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鉴定和验证与失巢凋亡相关的基因特征,以预测胶质母细胞瘤的临床特征、干性、IDH 突变和免疫滤过。

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma.

机构信息

Department of Neurosurgery, The Second Hospital of Shandong University, Jinan, China.

Department of Neurosurgery, Dongying City District People's Hospital, Dongying, China.

出版信息

Front Immunol. 2022 Aug 25;13:939523. doi: 10.3389/fimmu.2022.939523. eCollection 2022.

Abstract

BACKGROUND

Glioblastoma (GBM) is the most prominent and aggressive primary brain tumor in adults. Anoikis is a specific form of programmed cell death that plays a key role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance.

METHODS

The non-negative matrix factorization algorithm was used for effective dimension reduction for integrated datasets. Differences in the tumor microenvironment (TME), stemness indices, and clinical characteristics between the two clusters were analyzed. Difference analysis, weighted gene coexpression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator regression were leveraged to screen prognosis-related genes and construct a risk score model. Immunohistochemistry was performed to evaluate the expression of representative genes in clinical specimens. The relationship between the risk score and the TME, stemness, clinical traits, and immunotherapy response was assessed in GBM and pancancer.

RESULTS

Two definite clusters were identified on the basis of anoikis-related gene expression. Patients with GBM assigned to C1 were characterized by shortened overall survival, higher suppressive immune infiltration levels, and lower stemness indices. We further constructed a risk scoring model to quantify the regulatory patterns of anoikis-related genes. The higher risk score group was characterized by a poor prognosis, the infiltration of suppressive immune cells and a differentiated phenotype, whereas the lower risk score group exhibited the opposite effects. In addition, patients in the lower risk score group exhibited a higher frequency of isocitrate dehydrogenase (IDH) mutations and a more sensitive response to immunotherapy. Drug sensitivity analysis was performed, revealing that the higher risk group may benefit more from drugs targeting the PI3K/mTOR signaling pathway.

CONCLUSION

We revealed potential relationships between anoikis-related genes and clinical features, TME, stemness, IDH mutation, and immunotherapy and elucidated their therapeutic value.

摘要

背景

胶质母细胞瘤(GBM)是成人中最显著和侵袭性最强的原发性脑肿瘤。细胞凋亡是一种特定的程序性细胞死亡形式,在肿瘤侵袭和转移中起着关键作用。抗凋亡因子的存在与肿瘤的侵袭性和耐药性有关。

方法

采用非负矩阵分解算法对整合数据集进行有效降维。分析两个聚类之间肿瘤微环境(TME)、干性指数和临床特征的差异。采用差异分析、加权基因共表达网络分析(WGCNA)、单变量 Cox 回归和最小绝对收缩和选择算子回归筛选预后相关基因并构建风险评分模型。免疫组织化学法评估临床标本中代表性基因的表达。在 GBM 和泛癌中评估风险评分与 TME、干性、临床特征和免疫治疗反应的关系。

结果

根据细胞凋亡相关基因的表达,确定了两个明确的聚类。被分配到 C1 的 GBM 患者总生存期较短,抑制性免疫浸润水平较高,干性指数较低。我们进一步构建了一个风险评分模型来量化细胞凋亡相关基因的调控模式。风险评分较高的组具有较差的预后、抑制性免疫细胞的浸润和分化的表型,而风险评分较低的组则表现出相反的效果。此外,风险评分较低组的患者 IDH 突变频率更高,对免疫治疗的反应更敏感。进行药物敏感性分析发现,较高风险组可能更受益于针对 PI3K/mTOR 信号通路的药物。

结论

我们揭示了细胞凋亡相关基因与临床特征、TME、干性、IDH 突变和免疫治疗之间的潜在关系,并阐明了它们的治疗价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7b9/9452727/cfd568cf9471/fimmu-13-939523-g001.jpg

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