Abstract 1503: Elucidating the role of transcription coregulator MED15 in cancer cell oxidative stress response and proliferation
Bibliographic record
Abstract
Abstract Hyperproliferation is a hallmark of cancer that leads to increased ROS levels, leading to oxidative stress, which causes DNA damage and reinforces cell proliferation. To grow in these conditions, cancer cells activate cellular pathways to rewire the transcriptome to promote oxidative stress resistance. Mapping these response pathways can lead to potential new drugs. Mediator complex subunit MED15 is upregulated in many cancer types and confers oxidative stress resistance in lower animals. To test if MED15 promotes oxidative stress resistance in cancer, we generated three MED15 knockout A549 lung adenocarcinoma cells. Transcriptome, real-time quantitative PCR, and Western Blot analysis showed that MED15 loss downregulates oxidative stress response genes, both at baselines and after stress-inducing compounds. Furthermore, the MED15 knockouts were observed to proliferate slower, so I performed cell cycle analysis using flow cytometry which showed that MED15 knockouts arrest cell cycle more after serum starvation compared to their wild-type counterparts. In sum, our data indicate that MED15 is required for normal cancer cell stress resistance and growth. This has clinical potential, as MED15 can be targeted by small molecules, making it a promising drug target. Citation Format: Chiaki Shuzenji, Xuanjin Cheng, Stefan Taubert. Elucidating the role of transcription coregulator MED15 in cancer cell oxidative stress response and proliferation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1503.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".