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MDSC: Markers, development, states, and unaddressed complexity
Samarth Hegde1, Andrew M Leader1, Miriam Merad2
1The Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Myeloid-derived suppressor cells (MDSCs) are one of the most discussed biological entities in immunology. While the context and classification of this group of cells has evolved, MDSCs most commonly describe cells arising during chronic inflammation, especially late-stage cancers, and are defined by their T cell immunosuppressive functions. This MDSC concept has helped explain myeloid phenomena associated with disease outcome, but currently lacks clear definitions and a unifying framework across pathologies. Here, we propose such a framework to classify MDSCs as discrete cell states based on activation signals in myeloid populations leading to suppressive modes characterized by specific, measurable effects. Developing this level of knowledge of myeloid states across pathological conditions may ultimately transform how disparate diseases are grouped and treated.
Myeloid-derived suppressor cells (MDSCs) are one of the most discussed biological entities in immunology. While the context and classification of this group of cells has evolved, MDSCs most commonly describe cells arising during chronic inflammation, especially late-stage cancers, and are defined by their T cell immunosuppressive functions. This MDSC concept has helped explain myeloid phenomena associated with disease outcome, but currently lacks clear definitions and a unifying framework across pathologies. Here, we propose such a framework to classify MDSCs as discrete cell states based on activation signals in myeloid populations leading to suppressive modes characterized by specific, measurable effects. Developing this level of knowledge of myeloid states across pathological conditions may ultimately transform how disparate diseases are grouped and treated.
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