• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

胶质母细胞瘤中细胞吞噬相关亚型的相互作用、免疫浸润特征和预后建模。

Interaction, immune infiltration characteristics and prognostic modeling of efferocytosis-related subtypes in glioblastoma.

机构信息

Department of Neurosurgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.

Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Zhenjiang, China.

出版信息

BMC Med Genomics. 2023 Oct 18;16(1):248. doi: 10.1186/s12920-023-01688-4.

DOI:10.1186/s12920-023-01688-4
PMID:37853449
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10583324/
Abstract

BACKGROUND

Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation.

METHODS

In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system.

RESULTS

Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy.

CONCLUSIONS

Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment.

摘要

背景

噬作用是一种生物学过程,其中吞噬细胞从组织中清除凋亡细胞和小泡。这个过程是由凋亡细胞释放炎症介质引发的,在炎症的解决中起着至关重要的作用。噬作用相关的信号已被发现调节炎症反应和肿瘤微环境(TME),从而促进肿瘤细胞的免疫逃逸。然而,噬作用在多形性胶质母细胞瘤(GBM)中的作用尚不清楚,需要进一步研究。

方法

在这项研究中,我们通过搜索与噬作用相关的研究,对 22 个噬作用相关基因(ERGs)进行了全面分析。我们使用批量 RNA-Seq 和单细胞测序数据,分析了这些 ERGs 的表达和突变特征。通过使用无监督聚类算法,我们从 549 名 GBM 患者中获得了 ERG 聚类,并评估了每个聚类的免疫浸润特征。然后,我们在两个 ERG 聚类中鉴定了差异基因(DEGs),并使用单变量 cox 分析和无监督聚类算法将 GBM 患者分类为不同的基因聚类。最后,我们利用 Boruta 算法筛选预后基因并降低维度,并用 PCA 算法创建了一种新的噬作用相关评分系统。

结果

通过 rt-PCR 分析了胶质瘤细胞系和正常细胞中 ERGs 的差异表达。另一方面,细胞功能实验验证了 TIMD4 是 GBM 中的肿瘤风险因素。我们发现,不同的 ERG 聚类和基因聚类具有不同的预后和免疫浸润特征。我们开发的 ERG 特征提供了对 GBM 肿瘤微环境的深入了解。具有较低 ERG 评分的患者具有更好的生存率和更有可能受益于免疫治疗。

结论

我们新开发的噬作用相关特征具有用于 GBM 患者风险分层和选择可能对免疫治疗有反应的个体的潜力。这可以帮助临床医生在开始临床治疗之前设计适当的靶向治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/7347e792583e/12920_2023_1688_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/68cde0826871/12920_2023_1688_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/8bdeb363e33c/12920_2023_1688_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/7e8526149f47/12920_2023_1688_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/bfa472ef854b/12920_2023_1688_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/1eabb4e6bfac/12920_2023_1688_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/96d83b04e092/12920_2023_1688_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/3fd58f76dff9/12920_2023_1688_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/54223bd726e3/12920_2023_1688_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/f2b02a430272/12920_2023_1688_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/5e898f5cb00a/12920_2023_1688_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/7347e792583e/12920_2023_1688_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/68cde0826871/12920_2023_1688_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/8bdeb363e33c/12920_2023_1688_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/7e8526149f47/12920_2023_1688_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/bfa472ef854b/12920_2023_1688_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/1eabb4e6bfac/12920_2023_1688_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/96d83b04e092/12920_2023_1688_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/3fd58f76dff9/12920_2023_1688_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/54223bd726e3/12920_2023_1688_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/f2b02a430272/12920_2023_1688_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/5e898f5cb00a/12920_2023_1688_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c7/10583324/7347e792583e/12920_2023_1688_Fig11_HTML.jpg

