Overexpression of CD200 is a stem cell-specific mechanism of immune evasion in AML
Bibliographic record
Abstract
Background Acute myeloid leukemia (AML) stem cells (LSCs) are capable of surviving current standard chemotherapy and are the likely source of deadly, relapsed disease. While stem cell transplant serves as proof-of-principle that AML LSCs can be eliminated by the immune system, the translation of existing immunotherapies to AML has been met with limited success. Consequently, understanding and exploiting the unique immune-evasive mechanisms of AML LSCs is critical. Methods Analysis of stem cell datasets and primary patient samples revealed CD200 as a putative stem cell–specific immune checkpoint overexpressed in AML LSCs. Isogenic cell line models of CD200 expression were employed to characterize the interaction of CD200 + AML with various immune cell subsets both in vitro and in peripheral blood mononuclear cell (PBMC)–humanized mouse models. CyTOF and RNA-sequencing were performed on humanized mice to identify novel mechanisms of CD200-mediated immunosuppression. To clinically translate these findings, we developed a fully humanized CD200 antibody (IgG1) that removed the immunosuppressive signal by blocking interaction with the CD200 receptor while also inducing a potent Fc-mediated response. Therapeutic efficacy of the CD200 antibody was evaluated using both humanized mice and patient-derived xenograft models. Results Our results demonstrate that CD200 is selectively overexpressed in AML LSCs and is broadly immunosuppressive by impairing cytokine secretion in both innate and adaptive immune cell subsets. In a PBMC-humanized mouse model, CD200 + leukemia progressed rapidly, escaping elimination by T cells, compared with CD200 − AML. T cells from mice with CD200 + AML were characterized by an abundance of metabolically quiescent CD8 + central and effector memory cells. Mechanistically, CD200 expression on AML cells significantly impaired OXPHOS metabolic activity in T cells from healthy donors. Importantly, CD200 antibody therapy could eliminate disease in the presence of graft-versus-leukemia in immune competent mice and could significantly improve the efficacy of low-intensity azacitidine/venetoclax chemotherapy in immunodeficient hosts. Conclusions Overexpression of CD200 is a stem cell–specific marker that contributes to immunosuppression in AML by impairing effector cell metabolism and function. CD200 antibody therapy is capable of simultaneously reducing CD200-mediated suppression while also engaging macrophage activity. This study lays the groundwork for CD200-targeted therapeutic strategies to eliminate LSCs and prevent AML relapse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".