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高表观遗传风险评分塑造乳腺癌的非炎症性肿瘤微环境。

A High Epigenetic Risk Score Shapes the Non-Inflamed Tumor Microenvironment in Breast Cancer.

作者信息

Zhang Dong, Wang Yingnan, Yang Qifeng

机构信息

Department of Breast Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.

Department of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, China.

出版信息

Front Mol Biosci. 2021 Jul 26;8:675198. doi: 10.3389/fmolb.2021.675198. eCollection 2021.

Abstract

Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC). Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled ( = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options. A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy. Our work highlights the complementary roles of 10CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

摘要

通过异常DNA甲基化导致的表观遗传失调已逐渐被认为是预测肿瘤预后和对治疗靶点反应的有效标志。然而,关于描述肿瘤发生的可靠DNA甲基化生物标志物在乳腺癌(BC)中的预后和治疗潜力仍有待全面探索。对从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)整合的全基因组甲基化数据集进行了分析(n = 1,268)。在质量控制、严格筛选和降维后,采用三阶段选择程序(发现、训练和外部验证)从超过30万个CpG位点中筛选出突出的生物标志物并建立稳健的风险评分。此外,基因集富集分析引导我们系统地将这种表观遗传风险评分与免疫特征相关联,包括免疫调节剂、抗癌免疫循环、免疫检查点、肿瘤浸润免疫细胞以及调节BC肿瘤微环境(TME)内成分时的一系列特征。进行多组学数据分析以解读低风险和高风险患者的特定基因组改变。此外,我们还分析了风险评分在预测对几种治疗方案反应中的作用。建立了一个基于10个CpG的预后特征,该特征可以显著且独立地将BC患者分为不同的预后,并进行了充分验证。我们假设该特征基于以下证据设计了BC中的非炎症性TME:得出的风险评分与肿瘤相关浸润免疫细胞、抗癌免疫循环、免疫检查点、免疫细胞溶解活性、T细胞炎症评分、免疫表型评分以及绝大多数免疫调节剂呈负相关。所鉴定的高风险患者的特征是免疫抑制致癌途径上调、TP53突变和拷贝数负担较高,但对癌症免疫疗法和化疗的反应较低。我们的工作突出了基于10个CpG的特征在估计BC患者总生存中的互补作用,为目前研究免疫疗法失败事件提供了新的思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62b4/8350480/c9a90b05eee1/fmolb-08-675198-g001.jpg

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