The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.
Macrophage diversity in cancer revisited in the era of single-cell omics
Open accessAbstract
Tumor-associated macrophages (TAMs) have multiple potent functions in cancer and, thus, represent important therapeutic targets. These diverse functions highlight the heterogenous nature of TAMs. Recent single cell omics technologies have significantly advanced our understanding of the molecular diversity of TAMs. However, a unifying nomenclature of TAM diversity and annotation of their molecular signatures is lacking. Here, we review recent major studies of single cell transcriptome, epigenome, metabolome, and spatial omics of cancer with a specific focus on TAMs. We also propose a consensus model of TAM diversity and present avenues for future research.
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Cites
Exploring the full spectrum of macrophage activation
Mosser, D. M., & Edwards, J. P. (2008) · Nature Reviews Immunology · doi:10.1038/nri2448 · Cited by 9,144
Scenic: single-cell regulatory network inference and clustering.
Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4463 · Cited by 6,520
Macrophage Diversity Enhances Tumor Progression and Metastasis
Qian, B.-Z., & Pollard, J. W. (2010) · Cell · doi:10.1016/j.cell.2010.03.014 · Cited by 5,188
Self-citationThe M1 and M2 paradigm of macrophage activation: Time for reassessment
Martinez, F. O., & Gordon, S. (2014) · F1000Prime Reports · doi:10.12703/p6-13 · Cited by 4,689
Tumour-associated macrophages as treatment targets in oncology
Mantovani, A., Marchesi, F., Malesci, A., Laghi, L., & Allavena, P. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.217 · Cited by 4,033
Blood Monocytes Consist of Two Principal Subsets with Distinct Migratory Properties
Geissmann, F., Jung, S., & Littman, D. R. (2003) · Immunity · doi:10.1016/s1074-7613(03)00174-2 · Cited by 3,391
A guide to immunometabolism for immunologists
O'Neill, L. A. J., Kishton, R. J., & Rathmell, J. (2016) · Nature Reviews Immunology · doi:10.1038/nri.2016.70 · Cited by 3,315
M-1/M-2 Macrophages and the Th1/Th2 Paradigm
Mills, C. D., Kincaid, K., Alt, J. M., Heilman, M. J., & Hill, A. M. (2000) · The Journal of Immunology · doi:10.4049/jimmunol.164.12.6166 · Cited by 3,287
Simultaneous epitope and transcriptome measurement in single cells
Stoeckius, M., Hafemeister, C., Stephenson, W., Houck-Loomis, B., Chattopadhyay, P. K., Swerdlow, H., Satija, R., & Smibert, P. (2017) · Nature Methods · doi:10.1038/nmeth.4380 · Cited by 3,098
CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis
Qian, B.-Z., Li, J., Zhang, H., Kitamura, T., Zhang, J., Campion, L. R., Kaiser, E. A., Snyder, L. A., & Pollard, J. W. (2011) · Nature · doi:10.1038/nature10138 · Cited by 2,874
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Cited by
The evolving tumor microenvironment: From cancer initiation to metastatic outgrowth
de Visser, K. E., & Joyce, J. A. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.02.016 · Cited by 4,059
De Leo, A., Ugolini, A., Yu, X., Scirocchi, F., Scocozza, D., Peixoto, B., Pace, A., D’Angelo, L., Liu, J. K. C., Etame, A. B., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.04.006 · Cited by 319
An exhausted-like microglial population accumulates in aged and APOE4 genotype Alzheimer’s brains
Millet, A., Ledo, J. H., & Tavazoie, S. F. (2024) · Immunity · doi:10.1016/j.immuni.2023.12.001 · Cited by 132
Allgayer, H., Mahapatra, S., Mishra, B., Swain, B., Saha, S., Khanra, S., Kumari, K., Panda, V. K., Malhotra, D., Patil, N. S., et al. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02338-2 · Cited by 127
Timperi, E., Croizer, H., Khantakova, D., Rana, M., Molgora, M., Guerriero, J. L., Mechta-Grigoriou, F., & Romano, E. (2024) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-24-1690 · Cited by 49
Metadata
- Authors
- Ma, R.-Y., Black, A., & Qian, B.-Z.
- Venue
- Trends in Immunology
- Publisher
- Elsevier BV
- Published
- 2022-07
- Volume
- 43
- Issue
- 7
- Pages
- 546-563
- ISSN
- 1471-4906 (ISSN-L)
- OpenAlex
- W4282943635
- Cited by
- 698
- References
- 113
- FWCI
- 12.17
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Ma, R.-Y., Black, A., & Qian, B.-Z. (2022). Macrophage diversity in cancer revisited in the era of single-cell omics. Trends in Immunology. https://doi.org/10.1016/j.it.2022.04.008
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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