Hereditary ovarian cancer and two-compartment tumor metabolism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mutations in the BRCA1 tumor suppressor gene are commonly found in hereditary ovarian cancers. Here, we used a co-culture approach to study the metabolic effects of BRCA1-null ovarian cancer cells on adjacent tumor-associated stromal fibroblasts. Our results directly show that BRCA1-null ovarian cancer cells produce large amounts of hydrogen peroxide, which can be abolished either by administration of simple antioxidants (N-acetyl-cysteine; NAC) or by replacement of the BRCA1 gene. Thus, the BRCA1 gene normally suppresses tumor growth by functioning as an antioxidant. Importantly, hydrogen peroxide produced by BRCA1-null ovarian cancer cells induces oxidative stress and catabolic processes in adjacent stromal fibroblasts, such as autophagy, mitophagy and glycolysis, via stromal NFκB activation. Catabolism in stromal fibroblasts was also accompanied by the upregulation of MCT4 and a loss of Cav-1 expression, which are established markers of a lethal tumor microenvironment. In summary, loss of the BRCA1 tumor suppressor gene induces hydrogen peroxide production, which then leads to metabolic reprogramming of the tumor stroma, driving stromal-epithelial metabolic coupling. Our results suggest that new cancer prevention trials with antioxidants are clearly warranted in patients that harbor hereditary/familial BRCA1 mutations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 it