Genomics of <i>ERBB2</i>-Positive Breast Cancer in Young Women Before and After Exposure to Chemotherapy Plus Trastuzumab
Bibliographic record
Abstract
PURPOSE Erb-B2 receptor tyrosine kinase 2 ( ERBB2)–positive breast cancer (BC) is particularly common in young women. Genomic features of ERBB2-positive tumors before and after chemotherapy and trastuzumab (chemo + H) have not been described in young women and are important for guiding study of therapeutic resistance in this population. METHODS From a large prospective cohort of women age 40 years or younger with BC, we identified patients with ERBB2-positive BC and tumor tissue available before and after chemo + H. Whole-exome sequencing (WES) was performed on each tumor and on germline DNA from blood. Tumor-normal pairs were analyzed for mutations and copy number (CN) changes. RESULTS Twenty-two women had successful WES on samples from at least one time point; 12 of these had paired sequencing results from before and after chemo + H and 10 had successful sequencing from either time point. TP53 was the only significantly recurrently mutated gene in both pre- and post-treatment samples. MYC gene amplification was observed in four post-treatment tumors. Seven of 12 patients with paired samples showed acquired and/or clonally enriched alterations in cancer-related genes. One patient had an increased clonality putative activating mutation in ERBB2. Another patient acquired a clonal hotspot mutation in TP53. Other genomic changes acquired in post-treatment specimens included alterations in NOTCH2, STIL, PIK3CA, and GATA3. There was no significant change in median ERBB2 CN (20.3 v 22.6; Wilcoxon P = .79) between paired samples. CONCLUSION ERBB2-positive BCs in young women displayed substantial genomic evolution after treatment with chemo + H. Approximately half of patients with paired samples demonstrated acquired and/or clonally enriched genomic changes in cancer genes. ERBB2 CN changes were uncommon. We identified several genes warranting exploration as potential mechanisms of resistance to therapy in this population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".