Impact of interferon-γ on hematopoiesis
Open accessAbstract
The proinflammatory cytokine interferon-γ (IFN-γ) is well known for its important role in innate and adaptive immunity against intracellular infections and for tumor control. Yet, it has become clear that IFN-γ also has a strong impact on bone marrow (BM) output during inflammation, as it affects the differentiation of most hematopoietic progenitor cells. Here, we review the impact of IFN-γ on hematopoiesis, including the function of hematopoietic stem cells (HSCs) and more downstream progenitors. We discuss which hematopoietic lineages are functionally modulated by IFN-γ and through which underlying molecular mechanism(s). We propose the novel concept that IFN-γ acts through upregulation of suppressor of cytokine signaling molecules, which impairs signaling of several cytokine receptors. IFN-γ has also gained clinical interest from different angles, and we discuss how chronic IFN-γ production can lead to the development of anemia and BM failure and how it is involved in malignant hematopoiesis. Overall, this review illustrates the wide-ranging effect of IFN-γ on the (patho-)physiological processes in the BM.
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Chronic exposure to IFN-g functionally impairs HSCs in vitro and in vivo, particularly when secreted by stromal cells within the hematopoietic niche.
“Chronic exposure, however, functionally impairs HSCs in vitro and in vivo, 21 in particular when secreted by stromal cells within the hematopoietic niche.22”
From Inflammatory bone marrow microenvironment (2019) · cites this paper as [21]
IFN-g mainly affects the self-renewal and repopulating capacity of hematopoietic progenitors by moderating their response to other cytokines, mediated by STAT1 and SOCS1 and SOCS3.
“IFN-g mainly affects the self-renewal and repopulating capacity of hematopoietic progenitors by moderating their response to other cytokines.23 This effect is mainly mediated by STAT1 and suppressor of cytokine signaling 1 (SOCS1) and SOCS3 as effector molecules.21,24”
From Inflammatory bone marrow microenvironment (2019) · cites this paper as [21]
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Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453 · see citing works
Inflammation: a key regulator of hematopoietic stem cell fate in health and disease
Pietras, E. M. (2017) · Blood · doi:10.1182/blood-2017-06-780882 · Cited by 417 · see citing works
Cheng, L., Jin, H., Qiang, Y., Wu, S., Yan, C., Han, M., Xiao, T., Yan, N., An, H., Zhou, X., et al. (2016) · International Immunopharmacology · doi:10.1016/j.intimp.2016.08.018 · Cited by 98 · see citing works
Chen, J., Feng, X., Desierto, M. J., Keyvanfar, K., & Young, N. S. (2015) · Blood · doi:10.1182/blood-2015-06-652453 · Cited by 97 · see citing works
Inflammatory bone marrow microenvironment
Leimkühler, N. B., & Schneider, R. K. (2019) · Hematology · doi:10.1182/hematology.2019000045 · Cited by 82 · see citing works
Inflammatory signals directly instruct PU.1 in HSCs via TNF
Etzrodt, M., Ahmed, N., Hoppe, P. S., Loeffler, D., Skylaki, S., Hilsenbeck, O., Kokkaliaris, K. D., Kaltenbach, H.-M., Stelling, J., Nerlov, C., et al. (2019) · Blood · doi:10.1182/blood-2018-02-832998 · Cited by 67 · see citing works
Inflammation and the Alteration of B-Cell Physiology in Aging
Hagen, M., & Derudder, E. (2020) · Gerontology · doi:10.1159/000501963 · Cited by 58 · see citing works
Pascutti, M. F., Geerman, S., Collins, N., Brasser, G., Nota, B., Stark, R., Behr, F., Oja, A., Slot, E., Panagioti, E., et al. (2019) · European Journal of Immunology · doi:10.1002/eji.201848003 · Cited by 37 · see citing works
Self-citationKroczynska, B., Rafidi, R. L., Majchrzak-Kita, B., Kosciuczuk, E. M., Blyth, G. T., Jemielity, J., Warminska, Z., Saleiro, D., Mehrotra, S., Arslan, A. D., et al. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.m115.664995 · Cited by 29 · see citing works
Cell signaling and the aging of B cells
Labi, V., & Derudder, E. (2020) · Experimental Gerontology · doi:10.1016/j.exger.2020.110985 · Cited by 9 · see citing works
- Authors
- de Bruin, A. M., Voermans, C., & Nolte, M. A.
- Affiliations
- Department of Pathology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and
- Amsterdam UMC Location University of Amsterdam (NL)
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2014-10-16
- Volume
- 124
- Issue
- 16
- Pages
- 2479-2486
- ISSN
- 0006-4971 (ISSN-L)
- 1528-0020
- OpenAlex
- W2050676604
- Cited by
- 215
- References
- 98
- Citations by year
- 2026: 20 · 2025: 19 · 2024: 13 · 2023: 15 · 2022: 18 · 2021: 24 · 2020: 15 · 2019: 19 · 2018: 21 · 2017: 18 · 2016: 16 · 2015: 13 · 2014: 4
- FWCI
- 2.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Blood (publishedVersion)
- PubMed (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Funders
- Landsteiner Foundation for Blood Transfusion Research
- National Cancer Institute
- Topics
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Health Sciences › Medicine › Oncology › Cytokine Signaling Pathways and Interactions
- Life Sciences › Immunology and Microbiology › Immunology › interferon and immune responses
- Keywords
- interferon-gamma, hematopoiesis, bone marrow, hematopoietic stem cells, hematopoietic progenitor cells, suppressor of cytokine signaling, cytokine receptor signaling, inflammation, anemia of chronic disease, bone marrow failure, malignant hematopoiesis, hematopoietic differentiation
- MeSH terms
- Animals, Bone Marrow, Hematopoiesis, Hematopoietic Stem Cells, Humans, Interferon-gamma, Transcription Factors, Signal Transduction, Cytokines, Gene Expression Regulation, Developmental
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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