• 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

单细胞转录组学揭示急性髓系白血病中髓系前体细胞的异质性和预后标志物。

Single-cell transcriptomics reveals heterogeneity and prognostic markers of myeloid precursor cells in acute myeloid leukemia.

作者信息

He Guangfeng, Jiang Lai, Zhou Xuancheng, Gu Yuheng, Tang Jingyi, Zhang Qiang, Hu Qingwen, Huang Gang, Zhuang Ziye, Gao Xinrui, Xu Ke, Xiao Yewei

机构信息

Department of Hematology, Affiliated Hospital of Southwest Medical University, Luzhou, China.

Department of Clinical Medicine, Southwest Medical University, Luzhou, China.

出版信息

Front Immunol. 2024 Dec 16;15:1494106. doi: 10.3389/fimmu.2024.1494106. eCollection 2024.

DOI:10.3389/fimmu.2024.1494106
PMID:39737198
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11683592/
Abstract

BACKGROUND

Acute myeloid leukemia (AML) is a hematologic tumor with poor prognosis and significant clinical heterogeneity. By integrating transcriptomic data, single-cell RNA sequencing data and independently collected RNA sequencing data this study aims to identify key genes in AML and establish a prognostic assessment model to improve the accuracy of prognostic prediction.

MATERIALS AND METHODS

We analyzed RNA-seq data from AML patients and combined it with single-cell RNA sequencing data to identify genes associated with AML prognosis. Key genes were screened by bioinformatics methods, and a prognostic assessment model was established based on these genes to validate their accuracy.

RESULTS

The study identified eight key genes significantly associated with AML prognosis: SPATS2L, SPINK2, AREG, CLEC11A, HGF, IRF8, ARHGAP5, and CD34. The prognostic model constructed on the basis of these genes effectively differentiated between high-risk and low-risk patients and revealed differences in immune function and metabolic pathways of AML cells.

CONCLUSION

This study provides a new approach to AML prognostic assessment and reveals the role of key genes in AML. These genes may become new biomarkers and therapeutic targets that can help improve prognostic prediction and personalized treatment of AML.

摘要

背景

急性髓系白血病（AML）是一种预后较差且具有显著临床异质性的血液肿瘤。本研究通过整合转录组数据、单细胞RNA测序数据以及独立收集的RNA测序数据，旨在识别AML中的关键基因，并建立一种预后评估模型以提高预后预测的准确性。

材料与方法

我们分析了AML患者的RNA测序数据，并将其与单细胞RNA测序数据相结合，以识别与AML预后相关的基因。通过生物信息学方法筛选关键基因，并基于这些基因建立预后评估模型以验证其准确性。

结果

该研究确定了八个与AML预后显著相关的关键基因：SPATS2L、SPINK2、AREG、CLEC11A、HGF、IRF8、ARHGAP5和CD34。基于这些基因构建的预后模型有效地区分了高危和低危患者，并揭示了AML细胞免疫功能和代谢途径的差异。

结论

本研究为AML预后评估提供了一种新方法，并揭示了关键基因在AML中的作用。这些基因可能成为新的生物标志物和治疗靶点，有助于改善AML的预后预测和个性化治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/b49e72a4e302/fimmu-15-1494106-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/723e4370f664/fimmu-15-1494106-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/d99882e4dd89/fimmu-15-1494106-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/a9fd7ec66814/fimmu-15-1494106-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/5cc4405cc29f/fimmu-15-1494106-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/5cfcdf4341c3/fimmu-15-1494106-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/5ea205f978a6/fimmu-15-1494106-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/d3783bf89fa0/fimmu-15-1494106-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/87e6f17893a2/fimmu-15-1494106-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/b49e72a4e302/fimmu-15-1494106-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/723e4370f664/fimmu-15-1494106-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/d99882e4dd89/fimmu-15-1494106-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/a9fd7ec66814/fimmu-15-1494106-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/5cc4405cc29f/fimmu-15-1494106-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/5cfcdf4341c3/fimmu-15-1494106-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/5ea205f978a6/fimmu-15-1494106-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/d3783bf89fa0/fimmu-15-1494106-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/87e6f17893a2/fimmu-15-1494106-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dde9/11683592/b49e72a4e302/fimmu-15-1494106-g009.jpg

