Erythroid-myeloid transition: a mechanism of tumor-driven immunosuppression in breast cancer 3720
Bibliographic record
Abstract
Abstract Description Breast cancer is the second leading cause of cancer death in females, and triple-negative breast cancer (TNBC), which lacks ER, PR, and HER2, is one of the most aggressive types. Current treatments for metastatic breast cancer remain ineffective, highlighting the need to understand TNBC progression. Hematopoiesis is traditionally viewed as a conserved, hierarchical process in which mature myeloid cells arise from granulocyte-macrophage progenitors. In this study, we identify a novel population of immature red blood cells, termed CD71? erythroid cells (CECs), which in a 4T1 murine model of TNBC transdifferentiate from the erythroid lineage to produce mature myeloid cells with potent immunosuppressive functions. Through single-cell RNA sequencing, we have characterized these cells in comparison to conventional erythroid and myeloid cells and delineated their differentiation trajectory. Our findings suggest that tumor cells modulate erythropoiesis to generate erythroid-myeloid cells, which by secreting Galectin-1 promote the differentiation of regulatory T cells (Tregs), contributing to an immunosuppressive microenvironment. This novel mechanism highlights a tumor-driven strategy to exploit erythropoiesis for immune evasion. In conclusion, this study offers a comprehensive understanding of the complex role of erythroid/myeloid precursors in TNBC and highlight the therapeutic potential of targeting this population to mitigate immunosuppression and enhance anti-tumor immunity. Funding Sources Supported by Canadian Institutes of Health Research and Cancer Research Society Topic Categories Hematopoiesis and Immune System Development (HEM)
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".