Autophagy-dependent alternative splicing event produces a more stable ribosomal protein S24 isoform that aids in hypoxic cell survival
Bibliographic record
Abstract
ABSTRACT Overlapping or convergent stress-activated molecular pathways exist to coordinate cell fate in response to stimuli such as hypoxia, oxidative stress, DNA damage, and unfolded proteins. Cells can remodel the splicing and translation machineries to mount a specialized gene expression response to certain stresses. Here, we show that hypoxic human cells in 2D and 3D culture models increase the relative abundance by 1.7- to 2.6-fold and 4.7- to 11.5-fold, respectively, of a longer mRNA variant of ribosomal protein S24 (RPS24L) compared to a shorter mRNA variant (RPS24S) by favoring the inclusion of a 22 bp cassette exon. Mechanistically, RPS24L and RPS24S are induced and repressed, respectively, by distinct parallel pathways in hypoxia: RPS24L is induced in an autophagy-dependent manner, while RPS24S is reduced by mTORC1 repression and in a HIF-dependent manner. RPS24L is a more stable mRNA in hypoxia and produces a more stable protein isoform compared to RPS24S. Cells overexpressing RPS24L display improved survival and growth in hypoxia relative to control cells and cells overexpressing RPS24S, which display impaired survival. Previous work from our group showed a correlation between RPS24L levels and tumor hypoxia in prostate cancer. These data highlight RPS24L as a stress-induced alternative splicing event that favors hypoxic cell survival, which could be exploited by cancer cells in the tumor microenvironment.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".