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A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells
Open accessAbstract
cDCs revealed their differences in transcription factors and external stimulus. Additionally, pro-angiogenic tumor-associated macrophages (TAMs) were characterized with diverse markers across different cancer types, and the composition of TIMs appeared to be associated with certain features of somatic mutations and gene expressions. Our results provide a systematic view of the highly heterogeneous TIMs and suggest future avenues for rational, targeted immunotherapies.
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“This is in agreement with previous observations showing low expression of Toll-like receptor (TLR) signaling genes and low innate immune activity of cDC3_LAMP348 and the “pro-inflammatory” properties of cDC2_FCN1 and cDC2_IL1B in blood51.”
From Transformer for one stop interpretable cell type annotation (2023) · cites this paper as [48]
In the citing paper
“On the cDCs populations, TOSICA reveals that the same cDC subsets from different tumor types are clustered together (Supplementary Fig. 12b), which is consistent with previous observations48.”
From Transformer for one stop interpretable cell type annotation (2023) · cites this paper as [48]
In the citing paper
“As interpretable trajectories, the diffusion map52 based on TOSICA attention embedding confirms two potential origins of the cDC3_LAMP3 from cDC1s and cDC2-CXCL9, as previously suggested48 (Fig. 4d).”
From Transformer for one stop interpretable cell type annotation (2023) · cites this paper as [48]
In the citing paper
“Furthermore, benefiting from its high resolution, TOSICA identifies several subtypes of monocytes that have not been discovered in the original publication48 (Fig. 4h), all having their own biological signatures and potentially different functions (Supplementary Fig. 12e).”
From Transformer for one stop interpretable cell type annotation (2023) · cites this paper as [48]
In the citing paper
“Furthermore, the map reveals another state transition path from cDC2 to pro-inflammatory cDC2 subtypes (Fig. 4d), which has not been observed in the previous analysis48.”
From Transformer for one stop interpretable cell type annotation (2023) · cites this paper as [48]
In the citing paper
“This dataset contains tumor infiltrating myeloid cells from multiple different tumor types [21].”
From A Deep Dive into Single-Cell RNA Sequencing Foundation Models (2023) · cites this paper as [21]
Citations
Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,724
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
Fast and accurate long-read alignment with Burrows-Wheeler transform.
Li, H., & Durbin, R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp698 · Cited by 12,063
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,457
SCANPY: large-scale single-cell gene expression data analysis
Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology · doi:10.1186/s13059-017-1382-0 · Cited by 8,881
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
Alternative activation of macrophages
Gordon, S. (2003) · Nature Reviews Immunology · doi:10.1038/nri978 · Cited by 6,189
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de Visser, K. E., & Joyce, J. A. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.02.016 · Cited by 4,059
Macrophages as tools and targets in cancer therapy
Mantovani, A., Allavena, P., Marchesi, F., & Garlanda, C. (2022) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00520-5 · Cited by 1,807
scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI
Cui, H., Wang, C., Maan, H., Pang, K., Luo, F., & Wang, B. (2023) · doi:10.1101/2023.04.30.538439 · Cited by 1,694
“) dataset [33] can be accessed from the Gene Expression Omnibus 794 (GEO) database using the accession number GSE154763.”
