM患者的临床病理信息和mRNA表达数据。通过基因集富集分析研究了与10条致癌信号通路相关的基因集。对GBM患者中每条致癌信号通路中与死亡率和疾病进展显著相关的所有基因进行多变量Cox回归分析。我们从10条致癌信号通路中发现了12个独立基因,它们与GBM患者的死亡率和疾病进展显著相关。考虑到这12个重要基因在癌症中的作用,我们提出了影响GBM预后的可能机制。我们还观察到,与GBM预后不良显著相关的6个基因的表达在GBM组织中与CD8 + T细胞呈负相关。利用大规模开放数据库,我们鉴定出了属于10条著名致癌经典通路的12个基因,它们与GBM患者的死亡率和疾病进展显著相关。我们相信,我们的研究结果将有助于未来更好地理解GBM病理生理学的潜在机制。