Suppr超能文献

利用长链非编码RNA测序揭示潜在的长链非编码RNA-信使核糖核酸关联网络以及PCBP1-AS1在宫颈癌发病机制中的潜在作用。

Using lncRNA Sequencing to Reveal a Putative lncRNA-mRNA Correlation Network and the Potential Role of PCBP1-AS1 in the Pathogenesis of Cervical Cancer.

作者信息

Li Linhan, Peng Qisong, Gong Min, Ling Ling, Xu Yingxue, Liu Qiaoling

机构信息

Department of Gynaecology and Obstetrics, Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.

Department of Clinical Laboratory, Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Front Oncol. 2021 Mar 23;11:634732. doi: 10.3389/fonc.2021.634732. eCollection 2021.

Abstract

BACKGROUND/AIMS: Long non-coding RNAs (lncRNAs) play important roles in many diseases and participate in posttranscriptional regulatory networks in tumors. However, the functions of major lncRNAs in cervical cancer are unclear. Therefore, the aim of this study was to construct a lncRNA-mRNA coexpression functional network and analyze lncRNAs that might contribute to the pathogenesis of cervical cancer.

METHODS

Differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between three pairs of cervical cancer tissues and adjacent mucosa were identified by lncRNA microarray analysis. LncRNA-mRNA correlation analysis and functional enrichment were performed on the DEGs. From the correlation network, PCBP1-AS1 was selected as a candidate for further analysis. PCBP1-AS1 expression was examined by qPCR, and Kaplan-Meier survival, clinicopathology, GSEA, and immune infiltration analysis of PCBP1-AS1 were performed. The immune responses of PCBP1-AS1 expression in cervical cancer were analyzed using TIMER and western blot. PCBP1-AS1 was knocked down and overexpressed to evaluate its role in cell proliferation, migration, and invasion.

RESULTS

A total of 130 lncRNAs were significantly differentially expressed in cervical cancer patient samples compared with control samples. Differentially expressed mRNAs in the lncRNA-mRNA interaction network were involved in the EMT process. Combined with the Kaplan-Meier survival analyses, the coexpression network revealed that PCBP1-AS1 was significantly associated with OS and clinicopathological parameters in cervical cancer patients. Moreover, PCBP1-AS1 expression was not only significantly increased in cervical cancer specimens but also associated with tumor stage, TNM, and invasion. GSEA revealed that PCBP1-AS1 is closely correlated with cell biological function the p53 and notch signaling pathways. TIMER analysis revealed that the numbers of NK cells and M2 macrophages decreased when PCBP1-AS1 expression was high, which was consistent with the western blot results in clinical samples. Furthermore, experiments showed that high expression of PCBP1-AS1 promoted cell proliferation, migration, and invasion.

CONCLUSIONS

Transcriptomic and lncRNA-mRNA correlation analyses revealed that PCBP1-AS1 plays a key role as an independent prognostic factor in patients with cervical cancer. The identification of PCBP1-AS1 as a new biomarker for cervical cancer could help explain how changes in the immune environment promote cervical cancer development.

摘要

背景/目的:长链非编码RNA(lncRNA)在多种疾病中发挥重要作用,并参与肿瘤的转录后调控网络。然而,主要lncRNA在宫颈癌中的功能尚不清楚。因此,本研究的目的是构建lncRNA-mRNA共表达功能网络,并分析可能导致宫颈癌发病机制的lncRNA。

方法

通过lncRNA芯片分析鉴定三对宫颈癌组织和相邻黏膜之间差异表达的lncRNA(DElncRNA)和mRNA(DEmRNA)。对差异表达基因进行lncRNA-mRNA相关性分析和功能富集分析。从相关网络中,选择PCBP1-AS1作为进一步分析的候选对象。通过qPCR检测PCBP1-AS1的表达,并对PCBP1-AS1进行Kaplan-Meier生存分析、临床病理分析、基因集富集分析(GSEA)和免疫浸润分析。使用TIMER和蛋白质免疫印迹法分析PCBP1-AS1在宫颈癌中的免疫反应。敲低和过表达PCBP1-AS1以评估其在细胞增殖、迁移和侵袭中的作用。

结果

与对照样本相比,宫颈癌患者样本中共有130种lncRNA显著差异表达。lncRNA-mRNA相互作用网络中差异表达的mRNA参与上皮-间质转化(EMT)过程。结合Kaplan-Meier生存分析,共表达网络显示PCBP1-AS1与宫颈癌患者的总生存期(OS)和临床病理参数显著相关。此外,PCBP1-AS1不仅在宫颈癌标本中显著增加,而且与肿瘤分期、TNM分期和侵袭相关。GSEA显示PCBP1-AS1与细胞生物学功能、p53和Notch信号通路密切相关。TIMER分析显示,当PCBP1-AS1表达较高时,自然杀伤(NK)细胞和M2巨噬细胞数量减少,这与临床样本中的蛋白质免疫印迹结果一致。此外,实验表明PCBP1-AS1的高表达促进细胞增殖、迁移和侵袭。

结论

转录组学和lncRNA-mRNA相关性分析表明,PCBP1-AS1作为独立的预后因素在宫颈癌患者中起关键作用。将PCBP1-AS1鉴定为宫颈癌的新生物标志物有助于解释免疫环境变化如何促进宫颈癌的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0719/8023048/2d47656952a6/fonc-11-634732-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验