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泛癌种保守的微环境亚型可预测免疫治疗的反应。

Conserved pan-cancer microenvironment subtypes predict response to immunotherapy.

机构信息

BostonGene, Waltham, MA 02453, USA.

BostonGene, Waltham, MA 02453, USA.

出版信息

Cancer Cell. 2021 Jun 14;39(6):845-865.e7. doi: 10.1016/j.ccell.2021.04.014. Epub 2021 May 20.

Abstract

The clinical use of molecular targeted therapy is rapidly evolving but has primarily focused on genomic alterations. Transcriptomic analysis offers an opportunity to dissect the complexity of tumors, including the tumor microenvironment (TME), a crucial mediator of cancer progression and therapeutic outcome. TME classification by transcriptomic analysis of >10,000 cancer patients identifies four distinct TME subtypes conserved across 20 different cancers. The TME subtypes correlate with patient response to immunotherapy in multiple cancers, with patients possessing immune-favorable TME subtypes benefiting the most from immunotherapy. Thus, the TME subtypes act as a generalized immunotherapy biomarker across many cancer types due to the inclusion of malignant and microenvironment components. A visual tool integrating transcriptomic and genomic data provides a global tumor portrait, describing the tumor framework, mutational load, immune composition, anti-tumor immunity, and immunosuppressive escape mechanisms. Integrative analyses plus visualization may aid in biomarker discovery and the personalization of therapeutic regimens.

摘要

分子靶向治疗的临床应用正在迅速发展,但主要集中在基因组改变上。转录组分析提供了一个剖析肿瘤复杂性的机会,包括肿瘤微环境(TME),它是癌症进展和治疗结果的关键介质。对超过 10000 名癌症患者的转录组分析进行 TME 分类,确定了 20 种不同癌症中存在的四种不同的 TME 亚型。TME 亚型与多种癌症中免疫治疗的患者反应相关,具有免疫有利 TME 亚型的患者从免疫治疗中获益最多。因此,由于包含恶性和微环境成分,TME 亚型成为许多癌症类型的通用免疫治疗生物标志物。整合转录组和基因组数据的可视化工具提供了一个全局肿瘤图像,描述了肿瘤框架、突变负荷、免疫组成、抗肿瘤免疫和免疫抑制逃逸机制。综合分析加可视化可能有助于发现生物标志物和治疗方案的个性化。

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