研究动态
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基于干细胞相关标志物的预后,构建卵巢癌转移专用调节网络。

Construction of Metastasis-Specific Regulation Network in Ovarian Cancer Based on Prognostic Stemness-Related Signatures.

发表日期:2023 Mar 20
作者: Wenwen Wang, Hongjun Guo, Shengyu Wu, Shuyuan Xian, Weiwei Zhang, Ruitao Zhang, Zhihua Chen, Ke Su, Ying Zhang, Ying Zhu, Danxia Chu, Mengling Zhao, Zhihua Tang, Chunlan Zheng, Zongqiang Huang, Qian Ma, Ruixia Guo
来源: GENES & DEVELOPMENT

摘要:

我们旨在揭示卵巢癌(OV)转移与OV中癌干细胞性质的相关性。从TCGA获取了591个OV样本(551个没有转移和40个有转移的)的RNA-seq数据和临床信息。使用edgeR方法确定差异表达基因(DEGs)和转录因子(DETFs)。然后,使用单类逻辑回归(OCLR)计算基于mRNA表达的干细胞指数。使用加权基因共表达网络分析(WGCNA)来定义与干细胞相关的基因(SRGs)。进行单因素和多因素Cox比例风险回归,以识别预后SRGs(PSRGs)。将PSRGs、DETFs和基于基因集变异分析(GSVA)量化的50个标志性通路整合到Pearson共表达分析中。利用显著共表达相互作用构建OV转移特异性调控网络。根据单细胞RNA测序数据进行细胞通信分析,探索OV的分子调节机制。最终,利用可靠性的目标染色质可接近性检测高通量测序(ATAC)、染色质免疫共沉淀测序(ChIP-seq)验证和多个数据集验证关键的干细胞相关签名的表达水平和预后价值。此外,使用连接图谱(CMap)识别干细胞相关标志物的潜在抑制剂。基于edgeR、WGCNA和Cox比例风险回归,定义了22个PSRGs,用于构建转移性OV的预后预测模型。在转移特异性调控网络中,关键的TF-PSRS互作对是NR4A1-EGR3(相关系数=0.81,p<0.05,正相关),以及关键的PSRG-标志性通路互作对是EGR3-TNFα信号经过NFκB(相关系数=0.44,p<0.05,正相关),并在多组学数据库中进行验证。Thioridazine被认为是治疗OV转移最重要的化合物。PSRGs在OV转移中发挥关键作用。具体而言,EGR3是最重要的PSRG,受DETF NR4A1正调节,通过TNFα信号诱导转移。©2023年作者。在独家许可下授权给生殖研究协会。
WE aimed to reveal the correlation between ovarian cancer (OV) metastasis and cancer stemness in OV. RNA-seq data and clinical information of 591 OV samples (551 without metastasis and 40 with metastasis) were obtained from TCGA. The edgeR method was used to determine differentially expressed genes (DEGs) and transcription factors (DETFs). Then, mRNA expression-based stemness index was calculated using one-class logistic regression (OCLR). Weighted gene co-expression network analysis (WGCNA) was used to define stemness-related genes (SRGs). Univariate and multivariate Cox proportional hazard regression were conducted to identify the prognostic SRGs (PSRGs). PSRGs, DETFs, and 50 hallmark pathways quantified by gene set variation analysis (GSVA) were integrated into Pearson co-expression analysis. Significant co-expression interactions were utilized to construct an OV metastasis-specific regulation network. Cell communication analysis was carried out based on single cell RNA sequencing data to explore the molecular regulation mechanism of OV. Eventually, assay for targeting accessible-chromatin with high throughout sequencing (ATAC), chromatin immunoprecipitation sequencing (ChIP-seq) validation, and multiple data sets were used to validate the expression levels and prognostic values of key stemness-related signatures. Moreover, connectivity map (CMap) was used to identify potential inhibitors of stemness-related signatures. Based on edgeR, WGCNA, and Cox proportional hazard regression, 22 PSRGs were defined to construct a prognostic prediction model for metastatic OV. In the metastasis-specific regulation network, key TF-PSRS interaction pair was NR4A1-EGR3 (correlation coefficient = 0.81, p < 0.05, positive), and key PSRG-hallmark pathway interaction pair was EGR3-TNFα signaling via NFκB (correlation coefficient = 0.44, p < 0.05, positive), which were validated in multi-omics databases. Thioridazine was postulated to be the most significant compound in treatment of OV metastasis. PSRGs played critical roles in OV metastasis. Specifically, EGR3 was the most significant PSRG, which was positively regulated by DETF NR4A1, inducing metastasis via TNFα signaling.© 2023. The Author(s), under exclusive licence to Society for Reproductive Investigation.