• 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

从癌前病变到浸润性肺腺癌的进化代谢景观。

Evolutionary metabolic landscape from preneoplasia to invasive lung adenocarcinoma.

机构信息

School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China.

Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China.

出版信息

Nat Commun. 2021 Nov 10;12(1):6479. doi: 10.1038/s41467-021-26685-y.

DOI:10.1038/s41467-021-26685-y
PMID:34759281
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8580984/
Abstract

Metabolic reprogramming evolves during cancer initiation and progression. However, thorough understanding of metabolic evolution from preneoplasia to lung adenocarcinoma (LUAD) is still limited. Here, we perform large-scale targeted metabolomics on resected lesions and plasma obtained from invasive LUAD and its precursors, and decipher the metabolic trajectories from atypical adenomatous hyperplasia (AAH) to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC), revealing that perturbed metabolic pathways emerge early in premalignant lesions. Furthermore, three panels of plasma metabolites are identified as non-invasive predictive biomarkers to distinguish IAC and its precursors with benign diseases. Strikingly, metabolomics clustering defines three metabolic subtypes of IAC patients with distinct clinical characteristics. We identify correlation between aberrant bile acid metabolism in subtype III with poor clinical features and demonstrate dysregulated bile acid metabolism promotes migration of LUAD, which could be exploited as potential targetable vulnerability and for stratifying patients. Collectively, the comprehensive landscape of the metabolic evolution along the development of LUAD will improve early detection and provide impactful therapeutic strategies.

摘要

代谢重编程在癌症的发生和发展过程中不断演变。然而,人们对从癌前病变到肺腺癌(LUAD)的代谢演变的全面理解仍然有限。在这里,我们对从侵袭性 LUAD 及其前体中切除的病变和血浆进行了大规模的靶向代谢组学分析,并揭示了从非典型腺瘤性增生(AAH)到原位腺癌(AIS)、微浸润性腺癌(MIA)和侵袭性腺癌(IAC)的代谢轨迹,表明失调的代谢途径在癌前病变中很早就出现了。此外,我们还鉴定出了三个血浆代谢物面板,它们可作为非侵入性预测生物标志物,用于区分 IAC 及其伴良性疾病的前体。引人注目的是,代谢组学聚类定义了三种具有不同临床特征的 IAC 患者的代谢亚型。我们发现,III 型代谢亚型中异常的胆汁酸代谢与不良的临床特征相关,并证明了胆汁酸代谢失调促进了 LUAD 的迁移,这可能成为潜在的靶向弱点,并用于对患者进行分层。总的来说,LUAD 发展过程中代谢演变的全面情况将提高早期检测水平,并提供有影响力的治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/475b891c1f6f/41467_2021_26685_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/ff470668f551/41467_2021_26685_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/053eadb451a8/41467_2021_26685_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/6327a58cdeb0/41467_2021_26685_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/78460e74a5f0/41467_2021_26685_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/3a0b22f3ebde/41467_2021_26685_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/475b891c1f6f/41467_2021_26685_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/ff470668f551/41467_2021_26685_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/053eadb451a8/41467_2021_26685_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/6327a58cdeb0/41467_2021_26685_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/78460e74a5f0/41467_2021_26685_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/3a0b22f3ebde/41467_2021_26685_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85b7/8580984/475b891c1f6f/41467_2021_26685_Fig6_HTML.jpg

