Spatial and molecular profiling of the classic Hodgkin lymphoma microenvironment reveals an immunosuppressive mononuclear phagocyte network
Bibliographic record
Abstract
Abstract Although a lymph node infiltrated by classic Hodgkin lymphoma is mostly composed of non-neoplastic immune cells, the malignant Hodgkin Reed-Sternberg cells (HRSC) successfully suppress an anti-tumor immune response, to create a cancer-permissive microenvironment. Accordingly, unleashing the dormant immune cells, for example by checkpoint inhibition, has been a central focus of recent therapeutic advances for this disease. Here, we profiled the global immune cell composition of normal and diseased lymph nodes by single-cell RNA sequencing, as a basis for interrogating the immediate vicinity of HRSC, first regionally and then at cellular resolution. Our analyses revealed specific immune cells and functional states associated with HRSC. Most prominently, we discovered a non-random spatial association of immunoregulatory mononuclear phagocytes positioned around HRSC, which express the immune checkpoints PD-L1, TIM-3, and the tryptophan-catabolizing protein IDO1. These findings provide a basis for rational targeting and activation of the anti-tumor immune response in classic Hodgkin lymphoma.
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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 | 0.000 |
| 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 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".