Shen Dan, Hong Yin, Feng Zhengyang, Chen Xiangying, Cai Yuxing, Peng Qiliang, Tu Jian
Department of Oncology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Department of Cardiothoracic Surgery, Suzhou BenQ Hospital, Suzhou, China.
Front Genet. 2022 Dec 5;13:966247. doi: 10.3389/fgene.2022.966247. eCollection 2022.
This study was performed to identify key regulatory network biomarkers including transcription factors (TFs), miRNAs and lncRNAs that may affect the oncogenesis of EBV positive PTCL-U. GSE34143 dataset was downloaded and analyzed to identify differentially expressed genes (DEGs) between EBV positive PTCL-U and normal samples. Gene ontology and pathway enrichment analyses were performed to illustrate the potential function of the DEGs. Then, key regulators including TFs, miRNAs and lncRNAs involved in EBV positive PTCL-U were identified by constructing TF-mRNA, lncRNA-miRNA-mRNA, and EBV encoded miRNA-mRNA regulatory networks. A total of 96 DEGs were identified between EBV positive PTCL-U and normal tissues, which were related to immune responses, B cell receptor signaling pathway, chemokine activity. Pathway analysis indicated that the DEGs were mainly enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. Based on the TF network, hub TFs were identified regulate the target DEGs. Afterwards, a ceRNA network was constructed, in which miR-181(a/b/c/d) and lncRNA LINC01744 were found. According to the EBV-related miRNA regulatory network, CXCL10 and CXCL11 were found to be regulated by EBV-miR-BART1-3p and EBV-miR-BHRF1-3, respectively. By integrating the three networks, some key regulators were found and may serve as potential network biomarkers in the regulation of EBV positive PTCL-U. The network-based approach of the present study identified potential biomarkers including transcription factors, miRNAs, lncRNAs and EBV-related miRNAs involved in EBV positive PTCL-U, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of EBV positive PTCL-U.
本研究旨在鉴定可能影响EBV阳性外周T细胞淋巴瘤未特指型（PTCL-U）肿瘤发生的关键调控网络生物标志物，包括转录因子（TFs）、微小RNA（miRNAs）和长链非编码RNA（lncRNAs）。下载并分析GSE34143数据集，以鉴定EBV阳性PTCL-U与正常样本之间的差异表达基因（DEGs）。进行基因本体论和通路富集分析，以阐明DEGs的潜在功能。然后，通过构建TF-mRNA、lncRNA-miRNA-mRNA和EBV编码的miRNA-mRNA调控网络，鉴定参与EBV阳性PTCL-U的关键调控因子，包括TFs、miRNAs和lncRNAs。在EBV阳性PTCL-U与正常组织之间共鉴定出96个DEGs，它们与免疫反应、B细胞受体信号通路、趋化因子活性有关。通路分析表明，DEGs主要富集于细胞因子-细胞因子受体相互作用和趋化因子信号通路。基于TF网络，鉴定出调控靶标DEGs的枢纽TFs。随后，构建了一个竞争性内源RNA（ceRNA）网络，其中发现了miR-181（a/b/c/d）和lncRNA LINC01744。根据EBV相关的miRNA调控网络，发现CXCL10和CXCL11分别受EBV-miR-BART1-3p和EBV-miR-BHRF1-3调控。通过整合这三个网络，发现了一些关键调控因子，它们可能作为EBV阳性PTCL-U调控中的潜在网络生物标志物。本研究基于网络的方法鉴定出了参与EBV阳性PTCL-U的潜在生物标志物，包括转录因子、miRNAs、lncRNAs和EBV相关的miRNAs，有助于我们理解EBV阳性PTCL-U致癌和进展的分子机制。
