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文献精选 > 近年高分"单细胞测序"研究（IF≥30，近5年）

Resolving the Spatial and Cellular Architecture of Lung Adenocarcinoma by Multiregion Single-Cell Sequencing. ​

文献信息 ​

DOI10.1158/2159-8290.CD-20-1285
PMID33972311
期刊Cancer discovery
影响因子33.3
JCR 分区Q1
发表年份2021
被引次数78
关键词肺腺癌, 单细胞RNA测序, 细胞异质性, 空间生态, 转录组特征
文献类型Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't
ISSN2159-8274
页码2506-2523
期号11(10)
作者Ansam Sinjab, Guangchun Han, Warapen Treekitkarnmongkol, Kieko Hara, Patrick M Brennan, Minghao Dang, Dapeng Hao, Ruiping Wang, Enyu Dai, Hitoshi Dejima, Jiexin Zhang, Elena Bogatenkova, Beatriz Sanchez-Espiridion, Kyle Chang, Danielle R Little, Samer Bazzi, Linh M Tran, Kostyantyn Krysan, Carmen Behrens, Dzifa Y Duose, Edwin R Parra, Maria Gabriela Raso, Luisa M Solis, Junya Fukuoka, Jianjun Zhang, Boris Sepesi, Tina Cascone, Lauren Averett Byers, Don L Gibbons, Jichao Chen, Seyed Javad Moghaddam, Edwin J Ostrin, Daniel Rosen, John V Heymach, Paul Scheet, Steven M Dubinett, Junya Fujimoto, Ignacio I Wistuba, Christopher S Stevenson, Avrum Spira, Linghua Wang, Humam Kadara

一句话小结 ​

本研究通过对五例早期肺腺癌（LUAD）及其周围正常肺组织的单细胞RNA测序，揭示了LUAD细胞群体在空间上的演变及其与正常组织的差异，发现肿瘤内细胞异质性和转录谱系的塑性，同时识别出促肿瘤表型的关键调节因子。这些结果为LUAD的空间生态系统提供了重要的基础数据，并为未来的早期干预和治疗靶点识别奠定了基础。

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肺腺癌 · 单细胞RNA测序 · 细胞异质性 · 空间生态 · 转录组特征

摘要 ​

对肺腺癌（LUAD）个体细胞群体的地理空间结构知之甚少。在此，我们对来自五例早期LUAD的186,916个细胞以及14个空间上与肿瘤相关的多区域正常肺组织进行了单细胞RNA测序。我们显示，细胞谱系、状态和转录组特征在正常区域到LUAD之间呈现地理空间演变。LUAD还表现出在单个部位内显著的肿瘤内细胞异质性以及转录谱系塑性程序。与此相反，靠近LUAD的正常组织中调节性T细胞表型增加，而细胞毒性CD8+ T细胞、抗原呈递巨噬细胞和炎症树突细胞的特征和比例则减少。我们进一步发现，LUAD配体-受体相互作用组中上调了上皮CD24的表达，这促进了促肿瘤表型的形成。这些数据提供了LUAD演变的空间图谱，并为其治疗靶点的识别提供了资源。重要性：外周肺和早期LUAD的地理空间生态系统尚不为人知。我们的多区域单细胞测序分析揭示了LUAD从肺部的空间和生态演变中的细胞群体、状态和表型，这些都构成了早期干预的高潜力靶点。本文在本期的“本期热点”中被突出展示，见第2355页。