MethodImmune checkpoint therapy—current perspectives and future directions
Sharma, P., Goswami, S., Raychaudhuri, D., Siddiqui, B. A., Singh, P., Nagarajan, A., Liu, J., Subudhi, S. K., Poon, C., Gant, K. L., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.006 · Cited by 1,206
Qi, J., Sun, H., Zhang, Y., Wang, Z., Xun, Z., Li, Z., Ding, X., Bao, R., Hong, L., Jia, W., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29366-6 · Cited by 997
Self-citationAn integrated cell atlas of the lung in health and disease
Sikkema, L., Ramírez-Suástegui, C., Strobl, D. C., Gillett, T. E., Zappia, L., Madissoon, E., Markov, N. S., Zaragosi, L., Ji, Y., Ansari, M., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02327-2 · Cited by 930
Zhang, Y., Chen, H., Mo, H., Hu, X., Gao, R., Zhao, Y., Liu, B., Niu, L., Sun, X., Yu, X., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.09.010 · Cited by 783
Self-citationClinical relevance of tumour-associated macrophages
Pittet, M. J., Michielin, O. A., & Migliorini, D. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-022-00620-6 · Cited by 793
Cold and hot tumors: from molecular mechanisms to targeted therapy
Wu, B., Zhang, B., Li, B., Wu, H., & Jiang, M. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01979-x · Cited by 811
Self-citationMacrophage diversity in cancer revisited in the era of single-cell omics
Ma, R., Black, A., & Qian, B. (2022) · Trends in Immunology · doi:10.1016/j.it.2022.04.008 · Cited by 732
CXCL9:SPP1 macrophage polarity identifies a network of cellular programs that control human cancers
Bill, R., Wirapati, P., Messemaker, M., Roh, W., Zitti, B., Duval, F., Kiss, M., Park, J. C., Saal, T. M., Hoelzl, J., et al. (2023) · Science · doi:10.1126/science.ade2292 · Cited by 698
Dimitrov, D., Türei, D., Garrido-Rodriguez, M., Burmedi, P. L., Nagai, J. S., Boys, C., Ramirez Flores, R. O., Kim, H., Szalai, B., Costa, I. G., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30755-0 · Cited by 664
Dendritic cell subsets in cancer immunity and tumor antigen sensing
Prete, A. D., Salvi, V., Soriani, A., Laffranchi, M., Sozio, F., Bosisio, D., & Sozzani, S. (2023) · Cellular and Molecular Immunology · doi:10.1038/s41423-023-00990-6 · Cited by 682
Macrophages in health and disease
Park, M. D., Silvin, A., Ginhoux, F., & Merad, M. (2022) · Cell · doi:10.1016/j.cell.2022.10.007 · Cited by 644
A timeline of tumour-associated macrophage biology
Cassetta, L., & Pollard, J. W. (2023) · Nature reviews. Cancer · doi:10.1038/s41568-022-00547-1 · Cited by 615
Applications of single-cell sequencing in cancer research: progress and perspectives
Lei, Y., Tang, R., Xu, J., Wang, W., Zhang, B., Liu, J., Yu, X., & Shi, S. (2021) · Journal of Hematology & Oncology · doi:10.1186/s13045-021-01105-2 · Cited by 610
Self-citationCancer stem cells: advances in knowledge and implications for cancer therapy
Chu, X., Tian, W., Ning, J., Xiao, G., Zhou, Y., Wang, Z., Zhai, Z., Tanzhu, G., Yang, J., & Zhou, R. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01851-y · Cited by 656
Luo, H., Xia, X., Huang, L., An, H., Cao, M., Kim, G. D., Chen, H., Zhang, W., Shu, Y., Kong, X., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34395-2 · Cited by 610
Self-citationLu, Y., Yang, A., Quan, C., Pan, Y., Zhang, H., Li, Y., Gao, C., Lu, H. X., Wang, X., Cao, P., et al. (2020) · Nature Communications · doi:10.1038/s41467-022-32283-3 · Cited by 564
