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METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics

Author

Listed:
  • Jiahui Jiang

    (The University of Texas MD Anderson Cancer Center
    The University of Texas Health Science Center at Houston)

  • Yunhe Liu

    (The University of Texas MD Anderson Cancer Center)

  • Jiangjiang Qin

    (Zhejiang Cancer Hospital
    Chinese Academy of Sciences)

  • Jianfeng Chen

    (The University of Texas MD Anderson Cancer Center)

  • Jingjing Wu

    (The University of Texas MD Anderson Cancer Center)

  • Melissa P. Pizzi

    (The University of Texas MD Anderson Cancer Center)

  • Rossana Lazcano

    (The University of Texas MD Anderson Cancer Center)

  • Kohei Yamashita

    (The University of Texas MD Anderson Cancer Center)

  • Zhiyuan Xu

    (Zhejiang Cancer Hospital)

  • Guangsheng Pei

    (The University of Texas MD Anderson Cancer Center)

  • Kyung Serk Cho

    (The University of Texas MD Anderson Cancer Center
    The University of Texas Health Science Center at Houston)

  • Yanshuo Chu

    (The University of Texas MD Anderson Cancer Center)

  • Ansam Sinjab

    (The University of Texas MD Anderson Cancer Center)

  • Fuduan Peng

    (The University of Texas MD Anderson Cancer Center)

  • Xinmiao Yan

    (The University of Texas MD Anderson Cancer Center)

  • Guangchun Han

    (The University of Texas MD Anderson Cancer Center)

  • Ruiping Wang

    (The University of Texas MD Anderson Cancer Center)

  • Enyu Dai

    (The University of Texas MD Anderson Cancer Center)

  • Yibo Dai

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences (GSBS))

  • Bogdan A. Czerniak

    (The University of Texas MD Anderson Cancer Center)

  • Andrew Futreal

    (The University of Texas MD Anderson Cancer Center)

  • Anirban Maitra

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Alexander Lazar

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center)

  • Humam Kadara

    (The University of Texas MD Anderson Cancer Center)

  • Amir A. Jazaeri

    (The University of Texas MD Anderson Cancer Center)

  • Xiangdong Cheng

    (Zhejiang Cancer Hospital)

  • Jaffer Ajani

    (The University of Texas MD Anderson Cancer Center)

  • Jianjun Gao

    (The University of Texas MD Anderson Cancer Center)

  • Jian Hu

    (Emory School of Medicine)

  • Linghua Wang

    (The University of Texas MD Anderson Cancer Center
    The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences (GSBS))

Abstract

Recent advances in spatial transcriptomics (ST) techniques provide valuable insights into cellular interactions within the tumor microenvironment (TME). However, most analytical tools lack consideration of histological features and rely on matched single-cell RNA sequencing data, limiting their effectiveness in TME studies. To address this, we introduce the Morphology-Enhanced Spatial Transcriptome Analysis Integrator (METI), an end-to-end framework that maps cancer cells and TME components, stratifies cell types and states, and analyzes cell co-localization. By integrating spatial transcriptomics, cell morphology, and curated gene signatures, METI enhances our understanding of the molecular landscape and cellular interactions within the tissue. We evaluate the performance of METI on ST data generated from various tumor tissues, including gastric, lung, and bladder cancers, as well as premalignant tissues. We also conduct a quantitative comparison of METI with existing clustering and cell deconvolution tools, demonstrating METI’s robust and consistent performance.

Suggested Citation

  • Jiahui Jiang & Yunhe Liu & Jiangjiang Qin & Jianfeng Chen & Jingjing Wu & Melissa P. Pizzi & Rossana Lazcano & Kohei Yamashita & Zhiyuan Xu & Guangsheng Pei & Kyung Serk Cho & Yanshuo Chu & Ansam Sinj, 2024. "METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51708-9
    DOI: 10.1038/s41467-024-51708-9
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    References listed on IDEAS

    as
    1. Ruidong Xue & Qiming Zhang & Qi Cao & Ruirui Kong & Xiao Xiang & Hengkang Liu & Mei Feng & Fangyanni Wang & Jinghui Cheng & Zhao Li & Qimin Zhan & Mi Deng & Jiye Zhu & Zemin Zhang & Ning Zhang, 2022. "Liver tumour immune microenvironment subtypes and neutrophil heterogeneity," Nature, Nature, vol. 612(7938), pages 141-147, December.
    2. Guangchun Han & Ansam Sinjab & Zahraa Rahal & Anne M. Lynch & Warapen Treekitkarnmongkol & Yuejiang Liu & Alejandra G. Serrano & Jiping Feng & Ke Liang & Khaja Khan & Wei Lu & Sharia D. Hernandez & Yu, 2024. "An atlas of epithelial cell states and plasticity in lung adenocarcinoma," Nature, Nature, vol. 627(8004), pages 656-663, March.
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