Epidermal growth factor regulates Mcl-1 expression through the MAPK-Elk-1 signalling pathway contributing to cell survival in breast cancer
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
Myeloid cell leukaemia-1 (Mcl-1) is an anti-apoptotic member of the Bcl-2 family that is elevated in a variety of tumour types including breast cancer. In breast tumours, increased Mcl-1 expression correlates with high tumour grade and poor patient survival. We have previously demonstrated that Her-2 levels correspond to increased Mcl-1 expression in breast tumours. Epidermal growth factor (EGF) receptor signalling is frequently deregulated in breast cancer and leads to increased proliferation and survival. Herein, we determined the critical downstream signals responsible for the EGF mediated increase of Mcl-1 and their role in cell survival. We found that both Mcl-1 mRNA and protein levels are rapidly induced upon stimulation with EGF. Promoter analysis revealed that an Elk-1 transcription factor-binding site is critical for EGF activation of the Mcl-1 promoter. Furthermore, we found that knockdown of Elk-1 or inhibition of the Erk signalling pathway was sufficient to block EGF upregulation of Mcl-1 and EGF mediated cell survival. Using chromatin immunoprecipitation and biotin labelled probes of the Mcl-1 promoter, we found that Elk-1 and serum response factor are bound to the promoter after EGF stimulation. To determine whether Mcl-1 confers a survival advantage, we found that knockdown of Mcl-1 expression increased apoptosis whereas overexpression of Mcl-1 inhibited drug induced cell death. In human breast tumours, we found a correlation between phosphorylated Elk-1 and Mcl-1 protein levels. These results indicate that the EGF induced activation of Elk-1 is an important mediator of Mcl-1 expression and cell survival and therefore a potential therapeutic target in breast cancer.
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 | 0.000 | 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 it