Cited by 1,526

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Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer

Zhang, Lei, Li, Ziyi, Skrzypczynska, Katarzyna M., Fang, Qiao, Zhang, Wei, O’Brien, Sarah A., He, Yao, Wang, Lynn, Zhang, Qiming, Kim, Aeryon, Gao, Ranran, Orf, Jessica, Wang, Tao, Sawant, Deepali, Kang, Jiajinlong, Bhatt, Dev, Lu, Daniel, Li, Chi-Ming, Rapaport, Aaron S., Perez, Kristy, Ye, Yingjiang, Wang, Shan, Hu, Xueda, Ren, Xianwen, Ouyang, Wenjun, Shen, Zhanlong, Egen, Jackson G., Zhang, Zemin, Yu, Xin·2020·Cell

Abstract

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for defining cellular diversity in tumors, but its application toward dissecting mechanisms underlying immune-modulating therapies is scarce. We performed scRNA-seq analyses on immune and stromal populations from colorectal cancer patients, identifying specific macrophage and conventional dendritic cell (cDC) subsets as key mediators of cellular cross-talk in the tumor microenvironment. Defining comparable myeloid populations in mouse tumors enabled characterization of their response to myeloid-targeted immunotherapy. Treatment with anti-CSF1R preferentially depleted macrophages with an inflammatory signature but spared macrophage populations that in mouse and human expresses pro-angiogenic/tumorigenic genes. Treatment with a CD40 agonist antibody preferentially activated a cDC population and increased Bhlhe40 + Th1-like cells and CD8 + memory T cells. Our comprehensive analysis of key myeloid subsets in human and mouse identifies critical cellular interactions regulating tumor immunity and defines mechanisms underlying myeloid-targeted immunotherapies currently undergoing clinical testing.

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Crossref · 10.1016/j.cell.2020.03.048

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Research works printed but not linked: 52