相似文献

1
Interaction, immune infiltration characteristics and prognostic modeling of efferocytosis-related subtypes in glioblastoma.胶质母细胞瘤中细胞吞噬相关亚型的相互作用、免疫浸润特征和预后建模。
BMC Med Genomics. 2023 Oct 18;16(1):248. doi: 10.1186/s12920-023-01688-4.
2
Development of a prognostic model for glioblastoma multiforme based on the expression levels of efferocytosis-related genes.基于噬排相关基因表达水平的胶质母细胞瘤预后模型的建立。
Aging (Albany NY). 2023 Dec 29;15(24):15578-15598. doi: 10.18632/aging.205422.
3
Development and validation a prognostic model based on natural killer T cells marker genes for predicting prognosis and characterizing immune status in glioblastoma through integrated analysis of single-cell and bulk RNA sequencing.通过单细胞和批量 RNA 测序的综合分析,开发和验证一种基于自然杀伤 T 细胞标记基因的预后模型,用于预测胶质母细胞瘤的预后和表征免疫状态。
Funct Integr Genomics. 2023 Aug 31;23(3):286. doi: 10.1007/s10142-023-01217-7.
4
Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients.联合单细胞测序和空间转录组测序鉴定胶质母细胞瘤中与外泌体相关的特征,并构建预后模型鉴定 BARD1 作为 GBM 患者的潜在治疗靶点。
Front Immunol. 2023 Aug 31;14:1263329. doi: 10.3389/fimmu.2023.1263329. eCollection 2023.
5
Identification of Necroptosis-related Molecular Subtypes and Construction of Necroptosis-related Gene Signature for Glioblastoma Multiforme.胶质母细胞瘤中坏死性细胞死亡相关分子亚型的鉴定和坏死性细胞死亡相关基因特征的构建。
Curr Med Chem. 2024;31(33):5417-5431. doi: 10.2174/0929867331666230804104329.
6
Identification of Hypoxia Prognostic Signature in Glioblastoma Multiforme Based on Bulk and Single-Cell RNA-Seq.基于批量和单细胞RNA测序的多形性胶质母细胞瘤缺氧预后特征的鉴定
Cancers (Basel). 2024 Feb 1;16(3):633. doi: 10.3390/cancers16030633.
7
Expression of hub genes of endothelial cells in glioblastoma-A prognostic model for GBM patients integrating single-cell RNA sequencing and bulk RNA sequencing.内皮细胞枢纽基因在胶质母细胞瘤中的表达——整合单细胞 RNA 测序和批量 RNA 测序的 GBM 患者预后模型。
BMC Cancer. 2022 Dec 6;22(1):1274. doi: 10.1186/s12885-022-10305-z.
8
Systematic identification, development, and validation of prognostic biomarkers involving the tumor-immune microenvironment for glioblastoma.系统识别、开发和验证涉及胶质母细胞瘤肿瘤免疫微环境的预后生物标志物。
J Cell Physiol. 2021 Jan;236(1):507-522. doi: 10.1002/jcp.29878. Epub 2020 Jun 22.
9
A new prognostic model for glioblastoma multiforme based on coagulation-related genes.一种基于凝血相关基因的多形性胶质母细胞瘤新预后模型。
Transl Cancer Res. 2023 Oct 31;12(10):2898-2910. doi: 10.21037/tcr-23-322. Epub 2023 Oct 10.
10
Identification and validation of neurotrophic factor-related gene signatures in glioblastoma and Parkinson's disease.胶质母细胞瘤和帕金森病中神经营养因子相关基因特征的鉴定和验证。
Front Immunol. 2023 Feb 7;14:1090040. doi: 10.3389/fimmu.2023.1090040. eCollection 2023.

引用本文的文献

1
Diagnostic value of thyroid-related serological indicators and pan-immune-inflammation value for differentiated thyroid carcinoma.甲状腺相关血清学指标及全免疫炎症值对分化型甲状腺癌的诊断价值
Front Immunol. 2025 Aug 20;16:1662638. doi: 10.3389/fimmu.2025.1662638. eCollection 2025.
2
Pan-cancer analysis of tumor suppressor ZNF132 reveals its diagnostic and prognostic significance with immunomodulatory implications in colorectal cancer.肿瘤抑制因子ZNF132的泛癌分析揭示了其在结直肠癌中的诊断和预后意义以及免疫调节作用。
BMC Cancer. 2025 Sep 2;25(1):1416. doi: 10.1186/s12885-025-14810-9.
3
Qingxie Fuzheng granules attenuate cancer cachexia by restoring gut microbiota homeostasis and suppressing IL-6/NF-κB signaling in colorectal adenocarcinoma.

