Inhibition of autophagy augments apoptosis in human oral squamous cell carcinoma under nutrient depletion
Bibliographic record
Abstract
There has been little research conducted regarding autophagy in oral squamous cell carcinoma (OSCC). Given the prevalence of oral cancers which are OSCC and the severe side effects of current treatments, there is a pressing need to develop effective alternative therapies. In this study, we have endeavored to explore the biological characteristics of oral squamous cell carcinoma cell line KB cells, in particular with regard to the role played by autophagy in their survival. Autophagy was activated by nutrient depletion via culturing cells in Earle's balanced salts (EBSS) and was measured via indices relating to Beclin 1, microtubule-associated protein light chain 3 (MAPLC3, LC3), p62, and Green fluorescent protein-light chain 3 plasmid transfection (GFP-LC3). Cell death and apoptosis induced by nutrient depletion was measured using both MTT assay and flow cytometry (FCM). Compared to initial levels at 0 h, Beclin 1 density in EBSS-treated cells was found to have increased at 6, 12, and 18 h in a time-dependent manner and was found to have subsequently declined at 24 and 48 h. p62 levels, LC3-II/LC3-I ratio, and GFP-LC3 levels increased at 6, 12, 18, 24, and 48 h in a time-dependent manner. 3-methyladenine (3-MA) was found to inhibit autophagy and the expression of Beclin 1 and significantly enhanced nutrient depletion-induced apoptosis and death. We concluded that nutrient depletion enhances OSCC cell autophagy in time-course patterns and that the inhibition of autophagy augments apoptosis in OSCC cells. We also deduced that Beclin 1 takes part in the development and progression of autophagy, potentially playing an important role in the crosstalk between apoptosis and autophagy in OSCC cells. These findings suggest that nutrient depletion may be an effective way to explore autophagy and that autophagy inhibitors should be investigated as a potential novel agent for the adjuvant treatment of human OSCC.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".