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单细胞 RNA 测序和空间转录组揭示了肺癌脑转移的潜在分子机制。

Single-cell RNA sequencing and spatial transcriptome reveal potential molecular mechanisms of lung cancer brain metastasis.

机构信息

Department of Statistics, School of Science, Wuhan University of Technology, 122 Luoshi Road, Wuhan 430070, China.

Department of Statistics, School of Science, Wuhan University of Technology, 122 Luoshi Road, Wuhan 430070, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China.

出版信息

Int Immunopharmacol. 2024 Oct 25;140:112804. doi: 10.1016/j.intimp.2024.112804. Epub 2024 Jul 29.

Abstract

BACKGROUND

Lung cancer is a highly aggressive and prevalent disease worldwide. By the time it is first diagnosed, distant metastases have usually already occurred. Among them, the prognosis of patients with brain metastasis from lung cancer is very poor. Therefore, it is particularly important to identify the evolutionary status of tumor cells during lung cancer brain metastases and discover the underlying mechanisms of lung cancer brain metastases.

METHODS

In this study, we analysed three types of data: single-cell RNA sequencing, bulk RNA sequencing, and spatial transcriptome. Firstly, we identified early metastatic epithelial cell clusters (EMEC) using CNV and trajectory analysis in scRNA-seq data. Secondly, we integrated scRNA-seq and spatial transcriptome data with the help of MIA (Multimodal intersection analysis) to explore the biological characteristics of EMEC. Finally, we used bulk RNA-seq data to validate the molecular characteristics of EMEC.

RESULT

A total of 55,763 single cells were obtained and divided into 9 cell types. In brain metastasis, we found a significantly higher proportion of epithelial cells. In addition, we identified a specific subpopulation of epithelial cells, which was named as "early metastatic epithelial cell clusters (EMEC)". It is enriched in oxidative phosphorylation, coagulation, complement. Moreover, we also found that EMEC underwent cellular communication with other immune cells through ligand-receptor pairs such as MIF-(CD74 + CXCR4) and MIF-(CD74 + CD44). Next, we validated that EMEC were associated with poor clinical prognosis using three independent external datasets. Finally, spatial transcriptome analysis revealed specificity in the spatial distribution of EMEC, which shifted from the peripheral regions to the central regions of the tumour as the depth of tumor invasion progressed.

CONCLUSION

This study reveals the potential molecular mechanisms of lung cancer brain metastasis from both single-cell and spatial transcriptomic perspectives, providing biological insights and clinical reference value for detecting patients suffering from lung cancer brain metastasis.

摘要

背景

肺癌是一种在全球范围内具有高度侵袭性和普遍性的疾病。在首次诊断时,通常已经发生了远处转移。其中,肺癌脑转移患者的预后非常差。因此,识别肺癌脑转移过程中肿瘤细胞的进化状态并发现肺癌脑转移的潜在机制尤为重要。

方法

本研究分析了三种类型的数据:单细胞 RNA 测序、批量 RNA 测序和空间转录组。首先,我们使用 CNV 和轨迹分析在 scRNA-seq 数据中鉴定早期转移上皮细胞簇(EMEC)。其次,我们借助 MIA(多模态交集分析)整合 scRNA-seq 和空间转录组数据,以探索 EMEC 的生物学特征。最后,我们使用批量 RNA-seq 数据验证 EMEC 的分子特征。

结果

共获得 55763 个单细胞,分为 9 种细胞类型。在脑转移中,我们发现上皮细胞的比例明显更高。此外,我们鉴定出一种特定的上皮细胞亚群,命名为“早期转移上皮细胞簇(EMEC)”。它富含氧化磷酸化、凝血、补体。此外,我们还发现 EMEC 通过 MIF-(CD74+CXCR4) 和 MIF-(CD74+CD44) 等配体-受体对与其他免疫细胞进行细胞间通讯。接下来,我们使用三个独立的外部数据集验证了 EMEC 与不良临床预后相关。最后,空间转录组分析揭示了 EMEC 特异性的空间分布,随着肿瘤侵袭深度的增加,它们从肿瘤的外周区域转移到中央区域。

结论

本研究从单细胞和空间转录组学的角度揭示了肺癌脑转移的潜在分子机制,为检测肺癌脑转移患者提供了生物学见解和临床参考价值。

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