英文摘要 ​

Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing of 186,916 cells from five early-stage LUADs and 14 multiregion normal lung tissues of defined spatial proximities from the tumors. We show that cellular lineages, states, and transcriptomic features geospatially evolve across normal regions to LUADs. LUADs also exhibit pronounced intratumor cell heterogeneity within single sites and transcriptional lineage-plasticity programs. T regulatory cell phenotypes are increased in normal tissues with proximity to LUAD, in contrast to diminished signatures and fractions of cytotoxic CD8+ T cells, antigen-presenting macrophages, and inflammatory dendritic cells. We further find that the LUAD ligand-receptor interactome harbors increased expression of epithelial CD24, which mediates protumor phenotypes. These data provide a spatial atlas of LUAD evolution, and a resource for identification of targets for its treatment. SIGNIFICANCE: The geospatial ecosystem of the peripheral lung and early-stage LUAD is not known. Our multiregion single-cell sequencing analyses unravel cell populations, states, and phenotypes in the spatial and ecologic evolution of LUAD from the lung that comprise high-potential targets for early interception.This article is highlighted in the In This Issue feature, p. 2355.

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主要研究问题 ​

  1. 在多区域单细胞测序中，如何确保样本的代表性以反映不同阶段的肺腺癌演变？
  2. 除了T调节细胞外，是否还有其他免疫细胞在肺腺癌微环境中发挥关键作用？
  3. 在LUAD的细胞异质性中，是否可以识别出特定的基因表达模式与肿瘤进展相关？
  4. 针对肺腺癌的治疗，如何利用单细胞RNA测序数据来识别潜在的靶点？
  5. 在肺腺癌的研究中，如何评估正常肺组织与肿瘤组织之间的细胞相互作用及其影响？

核心洞察 ​

研究背景和目的 ​

肺腺癌（LUAD）的细胞群体在空间上的结构尚不明确。本文旨在通过单细胞RNA测序技术，探讨早期LUAD中细胞群体的地理空间演变，揭示正常肺组织与LUAD之间的细胞谱系、状态及转录组特征的变化。

主要方法/材料/实验设计 ​

研究采用单细胞RNA测序技术，对来自五例早期LUAD的186,916个细胞及14个不同空间位置的正常肺组织进行分析。实验设计如下：

Mermaid diagram
  1. 样本收集：选择五例早期LUAD及其周围14个正常肺组织样本。
  2. 单细胞RNA测序：对收集的细胞进行高通量单细胞RNA测序。
  3. 数据分析：使用生物信息学工具分析细胞谱系、转录组特征和细胞表型。
  4. 细胞异质性评估：分析LUAD内细胞的异质性和转录谱系的可塑性。

关键结果和发现 ​

  • LUAD的细胞谱系、状态和转录组特征在正常组织到LUAD之间呈现空间演变。
  • LUAD内部存在显著的细胞异质性，尤其是在单个肿瘤部位。
  • 正常组织中靠近LUAD的区域，调节性T细胞表型增加，而细胞毒性CD8+ T细胞、抗原呈递巨噬细胞和炎症树突状细胞的数量和特征则减少。
  • LUAD的配体-受体相互作用网络中，表皮细胞CD24的表达增加，可能促进肿瘤表型的形成。

主要结论/意义/创新性 ​

本研究提供了LUAD演变的空间图谱，揭示了正常肺与早期LUAD之间的细胞群体和表型的生态演变。这些发现为LUAD的早期干预提供了高潜力的靶点，具有重要的临床意义和创新性。

研究局限性和未来方向 ​

  • 研究仅限于早期LUAD，尚需在不同阶段的LUAD中进行验证。
  • 未来可结合临床数据，探讨这些细胞群体与患者预后之间的关系。
  • 建议开展更大规模的多中心研究，以进一步验证和扩展这些发现。

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  10. Spatial reconstruction of single-cell gene expression data. - Rahul Satija;Jeffrey A Farrell;David Gennert;Alexander F Schier;Aviv Regev - Nature biotechnology (2015)

