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一种新的免疫分类揭示了不同的免疫逃逸机制和基因组改变:对肝细胞癌免疫治疗的意义。

A novel immune classification reveals distinct immune escape mechanism and genomic alterations: implications for immunotherapy in hepatocellular carcinoma.

机构信息

Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.

Department of Colorectal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.

出版信息

J Transl Med. 2021 Jan 6;19(1):5. doi: 10.1186/s12967-020-02697-y.

DOI:10.1186/s12967-020-02697-y
PMID:33407585
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7789239/
Abstract

BACKGROUND

The tumor immunological microenvironment (TIME) has a prominent impact on prognosis and immunotherapy. However, the heterogeneous TIME and the mechanisms by which TIME affects immunotherapy have not been elucidated in hepatocellular carcinoma (HCC).

METHODS

A total of 2195 eligible HCC patients from TCGA and GEO database were collected. We comprehensively explored the different heterogeneous TIME phenotypes and its clinical significance. The potential immune escape mechanisms and what genomic alterations may drive the formation of different phenotypes were further investigated.

RESULTS

We identified three phenotypes in HCC: TIME-1, the "immune-deficiency" phenotype, with immune cell depletion and proliferation; TIME-2, the "immune-suppressed" phenotype, with enrichment of immunosuppressive cells; TIME-3, the "immune-activated phenotype", with abundant leukocytes infiltration and immune activation. The prognosis and sensitivity to both sorafenib and immunotherapy differed among the three phenotypes. We also underlined the potential immune escape mechanisms: lack of leukocytes and defective tumor antigen presentation capacity in TIME-1, increased immunosuppressive cells in TIME-2, and rich in immunoinhibitory molecules in TIME-3. The different phenotypes also demonstrated specific genomic events: TIME-1 characterized by TP53, CDKN2A, CTNNB1, AXIN1 and FOXD4 alterations; TIME-2 characterized by significant alteration patterns in the PI3K pathway; TIME-3 characterized by ARID1A mutation. Besides, the TIME index (TI) was proposed to quantify TIME infiltration pattern, and it was a superior prognostic and immunotherapy predictor. A pipeline was developed to classify single patient into one of these three subtypes and calculated the TI.

CONCLUSIONS

We identified three TIME phenotypes with different clinical outcomes, immune escape mechanisms and genomic alterations in HCC, which could present strategies for improving the efficacy of immunotherapy. TI as a novel prognostic and immunotherapeutic signature that could guide personalized immunotherapy and clinical management of HCC.

摘要

背景

肿瘤免疫微环境(TIME)对预后和免疫治疗有显著影响。然而,在肝细胞癌(HCC)中,TIME 的异质性及其影响免疫治疗的机制尚不清楚。

方法

本研究共纳入了来自 TCGA 和 GEO 数据库的 2195 名符合条件的 HCC 患者。我们全面探讨了不同的异质性 TIME 表型及其临床意义。进一步研究了潜在的免疫逃逸机制以及哪些基因组改变可能导致不同表型的形成。

结果

我们在 HCC 中鉴定出三种表型:TIME-1,“免疫缺陷”表型,表现为免疫细胞耗竭和增殖;TIME-2,“免疫抑制”表型,富含免疫抑制细胞;TIME-3,“免疫激活”表型,富含白细胞浸润和免疫激活。三种表型的预后和对索拉非尼和免疫治疗的敏感性不同。我们还强调了潜在的免疫逃逸机制:TIME-1 中缺乏白细胞和肿瘤抗原呈递能力缺陷,TIME-2 中免疫抑制细胞增加,TIME-3 中富含免疫抑制分子。不同的表型还表现出特定的基因组事件:TIME-1 特征为 TP53、CDKN2A、CTNNB1、AXIN1 和 FOXD4 改变;TIME-2 特征为 PI3K 通路的显著改变模式;TIME-3 特征为 ARID1A 突变。此外,提出了 TIME 指数(TI)来量化 TIME 浸润模式,它是一种优越的预后和免疫治疗预测指标。开发了一个管道来将单个患者分类为这三种亚型之一,并计算 TI。

结论

我们在 HCC 中鉴定出三种具有不同临床结局、免疫逃逸机制和基因组改变的 TIME 表型,这为提高免疫治疗的疗效提供了策略。TI 作为一种新的预后和免疫治疗标志物,可指导 HCC 的个体化免疫治疗和临床管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/dc12dc508fa7/12967_2020_2697_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/7d5af418f7ed/12967_2020_2697_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/f0d399a2bd52/12967_2020_2697_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/e8259f18b1c6/12967_2020_2697_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/9300f343fb10/12967_2020_2697_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/ce32fa6cbe7c/12967_2020_2697_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/dc12dc508fa7/12967_2020_2697_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/7d5af418f7ed/12967_2020_2697_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/9356cf2b758d/12967_2020_2697_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/f0d399a2bd52/12967_2020_2697_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/e8259f18b1c6/12967_2020_2697_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/9300f343fb10/12967_2020_2697_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/ce32fa6cbe7c/12967_2020_2697_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a5/7789239/dc12dc508fa7/12967_2020_2697_Fig7_HTML.jpg

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