Integrated Cell-Based Platform to Study EGFR Activation and Transactivation
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
The epidermal growth factor receptor (EGFR) pathway is one of the most deregulated molecular pathways in human epithelial cancers. Many approved drugs were optimized to directly target EGFR but yielded only modest clinical improvement in cancer patients due to low efficacy and drug resistance. Transactivation of EGFR by other cell surface receptors such as G-protein-coupled receptors (GPCRs) was proposed to explain this lack of efficacy. Even if direct EGFR activation and transactivation by GPCR contribute to the activation of the same signaling pathways, they are often studied as independent events resulting in partial investigation of a drug's mechanism of action. We present a novel high-throughput approach that integrates interrogation of direct activation of EGFR and its transactivation via GPCR activation. Using distinct technology platforms, three readouts were used to measure (1) direct activation of GPCR via cyclic adenosine monophosphate (cAMP) detection, (2) direct activation of EGFR through the release of intracellular Ca(2+), and (3) EGFR transactivation by GPCR using the detection of p-extracellular-signal-regulated kinases 1/2 (p-ERK1/2). In addition to being simple, quick, and homogenous, our methods were shown to be more sensitive than those in current use. These enabling tools should improve the knowledge pertaining to GPCRs and receptor tyrosine kinases trans-regulation and facilitate the design of more potent and better targeted new therapeutic strategies.
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