Self-citationBarkley, D., Moncada, R., Pour, M., Liberman, D. A., Dryg, I., Werba, G., Wang, W., Baron, M., Rao, A., Xia, B., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01141-9 · Cited by 532
Lactate and lactylation in cancer
Chen, J., Huang, Z., Chen, Y., Tian, H., Chai, P., Shen, Y., Yao, Y., Xu, S., Ge, S., & Jia, R. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02082-x · Cited by 545
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Lasser, S., Kurt, F. G. Ö., Arkhypov, I., Utikal, J. S., & Umansky, V. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00846-y · Cited by 523
Rational combinations of targeted cancer therapies: background, advances and challenges
Jin, H., Wang, L., & Bernards, R. (2023) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00615-z · Cited by 503
A pan-cancer single-cell panorama of human natural killer cells
Tang, F., Li, J., Qi, L., Liu, D., Bo, Y., Qin, S., Miao, Y., Yu, K., Hou, W., Li, J., et al. (2023) · Cell · doi:10.1016/j.cell.2023.07.034 · Cited by 450
Self-citationNeutrophil profiling illuminates anti-tumor antigen-presenting potency
Wu, Y. C., Ma, J., Yang, X., Fang, N., Zhang, T., Ji, S., Rao, D., Feng, H., Gao, K., Gu, X., et al. (2024) · Cell · doi:10.1016/j.cell.2024.02.005 · Cited by 453
Self-citationImmune regulation through tryptophan metabolism
Seo, S., & Kwon, B. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-023-01028-7 · Cited by 440
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Caronni, N., Terza, F. L., Vittoria, F. M., Barbiera, G., Mezzanzanica, L., Cuzzola, V., Barresi, S., Pellegatta, M., Canevazzi, P., Dunsmore, G., et al. (2023) · Nature · doi:10.1038/s41586-023-06685-2 · Cited by 418
Andersson, A., Larsson, L., Stenbeck, L., Salmén, F., Ehinger, A., Wu, S. Z., Al-Eryani, G., Roden, D., Swarbrick, A., Borg, Å., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26271-2 · Cited by 404
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Heras‐Murillo, I., Adán‐Barrientos, I., Galán, M. Á., Wculek, S. K., & Sancho, D. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-024-00859-1 · Cited by 418
Hu, J., Zhang, L., Xia, H., Yan, Y., Zhu, X., Sun, F., Sun, L., Li, S., Li, D., Wang, J., et al. (2023) · Genome Medicine · doi:10.1186/s13073-023-01164-9 · Cited by 410
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Sorin, M., Rezanejad, M., Karimi, E., Fiset, B., Desharnais, L., Perus, L. J. M., Milette, S., Yu, M. W., Maritan, S. M., Doré, S., et al. (2023) · Nature · doi:10.1038/s41586-022-05672-3 · Cited by 395
Duong, E., Fessenden, T. B., Lutz, E., Dinter, T., Yim, L., Blatt, S., Bhutkar, A., Wittrup, K. D., & Spranger, S. (2022) · Immunity · doi:10.1016/j.immuni.2021.10.020 · Cited by 372
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Zhang, A., Miao, K., Sun, H., & Deng, C. (2022) · International Journal of Biological Sciences · doi:10.7150/ijbs.72534 · Cited by 379
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Binnewies, M., Pollack, J. L., Rudolph, J., Dash, S., Abushawish, M., Lee, T., Jahchan, N. S., Canaday, P., Lu, E., Norng, M., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109844 · Cited by 365
Roles of macrophages in tumor development: a spatiotemporal perspective
Bied, M., Ho, W. W., Ginhoux, F., & Blériot, C. (2023) · Cellular and Molecular Immunology · doi:10.1038/s41423-023-01061-6 · Cited by 381
