Sirt3 Regulates Radioresistance of Non-small Cell Lung Cancer through ATM-Chk2 Pathway
Bibliographic record
Abstract
Abstract With high incidence and mortality, non-small cell lung cancer (NSCLC) represent 85-90% in all lung cancer patients. In addition to surgery and chemotherapy, radiotherapy is an indispensable approach for cancer treatment. However, cellular resistance to ionizing radiation often results in failure in treatment. In this study, we aimed to investigate the role of Sirt3 in radiotherapy on NSCLC. Briefly, survival as well as apoptosis assay were used to determine the cellular radiosensitivity, and an in situ lung cancer model to test the radiosensitivity in vivo. Firstly, our data show that Sirt3 is upregulated in NSCLC cell lines, as well as tissues compared with normal tissues. Then we generated Sirt3 knockdown cells and overexpression cells and found that Sirt3 knockdown increased radiosensitivity, while Sirt3 overexpression caused resistance. Sirt3 knockdown also aggravated the G2/M cell cycle arrest caused by irradiation. Furthermore, Sirt3 was found to be critical for the activation of ATM-Chk2 pathway upon irradiation. Finally, our in vivo model showed that targeting Sirt3 significantly sensitized lung cancer to radiotherapy. In conclusion, our findings identified a significant role of Sirt3 in radioresistanct of NSCLC, which provides novel mechanism as well as target for radiotherapy.
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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 | 0.001 |
| 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) | 0.005 | 0.001 |
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".