引用本文的文献 ​

  1. Applications of single-cell sequencing in cancer research: progress and perspectives. - Yalan Lei;Rong Tang;Jin Xu;Wei Wang;Bo Zhang;Jiang Liu;Xianjun Yu;Si Shi - Journal of hematology & oncology (2021)
  2. Tumor Immunology and Immunotherapy of Non-Small-Cell Lung Cancer. - Tina Cascone;Jared Fradette;Monika Pradhan;Don L Gibbons - Cold Spring Harbor perspectives in medicine (2022)
  3. Lung Cancer Computational Biology and Resources. - Ling Cai;Guanghua Xiao;David Gerber;John D Minna;Yang Xie - Cold Spring Harbor perspectives in medicine (2022)
  4. Weighted Gene Co-Expression Network Analysis and Treatment Strategies of Tumor Recurrence-Associated Hub Genes in Lung Adenocarcinoma. - Zhengze Shen;Shengwei Liu;Jie Liu;Jingdong Liu;Caoyuan Yao - Frontiers in genetics (2021)
  5. Potential Immune Biomarker Candidates and Immune Subtypes of Lung Adenocarcinoma for Developing mRNA Vaccines. - Yang Wang;Huaicheng Tan;Ting Yu;Xiaoxuan Chen;Fangqi Jing;Huashan Shi - Frontiers in immunology (2021)
  6. Deciphering the Immune-Tumor Interplay During Early-Stage Lung Cancer Development via Single-Cell Technology. - Wei-Wei Chen;Wei Liu;Yingze Li;Jun Wang;Yijiu Ren;Guangsuo Wang;Chang Chen;Hanjie Li - Frontiers in oncology (2021)
  7. Differential LysoTracker Uptake Defines Two Populations of Distal Epithelial Cells in Idiopathic Pulmonary Fibrosis. - Roxana Maria Wasnick;Irina Shalashova;Jochen Wilhelm;Ali Khadim;Nicolai Schmidt;Holger Hackstein;Andreas Hecker;Konrad Hoetzenecker;Werner Seeger;Saverio Bellusci;Elie El Agha;Clemens Ruppert;Andreas Guenther - Cells (2022)
  8. Single-Cell RNA Sequencing in Lung Cancer: Revealing Phenotype Shaping of Stromal Cells in the Microenvironment. - Jianhong Zhang;Chengyang Song;Ye Tian;Xueying Yang - Frontiers in immunology (2021)
  9. Distinct Immune Gene Programs Associated with Host Tumor Immunity, Neoadjuvant Chemotherapy, and Chemoimmunotherapy in Resectable NSCLC. - Pedro Rocha;Jiexin Zhang;Raquel Laza-Briviesca;Alberto Cruz-Bermúdez;Neus Bota-Rabassedas;Beatriz Sanchez-Espiridon;Katsuhiro Yoshimura;Carmen Behrens;Wei Lu;Ximing Tang;Apar Pataer;Edwin R Parra;Cara Haymaker;Junya Fujimoto;Stephen G Swisher;John V Heymach;Don L Gibbons;J Jack Lee;Boris Sepesi;Tina Cascone;Luisa M Solis;Mariano Provencio;Ignacio I Wistuba;Humam Kadara - Clinical cancer research : an official journal of the American Association for Cancer Research (2022)
  10. Distinct molecular and immune hallmarks of inflammatory arthritis induced by immune checkpoint inhibitors for cancer therapy. - Sang T Kim;Yanshuo Chu;Mercy Misoi;Maria E Suarez-Almazor;Jean H Tayar;Huifang Lu;Maryam Buni;Jordan Kramer;Emma Rodriguez;Zulekha Hussain;Sattva S Neelapu;Jennifer Wang;Amishi Y Shah;Nizar M Tannir;Matthew T Campbell;Don L Gibbons;Tina Cascone;Charles Lu;George R Blumenschein;Mehmet Altan;Bora Lim;Vincente Valero;Monica E Loghin;Janet Tu;Shannon N Westin;Aung Naing;Guillermo Garcia-Manero;Noha Abdel-Wahab;Hussein A Tawbi;Patrick Hwu;Isabella C Glitza Oliva;Michael A Davies;Sapna P Patel;Jun Zou;Andrew Futreal;Adi Diab;Linghua Wang;Roza Nurieva - Nature communications (2022)

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