Partners, C.-N. M. A., Bai, X. L., Bào, Y., Bei, S., Bu, C., Cao, R., Cao, Y., Cen, H., Chao, J., Chen, F., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1078 · Cited by 355
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Kersten, K., Hu, K. H., Combes, A. J., Samad, B., Harwin, T., Ray, A., Rao, A. A., Cai, E., Marchuk, K., Artichoker, J., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2022.05.004 · Cited by 357
Dendritic cells as shepherds of T cell immunity in cancer
Pittet, M. J., Pilato, M. D., Garris, C., & Mempel, T. R. (2023) · Immunity · doi:10.1016/j.immuni.2023.08.014 · Cited by 337
SLC38A2 and glutamine signalling in cDC1s dictate anti-tumour immunity
Guo, C., You, Z., Shi, H., Sun, Y., Du, X., Palacios, G. F., Guy, C. S., Yuan, S., Chapman, N. M., Lim, S. A., et al. (2023) · Nature · doi:10.1038/s41586-023-06299-8 · Cited by 325
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Marciscano, A. E. E., & Anandasabapathy, N. (2021) · Seminars in Immunology · doi:10.1016/j.smim.2021.101481 · Cited by 314
Gao, Y., Li, J., Cheng, W., Diao, T., Liu, H., Bo, Y., Liu, C., Zhou, W., Chen, M., Zhang, Y., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.08.020 · Cited by 320
Self-citationWerba, G., Weissinger, D., Kawaler, E. A., Zhao, E., Kalfakakou, D., Dhara, S., Wang, L., Lim, H. B., Oh, G., Jing, X., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36296-4 · Cited by 303
Zou, Y., Ye, F., Kong, Y., Hu, X., Deng, X., Xie, J., Song, C., Ou, X., Wu, S., Wu, L., et al. (2022) · Advanced Science · doi:10.1002/advs.202203699 · Cited by 285
Self-citationShi, X., Wang, X., Yao, W., Shi, D., Shao, X., Lu, Z., Chai, Y., Song, J., Tang, W., & Wang, X. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01885-2 · Cited by 296
Self-citationKundu, M., Butti, R., Panda, V. K., Malhotra, D., Das, S., Mitra, T., Kapse, P., Gosavi, S., & Kundu, G. C. (2024) · Molecular Cancer · doi:10.1186/s12943-024-01990-4 · Cited by 284
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Reiss, K. A., Angelos, M. G., Dees, E. C., Yuan, Y., Ueno, N. T., Pohlmann, P. R., Johnson, M. L., Chao, J., Shestova, O. E., Serody, J. S., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03495-z · Cited by 268
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van Vlerken-Ysla, L. E., Tyurina, Y. Y., Kagan, V. E., & Gabrilovich, D. I. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.02.009 · Cited by 274
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Kvedaraite, E., & Ginhoux, F. (2022) · Science Immunology · doi:10.1126/sciimmunol.abm9409 · Cited by 272
Tan, J., Fan, W., Liu, T., Zhu, B., Liu, Y., Wang, S., Wu, J. H., Liu, J., Zou, F., Wei, J., et al. (2023) · Journal of Hepatology · doi:10.1016/j.jhep.2023.02.032 · Cited by 261
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Kumar, T., Nee, K., Wei, R., He, S., Nguyen, Q., Bai, S., Blake, K., Pein, M., Gong, Y., Sei, E., et al. (2023) · Nature · doi:10.1038/s41586-023-06252-9 · Cited by 260
Wang, C., Yu, Q., Song, T., Wang, Z., Song, L., Yang, Y., Shao, J., Li, J., Ni, Y., Chao, N., et al. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01130-8 · Cited by 255
Self-citationMapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer
Li, R., Ferdinand, J. R., Loudon, K. W., Bowyer, G., Laidlaw, S., Muyas, F., Mamanova, L., Neves, J. B., Bolt, L., Fasouli, E. S., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.11.001 · Cited by 254
