Abstract B69: Dynamic reprogramming of signaling following Met inhibition reveals pathways for cell proliferation and negative feedback in gastric cancer.
Bibliographic record
Abstract
Abstract The Met receptor tyrosine kinase activates multiple signalling pathways in response to stimulation by ligand. However, the signalling events that occur under chronic Met activation in cancer cells are poorly understood. Utilizing a pharmacological small-molecule inhibitor of Met, we demonstrate that the gastric cancer cell lines, Okajima, MKN45, Snu-5 and KATO II are dependent on Met signalling for proliferation and anchorage-independent growth. We show that short-term inhibition of Met leads to waves of changes in gene expression such as a rapid loss of immediate-early genes, negative regulators, and a more delayed decrease in genes involved in the cell-cycle and proliferation. At the post-translational level, the Ras-Erk, PI3K-Akt and STAT3 pathways were all found to be dependent on Met signalling in these cells, though STAT3 signalling was the key requirement for proliferation, downstream from Met. We also observed the loss of negative regulators of Erk signalling, such as DUSP4 and DUSP6, which allowed for Mek-dependent reactivation of Erk, in the presence of Met inhibitor. As Met inhibitors are currently in clinical trials, it is essential to understand the molecular events that occur upon treatment, such that we can more effectively target sensitive tumours and avoid resistance. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B69. Citation Format: Andrea Lai, Sean Cory, Hong Zhao, Bita Sehat, Ali Tofigh, Marie-Christine Guiot, Crista Thompson, Emily S. Bell, Nicholas Bertos, Lorenzo E. Ferri, Michael Hallett, Morag Park. Dynamic reprogramming of signaling following Met inhibition reveals pathways for cell proliferation and negative feedback in gastric cancer. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B69.
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.
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 | 0.000 | 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 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".