4.7 Article

Identification of multiple organ metastasis-associated hub mRNA/miRNA signatures in non-small cell lung cancer

期刊

CELL DEATH & DISEASE
卷 14, 期 12, 页码 -

出版社

SPRINGERNATURE
DOI: 10.1038/s41419-023-06286-x

关键词

-

向作者/读者索取更多资源

This study characterized the transcriptomic landscape of NSCLC cells with organ-specific metastatic potentials and identified miR-660-5p as a key driver associated with NSCLC progression and distant metastasis. A six-gene signature was established to predict NSCLC metastasis, and three genes and two transcription factors from this signature were validated. Aberrant gene signature and miRNA can serve as biomarkers for predicting NSCLC distant metastasis.
Metastasis remains major cause of treatment failure in non-small cell lung cancer (NSCLC). A comprehensive characterization of the transcriptomic landscape of NSCLC-cells with organ-specific metastatic potentials would advance our understanding of NSCLC metastasis process. In this study, we established NSCLC bone-metastatic (BoM), brain-metastatic (BrM), and lymph-metastatic (LnM) cells by an in vivo spontaneous metastatic model. Subsequently, by analyzing the entire transcriptomic profiles of BoM, BrM, LnM, LuM, in comparison with their parental cell line L9981, we identified miR-660-5p as a key driver that is associated with NSCLC progression and distant metastasis, potentially through its targeting of LIMCH1, SMARCA5 and TPP2. In addition, a six-gene signature (ADRB2, DPYSL2, IL7R, LIMCH1, PIK3R1, and SOX2) was subsequently established to predict NSCLC metastasis based on differentially expressed genes, three of which (DPYSL2, PIK3R1, LIMCH1) along with the transcriptional factors RB1 and TP63, were ultimately validated by experiments. Taken together, aberrant gene signature and miRNA can serve as biomarkers for predicting NSCLC distant metastasis, and targeting them could potentially contribute to the development of novel therapeutic strategies.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据