Wang, F., Long, J., Li, L., Wu, Z., Da, T.-T., Wang, X., Huang, C., Jiang, Y., Yao, X., Ma, H., et al. (2023) · Science Advances · doi:10.1126/sciadv.adf5464 · Cited by 263
Self-citationExploiting innate immunity for cancer immunotherapy
Yi, M., Li, T., Niu, M., Mei, Q., Zhao, B., Chu, Q., Dai, Z., & Wu, K. (2023) · Molecular Cancer · doi:10.1186/s12943-023-01885-w · Cited by 250
Han, G., Yang, G., Hao, D., Lü, Y., Thein, K. Z., Simpson, B. S. S., Chen, J., Sun, R., Alhalabi, O., Wang, R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25894-9 · Cited by 238
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Kloosterman, D. J., Erbani, J., Boon, M., Farber, M., Handgraaf, S. M., Ando-Kuri, M., Sánchez-López, E., Fontein, B., Mertz, M., Nieuwland, M., et al. (2024) · Cell · doi:10.1016/j.cell.2024.07.030 · Cited by 231
Wang, W., Li, T., Cheng, Y., Li, F., Qi, S., Mao, M., Wu, J., Liu, Q., Zhang, X., Li, X., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.03.013 · Cited by 246
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Chu, X., Tian, Y., & Lv, C. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02064-1 · Cited by 234
Zhang, Y., Liu, G., Zeng, Q., Wu, W., Lei, K., Zhang, C., Tang, M., Zhang, Y., Xiang, X., Tan, L., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.07.006 · Cited by 242
Self-citationTietscher, S., Wagner, J., Anzeneder, T., Langwieder, C., Rees, M., Sobottka, B., de Souza, N., & Bodenmiller, B. (2023) · Nature Communications · doi:10.1038/s41467-022-35238-w · Cited by 233
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Khaliq, A. M., Erdoğan, C., Kurt, Z., Turgut, S. S., Grunvald, M. W., Rand, T., Khare, S., Borgia, J. A., Hayden, D. M., Pappas, S. G., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02677-z · Cited by 246
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Baharom, F., Ramirez-Valdez, R. A., Khalilnezhad, A., Khalilnezhad, S., Dillon, M., Hermans, D., Fussell, S. C., Tobin, K. K. S., Dutertre, C., Lynn, G. M., et al. (2022) · Cell · doi:10.1016/j.cell.2022.10.006 · Cited by 220
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Yu, Y., Chen, X., Pan, J., Ning, H., Zhang, Y., Bo, Y., Ren, X., Li, J., Qin, S., Wang, D., et al. (2024) · Cell · doi:10.1016/j.cell.2024.06.038 · Cited by 223
Self-citationSathe, A., Mason, K., Grimes, S. M., Zhou, Z., Lau, B. T., Bai, X., Su, A., Tan, X., Lee, H., Suarez, C. J., et al. (2022) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-22-2041 · Cited by 225
Chen, Y., Wang, D., Li, Y., Lu, Q., Si, W., Bo, Y., Chen, X., Ye, Z., Fan, H., Liu, B., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.06.009 · Cited by 229
Self-citationTan, Y., Flynn, W. F., Sivajothi, S. K., Luo, D., Bozal, S. B., Davé, M., Luciano, A. A., Robson, P., Luciano, D. E., & Courtois, E. T. (2022) · Nature Cell Biology · doi:10.1038/s41556-022-00961-5 · Cited by 223
Xiao, J., Wang, S., Chen, L., Ding, X., Dang, Y., Han, M., Zheng, Y., Shen, H., Wu, S., Wang, M., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.03.021 · Cited by 220
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Lyu, A., Fan, Z., Clark, M., Lea, A., Luong, D., Setayesh, A., Starzinski, A., Wolters, R. M., Arias-Badia, M., Allaire, K., et al. (2024) · Nature · doi:10.1038/s41586-024-08290-3 · Cited by 230
Meiser, P., Knolle, M. A., Hirschberger, A., de Almeida, G. P., Bayerl, F., Lacher, S. B., Pedde, A., Flommersfeld, S., Hönninger, J., Stark, L., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.06.008 · Cited by 208
