Hyperacute response proteins synthesized on γ-tubulin-FTO-MARK4 translation microdomains regulate cancer’s acute stress response
Bibliographic record
Abstract
Compared to normal cells, cancer cells are particularly resistant to stress, and their immediate response to stress is critical for subsequent adaptation, a major clinical challenge. With unbiased proteomics and transcriptomics, we identify a list of hyperacute response proteins (HARPs) translated from pre-existing mRNAs within 20 min of diverse stresses in several cancer cells, despite the known suppressed global translation in stress. HARP mRNAs are translated on microtubule-associated translation microdomains (MATMs) located on γ-tubulin, which host FTO and specialized distinct cytoskeletal ribosomes. FTO exits the nucleus immediately after stress and is activated by microtubule-associated kinase MARK4, demethylating a translation-inhibiting m6A mRNA methylation signature and facilitating compartmentalized HARP translation on MATMs, while non-HARP mRNAs remain inhibited. FTO or MARK4 inhibition suppresses HARP synthesis and increases apoptosis after various stresses, including chemotherapy. γ-tubulin, FTO, and MARK4 are therapeutic targets, as they comprehensively promote HARP translation, a potential Achilles' heel for cancer's resistance to physiologic or therapeutic stress.
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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) | 0.001 | 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".