Mechanisms of Tumor Regression and Resistance to Estrogen Deprivation and Fulvestrant in a Model of Estrogen Receptor–Positive, HER-2/<i>neu</i>-Positive Breast Cancer
Bibliographic record
Abstract
HER-2/neu in breast cancer is associated with tamoxifen resistance, but little data exist on its interaction with estrogen deprivation or fulvestrant. Here, we used an in vivo xenograft model of estrogen receptor (ER)-positive breast cancer with HER-2/neu overexpression (MCF7/HER-2/neu-18) to investigate mechanisms of growth inhibition and treatment resistance. MCF7/HER-2/neu-18 tumors were growth inhibited by estrogen deprivation and with fulvestrant, but resistance developed in 2 to 3 months. Inhibited tumors had reductions in ER, insulin-like growth factor-I receptor (IGF-IR), phosphorylated HER-2/neu (p-HER-2/neu), and phosphorylated p42/44 mitogen-activated protein kinase (p-MAPK). p27 was increased especially in tumors sensitive to estrogen deprivation. Tumors with acquired resistance to these therapies had complete loss of ER, increased p-HER-2/neu, increased p-MAPK, and reduced p27. In contrast, IGF-IR and phosphorylated AKT (p-AKT) levels were markedly reduced in these resistant tumors. The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib, which can block EGFR/HER-2/neu signaling, significantly delayed the emergence of resistance to both estrogen deprivation and fulvestrant. Levels of p-MAPK and p-AKT decreased with gefitinib, whereas high ER levels were restored. Eventually, however, tumors progressed in mice treated with gefitinib combined with estrogen deprivation or fulvestrant accompanied again by loss of ER and IGF-IR, increased p-HER-2/neu, high p-MAPK, and now increased p-AKT. Thus, estrogen deprivation and fulvestrant can effectively inhibit HER-2/neu-overexpressing tumors but resistance develops quickly. EGFR/HER-2/neu inhibitors can delay resistance, but reactivation of HER-2/neu and signaling through AKT leads to tumor regrowth. Combining endocrine therapy with EGFR/HER-2/neu inhibitors should be tested in clinical breast cancer, but a more complete blockade of EGFR/HER-2/neu may be optimal.
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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 | 0.000 | 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 | 0.001 |
| 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".