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Metabolic landscape of the tumor microenvironment at single cell resolution

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  • Zhengtao Xiao

    (Duke University School of Medicine)

  • Ziwei Dai

    (Duke University School of Medicine)

  • Jason W. Locasale

    (Duke University School of Medicine)

Abstract

The tumor milieu consists of numerous cell types each existing in a different environment. However, a characterization of metabolic heterogeneity at single-cell resolution is not established. Here, we develop a computational pipeline to study metabolic programs in single cells. In two representative human cancers, melanoma and head and neck, we apply this algorithm to define the intratumor metabolic landscape. We report an overall discordance between analyses of single cells and those of bulk tumors with higher metabolic activity in malignant cells than previously appreciated. Variation in mitochondrial programs is found to be the major contributor to metabolic heterogeneity. Surprisingly, the expression of both glycolytic and mitochondrial programs strongly correlates with hypoxia in all cell types. Immune and stromal cells could also be distinguished by their metabolic features. Taken together this analysis establishes a computational framework for characterizing metabolism using single cell expression data and defines principles of the tumor microenvironment.

Suggested Citation

  • Zhengtao Xiao & Ziwei Dai & Jason W. Locasale, 2019. "Metabolic landscape of the tumor microenvironment at single cell resolution," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11738-0
    DOI: 10.1038/s41467-019-11738-0
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    Cited by:

    1. Guohe Song & Yang Shi & Lu Meng & Jiaqiang Ma & Siyuan Huang & Juan Zhang & Yingcheng Wu & Jiaxin Li & Youpei Lin & Shuaixi Yang & Dongning Rao & Yifei Cheng & Jian Lin & Shuyi Ji & Yuming Liu & Shan , 2022. "Single-cell transcriptomic analysis suggests two molecularly distinct subtypes of intrahepatic cholangiocarcinoma," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Yuefan Huang & Vakul Mohanty & Merve Dede & Kyle Tsai & May Daher & Li Li & Katayoun Rezvani & Ken Chen, 2023. "Characterizing cancer metabolism from bulk and single-cell RNA-seq data using METAFlux," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Handong Sun & Lishen Zhang & Zhonglin Wang & Danling Gu & Mengyan Zhu & Yun Cai & Lu Li & Jiaqi Tang & Bin Huang & Bakwatanisa Bosco & Ning Li & Lingxiang Wu & Wei Wu & Liangyu Li & Yuan Liang & Lin L, 2023. "Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    4. Ke Song & Xinyan Yang & Geng An & Xinyu Xia & Jiexiang Zhao & Xiaoheng Xu & Cong Wan & Tianyuan Liu & Yi Zheng & Shaofang Ren & Mei Wang & Gang Chang & Shane J. F. Cronin & Josef M. Penninger & Tao Ji, 2022. "Targeting APLN/APJ restores blood-testis barrier and improves spermatogenesis in murine and human diabetic models," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    5. Bárbara Andrade Barbosa & Saskia D. Asten & Ji Won Oh & Arantza Farina-Sarasqueta & Joanne Verheij & Frederike Dijk & Hanneke W. M. Laarhoven & Bauke Ylstra & Juan J. Garcia Vallejo & Mark A. Wiel & Y, 2021. "Bayesian log-normal deconvolution for enhanced in silico microdissection of bulk gene expression data," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    6. Kang Wang & Ioannis Zerdes & Henrik J. Johansson & Dhifaf Sarhan & Yizhe Sun & Dimitris C. Kanellis & Emmanouil G. Sifakis & Artur Mezheyeuski & Xingrong Liu & Niklas Loman & Ingrid Hedenfalk & Jonas , 2024. "Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer," Nature Communications, Nature, vol. 15(1), pages 1-24, December.
    7. Zhong-Yin Huang & Ming-Ming Shao & Jian-Chu Zhang & Feng-Shuang Yi & Juan Du & Qiong Zhou & Feng-Yao Wu & Sha Li & Wei Li & Xian-Zhen Huang & Kan Zhai & Huan-Zhong Shi, 2021. "Single-cell analysis of diverse immune phenotypes in malignant pleural effusion," Nature Communications, Nature, vol. 12(1), pages 1-12, December.

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