相似文献

1
Evolutionary metabolic landscape from preneoplasia to invasive lung adenocarcinoma.从癌前病变到浸润性肺腺癌的进化代谢景观。
Nat Commun. 2021 Nov 10;12(1):6479. doi: 10.1038/s41467-021-26685-y.
2
Integrated whole-exome and bulk transcriptome sequencing delineates the dynamic evolution from preneoplasia to invasive lung adenocarcinoma featured with ground-glass nodules.整合全外显子组和 bulk 转录组测序描绘了以磨玻璃结节为特征的从癌前病变到浸润性肺腺癌的动态演变过程。
Cancer Med. 2024 Jun;13(11):e7383. doi: 10.1002/cam4.7383.
3
Excellent Prognosis of Patients With Invasive Lung Adenocarcinomas During Surgery Misdiagnosed as Atypical Adenomatous Hyperplasia, Adenocarcinoma In Situ, or Minimally Invasive Adenocarcinoma by Frozen Section.术中冰冻切片误诊为不典型腺瘤样增生、原位腺癌或微浸润性腺癌的浸润性肺腺癌患者预后良好。
Chest. 2021 Mar;159(3):1265-1272. doi: 10.1016/j.chest.2020.10.076. Epub 2020 Nov 14.
4
Evolution of lung adenocarcinoma from preneoplasia to invasive adenocarcinoma.肺腺癌从癌前病变到浸润性腺癌的演变。
Cancer Med. 2023 Mar;12(5):5545-5557. doi: 10.1002/cam4.5393. Epub 2022 Nov 3.
5
Delineating the dynamic evolution from preneoplasia to invasive lung adenocarcinoma by integrating single-cell RNA sequencing and spatial transcriptomics.通过整合单细胞 RNA 测序和空间转录组学,描绘从癌前病变到浸润性肺腺癌的动态演变过程。
Exp Mol Med. 2022 Nov;54(11):2060-2076. doi: 10.1038/s12276-022-00896-9. Epub 2022 Nov 25.
6
Multi-region exome sequencing reveals genomic evolution from preneoplasia to lung adenocarcinoma.多区域外显子组测序揭示了从癌前病变到肺腺癌的基因组进化。
Nat Commun. 2019 Jul 5;10(1):2978. doi: 10.1038/s41467-019-10877-8.
7
Pathomic Features Reveal Immune and Molecular Evolution From Lung Preneoplasia to Invasive Adenocarcinoma.Pathomic 特征揭示了从肺前瘤变到浸润性腺癌的免疫和分子进化。
Mod Pathol. 2023 Dec;36(12):100326. doi: 10.1016/j.modpat.2023.100326. Epub 2023 Sep 9.
8
Analysis of CT morphologic features and attenuation for differentiating among transient lesions, atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive and invasive adenocarcinoma presenting as pure ground-glass nodules.分析 CT 形态学特征及衰减值对以纯磨玻璃结节为表现的局灶性磨玻璃密度影、不典型腺瘤样增生、原位腺癌、微浸润腺癌和浸润性腺癌的鉴别诊断
Sci Rep. 2019 Oct 10;9(1):14586. doi: 10.1038/s41598-019-50989-1.
9
Genomic Landscape and Immune Microenvironment Features of Preinvasive and Early Invasive Lung Adenocarcinoma.肺浸润前和早期浸润性腺癌的基因组景观和免疫微环境特征。
J Thorac Oncol. 2019 Nov;14(11):1912-1923. doi: 10.1016/j.jtho.2019.07.031. Epub 2019 Aug 22.
10
CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction.实性部分磨玻璃结节型肺腺癌病理分类预测的CT特征及定量分析
BMC Cancer. 2020 Jan 28;20(1):60. doi: 10.1186/s12885-020-6556-6.

引用本文的文献

1
Metabolic Signatures in Lung Cancer: Prognostic Value of Acid-Base Disruptions and Serum Indices.肺癌中的代谢特征:酸碱失衡和血清指标的预后价值
Int J Mol Sci. 2025 Aug 25;26(17):8231. doi: 10.3390/ijms26178231.
2
DNA methylation cooperates with genomic alterations during non-small cell lung cancer evolution.在非小细胞肺癌演变过程中,DNA甲基化与基因组改变相互协作。
Nat Genet. 2025 Sep 10. doi: 10.1038/s41588-025-02307-x.
3
Cancer-specific Regulation of Metabolic and Epigenetic Pathways by Dietary Phytochemicals.膳食植物化学物质对代谢和表观遗传途径的癌症特异性调控

