Diosmetin enhances the sensitivity of radiotherapy by suppressing homologous recombination in endometrial cancer
Bibliographic record
Abstract
Radiotherapy is an essential treatment for endometrial cancer (EC), especially in advanced, metastatic, and recurrent cases. Combining radiotherapy, which mainly causes DNA double-strand breaks (DSBs), with small molecules targeting aberrantly activated homologous recombination (HR) repair pathways holds great potential for treating ECs in advanced stages. Here, we demonstrate that diosmetin (DIO), a natural flavonoid, suppresses HR, therefore inhibiting cell proliferation and enhancing the sensitivity of EC to radiotherapy. Clonogenic experiments revealed that combining DIO and X-ray significantly inhibited the viability of EC cells compared to cells treated with diosmetin or X-ray alone. The survival fraction of EC cells decreased to 40% when combining 0.4 Gy X-ray and 4 μM DIO; however, each treatment alone only caused death in approximately 15% and 22% of cancer cells, respectively. Further mechanistic studies showed that diosmetin inhibited the recruitment of RPA2 and RAD51, two critical factors involved in the HR repair pathway, upon the occurrence of DSBs. Thus, we propose that a combination of diosmetin and irradiation is a promising therapeutic strategy for treating endometrial cancer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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".