SOCS1 Protects Acute Myeloid Leukemia against Allogeneic T Cell–Mediated Cytotoxicity
Bibliographic record
Abstract
Abstract Despite the curative potential of allogeneic hematopoietic stem cell transplantation for acute myeloid leukemia (AML), its efficacy is limited by intrinsic resistance of cancer cells to donor-derived T-cell cytotoxicity. Using a genome-wide CRISPR screen, we identified the SOCS1–JAK1–STAT1 pathway as a mediator of AML susceptibility to T cells. Knockdown of SOCS1 in AML cells sensitized them to killing by allogeneic T cells, whereas SOCS1 overexpression in AML cells induced resistance to T-cell antileukemic activity. Mechanistically, SOCS1 protected AML cells from T-cell killing by antagonizing IFNγ–JAK1—induced ICAM-1 expression. Furthermore, primary AML cells with lower SOCS1 expression correlated with better overall survival in patients, especially those with a lower exhausted CD8+ T-cell score. Thus, this study reveals SOCS1 and its downstream mediators as a potential targetable pathway to enhance T cell–based immunotherapy for AML. Significance: Our investigation of the SOCS1 pathway in AML and T-cell interactions provides insights into potential mechanisms of resistance of AML to allogeneic hematopoietic stem cell transplantation and demonstrates the potential of targeting SOCS1 and its downstream mediators to enhance antileukemic T-cell activity. See related commentary by Fry, p. 157.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".