Abstract PR002: Hypoxia-induced epigenetic changes coordinate transcription start site selection and translational control through remodeling of 5’UTRs
Bibliographic record
Abstract
Abstract Adaptation to hypoxia enhances cancer cell malignancy and negatively impacts patient outcomes. Reprogramming of mRNA translation is an essential component of the hypoxia-adaptive response. During hypoxia, cells undergo a global decrease in protein synthesis. However, translation of subsets of transcripts encoding stress-response, survival and stemness factors is increased. This selective regulation is thought to be governed largely via the interactions between specific mRNA features and remodeling of the translational apparatus. However, our understanding of the mechanisms that govern translational perturbations under hypoxia remains incomplete. Here, we interrogated the effects of hypoxia on global changes in histone methylation and transcription start site (TSS) selection, coupled with monitoring corresponding alterations in total mRNA levels and translation efficiencies on a genome-wide scale in T47D breast cancer cells and H9 human embryonic stem cells. This revealed widespread epigenetic alterations leading to TSS switching and extensive remodeling of 5’UTRs, and allowed us to map the impact of specific 5’UTR features on translation efficiency under hypoxia. Pyruvate Dehydrogenase Kinase 1 (PDK1), a key enzyme in orchestrating metabolic adaption to hypoxia, undergoes TSS switching leading to increased availability of efficiently translated 5’UTR isoforms, and we show that this effect is coordinated at an epigenetic level. Therefore, our findings uncover a mechanism driving translational reprogramming under hypoxia, whereby alterations in translational apparatus are orchestrated with epigenetic perturbations that result in 5’UTR remodeling of the transcriptome. Citation Format: Kathleen Watt, Bianca Dauber, Krzysztof J Szkop, Laura Lee, Predrag Jovanovic, Shan Chen, Laia Masvidal, Kristofersson Tandoc, Ranveer Palia, Ivan Topisirovic, Ola Larsson, Lynne-Marie Postovit. Hypoxia-induced epigenetic changes coordinate transcription start site selection and translational control through remodeling of 5’UTRs [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr PR002.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".