Faculty Opinions recommendation of Notch-1-PTEN-ERK1/2 signaling axis promotes HER2+ breast cancer cell proliferation and stem cell survival.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Trastuzumab targets the HER2 receptor on breast cancer cells to attenuate HER2-driven tumor growth. However, resistance to trastuzumab-based therapy remains a major clinical problem for women with HER2+ breast cancer. Breast cancer stem cells (BCSCs) are suggested to be responsible for drug resistance and tumor recurrence. Notch signaling has been shown to promote BCSC survival and self-renewal. Trastuzumab-resistant cells have increased Notch-1 expression. Notch signaling drives cell proliferation in vitro and is required for tumor recurrence in vivo. We demonstrate herein a mechanism by which Notch-1 is required for trastuzumab resistance by repressing PTEN expression to contribute to activation of ERK1/2 signaling. Furthermore, Notch-1-mediated inhibition of PTEN is necessary for BCSC survival in vitro and in vivo. Inhibition of MEK1/2-ERK1/2 signaling in trastuzumab-resistant breast cancer cells mimics effects of Notch-1 knockdown on bulk cell proliferation and BCSC survival. These findings suggest that Notch-1 contributes to trastuzumab resistance by repressing PTEN and this may lead to hyperactivation of ERK1/2 signaling. Furthermore, high Notch-1 and low PTEN mRNA expression may predict poorer overall survival in women with breast cancer. Notch-1 protein expression predicts poorer survival in women with HER2+ breast cancer. These results support a potential future clinical trial combining anti-Notch-1 and anti-MEK/ERK therapy for trastuzumab-resistant breast cancer. PMID: 29743588
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it