Clonal Hematopoiesis Mutations in Patients with Lung Cancer Are Associated with Lung Cancer Risk Factors
Bibliographic record
Abstract
Abstract Clonal hematopoiesis (CH) is a phenomenon caused by expansion of white blood cells descended from a single hematopoietic stem cell. While CH can be associated with leukemia and some solid tumors, the relationship between CH and lung cancer remains largely unknown. To help clarify this relationship, we analyzed whole-exome sequencing (WES) data from 1,958 lung cancer cases and controls. Potential CH mutations were identified by a set of hierarchical filtering criteria in different exonic regions, and the associations between the number of CH mutations and clinical traits were investigated. Family history of lung cancer (FHLC) may exert diverse influences on the accumulation of CH mutations in different age groups. In younger subjects, FHLC was the strongest risk factor for CH mutations. Association analysis of genome-wide genetic variants identified dozens of genetic loci associated with CH mutations, including a candidate SNP rs2298110, which may promote CH by increasing expression of a potential leukemia promoter gene OTUD3. Hundreds of potentially novel CH mutations were identified, and smoking was found to potentially shape the CH mutational signature. Genetic variants and lung cancer risk factors, especially FHLC, correlated with CH. These analyses improve our understanding of the relationship between lung cancer and CH, and future experimental studies will be necessary to corroborate the uncovered correlations. Significance: Analysis of whole-exome sequencing data uncovers correlations between clonal hematopoiesis and lung cancer risk factors, identifies genetic variants correlated with clonal hematopoiesis, and highlights hundreds of potential novel clonal hematopoiesis mutations.
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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 | 0.002 |
| 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) | 0.003 | 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".