Exploration of patient plasma exosomal as biomarkers for predicting lung cancer brain metastasis

Lingyun Ye¹Xinnan Hu¹Shen Chen¹Hai Wang¹Juanjuan Li¹Lei Wang¹Guanghui Gao^1*Xiaoxia Chen^1*Xiao Song^2*

• ¹Tongji University Affiliated Shanghai Pulmonary Hospital, Shanghai, China
• ²Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Yangpu, China

Background Many studies have found exosomes have numerous advantages in early diagnosis of tumors. We detected and analyzed the plasma exosomes of lung cancer patients to identify potential biomarkers that can 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 by combining the selected exosomal miRNAs with metabolic molecules could improve the diagnostic performance with the AUC of 0.927. Conclusion The plasma exosomal miR-223-3p, miR-27a-3p, miR-27b-3p and IBA, IVA, VA, AA in advanced patients are closely related to brain metastasis and have the potential to act as biomarkers for predicting brain metastasis in lung cancer patients.