Translational control of aberrant stress responses as a hallmark of cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Altered mRNA translational control is emerging as a critical factor in cancer development and progression. Targeting specific elements of the translational machinery, such as mTORC1 or eIF4E, is emerging as a new strategy for innovative cancer therapy. While translation of most mRNAs takes place through cap-dependent mechanisms, a sub-population of cellular mRNA species, particularly stress-inducible mRNAs with highly structured 5'-UTR regions, are primarily translated through cap-independent mechanisms. Intriguingly, many of these mRNAs encode proteins that are involved in tumour cell adaptation to microenvironmental stress, and thus linked to aggressive behaviour including tumour invasion and metastasis. This necessitates a rigorous search for links between microenvironmental stress and aggressive tumour phenotypes. Under stress, cells block global protein synthesis to preserve energy while maintaining selective synthesis of proteins that support cell survival. One highly conserved mechanism to regulate protein synthesis under cell stress is to sequester mRNAs into cytosolic aggregates called stress granules (SGs), where their translation is silenced. SGs confer survival advantages and chemotherapeutic resistance to tumour cells under stress. Recently, it has been shown that genetically blocking SG formation dramatically reduces tumour invasive and metastatic capacity in vivo. Therefore, targeting SG formation might represent a potential treatment strategy to block cancer metastasis. Here, we present the critical link between selective mRNA translation, stress adaptation, SGs, and tumour progression. Further, we also explain how deciphering mechanisms of selective mRNA translation occurs under cell stress holds great promise for the identification of new targets in the treatment of cancer. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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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) | 0.001 | 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 it