  1. Angerer, 2016, destiny: diffusion maps for large-scale single-cell data in R, Bioinformatics, 32, 1241, 10.1093/bioinformatics/btv715 · DOI · Paper page
  2. Ardouin, 2016, Broad and Largely Concordant Molecular Changes Characterize Tolerogenic and Immunogenic Dendritic Cell Maturation in Thymus and Periphery, Immunity, 45, 305, 10.1016/j.immuni.2016.07.019 · DOI
  3. Azizi, 2018, Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment, Cell, 174, 1293, 10.1016/j.cell.2018.05.060 · DOI · Paper page
  4. Binnewies, 2018, Understanding the tumor immune microenvironment (TIME) for effective therapy, Nat. Med., 24, 541, 10.1038/s41591-018-0014-x · DOI · Paper page
  5. Binnewies, 2019, Unleashing Type-2 Dendritic Cells to Drive Protective Antitumor CD4(+) T Cell Immunity, Cell, 177, 556, 10.1016/j.cell.2019.02.005 · DOI
  6. Blatner, 2010, In colorectal cancer mast cells contribute to systemic regulatory T-cell dysfunction, Proc. Natl. Acad. Sci. USA, 107, 6430, 10.1073/pnas.0913683107 · DOI
  7. Brown, 2019, Transcriptional Basis of Mouse and Human Dendritic Cell Heterogeneity, Cell, 179, 846, 10.1016/j.cell.2019.09.035 · DOI
  8. Butowski, 2016, Orally administered colony stimulating factor 1 receptor inhibitor PLX3397 in recurrent glioblastoma: an Ivy Foundation Early Phase Clinical Trials Consortium phase II study, Neuro-oncol., 18, 557, 10.1093/neuonc/nov245 · DOI
  9. Cassier, 2015, CSF1R inhibition with emactuzumab in locally advanced diffuse-type tenosynovial giant cell tumours of the soft tissue: a dose-escalation and dose-expansion phase 1 study, Lancet Oncol., 16, 949, 10.1016/S1470-2045(15)00132-1 · DOI
  10. Cheong, 2010, Microbial stimulation fully differentiates monocytes to DC-SIGN/CD209(+) dendritic cells for immune T cell areas, Cell, 143, 416, 10.1016/j.cell.2010.09.039 · DOI
  11. Chevrier, 2017, An Immune Atlas of Clear Cell Renal Cell Carcinoma, Cell, 169, 736, 10.1016/j.cell.2017.04.016 · DOI
  12. Dalerba, 2011, Single-cell dissection of transcriptional heterogeneity in human colon tumors, Nat. Biotechnol., 29, 1120, 10.1038/nbt.2038 · DOI
  13. DeNardo, 2019, Macrophages as regulators of tumour immunity and immunotherapy, Nat. Rev. Immunol., 19, 369, 10.1038/s41577-019-0127-6 · DOI
  14. DeNardo, 2011, Leukocyte complexity predicts breast cancer survival and functionally regulates response to chemotherapy, Cancer Discov., 1, 54, 10.1158/2159-8274.CD-10-0028 · DOI · Paper page
  15. Dutertre, 2019, Single-Cell Analysis of Human Mononuclear Phagocytes Reveals Subset-Defining Markers and Identifies Circulating Inflammatory Dendritic Cells, Immunity, 51, 573, 10.1016/j.immuni.2019.08.008 · DOI
  16. Galon, 2019, Approaches to treat immune hot, altered and cold tumours with combination immunotherapies, Nat. Rev. Drug Discov., 18, 197, 10.1038/s41573-018-0007-y · DOI
  17. Ganesh, 2019, Immunotherapy in colorectal cancer: rationale, challenges and potential, Nat. Rev. Gastroenterol. Hepatol., 16, 361, 10.1038/s41575-019-0126-x · DOI · Paper page
  18. Grewal, 1998, CD40 and CD154 in cell-mediated immunity, Annu. Rev. Immunol., 16, 111, 10.1146/annurev.immunol.16.1.111 · DOI
  19. Gubin, 2018, High-Dimensional Analysis Delineates Myeloid and Lymphoid Compartment Remodeling during Successful Immune-Checkpoint Cancer Therapy, Cell, 175, 1443, 10.1016/j.cell.2018.11.003 · DOI · Paper page
  20. Gyori, 2018, Compensation between CSF1R+ macrophages and Foxp3+ Treg cells drives resistance to tumor immunotherapy, JCI Insight, 3, 120631, 10.1172/jci.insight.120631 · DOI
  21. Haniffa, 2013, Ontogeny and functional specialization of dendritic cells in human and mouse, Adv. Immunol., 120, 1, 10.1016/B978-0-12-417028-5.00001-6 · DOI
  22. Hume, 2019, The Mononuclear Phagocyte System: The Relationship between Monocytes and Macrophages, Trends Immunol., 40, 98, 10.1016/j.it.2018.11.007 · DOI
  23. Junttila, 2013, Influence of tumour micro-environment heterogeneity on therapeutic response, Nature, 501, 346, 10.1038/nature12626 · DOI · Paper page
  24. Kenny, 2008, The initial steps of ovarian cancer cell metastasis are mediated by MMP-2 cleavage of vitronectin and fibronectin, J. Clin. Invest., 118, 1367, 10.1172/JCI33775 · DOI
  25. Klose, 2016, Innate lymphoid cells as regulators of immunity, inflammation and tissue homeostasis, Nat. Immunol., 17, 765, 10.1038/ni.3489 · DOI
  26. Krystel-Whittemore, 2016, Mast Cell: A Multi-Functional Master Cell, Front. Immunol., 6, 620, 10.3389/fimmu.2015.00620 · DOI
  27. Kumar, 2017, Cancer-Associated Fibroblasts Neutralize the Anti-tumor Effect of CSF1 Receptor Blockade by Inducing PMN-MDSC Infiltration of Tumors, Cancer Cell, 32, 654, 10.1016/j.ccell.2017.10.005 · DOI · Paper page