本文引用的文献

1
Immune evolution from preneoplasia to invasive lung adenocarcinomas and underlying molecular features.从癌前病变到浸润性肺腺癌的免疫进化及其潜在分子特征。
Nat Commun. 2021 May 11;12(1):2722. doi: 10.1038/s41467-021-22890-x.
2
Metabolic barriers to cancer immunotherapy.癌症免疫疗法的代谢障碍。
Nat Rev Immunol. 2021 Dec;21(12):785-797. doi: 10.1038/s41577-021-00541-y. Epub 2021 Apr 29.
3
Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing.
Pharm Res. 2025 Aug;42(8):1443-1457. doi: 10.1007/s11095-025-03898-0. Epub 2025 Aug 4.
4
Deciphering bidirectional causal links between oxidative stress and lung cancer risk through Mendelian randomization.通过孟德尔随机化解读氧化应激与肺癌风险之间的双向因果关系。
Discov Oncol. 2025 Jul 28;16(1):1421. doi: 10.1007/s12672-025-03289-2.
5
Deciphering the transcriptional regulatory network driving lung adenocarcinoma progression.解析驱动肺腺癌进展的转录调控网络。
Med Oncol. 2025 Jul 14;42(8):330. doi: 10.1007/s12032-025-02887-y.
6
Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.肺腺癌中前列腺素D2信号轴的生物学及预后相关见解
Front Pharmacol. 2025 May 22;16:1562261. doi: 10.3389/fphar.2025.1562261. eCollection 2025.
7
Post-translational modifications and the reprogramming of tumor metabolism.翻译后修饰与肿瘤代谢重编程。
Discov Oncol. 2025 May 26;16(1):929. doi: 10.1007/s12672-025-02674-1.
8
Rapid and Noninvasive Early Detection of Lung Cancer by Integration of Machine Learning and Salivary Metabolic Fingerprints Using MS LOC Platform: A Large-Scale Multicenter Study.使用MS LOC平台整合机器学习和唾液代谢指纹图谱进行肺癌的快速无创早期检测:一项大规模多中心研究
Adv Sci (Weinh). 2025 Jun;12(22):e2416719. doi: 10.1002/advs.202416719. Epub 2025 May 14.
9
Metabolic characteristics of benign and malignant pulmonary nodules and establishment of invasive lung adenocarcinoma model by high-resolution mass spectrometry.良性与恶性肺结节的代谢特征及基于高分辨率质谱法建立浸润性肺腺癌模型
BMC Cancer. 2025 May 8;25(1):844. doi: 10.1186/s12885-025-14253-2.
10
Proteogenomic characterization reveals tumorigenesis and progression of lung cancer manifested as subsolid nodules.蛋白质基因组学特征揭示了以亚实性结节表现的肺癌的肿瘤发生和进展。
Nat Commun. 2025 Mar 11;16(1):2414. doi: 10.1038/s41467-025-57364-x.
通过单细胞RNA测序解析表现为肺亚实性结节的肺腺癌多细胞生态系统。
Sci Adv. 2021 Jan 27;7(5). doi: 10.1126/sciadv.abd9738. Print 2021 Jan.
4
Linking EMT programmes to normal and neoplastic epithelial stem cells.将 EMT 程序与正常和肿瘤上皮干细胞联系起来。
Nat Rev Cancer. 2021 May;21(5):325-338. doi: 10.1038/s41568-021-00332-6. Epub 2021 Feb 5.
5
Integrative Proteomic Characterization of Human Lung Adenocarcinoma.人类肺腺癌的综合蛋白质组学特征分析。
Cell. 2020 Jul 9;182(1):245-261.e17. doi: 10.1016/j.cell.2020.05.043.
6
Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression.东亚非吸烟肺癌的蛋白质基因组学揭示了发病机制和进展的分子特征。
Cell. 2020 Jul 9;182(1):226-244.e17. doi: 10.1016/j.cell.2020.06.012.
7
Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.基于基因组与蛋白质组联合分析的肺腺癌治疗靶点研究
Cell. 2020 Jul 9;182(1):200-225.e35. doi: 10.1016/j.cell.2020.06.013.
8
Metabolic reprogramming and cancer progression.代谢重编程与癌症进展。
Science. 2020 Apr 10;368(6487). doi: 10.1126/science.aaw5473.
9
Integrating genomic features for non-invasive early lung cancer detection.整合基因组特征进行非侵入性早期肺癌检测。
Nature. 2020 Apr;580(7802):245-251. doi: 10.1038/s41586-020-2140-0. Epub 2020 Mar 25.
10
Genomic and Transcriptomic Characterization of Natural Killer T Cell Lymphoma.自然杀伤 T 细胞淋巴瘤的基因组和转录组特征。
Cancer Cell. 2020 Mar 16;37(3):403-419.e6. doi: 10.1016/j.ccell.2020.02.005.