Targeted Next Generation Sequencing Reveals a Third Breakpoint Cluster Region and New Partner Genes in the <i>KMT2A</i> Recombinome
Bibliographic record
Abstract
Abstract Chromosomal rearrangements of the KMT2A gene are associated with acute leukemias and myelodysplastic syndromes. The large number of known KMT2A fusions (>100) renders a precise diagnosis a demanding task. More than 50% of all KMT2A partner genes have been analyzed at the DCAL, including the novel partner genes BCAS4, FAM13A, RANBP3, and STK4. Even though all KMT2A rearrangements are associated with high-risk acute leukemia, the outcome (poor or very poor) is influenced by the partner gene. So far, we have analyzed more than 3,200 patients positive for a KMT2A rearrangement. The breakpoints of these cases are located mainly in the major breakpoint cluster region (bcr1) and to a small extent in the recently described minor bcr (bcr2). A small number of breakpoints were also found outside of these two bcrs. Most of these patients were analyzed by long distance inverse (LDI)- or multiplex-PCR which only cover bcr1. More recently, we used targeted KMT2A-NGS with whole gene coverage in over 450 patients, which was initially applied selectively in patients negative by LDI- and multiplex-PCR and then used more widely. Within the KMT2A-NGS group, 410 patients had bcr1 breakpoints mainly between the KMT2A exons 7 and 13, while 46 patients bcr2 breakpoints mainly between exons 20 and 24. Of note, five patients had their breakpoint outside of these two bcrs: three of them within intron 2 and no functional KMT2A rearrangement; the other two within intron 35 and intron 36, fusing almost the whole KMT2A gene in frame to the respective partner genes ARHGEF12 and MLLT4. These two breakpoints may define a third and rare bcr (bcr3), although further cases are needed to support this hypothesis. Interestingly, 70 patients displayed a 3'-KMT2A deletion, indicating that the number of terminal deletions is higher than described previously. Two patients had a 5'-KMT2A deletion. All deletions started or ended in bcr1 and bcr2. We also observed a striking difference in the distribution of partner genes between bcr1 and bcr2. The most frequent translocation partners fused to bcr1 sites are transcription factors, while the partner genes linked to bcr2 sites generally code for cytosolic proteins. In bcr1, the 4 most frequent partner genes AFF1, MLLT3, MLLT1, and MLLT10, found in 80% of cases, all code for transcription factors that are part of the super elongation complex (SEC). These fusions therefore all lead to disruption of the hematopoietic lineage commitment. In contrast in bcr2, 3 partner genes USP2, MLLT4, and USP8 account for 85% of the cases. USP2 and USP8 are ubiquitin specific peptidases involved in cell signaling and exclusively fused to bcr2 in KMT2A. While MLLT4 is found as a partner in bcr1, bcr2 and bcr3 fusions; unlike other recurrent KMT2A partners linked to bcr1, it is not a transcription factor and it exerts oncogenic potential via dimerization like other cytosolic partners. We hypothesize that the oncogenic properties of USP2 and USP8 are dependent on dimerization like MLLT4 and that the most frequent fusions involving at different bcrs favor different oncogenic mechanisms: bcr1 transactivation and bcr2 dimerization. Further studies are needed to explain why USP2 and USP8 are exclusively associated with bcr2, and why the most frequent partner genes AFF1 and MLLT3 of the bcr1 are less frequent in bcr2. In conclusion, targeted NGS combined with bioinformatic analysis has expanded our knowledge of the KMT2A recombinome to include more fusion partners and has generated new hypotheses for future research on oncogenic mechanisms. Disclosures No relevant conflicts of interest to declare.
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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".