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Yan, Y., Sun, D., Hu, J., Chen, Y., Sun, L., Yu, H., Xiong, Y., Huang, Z., Xia, H., Zhu, X., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01998-y · Cited by 193
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Liu, Y., Feng, W., Dai, Y., Bao, M., Yuan, Z., He, M., Qin, Z., Liao, S., He, J., Huang, Q., et al. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.709210 · Cited by 190
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Matusiak, M., Hickey, J. W., van IJzendoorn, D. G. P., Lu, G., Kidziński, Ł., Zhu, S., Colburg, D. R. C., Luca, B. A., Phillips, D. J., Brubaker, S. W., et al. (2024) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-1300 · Cited by 190
Li, Y., Zheng, Y., Huang, J., Nie, R., Wu, Q., Zuo, Z., Yuan, S., Yu, K., Liang, C., Pan, Y., et al. (2024) · Gut · doi:10.1136/gutjnl-2024-333617 · Cited by 185
Liu, Z., Gao, Z., Li, B., Li, J., Ou, Y., Yu, X., Zhang, Z., Liu, S., Fu, X., Jin, H., et al. (2022) · OncoImmunology · doi:10.1080/2162402x.2022.2085432 · Cited by 175
Self-citationZheng, X., Wang, X., Cheng, X., Liu, Z., Yin, Y., Li, X., Huang, Z., Wang, Z., Guo, W., Ginhoux, F., et al. (2023) · Nature Cancer · doi:10.1038/s43018-023-00599-8 · Cited by 172
Self-citationSimple and effective embedding model for single-cell biology built from ChatGPT
Chen, Y. T., & Zou, J. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01284-6 · Cited by 205
Tumor macrophage functional heterogeneity can inform the development of novel cancer therapies
Nasir, I., McGuinness, C., Poh, A. R., Ernst, M., Darcy, P. K., & Britt, K. L. (2023) · Trends in Immunology · doi:10.1016/j.it.2023.10.007 · Cited by 168
Metabolism drives macrophage heterogeneity in the tumor microenvironment
Li, S., Yu, J., Huber, A. K., Kryczek, I., Wang, Z., Jiang, L., Li, X., Du, W., Li, G., Wei, S., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110609 · Cited by 179
Self-citationCancer cells impair monocyte-mediated T cell stimulation to evade immunity
Elewaut, A., Estivill, G., Bayerl, F., Castillon, L., Novatchkova, M., Pottendorfer, E., Hoffmann-Haas, L., Schönlein, M., Nguyễn, T. C. B., Lauss, M., et al. (2024) · Nature · doi:10.1038/s41586-024-08257-4 · Cited by 167
A single-cell atlas reveals immune heterogeneity in anti-PD-1-treated non-small cell lung cancer
Liu, Z., Yang, Z., Wu, J., Zhang, W., Sun, Y., Zhang, C., Bai, G., Li, Y., Fan, H., Chen, Y., et al. (2025) · Cell · doi:10.1016/j.cell.2025.03.018 · Cited by 184
Self-citationOver 1000 tools reveal trends in the single-cell RNA-seq analysis landscape
Zappia, L., & Theis, F. J. (2021) · Genome biology · doi:10.1186/s13059-021-02519-4 · Cited by 176
Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis
Xun, Z., Ding, X., Zhang, Y., Zhang, B., Lai, S., Zou, D., Zheng, J., Chen, G., Su, B., Han, L., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36560-7 · Cited by 169
Self-citationPlebanek, M. P., Xue, Y., Nguyen, Y.-V., DeVito, N. C., Wang, X., Holtzhausen, A., Beasley, G. M., Theivanthiran, B., & Hanks, B. A. (2024) · Science Immunology · doi:10.1126/sciimmunol.adi4191 · Cited by 164
Self-citationDiscovering dominant tumor immune archetypes in a pan-cancer census
Combes, A. J., Samad, B., Tsui, J. L., Chew, N. W., Yan, P., Reeder, G. C., Kushnoor, D., Shen, A. S., Davidson, B. R., Barczak, A. J., et al. (2021) · Cell · doi:10.1016/j.cell.2021.12.004 · Cited by 175
