Abstract 2246: Senescence as a result of impaired ribosome biogenesis
Bibliographic record
Abstract
Abstract Senescence is a stable arrest of cell proliferation in which the cells remain viable and metabolically active but display a constitutive activation of the DNA damage response and of the tumor suppressors p53 and RB. The senescent phenotype can be induced by multiple stresses including short telomeres and oncogenes. We have shown that senescence, involves the ERK-dependent degradation of selective proteins involved in cell cycle progression and tumorigenesis. We call this process senescence associated protein degradation (SAPD) and it involves many nucleolar proteins that play a role in ribosome biogenesis. Using tritium pulse labelling we found a strong decrease of rRNA synthesis in senescent cells indicating that the degradation of nucleolar proteins is functionally relevant. Because we know how exactly the human 47S precursor rRNA is processed, it was possible to design primers on both sides of some processing sites and study their maturation by QPCR. In this way we showed defects in the processing of rRNA in senescent cells. Knocking down some of the nucleolar proteins degraded in senescence was sufficient to trigger the process indicating that a decrease in ribosome biogenesis is causal to cellular senescence. Mechanistically, the degradation of nucleolar proteins during senescence involves the ubiquitin-proteasome system suggesting that E3 ligases link the oncogenic stress that trigger senescence to nucleolar proteins degradation. We will discuss ongoing efforts to identify these enzymes. Citation Format: Frédéric Lessard, Véronique Bourdeau, Xavier Deschênes-Simard, Sebastian Igelmann, Marinieve Montero, Gerardo Ferbeyre. Senescence as a result of impaired ribosome biogenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2246. doi:10.1158/1538-7445.AM2014-2246
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".