Heat Shock Protein 27 as a New Therapeutic Target for Radiation Sensitization of Head and Neck Squamous Cell Carcinoma
Bibliographic record
Abstract
In a wide range of human cancers, increased levels of heat shock protein 27 (Hsp27) are closely associated with tumorigenesis, metastasis, resistance to anticancer therapeutics, and thus poor prognosis. In this study, we evaluate the radiosensitizing effects of Hsp27 gene silencing using OGX-427, a second-generation antisense oligonucleotide (ASO), on the radioresistant head and neck squamous cell carcinoma (HNSCC) SQ20B cells. In vitro, the downregulation of Hsp27 significantly enhanced radiation-induced apoptotic and clonogenic death, and promoted Akt inactivation. In vivo, combining OGX-427 with local tumor irradiation (5 x 2 Gy) led to a significant regression of SQ20B tumors related to a high rate of apoptosis and decreased levels of glutathione antioxidant defenses. Increasing the total radiation dose (15 x 2 Gy) significantly amplified the radiosensitizing effect of OGX-427. Treatment of tumors with OGX-427 plus radiation resulted in a decrease in angiogenesis associated with a reduced activation of the Akt pathway. Furthermore, the combined treatment enhanced the survival of SQ20B-bearing mice and showed no signs of acute and delayed toxicity. Our findings demonstrate for the first time that Hsp27 knockdown enhances the cytotoxic effects of radiotherapy in vivo and provide preclinical proof of principle for clinical trials using Hsp27 antisense technology in the treatment of patients with HNSCC radioresistant cancers.
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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 | 0.000 |
| 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 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".