Abstract
Background
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.
Methods
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.
Results
Differences in macrophage s 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.
Conclusions
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.
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