Dual Inhibition of Autophagy and PI3K/AKT/MTOR Pathway as a Therapeutic Strategy in Head and Neck Squamous Cell Carcinoma
Bibliographic record
Abstract
Genomic analyses of head and neck squamous cell carcinoma (HNSCC) have highlighted alterations in the phosphatidylinositol 3-kinase (PI3K) signaling pathway, presenting a therapeutic target for multiple ongoing clinical trials with PI3K or PI3K/MTOR inhibitors. However, these inhibitors can potentially increase autophagy in HNSCC and indirectly support cancer cell survival. Here, we sought to understand the relationship between the PI3K signaling pathway and autophagy during their dual inhibition in a panel of HNSCC cell lines. We used acridine orange staining, immunoblotting, and tandem sensor Red Fluorescent Protein- Green Fluorescent Protein-, microtubule-associated protein 1 light chain 3 beta (RFP-GFP-LC3B) expression analysis to show that PI3K inhibitors increase autophagosomes in HNSCC cells, but that chloroquine treatment effectively inhibits the autophagy that is induced by PI3K inhibitors. Using the Bliss independence model, we determined that the combination of chloroquine with PI3K inhibitors works in synergy to decrease cancer cell proliferation, independent of the PIK3CA status of the cell line. Our results indicate that a strategy focusing on autophagy inhibition enhances the efficacy of therapeutics already in clinical trials. Our results suggest a broader application for this combination therapy that can be promptly translated to in vivo studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".