Chemoresistance in high grade serous ovarian cancer molecular subtypes and the role of NRF2.
Bibliographic record
Abstract
e17574 Background: Epithelial ovarian cancer accounts for 90% of ovarian cancer diagnoses, 70% of which are high grade serous subtype (HGSOC). The HGSOC is the most aggressive type of Ovarian Cancer with limited therapeutic options. Studies have shown that several molecular subtypes of HGSOC exist such as immunoreactive, differentiated, proliferative, and mesenchymal, which further complicate the effort of finding therapies for this deadly cancer. Nuclear erythroid-related factor-2 (NRF2) is a transcription factor that is found to be frequently activated in ovarian cancer. NRF2 normally protects cells from oxidative damage by regulating more than 500 genes in human body. Hyperactivation of NRF2 in cancer is found to protect cancer cells from oxidative damage, and thus, promotes tumor growth and metastases. NRF2 is also known as an anti-inflammatory pathway and a master regulator of immune cells differentiation, distribution, and infiltration. Patients with high-NRF2 tumors tend to have significantly lower survival than patients with Low-NRF2 tumors. In this study, we investigate the role of NRF2 in HGSOC subtype evolution and responses to chemotherapies. Methods: Two human HGSOC cell lines, OVCAR8 and PEO1 were used to identify and quantify the NRF2 protein level with its down-stream targets. We also quantified differentiation markers such as Vimentin, P63, PD-L1, that are associated with HGSOC subtypes, using western blotting. These human cell lines were also tested for Carboplatin and Paclitaxel half maximal inhibitory concentration (IC50) using MTT assay. RNA-seq data of human HGSOC from The Cancer Genome Atlas (TCGA) was analyzed to compare our in vitro studies with human tumors. Results: The human OVCAR8 cell line had a 50-fold higher expression of NRF2 and 12-fold higher expression of vimentin when compared to the PEO1 cell line. When treated with Carboplatin, the IC50 for OVCAR8 was 112 ± 3.6 µM vs 67.5 ± 5µM for PEO1. For Paclitaxel, the IC50s for the two cell lines were 5 ± 0.4nM and 4 ± 0.15nM, respectively. Finally, RNA sequencing data from the TCGA showed that the NRF2 activation score in mesenchymal subtype was significantly increased compared to the immunoreactive subtype (p=0.004). Conclusions: Our data show that expression of NRF2 is significantly higher in the mesenchymal (the most chemo-resistant and aggressive) subtype, while the subtypes with lower NRF2 tend to be more responsive to chemotherapies. These findings imply that targeting NRF2 in these subtypes could improve responses to chemotherapies and enhance tumor prognosis in patients with HGSOC.
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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".