Department of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
School of Pharmacy, Hengyang Medical College, University of South China, Hengyang, 421001, Hunan, China.
Inflamm Res. 2024 Jun;73(6):1047-1068. doi: 10.1007/s00011-024-01882-9. Epub 2024 Apr 15.
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.
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 CD24PANCKcells and exhausted CD8T cells.
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 CD24epithelial cells and CD8T cells. Subsequent MQIF demonstrated a strong interaction between CD24PANCK and exhausted CD8T cells with FOXP3 in breast cancer. Additionally, CD24PANCK and CD8FOXP3T cells were positively associated with lower survival rates.
This study highlights the importance of CD24breast cancer cells in clinical prognosis and immunosuppressive microenvironment, which may provide a new direction for improving patient outcomes.
肿瘤免疫疗法为乳腺癌患者带来了新的希望和活力，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 参与了乳腺癌中肿瘤免疫调节的重要过程，是免疫治疗的一个有前途的靶点。
本研究采用 t 分布随机邻域嵌入（t-SNE）方法对单细胞 RNA 测序（scRNA-seq）数据进行降维处理后，使用单细胞分析工具包 singleR 对每个细胞亚群进行注释。通过 Monocle2 包和 CellChat 分别对拟时轨迹分析和细胞通讯进行分析。采用多种机器学习方法构建基于 CD24 相关基因的预后模型。使用多重定量免疫荧光（MQIF）评估 CD24PANCK 细胞与耗竭型 CD8T 细胞之间的空间关系。
基于 scRNA-seq 分析，鉴定出 1488 个与 CD24 相关的差异基因，并结合 bulk 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低风险组。免疫景观分析显示，低风险组中促进免疫的细胞浸润程度更高，免疫反应更强。细胞通讯的结果表明，CD24 上皮细胞与 CD8T 细胞之间存在强烈的相互作用。随后的 MQIF 显示，在乳腺癌中，CD24PANCK 与耗竭型 CD8FOXP3T 细胞与 FOXP3 之间存在强烈的相互作用。此外，CD24PANCK 和 CD8FOXP3T 细胞与较低的生存率呈正相关。
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新的方向。
