Targeting of tumor endothelial cells combining 2 Gy/day of X‐ray with Everolimus is the effective modality for overcoming clinically relevant radioresistant tumors
Bibliographic record
Abstract
Radiotherapy is widely used to treat cancer because it has the advantage of physically and functionally conserving the affected organ. To improve radiotherapy and investigate the molecular mechanisms of cellular radioresistance, we established a clinically relevant radioresistant (CRR) cell line, SAS-R, from SAS cells. SAS-R cells continue to proliferate when exposed to fractionated radiation (FR) of 2 Gy/day for more than 30 days in vitro. A xenograft tumor model of SAS-R was also resistant to 2 Gy/day of X-rays for 30 days. The density of blood vessels in SAS-R tumors was higher than in SAS tumors. Everolimus, a mammalian target of rapamycin (mTOR) inhibitor, sensitized microvascular endothelial cells to radiation, but failed to radiosensitize SAS and SAS-R cells in vitro. Everolimus with FR markedly reduced SAS and SAS-R tumor volumes. Additionally, the apoptosis of endothelial cells (ECs) increased in SAS-R tumor tissues when both Everolimus and radiation were administered. Both CD34-positive and tomato lectin-positive blood vessel densities in SAS-R tumor tissues decreased remarkably after the Everolimus and radiation treatment. Everolimus-induced apoptosis of vascular ECs in response to radiation was also followed by thrombus formation that leads to tumor necrosis. We conclude that FR combined with Everolimus may be an effective modality to overcome radioresistant tumors via targeting tumor ECs.
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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 | 0.001 |
| 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 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".