HER2 heterogeneity and treatment response–associated profiles in HER2-positive breast cancer in the NCT02326974 clinical trial
Bibliographic record
Abstract
BACKGROUND HER2-targeting therapies have great efficacy in HER2-positive breast cancer, but resistance, in part due to HER2 heterogeneity (HET), is a significant clinical challenge. We previously described that in a phase II neoadjuvant trastuzumab emtansine (T-DM1) and pertuzumab (P) clinical trial in early-stage HER2-positive breast cancer, none of the patients with HER2-HET tumors had pathologic complete response (pCR). METHODS To investigate cellular and molecular differences among tumors according to HER2 heterogeneity and pCR, we performed RNA sequencing and ERBB2 FISH of 285 pretreatment and posttreatment tumors from 129 patients in this T-DM1+P neoadjuvant trial. A subset of cases was also subject to NanoString spatial digital profiling. RESULTS Pretreatment tumors from patients with pCR had the highest level of ERBB2 mRNA and ERBB signaling. HER2 heterogeneity was associated with no pCR, basal-like features, and low ERBB2 expression yet high ERBB signaling sustained by activation of downstream pathway components. Residual tumors showed decreased HER2 protein levels and ERBB2 copy number heterogeneity and increased PI3K pathway enrichment and luminal features. HET tumors showed minimal treatment-induced transcriptomic changes compared with non-HET tumors. Immune infiltration correlated with pCR and HER2-HET status. CONCLUSION Resistance mechanisms in HET and non-HET tumors are distinct. HER2-targeting antibodies have limited efficacy in HET tumors. Our results support the stratification of patients based on HET status and the use of agents that target downstream components of the ERBB signaling pathway in patients with HET tumors. TRIAL REGISTRATION ClinicalTrials.gov NCT02326974. FUNDING This study was funded by Roche and the National Cancer Institute.
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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 | 0.016 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".