Comprehensive tumor-agnostic evaluation of genomic and epigenomic-based approaches for the identification of circulating tumor DNA in early-stage breast cancer
Bibliographic record
Abstract
BACKGROUND: The detection of circulating tumor DNA (ctDNA) after curative-intent therapy, referred to as molecular/minimal residual disease (MRD), is prognostic of disease recurrence in early-stage breast cancer (EBC). Tumor-agnostic approaches that rely on mutation-based assessment in fixed panels of common cancer driver genes have shown limited utility for detecting MRD in EBC. Methylation-based MRD (mMRD) may overcome the limitations of genomic-based MRD (gMRD), though limited clinical validation is available. MATERIALS AND METHODS: To investigate this, we analyzed 290 longitudinally banked plasma samples from 95 participants diagnosed with early-stage estrogen receptor (ER)-positive/human epidermal growth factor receptor 2-negative (ER-positive) and triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy using a high-sensitivity genomic and epigenomic-based, tumor-agnostic ctDNA platform. RESULTS: The baseline (pre-chemotherapy) ctDNA detection (mMRD) rate was 72.5% (66/91) across all participants (ER-positive: 33/48, 69%; TNBC: 33/43, 77%). Baseline ctDNA detection (mMRD) was associated with a higher risk of recurrence [hazard ratio (HR) 9.4, 95% confidence interval (CI) 1.3-70.3, P = 0.03]. Detection of ctDNA (mMRD) in the post-operative and follow-up periods were prognostic of worse event-free survival (EFS) (HR 17.0, 95% CI 6.0-48.0, P < 0.0001) with 62.5% sensitivity and 100% specificity for recurrence (positive predictive value 100%). The median lead time from mMRD detection to clinical recurrence was 152 days (range 15-748 days). gMRD, derived from plasma-only panel-based next-generation sequencing, was evaluated in all matched time points; the prognostic value was limited by clonal hematopoiesis of indeterminate potential, including pathogenic mutations in common cancer driver genes. Despite refinements in gMRD analysis, it remained inferior to mMRD. A combination of mMRD and gMRD did not outperform mMRD alone. CONCLUSION: These results support further development of tumor-agnostic mMRD assays for the detection of ctDNA and assessment of these assays to develop clinical utility in this setting.
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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".