相似文献

1
Single-cell transcriptomics reveals heterogeneity and prognostic markers of myeloid precursor cells in acute myeloid leukemia.单细胞转录组学揭示急性髓系白血病中髓系前体细胞的异质性和预后标志物。
Front Immunol. 2024 Dec 16;15:1494106. doi: 10.3389/fimmu.2024.1494106. eCollection 2024.
2
Lysosome-related genes predict acute myeloid leukemia prognosis and response to immunotherapy.溶酶体相关基因预测急性髓系白血病的预后和免疫治疗反应。
Front Immunol. 2024 May 10;15:1384633. doi: 10.3389/fimmu.2024.1384633. eCollection 2024.
3
NAD metabolism-related genes provide prognostic value and potential therapeutic insights for acute myeloid leukemia.NAD 代谢相关基因可为急性髓系白血病提供预后价值和潜在的治疗见解。
Front Immunol. 2024 Jun 20;15:1417398. doi: 10.3389/fimmu.2024.1417398. eCollection 2024.
4
A Novel Prognostic Risk-Scoring Model Based on RAS Gene-Associated Cluster in Pediatric Acute Myeloid Leukemia.基于RAS基因相关簇的儿童急性髓系白血病新型预后风险评分模型
Cancer Med. 2025 Mar;14(5):e70716. doi: 10.1002/cam4.70716.
5
Construction of prognostic risk prediction model based on high-throughput sequencing expression profile data in childhood acute myeloid leukemia.基于高通量测序表达谱数据构建儿童急性髓系白血病的预后风险预测模型。
Blood Cells Mol Dis. 2019 Jul;77:43-50. doi: 10.1016/j.bcmd.2019.03.008. Epub 2019 Mar 28.
6
Identification of a novel unfolded protein response related signature for predicting the prognosis of acute myeloid leukemia.鉴定一种用于预测急性髓系白血病预后的新型未折叠蛋白反应相关特征。
Sci Rep. 2025 Feb 25;15(1):6705. doi: 10.1038/s41598-025-91524-9.
7
Identification of Prognostic Genes in Acute Myeloid Leukemia Microenvironment: A Bioinformatic and Experimental Analysis.急性髓系白血病微环境中预后基因的鉴定：一项生物信息学与实验分析
Mol Biotechnol. 2025 Apr;67(4):1423-1432. doi: 10.1007/s12033-024-01128-3. Epub 2024 May 7.
8
Machine learning-based bulk RNA analysis reveals a prognostic signature of 13 cell death patterns and potential therapeutic target of SMAD3 in acute myeloid leukemia.基于机器学习的批量RNA分析揭示了急性髓系白血病中13种细胞死亡模式的预后特征以及SMAD3的潜在治疗靶点。
BMC Cancer. 2025 Feb 15;25(1):273. doi: 10.1186/s12885-025-13658-3.
9
A novel N7-Methylguanine-related gene signature for predicting prognosis in acute myeloid leukemia: bioinformatic analysis and experimental verification.一种新型 N7-甲基鸟嘌呤相关基因标志物用于预测急性髓系白血病的预后：生物信息学分析和实验验证。
Hematology. 2024 Dec;29(1):2433905. doi: 10.1080/16078454.2024.2433905. Epub 2024 Nov 29.
10
Establishment and verification of a TME prognosis scoring model based on the acute myeloid leukemia single-cell transcriptome.基于急性髓系白血病单细胞转录组的 TME 预后评分模型的建立与验证。
Sci Rep. 2024 Aug 27;14(1):19811. doi: 10.1038/s41598-024-65345-1.

引用本文的文献

1
Revolutionizing cervical cancer treatment: single-cell sequencing of tumor EPCs and immune checkpoints to assess drug sensitivity and optimize therapy.变革宫颈癌治疗：肿瘤内皮祖细胞和免疫检查点的单细胞测序以评估药物敏感性并优化治疗
Front Immunol. 2025 Jul 24;16:1574174. doi: 10.3389/fimmu.2025.1574174. eCollection 2025.
2
Joint exposure to PM, warm-season heat, and sedentary behavior accelerates incident lung cancer in ageing Chinese adults: evidence from CHARLS.对中国老年成年人而言，同时暴露于细颗粒物、暖季高温及久坐行为会加速肺癌的发生：基于中国健康与养老追踪调查（CHARLS）的证据
Front Public Health. 2025 Jul 8;13:1622767. doi: 10.3389/fpubh.2025.1622767. eCollection 2025.
3

