Neuregulin Autocrine Signaling Promotes Self-Renewal of Breast Tumor-Initiating Cells by Triggering HER2/HER3 Activation
Bibliographic record
Abstract
Currently, only patients with HER2-positive tumors are candidates for HER2-targeted therapies. However, recent clinical observations suggest that the survival of patients with HER2-low breast cancers, who lack HER2 amplification, may benefit from adjuvant therapy that targets HER2. In this study, we explored a mechanism through which these benefits may be obtained. Prompted by the hypothesis that HER2/HER3 signaling in breast tumor-initiating cells (TIC) promotes self-renewal and survival, we obtained evidence that neuregulin 1 (NRG1) produced by TICs promotes their proliferation and self-renewal in HER2-low tumors, including in triple-negative breast tumors. Pharmacologic inhibition of EGFR, HER2, or both receptors reduced breast TIC survival and self-renewal in vitro and in vivo and increased TIC sensitivity to ionizing radiation. Through a tissue microarray analysis, we found that NRG1 expression and associated HER2 activation occurred in a subset of HER2-low breast cancers. Our results offer an explanation for why HER2 inhibition blocks the growth of HER2-low breast tumors. Moreover, they argue that dual inhibition of EGFR and HER2 may offer a useful therapeutic strategy to target TICs in these tumors. In generating a mechanistic rationale to apply HER2-targeting therapies in patients with HER2-low tumors, this work shows why these therapies could benefit a considerably larger number of patients with breast cancer than they currently reach.
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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 | 0.002 | 0.000 |
| 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) | 0.003 | 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".