Glioblastoma: two immune subtypes under the surface of the cold tumor

Wu Xiong, Cong Li, G. Kong, B. Wan, Siming Wang, Jin Fan
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引用次数: 1

Abstract

Glioblastoma is classified as an immunocompromised tumor. The immune pattern beneath the cold tumor surface, however, has yet to be confirmed. Understanding the immune pattern of glioblastoma will aid in the development of effective treatment strategies. We performed weighted gene co-expression network analysis on all immune-related genes in TCGA-GBM transcriptional data and screened 35 prognosis-related immune genes. Unsupervised consistent clustering of these genes was used to analyze the immunological pattern of GBM. A glioblastoma immune prognostic score was developed by using 13 genes discovered by cox regression methods and verified with the GEO dataset to assess the immune profile, prognosis, and immunotherapy effects in individual patients. Glioblastoma has two immune modalities, immune tolerance and immunodeficiency, with distinct immune microenvironments, tumor-associated macrophages being one of the most promising new therapeutic targets. GIPS is a promising biomarker for assessing immune evasion mechanisms, immunotherapy responses, and prognosis in patients.
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胶质母细胞瘤:冷瘤表面下的两种免疫亚型
胶质母细胞瘤是一种免疫功能低下的肿瘤。然而,冷肿瘤表面下的免疫模式尚未得到证实。了解胶质母细胞瘤的免疫模式将有助于制定有效的治疗策略。我们对TCGA-GBM转录数据中所有免疫相关基因进行加权基因共表达网络分析,筛选出35个预后相关免疫基因。这些基因的无监督一致聚类用于分析GBM的免疫模式。利用cox回归方法发现的13个基因建立了胶质母细胞瘤免疫预后评分,并与GEO数据集进行验证,以评估个体患者的免疫特征、预后和免疫治疗效果。胶质母细胞瘤具有免疫耐受和免疫缺陷两种免疫形态,具有独特的免疫微环境,肿瘤相关巨噬细胞是最有希望的新治疗靶点之一。GIPS是一种很有前景的生物标志物,可用于评估患者的免疫逃避机制、免疫治疗反应和预后。
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