Proteogenomic profiling of clonal hematopoiesis in the solid tumor microenvironment.
Bibliographic record
Abstract
2567 Background: Clonal hematopoiesis (CH) is caused by somatic mutations that provide a fitness advantage in hematopoietic stem cells, contributing to inflammation and disease. CH is common in solid tumor patients, and has shown context-dependent associations with survival; however, its contribution to the tumor microenvironment (TME) remains unclear. Here, we employ proteogenomic methods to define CH-associated alterations in the TME. Methods: We tested 1,550 patients across 10 primary, treatment-naïve cancers in the Clinical Proteomic Tumor Analysis Consortium cohort. CH calls were derived from peripheral blood and tumour whole exome sequencing (WES) data, and CH was defined as the presence of a somatic driver mutation at variant allele frequency (VAF) ≥2% in blood. Overall survival (OS) analysis was conducted using Cox proportional hazard models, controlled for age, sex, tumor type, metastatic status, and smoking. Tumor bulk RNA-sequencing and mass spectrometry proteomics data were processed for differential expression and gene set enrichment analyses. Abundance of immune cell populations was estimated with CibersortX. Results: 349 CH mutations were identified in 283 patients (18.3%). CH was strongly associated with age and mutations were mostly found in the epigenetic regulators DNMT3A(37.8%, n=132) and TET2(20.6%, n=72). CH was most prevalent in ovarian cancer (30%, n=27/90) and colorectal cancer (CRC; 28.3%, n=30/106). 103 blood CH mutations were also detected in tumor WES (CHTum), with presence in the tumor associated with higher tumor immune infiltration and peripheral blood VAF ≥10%. CHTum, but not CH, was associated with worse OS (CHTum HR = 1.74 [1.13-2.69]; CH HR = 1.12 [0.83-1.50]). CHTum was also associated with a reduced likelihood of patients being classified as tumor free at follow up (OR = 0.39 [0.19-0.82]). We did not identify a pan-cancer proteogenomic signature of CH in the TME. At the tumor-specific level, we consistently observed associations between CH and its subtypes with dysregulated inflammation, with high transcriptomic-proteomic concordance. In CRC, TET2-mutant CH was associated with greater infiltration of CD4+ T cells, monocyte/macrophages, NK cells, and B cells, alongside an inflammatory response characterized by IL6/JAK/STAT3 signalling, TNF signalling via NFκB, and IL2/STAT5 signalling. Conclusions: CH is common, even prior to therapy, in solid tumor patients and the infiltration of CH-mutant immune clones into the TME is linked with poor outcomes. Beyond confounding molecular tumor diagnostics, CH in the TME also dysregulates the anti-tumor immune response, highlighting the value of a blood reference in precision oncology. The lack of a pan-cancer CH signature in the TME supports a tumor-specific influence of CH. Further study is needed for mechanistic discovery and biomarker development to realize the potential of CH in immuno-oncology and improve patient outcomes.
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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 | 0.001 | 0.001 |
| 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".