Inflammatory reprogramming of the tumor microenvironment by infiltrating clonal hematopoiesis is associated with adverse outcomes in solid cancer
Bibliographic record
Abstract
Abstract Clonal hematopoiesis (CH) – the expansion of somatically-mutated hematopoietic cells in blood – is common in solid cancers. CH is associated with systemic inflammation that may lead to cancer, but its impact on tumor biology is underexplored. Here, we report the effects of CH on the tumor microenvironment (TME) using 1,550 treatment-naïve patient samples from the CPTAC cohort. CH was present in 18.3% of patients, with one-third of CH mutations also detectable in tumor-derived DNA from the same individual (CH-Tum), reflecting CH-mutant leukocyte infiltration. The presence of CH-Tum was associated with worse survival across cancers, particularly for glioblastoma. Transcriptomics and proteomics revealed that CH drives inflammation in the TME in a cancer- and CH driver-specific manner, and may improve immunotherapy responses. In glioblastoma, CH associated with pronounced macrophage infiltration, inflammation, and an aggressive, mesenchymal phenotype. Our findings demonstrate that CH shapes the TME, with potential applications as a biomarker in precision oncology.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".