Background: Leptomeningeal metastasis (LM) has frequently been observed in patients with lung adenocarcinoma. So far, its diagnosis and disease course monitoring are still extremely difficult. Moreover, there is no effective treatment regimen for LM due to a lack knowledge on the molecular mechanism of LM. This study aimed to identify LM-related cerebrospinal fluid (CSF) miRNAs, which have potential value for diagnosing and monitoring LM and exploring the molecular mechanism. Methods: CSF miRNAs were screened and verified by microarray analysis and quantitative real-time PCR (qRT-PCR) in LM patients with lung adenocarcinoma and non-LM controls, and the diagnostic performance of candidate miRNAs was evaluated. Then, candidate miRNAs in matched CSF samples from LM patients at diagnosis, after initial therapy, at relapse, and after salvage therapy, were analyzed to assess the relationship between CSF miRNAs and LM disease course. The effect of candidate miRNAs on proliferation, invasion, and migration of lung adenocarcinoma cell lines was assessed. The targeted genes of the candidate miRNA were predicted by TargetScan, miRDB, and miRTarbase online analysis tools. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the functional categories of predicted target genes. Results: CSF miR-7975, miR-7977, and miR-7641 were screened and verified to be statistically significantly up-regulated in LM patients compared to non-LM controls. The three miRNAs, when combined, exhibited optimal diagnostic performance. Longitudinal data of CSF miR-7975 and miR-7977 correlated well with clinical courses of LM. Overexpression of miR-7977 promoted proliferation, migration, and invasion of lung adenocarcinoma cells. Moreover, 385 targeted genes of miR-7977 were predicted and were involved in various pathways related to cancer metastasis. Conclusions: This study offers insights for future research of CSF miRNAs as robust tools for diagnosing and monitoring LM. It also reveals a novel pathway for exploration of underlying mechanisms of LM.
Keywords: bioinformatic analysis; cerebrospinal fluid; leptomeningeal metastasis; lung adenocarcinoma; microRNA profiling.
Copyright © 2020 Pan, Yang, He, Gao, Jiang, Chen and Zhao.