Circulating Tumor DNA in HER2-Amplified Breast Cancer: A Translational Research Substudy of the NeoALTTO Phase III Trial
Bibliographic record
Abstract
Abstract Purpose: In the neoadjuvant treatment (NAT) setting, dual HER2-targeted therapy is associated with increased pathologic complete response (pCR) rates compared with each therapy alone. Biomarkers allowing to predict treatment response during NAT are needed. We aim to evaluate whether circulating tumor DNA (ctDNA) is associated with response to anti-HER2–targeted therapy. Experimental Design: Plasma DNA collected before NAT, at week 2, and before surgery from patients enrolled in the NeoALTTO trial was assessed using digital PCR for PIK3CA and TP53 mutation detection. Results: A total of 69 of 455 (15.2%) patients had a PIK3CA and/or TP53 mutation detected in the baseline tumor sample and evaluable ctDNA results from baseline samples. CtDNA was detected in 41%, 20%, and 5% patients before NAT, at week 2, and before surgery, respectively. ctDNA detection before NAT was significantly associated with older age and ER-negative status. ctDNA detection before NAT was associated with decreased odds of achieving pCR (OR = 0.15; 95% CI, 0.034–0.7; P = 0.0089), but not with event-free survival (EFS). Analyses for EFS were underpowered. Interestingly, the patients with HER2-enriched subtype tumors and undetectable ctDNA at baseline had the highest pCR rates. In contrast, patients with persistent ctDNA detection at baseline and week 2 had the lowest rate of pCR. Conclusions: ctDNA detection before neoadjuvant anti-HER2 therapies is associated with decreased pCR rates. Interestingly, patients with HER2-enriched tumors and undetectable ctDNA at baseline had the highest pCR rates, therefore appearing as the best candidates for treatment deescalation strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".