Abstract SY26-02: Keeping Mitochondria Happy: How peroxisomes regulate mitochondria oxidative stress
Bibliographic record
Abstract
Abstract Cancer cells undergo complex metabolic reprogramming, allowing them to survive and proliferate in their specific niche. Mitochondria play a key role in metabolism remodeling, and these changes can often lead to mitochondrial stress. However, the cancer cells must keep mitochondria “happy” due to their role in cellular death pathways. Mitochondria are the major producer of reactive oxygen species (ROS). Although mitochondrial ROS is required for cell signaling, excessive ROS production can activate various cell death pathways. Thus, understanding how cancer cells regulate mitochondrial ROS may provide insights into new therapeutic targets for cancer treatments. Yet, our understanding of how cells regulate mitochondria redox homeostasis is limited. Peroxisomes possess one of the most potent antioxidants, Catalase, and it has long been believed to regulate cellular redox homeostasis by scavenging cellular ROS. Interestingly, genetic mutations in peroxisomal genes called Zellweger Spectrum Disorders (ZSD) result in the loss of peroxisomal structures but not Catalase. However, in both patient tissues and animal models of ZSD, an accumulation of oxidatively damaged mitochondria was observed in almost all cell types. This talk will present published and unpublished work addressing how peroxisomes regulate mitochondria redox homeostasis. Our work suggests that peroxisomes directly interact with respiring mitochondria to regulate mitochondrial redox homeostasis. In the end, we will present a model by which peroxisomes regulate mitochondria health during conditions of cellular stress and its potential as a therapeutic target to induce cell death. Citation Format: Peter Kijun Kim. Keeping Mitochondria Happy: How peroxisomes regulate mitochondria oxidative stress [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr SY26-02.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".