Disruption of the ribosomal P complex leads to stress-induced autophagy
Bibliographic record
Abstract
The human ribosomal P complex, which consists of the acidic ribosomal P proteins RPLP0, RPLP1, and RPLP2 (RPLP proteins), recruits translational factors, facilitating protein synthesis. Recently, we showed that overexpression of RPLP1 immortalizes primary cells and contributes to transformation. Moreover, RPLP proteins are overexpressed in human cancer, with the highest incidence in breast carcinomas. It is thought that disruption of the P complex would directly affect protein synthesis, causing cell growth arrest and eventually apoptosis. Here, we report a distinct mechanism by which cancer cells undergo cell cycle arrest and induced autophagy when RPLP proteins are downregulated. We found that absence of RPLP0, RPLP1, or RPLP2 resulted in reactive oxygen species (ROS) accumulation and MAPK1/ERK2 signaling pathway activation. Moreover, ROS generation led to endoplasmic reticulum (ER) stress that involved the EIF2AK3/PERK-EIF2S1/eIF2α-EIF2S2-EIF2S3-ATF4/ATF-4- and ATF6/ATF-6-dependent arms of the unfolded protein response (UPR). RPLP protein-deficient cells treated with autophagy inhibitors experienced apoptotic cell death as an alternative to autophagy. Strikingly, antioxidant treatment prevented UPR activation and autophagy while restoring the proliferative capacity of these cells. Our results indicate that ROS are a critical signal generated by disruption of the P complex that causes a cellular response that follows a sequential order: first ROS, then ER stress/UPR activation, and finally autophagy. Importantly, inhibition of the first step alone is able to restore the proliferative capacity of the cells, preventing UPR activation and autophagy. Overall, our results support a role for autophagy as a survival mechanism in response to stress due to RPLP protein deficiency.
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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) | 0.000 | 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 | 0.001 |
| 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".