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肿瘤微环境与弥漫性神经胶质瘤的临床和遗传特征相关,并可预测总体生存率。

Tumor microenvironment is associated with clinical and genetic properties of diffuse gliomas and predicts overall survival.

机构信息

Department of Neurosurgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.

Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, 100070, China.

出版信息

Cancer Immunol Immunother. 2022 Apr;71(4):953-966. doi: 10.1007/s00262-021-03058-4. Epub 2021 Sep 17.

Abstract

Tumor microenvironment (TME) is a complex and dynamic evolving environment which facilitates tumor proliferation and progression. We aimed at investigating the characteristics of tumor microenvironment and its prognostic value in gliomas. Transcriptome data of 702 glioma samples from The Cancer Genome Atlas were included as training dataset, while 325 samples from Chinese Glioma Genome Atlas database and 268 samples from GSE16011 database were used to validate. We found that the infiltration of stromal and immune cell varied in gliomas of different grades and pathological types, and was associated with poor prognosis. Based on the gene expression profile, we constructed a TME-related signature (TMERS), which was closely related to clinical features and genomic variation of gliomas. In TMERS-high group, specific gene mutations and increased copy number alternations were observed. Kaplan-Meier survival and Cox regression analysis showed that TMERS was an independent prognostic indicator. Then we developed a nomogram prognostic model to predict 1-year, 3-year and 5-year survival of patients. Functional analysis confirmed that TMERS could reflect the status of glioma microenvironment, and immunological analysis showed that macrophages were significantly enriched in the TMERS-high group. We established a novel TME-related signature for predicting prognosis and provided new insights into immunotherapy.

摘要

肿瘤微环境(TME)是一个复杂且动态演变的环境,有助于肿瘤的增殖和进展。我们旨在研究胶质瘤中肿瘤微环境的特征及其预后价值。纳入了 702 例来自癌症基因组图谱的胶质瘤样本的转录组数据作为训练数据集,同时使用来自中国胶质瘤基因组图谱数据库的 325 个样本和 GSE16011 数据库的 268 个样本进行验证。我们发现,不同级别和病理类型的胶质瘤中基质和免疫细胞的浸润程度不同,与预后不良有关。基于基因表达谱,我们构建了一个与肿瘤微环境相关的特征(TMERS),它与胶质瘤的临床特征和基因组变异密切相关。在 TMERS 高分组中,观察到特定的基因突变和拷贝数变异增加。Kaplan-Meier 生存和 Cox 回归分析表明,TMERS 是一个独立的预后指标。然后,我们开发了一个列线图预后模型来预测患者的 1 年、3 年和 5 年生存率。功能分析证实 TMERS 可以反映胶质瘤微环境的状态,免疫分析表明 TMERS 高分组中巨噬细胞明显富集。我们建立了一个新的与肿瘤微环境相关的特征,用于预测预后,并为免疫治疗提供了新的见解。

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