本文引用的文献

1
Role of glycosylation-related gene MGAT1 in pancreatic ductal adenocarcinoma.糖基化相关基因 MGAT1 在胰腺导管腺癌中的作用。
Front Immunol. 2024 Aug 1;15:1438935. doi: 10.3389/fimmu.2024.1438935. eCollection 2024.
2
Unravelling infiltrating T-cell heterogeneity in kidney renal clear cell carcinoma: Integrative single-cell and spatial transcriptomic profiling.解析肾透明细胞癌浸润性 T 细胞异质性：整合单细胞和空间转录组分析。
J Cell Mol Med. 2024 Jun;28(12):e18403. doi: 10.1111/jcmm.18403.
3
Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning.
Single-cell technologies and spatial transcriptomics: decoding immune low - response states in endometrial cancer.
单细胞技术与空间转录组学：解码子宫内膜癌中的免疫低反应状态
Front Immunol. 2025 Jul 2;16:1636483. doi: 10.3389/fimmu.2025.1636483. eCollection 2025.
4
The Key Role of COA6 in Pancreatic Ductal Adenocarcinoma: Metabolic Reprogramming and Regulation of the Immune Microenvironment.COA6在胰腺导管腺癌中的关键作用：代谢重编程与免疫微环境调节
J Cell Mol Med. 2025 Jul;29(13):e70685. doi: 10.1111/jcmm.70685.
5
Global research trends on Chinese patent drugs inducing programmed cell death in cancer: a bibliometric analysis (1998-2024).中药诱导癌细胞程序性死亡的全球研究趋势：文献计量分析（1998 - 2024年）
Discov Oncol. 2025 Jun 21;16(1):1171. doi: 10.1007/s12672-025-02913-5.
6
Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches.通过整合单细胞测序和机器学习方法揭示铜死亡在肝细胞癌异质性和肿瘤微环境中的意义。
Discov Oncol. 2025 May 24;16(1):900. doi: 10.1007/s12672-025-02696-9.
7
Integrating multi-omics and experimental techniques to decode ubiquitinated protein modifications in hepatocellular carcinoma.整合多组学和实验技术以解码肝细胞癌中泛素化蛋白质修饰
Front Pharmacol. 2025 Apr 11;16:1545472. doi: 10.3389/fphar.2025.1545472. eCollection 2025.
8
Exploring novel biomarkers and immunotherapeutic targets for biofeedback therapies to reveal the tumor-associated immune microenvironment through a multimetric analysis of kidney renal clear cell carcinoma.通过对肾透明细胞癌的多指标分析探索生物反馈疗法的新型生物标志物和免疫治疗靶点，以揭示肿瘤相关免疫微环境。
Discov Oncol. 2025 Mar 13;16(1):311. doi: 10.1007/s12672-025-02090-5.
解析透明细胞肾细胞癌的肿瘤微环境：基于机器学习的程序性死亡基因的预后见解。
J Cell Mol Med. 2024 Jul;28(13):e18524. doi: 10.1111/jcmm.18524.
4
Mitophagy and clear cell renal cell carcinoma: insights from single-cell and spatial transcriptomics analysis.自噬与透明细胞肾细胞癌：单细胞和空间转录组学分析的见解。
Front Immunol. 2024 Jun 27;15:1400431. doi: 10.3389/fimmu.2024.1400431. eCollection 2024.
5
Macrophage migration inhibitory factor blockade reprograms macrophages and disrupts prosurvival signaling in acute myeloid leukemia.巨噬细胞迁移抑制因子阻断可重编程巨噬细胞并破坏急性髓系白血病中的促生存信号。
Cell Death Discov. 2024 Mar 28;10(1):157. doi: 10.1038/s41420-024-01924-5.
6
Novel Therapeutic Targets in Acute Myeloid Leukemia (AML).急性髓系白血病（AML）的新型治疗靶点。
Curr Oncol Rep. 2024 Apr;26(4):409-420. doi: 10.1007/s11912-024-01503-y. Epub 2024 Mar 19.
7
Precision unveiled: Synergistic genomic landscapes in breast cancer-Integrating single-cell analysis and decoding drug toxicity for elite prognostication and tailored therapeutics.精准揭示：乳腺癌中的协同基因组景观——整合单细胞分析和破译药物毒性，以进行精英预后预测和定制治疗。
Environ Toxicol. 2024 Jun;39(6):3448-3472. doi: 10.1002/tox.24205. Epub 2024 Mar 7.
8
Relapse of acute myeloid leukemia after allogeneic stem cell transplantation: immune escape mechanisms and current implications for therapy.异基因造血干细胞移植后急性髓系白血病的复发：免疫逃逸机制及目前对治疗的影响。
Mol Cancer. 2023 Nov 11;22(1):180. doi: 10.1186/s12943-023-01889-6.
9
Uncovering the immune microenvironment and molecular subtypes of hepatitis B-related liver cirrhosis and developing stable a diagnostic differential model by machine learning and artificial neural networks.揭示乙型肝炎相关肝硬化的免疫微环境和分子亚型，并通过机器学习和人工神经网络建立稳定的诊断鉴别模型。
Front Mol Biosci. 2023 Sep 22;10:1275897. doi: 10.3389/fmolb.2023.1275897. eCollection 2023.
10
Construction of a diagnostic model for hepatitis B-related hepatocellular carcinoma using machine learning and artificial neural networks and revealing the correlation by immunoassay.基于机器学习和人工神经网络构建乙型肝炎相关肝细胞癌的诊断模型，并通过免疫测定揭示相关性。
Tumour Virus Res. 2023 Dec;16:200271. doi: 10.1016/j.tvr.2023.200271. Epub 2023 Sep 27.