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Record W4408091287 · doi:10.1016/j.xcrm.2025.101989

Inflammatory reprogramming of the solid tumor microenvironment by infiltrating clonal hematopoiesis is associated with adverse outcomes

2025· article· en· W4408091287 on OpenAlexafffund
Marco M. Buttigieg, Caitlyn Vlasschaert, Alexander G. Bick, Robert J. Vanner, Michael J. Rauh

Bibliographic record

VenueCell Reports Medicine · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health NetworkQueen's University
FundersCanadian Institutes of Health ResearchTerry Fox Research InstituteLeukemia and Lymphoma Society of CanadaBrain Tumour Foundation of CanadaOntario Institute for Cancer ResearchPew Charitable TrustsPrincess Margaret Cancer FoundationFoundation for the National Institutes of Health
KeywordsReprogrammingSolid tumorHaematopoiesisTumor microenvironmentCancer researchBiologyImmunologyTumor cellsStem cellCell biologyCancerGeneticsCell

Abstract

fetched live from OpenAlex

Clonal hematopoiesis (CH)-the expansion of somatically mutated hematopoietic cells-is common in solid cancers. CH is associated with systemic inflammation, but its impact on tumor biology is underexplored. Here, we report the effects of CH on the tumor microenvironment (TME) using 1,550 treatment-naive patient samples from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) cohort. CH is 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. Across cancers, the presence of CH-Tum is associated with worse survival outcomes. Molecular analyses reveal an association between CH-Tum and an immune-rich, inflammatory TME that is notably distinct from age-related gene expression changes. These effects are most prominent in glioblastoma, where CH correlates 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.004
GPT teacher head0.221
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2025
Admission routes2
Has abstractyes

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