• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

胶质母细胞瘤 TCGA 间充质和 IGS23 肿瘤可通过免疫组化鉴定,具有免疫表型,表明可能受益于免疫治疗。

Glioblastoma TCGA Mesenchymal and IGS 23 Tumors are Identifiable by IHC and have an Immune-phenotype Indicating a Potential Benefit from Immunotherapy.

机构信息

Pathology Department, Hospital Universitari Germans Trias i Pujol, Badalona, Spain.

Pathology Department, Neuropathology Unit, Hospital del Mar, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain.

出版信息

Clin Cancer Res. 2020 Dec 15;26(24):6600-6609. doi: 10.1158/1078-0432.CCR-20-2171. Epub 2020 Sep 30.

DOI:10.1158/1078-0432.CCR-20-2171
PMID:32998960
Abstract

PURPOSE

Molecular subtype classifications in glioblastoma may detect therapy sensitivities. IHC would potentially allow the identification of molecular subtypes in routine clinical practice.

EXPERIMENTAL DESIGN

Formalin-fixed, paraffin-embedded tumor samples of 124 uniformly treated, newly diagnosed patients with glioblastoma were submitted to RNA sequencing, IHC, and immune-phenotyping to identify differences in molecular subtypes associated with treatment sensitivities.

RESULTS

We detected high molecular and IHC overlapping of the The Cancer Genome Atlas (TCGA) mesenchymal subtype with instrinsic glioma subtypes (IGS) cluster 23 and of the TCGA classical subtype with IGS cluster 18. IHC patterns, gene fusion profiles, and immune-phenotypes varied across subtypes. IHC revealed that the TCGA classical subtype was identified by high expression of EGFR and low expression of PTEN, while the mesenchymal subtype was identified by low expression of SOX2 and high expression of two antibodies, SHC1 and TCIRG1, selected on the basis of RNA differential transcriptomic expression. The proneural subtype was identified by frequent positive IDH1 expression and high Olig2 and Ki67 expression. Immune-phenotyping showed that mesenchymal and IGS 23 tumors exhibited a higher positive effector cell score, a higher negative suppressor cell score, and lower levels of immune checkpoint molecules. The cell-type deconvolution analysis revealed that these tumors are highly enriched in M2 macrophages, resting memory CD4 T cells, and activated dendritic cells, indicating that they may be ideal candidates for immunotherapy, especially with anti-M2 and/or dendritic cell vaccination.

CONCLUSIONS

There is a subset of tumors, frequently classified as mesenchymal or IGS cluster 23, that may be identified with IHC and could well be optimal candidates for immunotherapy.

摘要

目的

胶质母细胞瘤的分子亚型分类可能检测到治疗敏感性。免疫组化(IHC)可能允许在常规临床实践中识别分子亚型。

实验设计

对 124 例经统一治疗的新诊断胶质母细胞瘤患者的福尔马林固定、石蜡包埋肿瘤样本进行 RNA 测序、免疫组化和免疫表型分析,以鉴定与治疗敏感性相关的分子亚型差异。

结果

我们检测到癌症基因组图谱(TCGA)间充质亚型与内在神经胶质瘤亚型(IGS)簇 23 以及 TCGA 经典亚型与 IGS 簇 18 的高度分子和 IHC 重叠。免疫组化模式、基因融合谱和免疫表型在不同亚型之间存在差异。免疫组化显示,TCGA 经典亚型的特征是 EGFR 高表达和 PTEN 低表达,而间充质亚型的特征是 SOX2 低表达和两种抗体 SHC1 和 TCIRG1 的高表达,这两种抗体是基于 RNA 差异转录组表达选择的。前体细胞亚型的特征是 IDH1 表达频繁阳性和 Olig2 和 Ki67 表达高。免疫表型显示,间充质和 IGS 23 肿瘤表现出更高的阳性效应细胞评分、更高的阴性抑制细胞评分和更低水平的免疫检查点分子。细胞类型去卷积分析显示,这些肿瘤富含 M2 巨噬细胞、静止记忆 CD4 T 细胞和激活树突状细胞,表明它们可能是免疫治疗的理想候选者,尤其是使用抗 M2 和/或树突状细胞疫苗。

