Evaluating the predictive value of biomarkers for efficacy outcomes in response to pertuzumab- and trastuzumab-based therapy: an exploratory analysis of the TRYPHAENA study
Bibliographic record
Abstract
INTRODUCTION: Molecular markers that predict responses to particular therapies are invaluable for optimization of patient treatment. The TRYPHAENA study showed that pertuzumab and trastuzumab with chemotherapy was an efficacious and tolerable combination for patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer in the neoadjuvant setting. We analyzed whether particular biomarkers correlated with the responses observed and therefore may predict outcomes in patients given pertuzumab plus trastuzumab. METHODS: We describe the analysis of a panel of biomarkers including HER2, human epidermal growth factor receptor 3 (HER3), epidermal growth factor receptor (EGFR), phosphatase and tensin homolog (PTEN), and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) by qRT-PCR, immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), enzyme-linked immunosorbent assay (ELISA), and PCR-based mutational analyses as appropriate. For each marker analyzed, patients were categorized into 'low' (generally below median) or 'high' (generally above median) subgroups at baseline and post-treatment. RESULTS: Correlation of marker subgroups with the achievement of a pathological complete response (pCR) (ypT0/is) was analyzed. HER2 protein and mRNA expression levels were associated with pCR rate in two of the three study arms and the pooled analyses. Correlations of biomarker status with pCR occurred in one individual arm only and the pooled analyses with EGFR and PTEN; however, interpretation of these results is limited by a strong imbalance in patient numbers between the high and low subgroups and inconsistency between arms. We also found no association between expression levels of TOP2A and pCR rate in either the anthracycline-containing or free arms of TRYPHAENA. CONCLUSIONS: According to these analyses, and in line with other analyses of pertuzumab and trastuzumab in the neoadjuvant setting, we conclude that HER2 expression remains the only marker suitable for patient selection for this regimen at present. TRIAL REGISTRATION: The TRYPHAENA study was registered with ClinicalTrials.gov, NCT00976989, on September 14 2009.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".