Predictive Biomarkers for Adjuvant Capecitabine Benefit in Early-Stage Triple-Negative Breast Cancer in the FinXX Clinical Trial
Bibliographic record
Abstract
Abstract Purpose: Recent studies have demonstrated a benefit of adjuvant capecitabine in early breast cancer, particularly in patients with triple-negative breast cancer (TNBC). However, TNBC is heterogeneous and more precise predictive biomarkers are needed. Experimental Design: Tumor tissues collected from TNBC patients in the FinXX trial, randomized to adjuvant anthracycline–taxane–based chemotherapy with or without capecitabine, were analyzed using a 770-gene panel targeting multiple biological mechanisms and additional 30-custom genes related to capecitabine metabolism. Hypothesis-generating exploratory analyses were performed to assess biomarker expression in relation to treatment effect using the Cox regression model and interaction tests adjusted for multiplicity. Results: One hundred eleven TNBC samples were evaluable (57 without capecitabine and 54 with capecitabine). The median follow-up was 10.2 years. Multivariate analysis showed significant improvement in recurrence-free survival (RFS) favoring capecitabine in four biologically important genes and metagenes, including cytotoxic cells [hazard ratio (HR) = 0.38; 95% confidence intervals (CI), 0.16–0.86, P-interaction = 0.01], endothelial (HR = 0.67; 95% CI, 0.20–2.22, P-interaction = 0.02), mast cells (HR = 0.78; 95% CI, 0.49–1.27, P-interaction = 0.04), and PDL2 (HR = 0.31; 95% CI, 0.12–0.81, P-interaction = 0.03). Furthermore, we identified 38 single genes that were significantly associated with capecitabine benefit, and these were dominated by immune response pathway and enzymes involved in activating capecitabine to fluorouracil, including TYMP. However, these results were not significant when adjusted for multiple testing. Conclusions: Genes and metagenes related to antitumor immunity, immune response, and capecitabine activation could identify TNBC patients who are more likely to benefit from adjuvant capecitabine. Given the reduced power to observe significant findings when correcting for multiplicity, our findings provide the basis for future hypothesis-testing validation studies on larger clinical trials.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".