Measuring on-treatment genome-wide tumor copy number alterations in cell-free DNA (cfDNA) in plasma is highly prognostic in metastatic breast cancer.
Bibliographic record
Abstract
1097 Background: The clinical management of metastatic breast cancer depends on the measurement of tumor response to successive drugs by serial imaging and changes in blood tumor markers, which remain the standard of care despite poor sensitivity and specificity. Highly sensitive and specific cfDNA secreted from the tumor can detect the changes in tumor-specific aberrations that have been shown to be associated with patient response in the metastatic setting. However, most approaches require prior sequencing of the tumor to target specific known mutations. Methods: Using low coverage genomic sequencing, a genomic instability number (GIN) was measured in cfDNA based on the detection of genome-wide tumor-specific DNA copy number alterations for 27 patients with metastatic breast cancer. The GIN value and its variation from baseline before treatment, as well as within 10 days and 3 weeks after start of therapy were compared with tumor response, progression free survival (PFS) and overall survival (OS) of the patients. Patients were followed for a median of 22 months and we used a previously published GIN threshold at 170 for high vs low GIN values. Sequencing was performed blinded to the clinical results. Results: Baseline GIN values were not associated with tumor response at 3or 6 months, but showed a trend towards lower OS with higher GIN (p = 0.12). GIN values fell by an average of 28% in responders (stable disease or response) and 23% in those with progression (p = 0.85), but remained lower at 3 weeks only in the responders. High GIN values within 10 days and 3 weeks were associated with markedly worse OS (p = 0.014 and p = 0.009 respectively) and those at 3 weeks with worse PFS (p = 0.017). Hence the median survival of patients with high GIN at 10 days or 3 weeks was 12 months vs not reached for those with low GIN. The percentage drop of GIN at 10 days but not at 3 weeks was significantly associated with PFS (p = 0.016). Conclusions: These results demonstrate that GIN values of cfDNA measured at early on-treatment time points can predict PFS and OS with a high degree of accuracy. These findings deserve further study in a larger cohort but hold the promise of early prediction of clinical outcomes in a tumor-independent genome-wide approach.
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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 | 0.001 | 0.002 |
| 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".