Exploración de exosomas de plasma de pacientes como biomarcadores para predecir metástasis cerebral de cáncer de pulmón
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Updated: Jan 7, 2026
Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
Published on: May 27, 2016
Lingyun Ye1, Xinnan Hu1, Shen Chen1
1Department of Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Background:
Many studies have found that exosomes have numerous advantages in the early diagnosis of tumors. We detected and analyzed plasma exosomes from lung cancer patients to identify potential biomarkers that could predict brain metastasis.
Method:
The total RNA of plasma exosomes of advanced lung cancer patients was extracted and sequenced. The BLAST software was used to align the predicted target gene sequence against the GO and KEGG databases, thereby acquiring annotation details for the target genes. The selected exosomal miRNAs and short-chain fatty acids were subjected to diagnostic performance validation analysis.
Results:
Exosomal miR-223-3p, miR-27a-3p, and miR-27b-3p were significantly increased in the plasma exosomes of lung cancer patients with brain metastasis. The concentrations of isobutyric acid (IBA), valeric acid (VA), isovaleric acid (IVA), and acetic acid (AA) were markedly elevated in the plasma exosomes of lung cancer patients with brain metastasis. Spearman correlation analysis revealed that both miR-27a-3p and miR-27b-3p had significant associations with IVA and VA. A multi-biomarker model combining the selected exosomal miRNAs with metabolic molecules could improve the diagnostic performance with an AUC of 0.927.
Conclusion:
Plasma exosomal miR-223-3p, miR-27a-3p, miR-27b-3p, and IBA, IVA, VA, and AA in advanced patients are closely associated with brain metastasis and have the potential to act as biomarkers for predicting brain metastasis in lung cancer patients.
