Exploring the Effect of Differentially Expressed Long Non-coding RNAs Driven by Copy Number Variation on Competing Endogenous RNA Network by Mining Lung Adenocarcinoma Data - Hu, Huihui; Xu, Hangdi; Lu, Fen; Zhang, Jisong; Xu, Li; Xu, Shan; Jiang, Hanliang; Zeng, Qingxin; Chen, Enguo; He, Zhengfu (Frontiers in Cell and Developmental Biology, 2021)
Lung cancer is the first cause of cancer death, and gene copy number variation (CNV) is a vital cause of lung cancer progression. Prognosis prediction of patients and medication guidance by detecting CNV of lung cancer are promising precision treatments in the future. In this paper, the differences in CNV, long non-coding RNA (lncRNA) expression, mRNA expression, and microRNA (miRNA) expression between cancer tissue and normal tissue of lung adenocarcinoma (LUAD) from TCGA-LUAD data set were analyzed, and greater differences were observed. Furthermore, CNV-driven differentially expressed lncRNAs (DElncRNAs) were screened out based on CNV of DElncRNA coding genes, and the competing endogenous RNA (ceRNA) regulatory network related to gene CNV was explored. It was found that the network contained 9 lncRNAs, 7 miRNAs and 178 downstream mRNAs. After obtaining the ceRNA regulatory network, pathway enrichment analyses were performed to find that downstream mRNAs were mainly enriched in biological pathways related to cell division, DNA repair and so on, which mainly affected the replication and growth of tumor cells. Besides, the relationship between lncRNAs and drug effects was explored based on previous studies, and it was found that LINC00511 and LINC00942 in the CNV-associated ceRNA network could be used to determine tumor response to drug treatment. The drugs affected by these two lncRNAs mainly focused on metabolism, TOR signaling pathway, PI3K signaling pathway, EGFR signaling pathway and cell cycle. In summary, research was conducted on the CNV, lncRNAs, mRNAs and miRNAs of lung cancer and 9 lncRNAs that could affect the ceRNA network were discovered. There were two lncRNAs in the CNV-associated ceRNA network that could be used to determine drug response.