<i>ETV6/RUNX1</i>‐like acute lymphoblastic leukemia: A novel B‐cell precursor leukemia subtype associated with the CD27/CD44 immunophenotype
Bibliographic record
Abstract
Abstract We have shown previously that ETV6/RUNX1‐positive acute lymphoblastic leukemia (ALL) is distinguishable from other ALL subtypes by CD27pos/CD44low‐neg immunophenotype. During diagnostic immunophenotyping of 573 childhood B‐cell precursor ALL (BCP‐ALL), we identified eight cases with this immunophenotype among “B‐other ALL” (BCP‐ALL cases negative for routinely tested chromosomal/genetic aberrations). We aimed to elucidate whether these cases belong to the recently described ETV6/RUNX1‐like ALL defined by the ETV6/RUNX1‐specific gene expression profile (GEP), harboring concurrent ETV6 and IKZF1 lesions. We performed comprehensive genomic analysis using single nucleotide polymorphism arrays, whole exome and transcriptome sequencing and GEP on microarrays. In unsupervised hierarchical clustering based on GEP, five out of seven analyzed CD27pos/CD44low‐neg B‐other cases clustered with ETV6/RUNX1‐positive ALL and were thus classified as ETV6/RUNX1‐like ALL. The two cases clustering outside ETV6/RUNX1‐positive ALL harbored a P2RY8/CRLF2 fusion with activating JAK2 mutations and a TCF3/ZNF384 fusion, respectively, assigning them to other ALL subtypes. All five ETV6/RUNX1‐like cases harbored ETV6 deletions; uniform intragenic ARPP21 deletions and various IKZF1 lesions were each found in three ETV6/RUNX1‐like cases. The frequency of ETV6 and ARPP21 deletions was significantly higher in ETV6/RUNX1‐like ALL compared with a reference cohort of 42 B‐other ALL. In conclusion, we show that ETV6/RUNX1‐like ALL is associated with CD27pos/CD44low‐neg immunophenotype and identify ARPP21 deletions to contribute to its specific genomic profile enriched for ETV6 and IKZF1 lesions. In conjunction with previously published data, our study identifies the ETV6 lesion as the only common genetic aberration and thus the most likely key driver of ETV6/RUNX1‐like ALL.
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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 | 0.000 | 0.000 |
| 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".