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肠型和弥漫型胃癌因果网络的主要调控因子及与 RNA 病毒感染途径的关系。

Master Regulators of Causal Networks in Intestinal- and Diffuse-Type Gastric Cancer and the Relation to the RNA Virus Infection Pathway.

机构信息

Division of Risk Assessment, Center for Biological Safety and Research, National Institute of Health Sciences, Kawasaki 210-9501, Japan.

Innovation Centre of NanoMedicine (iCONM), Kawasaki Institute of Industrial Promotion, Kawasaki 210-0821, Japan.

出版信息

Int J Mol Sci. 2024 Aug 13;25(16):8821. doi: 10.3390/ijms25168821.

Abstract

Causal networks are important for understanding disease signaling alterations. To reveal the network pathways affected in the epithelial-mesenchymal transition (EMT) and cancer stem cells (CSCs), which are related to the poor prognosis of cancer, the molecular networks and gene expression in diffuse- and intestinal-type gastric cancer (GC) were analyzed. The network pathways in GC were analyzed using Ingenuity Pathway Analysis (IPA). The analysis of the probe sets in which the gene expression had significant differences between diffuse- and intestinal-type GC in RNA sequencing of the publicly available data identified 1099 causal networks in diffuse- and intestinal-type GC. Master regulators of the causal networks included lenvatinib, pyrotinib, histone deacetylase 1 (HDAC1), mir-196, and erb-b2 receptor tyrosine kinase 2 (ERBB2). The analysis of the HDAC1-interacting network identified the involvement of EMT regulation via the growth factors pathway, the coronavirus pathogenesis pathway, and vorinostat. The network had RNA-RNA interactions with microRNAs such as mir-10, mir-15, mir-17, mir-19, mir-21, mir-223, mir-25, mir-27, mir-29, and mir-34. The molecular networks revealed in the study may lead to identifying drug targets for GC.

摘要

因果网络对于理解疾病信号改变很重要。为了揭示与癌症预后不良相关的上皮-间充质转化(EMT)和癌症干细胞(CSC)中的网络途径,分析了弥漫型和肠型胃癌(GC)中的分子网络和基因表达。使用 IPA 对 GC 中的网络途径进行了分析。对公开可用的 RNA 测序数据中弥漫型和肠型 GC 之间基因表达存在显著差异的探针集进行分析,鉴定出弥漫型和肠型 GC 中存在 1099 个因果网络。因果网络的主要调控因子包括仑伐替尼、吡咯替尼、组蛋白去乙酰化酶 1(HDAC1)、mir-196 和表皮生长因子受体酪氨酸激酶 2(ERBB2)。对 HDAC1 相互作用网络的分析表明,通过生长因子途径、冠状病毒发病途径和伏立诺他参与 EMT 调节。该网络与 mir-10、mir-15、mir-17、mir-19、mir-21、mir-223、mir-25、mir-27、mir-29 和 mir-34 等 microRNAs 存在 RNA-RNA 相互作用。本研究中揭示的分子网络可能有助于确定 GC 的药物靶点。

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