Wang Ting, Yang Chengliang, Li Bing, Xing Ying, Huang Jian, Zhang Yangping, Bu Shanshan, Ge Hong
Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
The Fourth Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Front Genet. 2021 Nov 12;12:758591. doi: 10.3389/fgene.2021.758591. eCollection 2021.
Tyrosine kinase inhibitors that act against epidermal growth factor receptor (EGFR) show strong efficacy against non-small cell lung cancer (NSCLC) involving mutated EGFRs. However, most such patients eventually develop resistance to EGFR-TKIs. Numerous researches have reported that messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) may be involved in EGFR-TKI resistance, but the comprehensive expression profile and competitive endogenous RNA (ceRNA) regulatory network between mRNAs and ncRNAs in EGFR-TKI resistance of NSCLC are incompletely known. We aimed to define a ceRNA regulatory network linking mRNAs and non-coding RNAs that may mediate this resistance. Using datasets GSE83666, GSE75309 and GSE103352 from the Gene Expression Omnibus, we identified long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs differentially expressed between NSCLC cells that were sensitive or resistant to EGFR-TKIs. The potential biological functions of the corresponding differentially expressed genes were analyzed based KEGG pathways. We combined interactions among lncRNAs, miRNAs and mRNAs in the RNAInter database with KEGG pathways to generate transcriptional regulatory ceRNA networks associated with NSCLC resistance to EGFR-TKIs. Kaplan-Meier analysis was used to assess the ability of core ceRNA regulatory sub-networks to predict the progression-free interval and overall survival of NSCLC. The expression of two core ceRNA regulatory sub-networks in NSCLC was validated by quantitative real-time PCR. We identified 8,989 lncRNAs, 1,083 miRNAs and 3,191 mRNAs that were differentially expressed between patients who were sensitive or resistant to the inhibitors. These DEGs were linked to 968 biological processes and 31 KEGG pathways. Pearson analysis of correlations among the DEGs of lncRNAs, miRNAs and mRNAs identified 12 core ceRNA regulatory sub-networks associated with resistance to EGFR-TKIs. The two lncRNAs ABTB1 and NPTN with the hsa-miR-150-5p and mRNA SERPINE1 were significantly associated with resistance to EGFR-TKIs and survival in NSCLC. These lncRNAs and the miRNA were found to be down-regulated, and the mRNA up-regulated, in a resistant NSCLC cell line relative to the corresponding sensitive cells. In this study, we provide new insights into the pathogenesis of NSCLC and the emergence of resistance to EGFR-TKIs, based on a lncRNA-miRNA-mRNA network.
作用于表皮生长因子受体（EGFR）的酪氨酸激酶抑制剂对涉及EGFR突变的非小细胞肺癌（NSCLC）显示出强大疗效。然而，大多数此类患者最终会对EGFR酪氨酸激酶抑制剂（EGFR-TKIs）产生耐药性。众多研究报道信使核糖核酸（mRNA）和非编码核糖核酸（ncRNA）可能与EGFR-TKI耐药性有关，但NSCLC的EGFR-TKI耐药性中mRNA与ncRNA之间的综合表达谱及竞争性内源RNA（ceRNA）调控网络尚不完全清楚。我们旨在确定一个连接mRNA和非编码RNA的ceRNA调控网络，其可能介导这种耐药性。利用来自基因表达综合数据库的数据集GSE83666、GSE75309和GSE103352，我们鉴定了在对EGFR-TKIs敏感或耐药的NSCLC细胞之间差异表达的长链非编码RNA（lncRNA）、微小RNA（miRNA）和mRNA。基于京都基因与基因组百科全书（KEGG）通路分析了相应差异表达基因的潜在生物学功能。我们将RNAInter数据库中lncRNA、miRNA和mRNA之间的相互作用与KEGG通路相结合，以生成与NSCLC对EGFR-TKIs耐药性相关的转录调控ceRNA网络。采用Kaplan-Meier分析评估核心ceRNA调控子网预测NSCLC无进展生存期和总生存期的能力。通过定量实时PCR验证了两个核心ceRNA调控子网在NSCLC中的表达。我们鉴定出8989个lncRNA、1083个miRNA和3191个mRNA在对抑制剂敏感或耐药的患者之间存在差异表达。这些差异表达基因与968个生物学过程和31条KEGG通路相关。对lncRNA、miRNA和mRNA的差异表达基因进行Pearson相关性分析，确定了12个与EGFR-TKI耐药性相关的核心ceRNA调控子网。lncRNA ABTB1和NPTN与hsa-miR-150-5p以及mRNA SERPINE在NSCLC中与EGFR-TKI耐药性和生存期显著相关。相对于相应的敏感细胞，在耐药NSCLC细胞系中发现这些lncRNA和miRNA下调，而mRNA上调。在本研究中，我们基于lncRNA-miRNA-mRNA网络，为NSCLC的发病机制及EGFR-TKI耐药性的产生提供了新见解。
