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Updated: Jun 4, 2026

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
Published on: August 16, 2020
Single-cell data analysis of lung cancer brain metastasis reveals SEC61G serves as a potential risk indicator
Yunjing Li1, Yuanyuan Zhang2, Wenxin Tian3
1Department of Thoracic Surgery, The First Medical Center of PLA General Hospital, Beijing, 100853, China. tgzy6668@163.com.
Abstract:
Lung adenocarcinoma is a highly malignant and life-threatening disease, with brain metastases representing a major cause of mortality in patients with lung cancer. Although extensive research has focused on interpreting single-cell data from lung cancer brain metastases, most studies emphasize the immune microenvironment, leaving the molecular mechanisms and pathways involving epithelial cells under explored. In this study, we investigated epithelial cells using single-cell data derived from lung cancer brain metastases (comprising six lung cancer and six lung-to-brain metastasis samples) and identified a significant enrichment of the protein-folding pathway in brain metastases, with SEC61G emerging as a particularly prominent contributor. Subsequent in silico replication in clinical samples and public cohort confirmed that SEC61G can serve as a biomarker for brain metastases in lung cancer. These results provide novel insights into the molecular mechanisms driving brain metastases in lung cancer and underscore the potential of SEC61G as both a therapeutic target and a diagnostic marker. Our findings advance understanding of the metastatic process in lung adenocarcinoma and provide a foundation for developing targeted therapies aimed at improving patient outcomes.

