脑转移瘤（BM）是最常见的颅内恶性肿瘤，导致严重的死亡率，肺癌是BM最常见的起源。然而，尚未确定肺腺癌（LUAD）的BM细胞起源和驱动因素。该细胞构成还包括了11个LUAD原发肿瘤（PT）和10个BM样本（GSE131907）的单细胞转录组谱。应用拷贝数变异（CNV）和克隆分析，阐明BM肿瘤的细胞起源。假定时间轨迹分析确定了与脑转移有关的上皮细胞（BMAEC）。通过使用机器学习算法，开发了BM指数，表示散布RNA-seq数据中BMAEC相对丰度的高风险指标。基于肿瘤细胞系的药敏数据，预测有针对性的治疗药物。用单细胞RNA（scRNA）和免疫组织化学及免疫荧光数据研究了PT和BM之间巨噬细胞和T细胞的差异。CNV分析证明BM来源于PT的亚克隆，具有染色体7的增益。然后，我们确定了BMAEC及其生物标志物S100A9。免疫荧光显示BMAEC与转移和预后的相关性，用北京协和医学院附属医院（PUMCH）的配对PT和BM样本进行评估。我们进一步评估了BM指数的临床意义，并确定了七种可能靶向BMAEC的药物。本研究在单个细胞水平阐明了转移性LUAD的可能细胞起源和驱动因素，为早期发现高风险BM的LUAD患者奠定了基础。©作者（2023）。由牛津大学出版社代表神经肿瘤学会出版。

Brain metastasis (BM) is the most common intracranial malignancy causing significant mortality, and lung cancer is the most common origin of BM. However, the cellular origins and drivers of BM from lung adenocarcinoma (LUAD) have yet to be defined.The cellular constitutions were characterized by single-cell transcriptomic profiles of 11 LUAD primary tumor (PT) and 10 BM samples (GSE131907). Copy number variation (CNV) and clonality analysis were applied to illustrate cellular origins of BM tumors. Brain metastasis-associated epithelial cells (BMAECs) were identified by pseudotime trajectory analysis. By using machine-learning algorithms, we developed the BM-index representing the relative abundance of BMAECs in the bulk RNA-seq data, indicating high risk of BM. Therapeutic drugs targeting BMAECs were predicted based on the drug sensitivity data of cancer cell lines.Differences in macrophages and T cells between PTs and BMs were investigated by single-cell RNA (scRNA) and immunohistochemistry and immunofluorescence data. CNV analysis demonstrated BM was derived from subclones of PT with a gain of chromosome 7. We then identified BMAECs and its biomarker, S100A9. Immunofluorescence indicated strong correlations of BMAECs with metastasis and prognosis evaluated by the paired PT and BM samples from Peking Union Medical College Hospital (PUMCH). We further evaluated the clinical significance of BM-index and identified 7 drugs that potentially target BMAECs.This study clarified possible cellular origins and drivers of metastatic LUAD at single cell level, and laid a foundation for early detections of LUAD patients with a high risk of BM.© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.