Sun, K., Xu, R., Ma, F., Yang, N., Li, Y., Sun, X., Jin, P., Kang, W., Jia, L., Xiong, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32627-z · Cited by 163
Chu, X., Li, X., Zhang, Y., Dang, G., Miao, Y., Xu, W., Wang, J., Zhang, Z., & Cheng, S. (2024) · Nature Cancer · doi:10.1038/s43018-024-00807-z · Cited by 183
Self-citationCAF-induced physical constraints controlling T cell state and localization in solid tumours
Arpinati, L., Carradori, G., & Scherz‐Shouval, R. (2024) · Nature reviews. Cancer · doi:10.1038/s41568-024-00740-4 · Cited by 162
Li, Y., Hu, X., Lin, R., Zhou, G., Zhao, L., Zhao, D., Zhang, Y., Li, W., Zhang, Y., Ma, P., et al. (2022) · Theranostics · doi:10.7150/thno.71833 · Cited by 158
Self-citationYou, S., Li, S., Zeng, L., Song, J., Li, Z., Li, W., Ni, H., Xu, X., Deng, W., Li, H., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.06.014 · Cited by 164
Self-citationClinical landscape of macrophage-reprogramming cancer immunotherapies
Rannikko, J. H., & Hollmén, M. (2024) · British Journal of Cancer · doi:10.1038/s41416-024-02715-6 · Cited by 169
Spatial landscapes of cancers: insights and opportunities
Chen, J., Larsson, L., Swarbrick, A., & Lundeberg, J. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-024-00926-7 · Cited by 156
High-throughput single-сell sequencing in cancer research
Jia, Q., Chu, H., Jin, Z., Long, H., & Zhu, B. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00990-4 · Cited by 157
Wang, Z., Wu, Z., Wang, H., Feng, R., Wang, G., Li, M., Wang, S.-Y., Chen, X., Su, Y., Wang, J., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.019 · Cited by 158
Single-cell transcriptomic profiling reveals the tumor heterogeneity of small-cell lung cancer
Tian, Y., Li, Q., Yang, Z., Zhang, S., Xu, J., Wang, Z., Bai, H., Duan, J., Zheng, B. J., Li, W., et al. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01150-4 · Cited by 153
Self-citation
Metadata
- Authors
- Cheng, S., Li, Z., Gao, R., Xing, B., Gao, Y., Yang, Y., Qin, S., Zhang, L., Ouyang, H., Du, P., Jiang, L., Zhang, B., Yang, Y., Wang, X., Ren, X., Bei, J.-X., Hu, X., Bu, Z., Ji, J., & Zhang, Z.
- Affiliations
- Peking University (CN)
- Peking University Cancer Hospital (CN)
- Peking University Third Hospital (CN)
- Sun Yat-sen University (CN)
- Corresponding author
- Bu, Zhaode
- Ji, Jiafu
- Zhang, Zemin
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 184
- Issue
- 3
- Pages
- 792-809.e23
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W3126902084
- Cited by
- 1,601
- References
- 84
- Citations by year
- 2026: 337 · 2025: 370 · 2024: 377 · 2023: 267 · 2022: 190 · 2021: 58
- FWCI
- 87.30
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China
- Beijing Municipal Science and Technology Commission
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Keywords
- tumor-infiltrating myeloid cells, pan-cancer, single-cell transcriptomics, myeloid dendritic cells, tumor-associated macrophages, myeloid heterogeneity, somatic mutations, cancer immunotherapy, tumor microenvironment
- MeSH terms
- Dendritic Cells, Female, Humans, Macrophages, Male, Mast Cells, Monocytes, Neoplasm Proteins, Neoplasms, Transcription, Genetic, Cell Lineage, Myeloid Cells, Cell Line, Tumor, Lysosomal Membrane Proteins, Single-Cell Analysis, Transcriptome, Lysosomal-Associated Membrane Protein 3
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