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基于肿瘤微环境状态的脑干胶质瘤分类

Classification of Brainstem Gliomas Based on Tumor Microenvironment Status.

作者信息

Xiao Xiong, Li Xiaoou, Wang Yi, Pan Changcun, Zhang Peng, Gu Guocan, Li Tian, Jiang Zhuang, Zhang Yang, Zhang Liwei

机构信息

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.

China National Clinical Research Center for Neurological Diseases, Beijing 100070, China.

出版信息

Cancers (Basel). 2023 Aug 23;15(17):4224. doi: 10.3390/cancers15174224.

DOI:10.3390/cancers15174224
PMID:37686499
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10487167/
Abstract

The inter-tumor heterogeneity of the tumor microenvironment (TME) and how it correlates with clinical profiles and biological characteristics in brainstem gliomas (BSGs) remain unknown, dampening the development of novel therapeutics against BSGs. The TME status was determined with a list of pan-cancer conserved gene expression signatures using a single-sample gene set enrichment analysis (ssGSEA) and was subsequently clustered via consensus clustering. BSGs exhibited a high inter-tumor TME heterogeneity and were classified into four clusters: "immune-enriched, fibrotic", "immune-enriched, non-fibrotic", "fibrotic", and "depleted". The "fibrotic" cluster had a higher proportion of diffuse intrinsic pontine gliomas ( = 0.041), and "PA-like" tumors were more likely to be "immune-enriched, fibrotic" ( = 0.044). The four TME clusters exhibited distinct overall survival ( < 0.001) and independently impacted BSG outcomes. A four-gene panel as well as a radiomics approach were constructed to identify the TME clusters and achieved high accuracy for determining the classification. Together, BSGs exhibited high inter-tumor heterogeneity in the TME and were classified into four clusters with distinct clinical outcomes and tumor biological properties. The TME classification was accurately identified using a four-gene panel that can potentially be examined with the immunohistochemical method and a non-invasive radiomics method, facilitating its clinical application.

摘要

肿瘤微环境(TME)的肿瘤间异质性及其与脑干胶质瘤(BSG)临床特征和生物学特性的相关性尚不清楚,这阻碍了针对BSG的新型治疗方法的开发。使用单样本基因集富集分析(ssGSEA),通过一组泛癌保守基因表达特征来确定TME状态,随后通过一致性聚类进行分类。BSG表现出较高的肿瘤间TME异质性,并被分为四个簇:“免疫富集、纤维化”、“免疫富集、非纤维化”、“纤维化”和“耗竭”。“纤维化”簇中弥漫性固有桥脑胶质瘤的比例较高( = 0.041),“PA样”肿瘤更可能是“免疫富集、纤维化”( = 0.044)。这四个TME簇表现出不同的总生存期( < 0.001),并独立影响BSG的预后。构建了一个四基因panel以及一种放射组学方法来识别TME簇,并在确定分类方面取得了高精度。总之,BSG在TME中表现出较高的肿瘤间异质性,并被分为四个具有不同临床结果和肿瘤生物学特性的簇。使用一个四基因panel准确识别了TME分类,该panel可能可以通过免疫组织化学方法和非侵入性放射组学方法进行检测,便于其临床应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/d08431f90c04/cancers-15-04224-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/0e2e5add3485/cancers-15-04224-g001a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/83828a43933d/cancers-15-04224-g002a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/879fc3bc3343/cancers-15-04224-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/ae3da5bc4a29/cancers-15-04224-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/1d219278e349/cancers-15-04224-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/d08431f90c04/cancers-15-04224-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/0e2e5add3485/cancers-15-04224-g001a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/83828a43933d/cancers-15-04224-g002a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/879fc3bc3343/cancers-15-04224-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/ae3da5bc4a29/cancers-15-04224-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/1d219278e349/cancers-15-04224-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b88/10487167/d08431f90c04/cancers-15-04224-g006.jpg

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本文引用的文献

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A multimodal imaging-based classification for pediatric diffuse intrinsic pontine gliomas.基于多模态影像的儿童弥漫性内在脑桥胶质瘤分类。
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