A universal single-cell atlas decodes pulmonary diseases
ID:68 View Protection:ATTENDEE Updated Time:2025-03-25 14:40:45 Hits:537 Oral Presentation

Start Time:2025-03-30 10:00(Asia/Shanghai)

Duration:20min

Session:S7 前沿论坛 (基因组大数据与AI) » s7前沿论坛(基因组大数据与AI)

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Abstract
Human lung is a complex organ susceptible to various diseases. Single-cell transcriptomic studies provide rich data for addressing specific research questions. Here, we present uniLUNG, the largest lung transcriptomic cell atlas, comprising over 10 million cells across 20 disease and healthy groups. By assembling a universal hierarchical annotation framework and performing a comprehensive data integration benchmarking, we established standardized lung cell nomenclature and marker genes. Using uniLUNG, we identified Lym-monocytes and T-like B cells, new cell types in certain lung diseases, confirming their existence by comparing with external single-cell atlases. Additionally, we discovered the NSCLC-like SCLC, a transitional malignant cell population related to NSCLC-to-SCLC transition, which was validated and characterized in spatial dimensions, revealing its complex role in tumour progression. Overall, uniLUNG provides an extensive representation of human lung cell diversity and serves as an invaluable data resource and a solid foundation for lung research.
Keywords
Speaker
李伟忠
教授 中山大学医学院

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Important Date
  • Conference Date

    Mar 28

    2025

    to

    Mar 30

    2025

  • Apr 15 2025

    Registration deadline

Sponsored By
中国生物信息学学会基因组信息学专业委员会
Organized By
中国农业科学院农业基因组研究所
大鹏湾实验室
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