Identification of hypoxia-immune-related signatures for predicting immune efficacy in triple-negative breast cancer

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-02-28 DOI:10.1515/oncologie-2023-0539

Luping Wang, Haote Han, Jiahui Ma, Yue Feng, Zhuo Han, Vinesh J Maharaj, Jingkui Tian, Wei Zhu, Shouxin Li, Xiying Shao

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Abstract

The therapeutic effect against triple-negative breast cancer (TNBC) varies among individuals. Finding signatures to predict immune efficacy is particularly urgent. Considering the connection between the microenvironment and hypoxia, hypoxia-related signatures could be more effective. Therefore, in this study, we aimed sought to construct a hypoxia-immune-related prediction model for breast cancer and identify therapeutic targets. Immune and hypoxia status in the TNBC microenvironment were investigated using single-sample Gene Set Enrichment Analysis (ssGSEA) and Uniform Manifold Approximation and Projection (UMAP). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were employed to build a prognostic model based on hypoxia-immune-related differentially expressed genes. The Cancer Genome Atlas (TCGA) cohort, real-time quantitative polymerase chain reaction (qRT-PCR), and immunofluorescence staining were utilized to analyze the expression differences. Tumor immune dysfunction and exclusion indexes were used to indicate the effect of immunotherapy. We identified 11 signatures related to hypoxia and immunity. Among these genes, C-X-C motif chemokine ligand (CXCL) 9, 10, and 11 were up-regulated in TNBC tissues compared to normal tissues. Furthermore, CXCL9, 10, 11, and 13 were found to enhance the effect of immunotherapy. These findings suggest the value of the hypoxia-immune-related prognostic model for estimating the risk in patients with TNBC, and CXCL9, 10, 11, and 13 are potential targets to overcome immune resistance in TNBC.

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确定缺氧-免疫相关特征以预测三阴性乳腺癌的免疫效果

针对三阴性乳腺癌（TNBC）的治疗效果因人而异。寻找预测免疫效果的特征尤为迫切。考虑到微环境与缺氧之间的联系，与缺氧相关的特征可能更有效。因此，在本研究中，我们旨在构建乳腺癌缺氧-免疫相关预测模型，并确定治疗靶点。我们使用单样本基因组富集分析（ssGSEA）和统一表层逼近与投影（UMAP）研究了 TNBC 微环境中的免疫和缺氧状态。利用最小绝对收缩和选择算子（LASSO）和多变量 Cox 回归分析，建立了基于缺氧-免疫相关差异表达基因的预后模型。癌症基因组图谱（TCGA）队列、实时定量聚合酶链反应（qRT-PCR）和免疫荧光染色被用来分析表达差异。肿瘤免疫功能障碍和排异指数用于显示免疫疗法的效果。我们发现了11个与缺氧和免疫相关的特征基因。在这些基因中，与正常组织相比，C-X-C motif趋化因子配体（CXCL）9、10和11在TNBC组织中上调。此外，研究还发现CXCL9、10、11和13能增强免疫疗法的效果。这些研究结果表明，缺氧-免疫相关预后模型对估计TNBC患者的风险有一定价值，CXCL9、10、11和13是克服TNBC免疫耐受的潜在靶点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.