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应激暴露下内质网应激与铁死亡分子相互作用的生物信息学分析。

Bioinformatics Analysis of Molecular Interactions between Endoplasmic Reticulum Stress and Ferroptosis under Stress Exposure.

机构信息

Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, No. 361 Zhongshan Dong Road, 050017 Shijiazhuang, China.

出版信息

Anal Cell Pathol (Amst). 2023 Mar 30;2023:9979291. doi: 10.1155/2023/9979291. eCollection 2023.

DOI:10.1155/2023/9979291
PMID:37035018
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10079382/
Abstract

Stress has become a universal biological phenomenon in the body, which leads to pathophysiological changes. However, the molecular network interactions between endoplasmic reticulum (ER) stress and ferroptosis under stressful conditions are not clear. For this purpose, we screened the gene expression profile of GSE173795 for intersection with ferroptosis genes and screened 68 differentially expressed genes (DEGs) (63 up-regulated, 5 down-regulated), mainly related to lipid and atherosclerosis, autophagy-animal, mitophagy-animal, focal adhesion, DNA replication, proteasome, oocyte meiosis, toll-like receptor signaling pathway, cell cycle, etc. Immune infiltration analysis revealed that stress resulted in decreased B cells memory, T cells CD8 and T cells CD4 memory resting, monocytes, macrophages M2, and increased B cells naive, T cells follicular helper, and macrophages M1. 19 core-DEGs (ASNS, TRIB3, ATF4, EIF2S1, CEBPG, RELA, HSPA5, DDIT3, STAT3, MAP3K5, HIF1A, HNF4A, MAPK14, HMOX1, CDKN1A, KRAS, SP1, SIRT1, EGFR) were screened, all of which were up-regulated DEGs. These biological processes and pathways were mainly involved in responding to ER stress, lipid and atherosclerosis, cellular response to stress, cellular response to chemical stress, and regulation of DNA-templated transcription in response to stress, etc. Spearman analysis did not find MAPK14 to be significantly associated with immune cells. Other core-DEGs were associated with immune cells, including B cells naive, T cells follicular helper, and monocytes. Based on core-DEGs, 283 miRNAs were predicted. Among the 22 miRNAs with highly cross-linked DEGs, 11 had upstream lncRNA, mainly targeting STAT3, SP1, CDKN1A, and SIRT1, and a total of 39 lncRNA were obtained. 85 potential drugs targeting 11 core-DEGs were identified and were expected to be potential immunotherapeutic agents for stress injury. Our experiments also confirmed that Liproxstatin-1 alleviates common cross-linked proteins between ER stress and ferroptosis. In conclusion, our study explored the molecular mechanisms and network interactions among stress-ER stress-ferroptosis from a novel perspective, which provides new research ideas for studying stressful injury.

摘要

压力已成为体内普遍存在的生物学现象,导致病理生理变化。然而,在应激条件下内质网(ER)应激与铁死亡之间的分子网络相互作用尚不清楚。为此,我们对 GSE173795 的基因表达谱进行了筛选,以与铁死亡基因进行交集,并筛选出 68 个差异表达基因(DEGs)(63 个上调,5 个下调),主要与脂质和动脉粥样硬化、自噬-动物、线粒体自噬-动物、焦点黏附、DNA 复制、蛋白酶体、卵母细胞减数分裂、Toll 样受体信号通路、细胞周期等有关。免疫浸润分析表明,压力导致 B 细胞记忆减少、T 细胞 CD8 和 T 细胞 CD4 记忆静止、单核细胞、M2 巨噬细胞增加、B 细胞幼稚、滤泡辅助性 T 细胞和 M1 巨噬细胞增加。筛选出 19 个核心 DEGs(ASNS、TRIB3、ATF4、EIF2S1、CEBPG、RELA、HSPA5、DDIT3、STAT3、MAP3K5、HIF1A、HNF4A、MAPK14、HMOX1、CDKN1A、KRAS、SP1、SIRT1、EGFR),均为上调 DEGs。这些生物过程和途径主要涉及内质网应激反应、脂质和动脉粥样硬化、细胞应激反应、细胞对化学应激的反应以及应激时 DNA 模板转录的调节等。Spearman 分析未发现 MAPK14 与免疫细胞显著相关。其他核心 DEGs 与免疫细胞相关,包括 B 细胞幼稚、滤泡辅助性 T 细胞和单核细胞。基于核心 DEGs,预测了 283 个 miRNA。在与 22 个具有高度交联 DEGs 的 miRNA 中,有 11 个 miRNA 具有上游 lncRNA,主要靶向 STAT3、SP1、CDKN1A 和 SIRT1,共获得 39 个 lncRNA。鉴定了针对 11 个核心 DEGs 的 85 种潜在药物,有望成为应激损伤的潜在免疫治疗药物。我们的实验还证实了 Liproxstatin-1 可减轻内质网应激与铁死亡之间常见的交联蛋白。总之,本研究从新的角度探讨了应激-内质网应激-铁死亡之间的分子机制和网络相互作用,为研究应激损伤提供了新的研究思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/384532885c1b/ACP2023-9979291.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/ec4de65669d5/ACP2023-9979291.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/0d84f0573252/ACP2023-9979291.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/384532885c1b/ACP2023-9979291.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/ec4de65669d5/ACP2023-9979291.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/7ddbc3f6edaa/ACP2023-9979291.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/450e21b4f69f/ACP2023-9979291.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/8c6c89341bf2/ACP2023-9979291.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/0d84f0573252/ACP2023-9979291.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b0/10079382/384532885c1b/ACP2023-9979291.006.jpg

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