本文引用的文献

1
Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer.鉴定卵巢癌中与铜代谢相关的亚型并建立预后模型。
Front Endocrinol (Lausanne). 2023 Mar 6;14:1145797. doi: 10.3389/fendo.2023.1145797. eCollection 2023.
2
Identification and validation of neurotrophic factor-related gene signatures in glioblastoma and Parkinson's disease.胶质母细胞瘤和帕金森病中神经营养因子相关基因特征的鉴定和验证。
Front Immunol. 2023 Feb 7;14:1090040. doi: 10.3389/fimmu.2023.1090040. eCollection 2023.
3
The Pan-Cancer Multi-Omics Landscape of FOXO Family Relevant to Clinical Outcome and Drug Resistance.
清泄扶正颗粒通过恢复肠道微生物群稳态和抑制结肠腺癌中的IL-6/NF-κB信号传导来减轻癌症恶病质。
Hereditas. 2025 Aug 29;162(1):178. doi: 10.1186/s41065-025-00541-1.
4
Analysis of standard vs dose-escalated stereotactic body radiation therapy in localized prostate cancer: a comparative evaluation of survival outcomes.局限性前列腺癌中标准与剂量递增立体定向体部放射治疗的分析:生存结果的比较评估
Front Immunol. 2025 Aug 13;16:1654174. doi: 10.3389/fimmu.2025.1654174. eCollection 2025.
5
Combined preoperative platelet-albumin ratio and cancer inflammation prognostic index predicts prognosis in colorectal cancer: a retrospective study.术前血小板-白蛋白比值与癌症炎症预后指数联合预测结直肠癌预后:一项回顾性研究
Sci Rep. 2025 Aug 12;15(1):29500. doi: 10.1038/s41598-025-15309-w.
6
Integrating single-cell RNA sequencing and spatial transcriptomics reveals the therapeutic effect of nitazoxanide in head and neck squamous cell carcinoma.整合单细胞RNA测序和空间转录组学揭示硝唑尼特对头颈部鳞状细胞癌的治疗效果。
Discov Oncol. 2025 Aug 8;16(1):1509. doi: 10.1007/s12672-025-03372-8.
7
Identifying risk factors and evaluating therapeutic interventions for anastomotic recurrence in postoperative esophageal squamous cell carcinoma.识别术后食管鳞状细胞癌吻合口复发的危险因素并评估治疗干预措施。
BMC Cancer. 2025 Jul 30;25(1):1245. doi: 10.1186/s12885-025-14671-2.
8
Prediction of biomarkers for brain metastasis in nonsmall cell lung cancer based on transcriptome sequencing.基于转录组测序预测非小细胞肺癌脑转移的生物标志物
Medicine (Baltimore). 2025 Jul 18;104(29):e43483. doi: 10.1097/MD.0000000000043483.
9
Taurine-mediated metabolic immune crosstalk indicates and promotes immunosuppression with anti-PD-1 resistance in bladder cancer.牛磺酸介导的代谢免疫串扰表明并促进膀胱癌中抗程序性死亡蛋白1(PD-1)耐药的免疫抑制。
Front Immunol. 2025 Jun 24;16:1618439. doi: 10.3389/fimmu.2025.1618439. eCollection 2025.
10
Integrated eQTL-pQTL Mendelian randomization and single-cell sequencing reveal therapeutic targets in ovarian clear cell cancer.整合的表达数量性状基因座-蛋白质数量性状基因座孟德尔随机化和单细胞测序揭示了卵巢透明细胞癌的治疗靶点。
Discov Oncol. 2025 Jul 1;16(1):1249. doi: 10.1007/s12672-025-03043-8.
FOXO 家族与临床结局和耐药性相关的泛癌多组学全景。
Int J Mol Sci. 2022 Dec 9;23(24):15647. doi: 10.3390/ijms232415647.
4
Expression of hub genes of endothelial cells in glioblastoma-A prognostic model for GBM patients integrating single-cell RNA sequencing and bulk RNA sequencing.内皮细胞枢纽基因在胶质母细胞瘤中的表达——整合单细胞 RNA 测序和批量 RNA 测序的 GBM 患者预后模型。
BMC Cancer. 2022 Dec 6;22(1):1274. doi: 10.1186/s12885-022-10305-z.
5
A Bioinformatics-Based Analysis of an Anoikis-Related Gene Signature Predicts the Prognosis of Patients with Low-Grade Gliomas.基于生物信息学的失巢凋亡相关基因特征分析预测低级别胶质瘤患者的预后
Brain Sci. 2022 Oct 5;12(10):1349. doi: 10.3390/brainsci12101349.
6
Machine learning-based tumor-infiltrating immune cell-associated lncRNAs for predicting prognosis and immunotherapy response in patients with glioblastoma.基于机器学习的肿瘤浸润免疫细胞相关 lncRNAs 预测胶质母细胞瘤患者的预后和免疫治疗反应。
Brief Bioinform. 2022 Nov 19;23(6). doi: 10.1093/bib/bbac386.
7
Machine learning-based identification of tumor-infiltrating immune cell-associated lncRNAs for improving outcomes and immunotherapy responses in patients with low-grade glioma.基于机器学习的肿瘤浸润免疫细胞相关长链非编码 RNA 鉴定,以改善低级别脑胶质瘤患者的预后和免疫治疗反应。
Theranostics. 2022 Aug 8;12(13):5931-5948. doi: 10.7150/thno.74281. eCollection 2022.
8
DNA methylation-regulated SNX20 overexpression correlates with poor prognosis, immune cell infiltration, and low-grade glioma progression.DNA 甲基化调控的 SNX20 过表达与不良预后、免疫细胞浸润和低级别胶质瘤进展相关。
Aging (Albany NY). 2022 Jun 27;14(12):5211-5222. doi: 10.18632/aging.204144.
9
Systemic Delivery of an Adjuvant CXCR4-CXCL12 Signaling Inhibitor Encapsulated in Synthetic Protein Nanoparticles for Glioma Immunotherapy.系统递送包含在合成蛋白纳米颗粒中的辅助 CXCR4-CXCL12 信号抑制剂用于神经胶质瘤免疫治疗。
ACS Nano. 2022 Jun 28;16(6):8729-8750. doi: 10.1021/acsnano.1c07492. Epub 2022 May 26.
10
Feature Selection of OMIC Data by Ensemble Swarm Intelligence Based Approaches.基于集成群体智能方法的组学数据特征选择
Front Genet. 2022 Mar 8;12:793629. doi: 10.3389/fgene.2021.793629. eCollection 2021.