  28. La Manno, 2018, RNA velocity of single cells, Nature, 560, 494, 10.1038/s41586-018-0414-6 · DOI · Paper page
  29. Lavin, 2017, Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses, Cell, 169, 750, 10.1016/j.cell.2017.04.014 · DOI · Paper page
  30. Lee, 2020, A phase I study of pexidartinib, a colony-stimulating factor 1 receptor inhibitor, in Asian patients with advanced solid tumors, Invest. New Drugs, 38, 99, 10.1007/s10637-019-00745-z · DOI
  31. Li, 2017, Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors, Nat. Genet., 49, 708, 10.1038/ng.3818 · DOI · Paper page
  32. Lin, 2016, IL-1-induced Bhlhe40 identifies pathogenic T helper cells in a model of autoimmune neuroinflammation, J. Exp. Med., 213, 251, 10.1084/jem.20150568 · DOI
  33. MacDonald, 2010, An antibody against the colony-stimulating factor 1 receptor depletes the resident subset of monocytes and tissue- and tumor-associated macrophages but does not inhibit inflammation, Blood, 116, 3955, 10.1182/blood-2010-02-266296 · DOI
  34. Mantovani, 2011, Neutrophils in the activation and regulation of innate and adaptive immunity, Nat. Rev. Immunol., 11, 519, 10.1038/nri3024 · DOI
  35. Müller, 2017, Single-cell profiling of human gliomas reveals macrophage ontogeny as a basis for regional differences in macrophage activation in the tumor microenvironment, Genome Biol., 18, 234, 10.1186/s13059-017-1362-4 · DOI
  36. Papadopoulos, 2017, First-in-Human Study of AMG 820, a Monoclonal Anti-Colony-Stimulating Factor 1 Receptor Antibody, in Patients with Advanced Solid Tumors, Clin. Cancer Res., 23, 5703, 10.1158/1078-0432.CCR-16-3261 · DOI
  37. Papalexi, 2018, Single-cell RNA sequencing to explore immune cell heterogeneity, Nat. Rev. Immunol., 18, 35, 10.1038/nri.2017.76 · DOI · Paper page
  38. Pradel, 2016, Macrophage Susceptibility to Emactuzumab (RG7155) Treatment, Mol. Cancer Ther., 15, 3077, 10.1158/1535-7163.MCT-16-0157 · DOI
  39. Puram, 2017, Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer, Cell, 171, 1611, 10.1016/j.cell.2017.10.044 · DOI · Paper page
  40. Ries, 2014, Targeting tumor-associated macrophages with anti-CSF-1R antibody reveals a strategy for cancer therapy, Cancer Cell, 25, 846, 10.1016/j.ccr.2014.05.016 · DOI · Paper page
  41. Sasaki, 2016, Reg4+ deep crypt secretory cells function as epithelial niche for Lgr5+ stem cells in colon, Proc. Natl. Acad. Sci. USA, 113, E5399, 10.1073/pnas.1607327113 · DOI · Paper page
  42. Savas, 2018, Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis, Nat. Med., 24, 986, 10.1038/s41591-018-0078-7 · DOI · Paper page
  43. Schelker, 2017, Estimation of immune cell content in tumour tissue using single-cell RNA-seq data, Nat. Commun., 8, 2032, 10.1038/s41467-017-02289-3 · DOI
  44. Smillie, 2019, Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis, Cell, 178, 714, 10.1016/j.cell.2019.06.029 · DOI
  45. Tait Wojno, 2019, The Immunobiology of the Interleukin-12 Family: Room for Discovery, Immunity, 50, 851, 10.1016/j.immuni.2019.03.011 · DOI
  46. Venteicher, 2017, Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq, Science, 355, eaai8478, 10.1126/science.aai8478 · DOI
  47. Zaki, 2011, The Nlrp3 inflammasome: contributions to intestinal homeostasis, Trends Immunol., 32, 171, 10.1016/j.it.2011.02.002 · DOI · Paper page
  48. Zhang, 2019, Recharacterizing Tumor-Infiltrating Lymphocytes by Single-Cell RNA Sequencing, Cancer Immunol. Res., 7, 1040, 10.1158/2326-6066.CIR-18-0658 · DOI
  49. Zheng, 2017, Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing, Cell, 169, 1342, 10.1016/j.cell.2017.05.035 · DOI · Paper page
  50. Zhu, 2017, Tissue-Resident Macrophages in Pancreatic Ductal Adenocarcinoma Originate from Embryonic Hematopoiesis and Promote Tumor Progression, Immunity, 47, 323, 10.1016/j.immuni.2017.07.014 · DOI
  51. Zilionis, 2019, Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species, Immunity, 50, 1317, 10.1016/j.immuni.2019.03.009 · DOI
  52. Zucker, 2004, Role of matrix metalloproteinases (MMPs) in colorectal cancer, Cancer Metastasis Rev., 23, 101, 10.1023/A:1025867130437 · DOI

Cited by

Metadata

Authors
Zhang, L., Li, Z., Skrzypczynska, K. M., Fang, Q., Zhang, W., O’Brien, S. A., He, Y., Wang, L., Zhang, Q., Kim, A., Gao, R., Orf, J., Wang, T., Sawant, D., Kang, J., Bhatt, D., Lu, D., Li, C.-M., Rapaport, A. S., Perez, K., Ye, Y., Wang, S., Hu, X., Ren, X., Ouyang, W., Shen, Z., Egen, J. G., Zhang, Z., & Yu, X.
Venue
Cell
Publisher
Elsevier BV
Published
2020-04
Volume
181
Issue
2
Pages
442-459.e29
ISSN
0092-8674
Cited by
1,526
References
29
Language
en
Funders
  • National Natural Science Foundation of China
  • Amgen
  • Key Technologies Research and Development Program

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