Common clonal origin of chronic myelomonocytic leukemia and B-cell acute lymphoblastic leukemia in a patient with a germline <i>CHEK2</i> variant
Bibliographic record
Abstract
Hematological malignancies are broadly divided into myeloid and lymphoid neoplasms, reflecting the two major cellular lineages of the hematopoietic system. It is generally rare for hematological malignancies to spontaneously progress with a switch from myeloid to lymphoid lineage. We describe the exceptional case of a patient who sequentially developed myelodysplastic syndrome (MDS), chronic myelomonocytic leukemia (CMML), and B-cell acute lymphoblastic leukemia (B-ALL), as well as our investigation into the underlying pathogenesis. Using whole-exome sequencing (WES) performed on sorted CMML and B-ALL cell fractions, we identified both common and unique potential driver mutations, suggesting a branching clonal evolution giving rise to both diseases. Interestingly, we also identified a germline variant in the cancer susceptibility gene CHEK2. We validated that this variant (c.475T > C; p.Y159H), located in the forkhead-associated (FHA) domain, impairs its capacity to bind BRCA1 in cellulo. This unique case provides novel insight into the genetics of complex hematological diseases and highlights the possibility that such patients may carry inherited predispositions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".