结论

存在一个亚组肿瘤,通常被归类为间充质或 IGS 簇 23,可能通过 IHC 识别,并且可能是免疫治疗的最佳候选者。

相似文献

1
Glioblastoma TCGA Mesenchymal and IGS 23 Tumors are Identifiable by IHC and have an Immune-phenotype Indicating a Potential Benefit from Immunotherapy.胶质母细胞瘤 TCGA 间充质和 IGS23 肿瘤可通过免疫组化鉴定,具有免疫表型,表明可能受益于免疫治疗。
Clin Cancer Res. 2020 Dec 15;26(24):6600-6609. doi: 10.1158/1078-0432.CCR-20-2171. Epub 2020 Sep 30.
2
RNA sequencing and Immunohistochemistry Reveal as a Stronger Marker of Survival than Molecular Subtypes in G-CIMP-negative Glioblastoma.RNA 测序和免疫组织化学显示,在 G-CIMP 阴性的胶质母细胞瘤中, 比分子亚型更能强烈预测患者的生存情况。
Clin Cancer Res. 2021 Jan 15;27(2):645-655. doi: 10.1158/1078-0432.CCR-20-2141. Epub 2020 Oct 26.
3
A simplified integrated molecular and immunohistochemistry-based algorithm allows high accuracy prediction of glioblastoma transcriptional subtypes.一种简化的整合分子和免疫组织化学的算法可以高度准确地预测胶质母细胞瘤的转录亚型。
Lab Invest. 2020 Oct;100(10):1330-1344. doi: 10.1038/s41374-020-0437-0. Epub 2020 May 13.
4
Immune heterogeneity of glioblastoma subtypes: extrapolation from the cancer genome atlas.胶质母细胞瘤亚型的免疫异质性:从癌症基因组图谱推断。
Cancer Immunol Res. 2013 Aug;1(2):112-22. doi: 10.1158/2326-6066.CIR-13-0028.
5
Unique genome-wide map of TCF4 and STAT3 targets using ChIP-seq reveals their association with new molecular subtypes of glioblastoma.使用 ChIP-seq 绘制 TCF4 和 STAT3 靶点的全基因组独特图谱,揭示它们与胶质母细胞瘤新的分子亚型的关联。
Neuro Oncol. 2013 Mar;15(3):279-89. doi: 10.1093/neuonc/nos306. Epub 2013 Jan 7.
6
Genomics and proteomics to determine novel molecular subtypes and predict the response to immunotherapy and the effect of bevacizumab in glioblastoma.基因组学和蛋白质组学确定新型分子亚型,并预测免疫治疗的反应和贝伐珠单抗在胶质母细胞瘤中的疗效。
Sci Rep. 2024 Jul 31;14(1):17630. doi: 10.1038/s41598-024-68648-5.
7
Bioinformatic analyses reveal a distinct Notch activation induced by STAT3 phosphorylation in the mesenchymal subtype of glioblastoma.生物信息学分析揭示了胶质母细胞瘤间质亚型中由 STAT3 磷酸化诱导的 Notch 激活。
J Neurosurg. 2017 Jan;126(1):249-259. doi: 10.3171/2015.11.JNS15432. Epub 2016 Mar 11.
8
MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma.磁共振成像(MRI)定位活检显示胶质母细胞瘤边缘在分子和细胞组成上存在亚型特异性差异。
Proc Natl Acad Sci U S A. 2014 Aug 26;111(34):12550-5. doi: 10.1073/pnas.1405839111. Epub 2014 Aug 11.
9
Identification of Tumor Antigens and Immune Subtypes of Glioblastoma for mRNA Vaccine Development.鉴定脑胶质瘤的肿瘤抗原和免疫亚型,用于 mRNA 疫苗的开发。
Front Immunol. 2022 Feb 2;13:773264. doi: 10.3389/fimmu.2022.773264. eCollection 2022.
10
Molecular Subgroups of Glioblastoma- an Assessment by Immunohistochemical Markers.胶质母细胞瘤的分子亚群——通过免疫组化标志物进行评估
Pathol Oncol Res. 2019 Jan;25(1):21-31. doi: 10.1007/s12253-017-0311-6. Epub 2017 Sep 26.

引用本文的文献

1
Multikinase Treatment of Glioblastoma: Evaluating the Rationale for Regorafenib.胶质母细胞瘤的多激酶治疗:评估瑞戈非尼的理论依据。
Cancers (Basel). 2025 Jan 23;17(3):375. doi: 10.3390/cancers17030375.
2
The C250T Mutation of Might Grant a Better Prognosis to Glioblastoma by Exerting Less Biological Effect on Telomeres and Chromosomes Than the C228T Mutation.与C228T突变相比,C250T突变对端粒和染色体产生的生物学效应较小,可能会使胶质母细胞瘤的预后更好。
Cancers (Basel). 2024 Feb 9;16(4):735. doi: 10.3390/cancers16040735.
3
Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme.
免疫相关长链非编码RNA特征和放射组学特征预测多形性胶质母细胞瘤的预后和免疫微环境。
J Transl Med. 2024 Jan 26;22(1):107. doi: 10.1186/s12967-023-04823-y.
4
The clinical value of proneural, classical and mesenchymal protein signatures in WHO 2021 adult-type diffuse lower-grade gliomas.2021 年 WHO 成人型弥漫性低级别胶质瘤中前神经元、经典和间质蛋白特征的临床价值。
PLoS One. 2023 May 16;18(5):e0285732. doi: 10.1371/journal.pone.0285732. eCollection 2023.
5
Gal-1 Expression Analysis in the GLIOCAT Multicenter Study: Role as a Prognostic Factor and an Immune-Suppressive Biomarker.GLIOCAT 多中心研究中的 Gal-1 表达分析:作为预后因素和免疫抑制生物标志物的作用。
Cells. 2023 Mar 8;12(6):843. doi: 10.3390/cells12060843.
6
In silico validation of RNA-Seq results can identify gene fusions with oncogenic potential in glioblastoma.通过计算验证 RNA-Seq 结果可以识别出胶质母细胞瘤中具有致癌潜力的基因融合。
Sci Rep. 2022 Aug 24;12(1):14439. doi: 10.1038/s41598-022-18608-8.
7
Pan-Cancer Study of SHC-Adaptor Protein 1 (SHC1) as a Diagnostic, Prognostic and Immunological Biomarker in Human Cancer.SHC衔接蛋白1(SHC1)作为人类癌症诊断、预后和免疫生物标志物的泛癌研究
Front Genet. 2022 May 2;13:817118. doi: 10.3389/fgene.2022.817118. eCollection 2022.
8
Glioblastoma: Relationship between Metabolism and Immunosuppressive Microenvironment.胶质母细胞瘤:代谢与免疫抑制微环境的关系。
Cells. 2021 Dec 14;10(12):3529. doi: 10.3390/cells10123529.
9
Systematic Analyses of a Chemokine Family-Based Risk Model Predicting Clinical Outcome and Immunotherapy Response in Lung Adenocarcinoma.基于趋化因子家族的风险模型系统分析预测肺腺癌临床结局和免疫治疗反应。
Cell Transplant. 2021 Jan-Dec;30:9636897211055046. doi: 10.1177/09636897211055046.