Rationale for Ras and Raf-kinase as a Target for Cancer Therapeutics
Bibliographic record
Abstract
Improvements in our understanding of the intrinsic aberrancies in cancer cells have enabled the design and development of novel therapeutics that specifically target these changes. Among the many complex cellular pathways and mechanisms which have been unveiled by new molecular techniques, RAS-mediated signal transduction is one met with tremendous research interests. Activation of RAS initiates several signaling cascades, of which the RAS-RAF-MEK-ERK pathway is among the better delineated, and is the main focus of this review. Other cellular consequences of RAS activation including interactions with the RHO-family proteins, the PI3-kinase pathway, and other mitogen activated protein kinase cascades, will be discussed. The intricate balance and coordination of multiple RAS-mediated signals lead to ultimate effects on cell growth, differentiation, cycling and survival. Pharmacological strategies such as analog development, synthesis of small molecule inhibitors, antisense technology, and vaccine therapy have been utilized to intervene with key RAS-signaling proteins, in an attempt to provide rational therapeutic solutions in malignant diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".