Abstract 326: Chemotherapies change the NRF2 levels and impact the differentiation and growth of human high grade serous ovarian cancer
Bibliographic record
Abstract
Abstract NRF2, an antioxidant gene and anti-inflammatory pathway, is altered in about 50% of high grade serous ovarian cancer (HGSOC), the most aggressive type of ovarian cancer. NRF2 is implicated in the resistance to chemotherapies in several types of cancers. We aimed to understand if treatment with carboplatin or paclitaxel impacts the levels of NRF2 and if that changes the differentiation, growth, and metastasis of HGSOC. We used OVCAR8, a human HGSOC cell line with a basal level of NRF2, and induced overexpression of NRF2 using pIND20 system with NRF2E79Q mutation (one of the most common mutations of NRF2 found in human tumors). Our results showed high growth and invasion in high-NRF2 tumor cells compared to low-NRF2 tumor cells with and without chemotherapies. Treatment with carboplatin inhibits the levels of NRF2 in low-and high-NRF2 versions of OVCAR8. Carboplatin also inhibits the MYC, P63, and CD274 (PD-L1) protein levels, and the epithelial to mesenchymal transition (EMT) pathway (Vimentin). Additionally, in high-NRF2 tumor cells, paclitaxel increases the levels of NRF2, MYC, CD274 (PD-L1), and Vimentin, and decreases the levels of P63. In contrast, low-NRF2 tumor cells treated with paclitaxel show decreased MYC, CD274 (PD-L1) and Vimentin and increased P63. These changes impact the growth and metastasis (by scratch test) of OVCAR8. We found that carboplatin inhibits the growth and invasion while paclitaxel increases the growth and invasion in the high-NRF2 version of OVCAR8. These studies show that carboplatin might be a good option as a single treatment compared to paclitaxel. In addition to the increase in NRF2 and differentiation markers that support the tumor cell growth, paclitaxel also increased the PD-L1 protein levels in high-NRF2 tumor cells which might enhance the efficacy of anti-PDL1. Therefore, combination immunotherapy (anti-PDL1) with paclitaxel may have therapeutic benefit in patients with high-NRF2 HGSOC. Citation Format: Chelsea Katz, Helen Toma, Yaas Azmoudeh, Nasrine Bendjilali, Huseyin Karaduman, Hadi Shojaei, Gord Zhu, Lauren Krill, Chu Christina, David P. Warshal, Yemin Wang, Samera H Hamad. Chemotherapies change the NRF2 levels and impact the differentiation and growth of human high grade serous ovarian cancer [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 326.
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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) | 0.003 | 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".