Oncogenic RAS-induced downregulation of ATG12 is required for survival of malignant intestinal epithelial cells
Bibliographic record
Abstract
Activating mutations of RAS GTPase contribute to the progression of many cancers, including colorectal carcinoma. So far, attempts to develop treatments of mutant RAS-carrying cancers have been unsuccessful due to insufficient understanding of the salient mechanisms of RAS signaling. We found that RAS downregulates the protein ATG12 in colon cancer cells. ATG12 is a mediator of autophagy, a process of degradation and reutilization of cellular components. In addition, ATG12 can kill cells via autophagy-independent mechanisms. We established that RAS reduces ATG12 levels in cancer cells by accelerating its proteasomal degradation. We further observed that RAS-dependent ATG12 loss in these cells is mediated by protein kinases MAP2K/MEK and MAPK1/ERK2-MAPK3/ERK1, known effectors of RAS. We also demonstrated that the reversal of the effect of RAS on ATG12 achieved by the expression of exogenous ATG12 in cancer cells triggers both apoptotic and nonapoptotic signals and efficiently kills the cells. ATG12 is known to promote autophagy by forming covalent complexes with other autophagy mediators, such as ATG5. We found that the ability of ATG12 to kill oncogenic RAS-carrying malignant cells does not require covalent binding of ATG12 to other proteins. In summary, we have identified a novel mechanism by which oncogenic RAS promotes survival of malignant intestinal epithelial cells. This mechanism is driven by RAS-dependent loss of ATG12 in these cells.
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 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 | 0.000 | 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) | 0.001 | 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 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".