Detection of MDM2 amplification by shallow whole genome sequencing of cell-free DNA of patients with dedifferentiated liposarcoma
Bibliographic record
Abstract
High-level amplification of MDM2 and other genes in the 12q13-15 locus is a hallmark genetic feature of well-differentiated and dedifferentiated liposarcomas (WDLPS and DDLPS, respectively). Detection of this genomic aberration in plasma cell-free DNA may be a clinically useful assay for non-invasive distinction between these liposarcomas and other retroperitoneal tumors in differential diagnosis, and might be useful for the early detection of disease recurrence. In this study, we performed shallow whole genome sequencing of cell-free DNA extracted from 10 plasma samples from 3 patients with DDLPS and 1 patient with WDLPS. In addition, we studied 31 plasma samples from 11 patients with other types of soft tissue tumors. We detected MDM2 amplification in cell-free DNA of 2 of 3 patients with DDLPS. By applying a genome-wide approach to the analysis of cell-free DNA, we also detected amplification of other genes that are known to be recurrently affected in DDLPS. Based on the analysis of one patient with DDLPS with longitudinal plasma samples available, we show that tracking MDM2 amplification in cell-free DNA may be potentially useful for evaluation of response to treatment. The patient with WDLPS and patients with other soft tissue tumors in differential diagnosis were negative for the MDM2 amplification in cell-free DNA. In summary, we demonstrate the feasibility of detecting amplification of MDM2 and other DDLPS-associated genes in plasma cell-free DNA using technology that is already routinely applied for other clinical indications. Our results may have clinical implications for improved diagnosis and surveillance of patients with retroperitoneal tumors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".