Estrogen receptor β‐mediated nuclear interaction between IRS‐1 and Rad51 inhibits homologous recombination directed DNA repair in medulloblastoma
Bibliographic record
Abstract
In medulloblastomas, which are highly malignant cerebellar tumors of the childhood genotoxic treatments such as cisplatin or gamma-irradiation are frequently associated with DNA damage, which often associates with unfaithful DNA repair, selection of new adaptations and possibly tumor recurrences. Therefore, better understanding of molecular mechanisms which control DNA repair fidelity upon DNA damage is a critical task. Here we demonstrate for the first time that estrogen receptor beta (ERbeta) can contribute to the development of genomic instability in medulloblastomas. Specifically, ERbeta was found highly expressed and active in mouse and human medulloblastoma cell lines. Nuclear ERbeta was also present in human medulloblastoma clinical samples. Expression of ERbeta coincided with nuclear translocation of insulin receptor substrate 1 (IRS-1), which was previously reported to interfere with the faithful component of DNA repair when translocated to the nucleus. We demonstrated that ERbeta and IRS-1 bind each other, and the interaction involves C-terminal domain of IRS-1 (aa 931-1233). Following cisplatin-induced DNA damage, nuclear IRS-1 localized at the sites of damaged DNA, and interacted with Rad51--an enzymatic component of homologous recombination directed DNA repair (HRR). In medulloblastoma cells, engineered to express HRR-DNA reporter plasmid, ER antagonist, ICI 182,780, or IRS mutant (931-1233) significantly increased DNA repair fidelity. These data strongly suggest that both molecular and pharmacological interventions are capable of preventing ERbeta-mediated IRS-1 nuclear translocation, which in turn improves DNA repair fidelity and possibly counteracts accumulation of malignant mutations in actively growing medulloblastomas.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".