Integration of multiomics analyses reveals unique insights into CD24-mediated immunosuppressive tumor microenvironment of breast cancer

IF 4.8 3区 医学 Q2 CELL BIOLOGY
Haihong Hu, Hongxia Zhu, Wendi Zhan, Bo Hao, Ting Yan, Jingdi Zhang, Siyu Wang, Xuefeng Xu, Taolan Zhang
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Abstract

Background

Tumor immunotherapy brings new light and vitality to breast cancer patients, but low response rate and limitations of therapeutic targets become major obstacles to its clinical application. Recent studies have shown that CD24 is involved in an important process of tumor immune regulation in breast cancer and is a promising target for immunotherapy.

Methods

In this study, singleR was used to annotate each cell subpopulation after t-distributed stochastic neighbor embedding (t-SNE) methods. Pseudo-time trace analysis and cell communication were analyzed by Monocle2 package and CellChat, respectively. A prognostic model based on CD24-related genes was constructed using several machine learning methods. Multiple quantitative immunofluorescence (MQIF) was used to evaluate the spatial relationship between CD24+PANCK+cells and exhausted CD8+T cells.

Results

Based on the scRNA-seq analysis, 1488 CD24-related differential genes were identified, and a risk model consisting of 15 prognostic characteristic genes was constructed by combining the bulk RNA-seq data. Patients were divided into high- and low-risk groups based on the median risk score. Immune landscape analysis showed that the low-risk group showed higher infiltration of immune-promoting cells and stronger immune reactivity. The results of cell communication demonstrated a strong interaction between CD24+epithelial cells and CD8+T cells. Subsequent MQIF demonstrated a strong interaction between CD24+PANCK+ and exhausted CD8+T cells with FOXP3+ in breast cancer. Additionally, CD24+PANCK+ and CD8+FOXP3+T cells were positively associated with lower survival rates.

Conclusion

This study highlights the importance of CD24+breast cancer cells in clinical prognosis and immunosuppressive microenvironment, which may provide a new direction for improving patient outcomes.

Abstract Image

多组学分析的整合揭示了 CD24 介导的乳腺癌免疫抑制性肿瘤微环境的独特见解
背景肿瘤免疫治疗为乳腺癌患者带来了新的光明和活力,但低反应率和治疗靶点的局限性成为其临床应用的主要障碍。最近的研究表明,CD24参与了乳腺癌肿瘤免疫调节的一个重要过程,是一个很有前景的免疫治疗靶点。方法在这项研究中,采用t-分布随机邻域嵌入(t-SNE)方法,用singleR来注释每个细胞亚群。Monocle2软件包和CellChat分别对伪时轨迹分析和细胞通讯进行了分析。利用多种机器学习方法构建了基于CD24相关基因的预后模型。结果基于scRNA-seq分析,确定了1488个CD24相关差异基因,并结合大量RNA-seq数据构建了由15个预后特征基因组成的风险模型。根据中位风险评分将患者分为高危和低危两组。免疫图谱分析表明,低风险组的免疫促进细胞浸润更高,免疫反应性更强。细胞通讯结果表明,CD24+上皮细胞和CD8+T细胞之间有很强的相互作用。随后的 MQIF 显示,乳腺癌中 CD24+PANCK+ 与 FOXP3+ 的 CD8+T 细胞之间存在很强的相互作用。此外,CD24+PANCK+和CD8+FOXP3+T细胞与较低的生存率呈正相关。结论本研究强调了CD24+乳腺癌细胞在临床预后和免疫抑制微环境中的重要性,这可能为改善患者预后提供了一个新的方向。
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来源期刊
Inflammation Research
Inflammation Research 医学-免疫学
CiteScore
9.90
自引率
1.50%
发文量
134
审稿时长
3-8 weeks
期刊介绍: Inflammation Research (IR) publishes peer-reviewed papers on all aspects of inflammation and related fields including histopathology, immunological mechanisms, gene expression, mediators, experimental models, clinical investigations and the effect of drugs. Related fields are broadly defined and include for instance, allergy and asthma, shock, pain, joint damage, skin disease as well as clinical trials of relevant drugs.
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