Metabolic Regulator IAPP (Amylin) Is Required for BRAF and RAS Oncogene-Induced Senescence
Bibliographic record
Abstract
Abstract Cellular senescence is characterized by a prolonged and predominantly irreversible cell-cycle arrest state, which is linked to loss of tissue function and aging in mammals. Moreover, in response to aberrant oncogenic signals such as those from oncogenic RAS or BRAF, senescence functions as an intrinsic tumor suppressor mechanism restraining tumor progression. In addition to this durable proliferative block, senescent cells adopt altered morphologies, transcriptional profiles, and metabolism, while often possessing unusual heterochromatin formation termed senescence-associated heterochromatic foci. To uncover genes that are required to permit proliferation in the face of sustained oncogene signaling, we conducted an shRNA-based genetic screen in primary cells expressing inducible BRAF. Here we show that depletion of a known glycolysis regulator, islet amylin polypeptide (IAPP also known as amylin), prevents RAS and BRAF oncogene-induced senescence (OIS) in human cells. Importantly, depletion of IAPP resulted in changes of the cells' metabolome and this metabolic reprogramming was associated with widespread alterations in chromatin modifications compared with senescent cells. Conversely, exogenous treatment of IAPP-depleted cells with amylin restored OIS. Together, our results demonstrate that the metabolic regulator IAPP is important regulator of OIS. Moreover, they suggest that IAPP analog treatment or activation of IAPP signaling in RAS/BRAF mutant tumors may have therapeutic potential through senescence induction. Implications: These findings demonstrate that IAPP is a novel metabolic regulator of oncogene-induced senescence and use of IAPP analogs may be therapeutically effective to restore growth arrest to BRAF and/or RAS mutant cancers.
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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 | 0.001 | 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".