Mammalian Target of Rapamycin Inhibitors as Possible Adjuvant Therapy for Microscopic Residual Disease in Head and Neck Squamous Cell Cancer
Bibliographic record
Abstract
Molecular therapeutics identifies an aberration in tumors to select patients that benefit from molecular targeted therapy. Overexpression of eIF4E in histologically "tumor-free" surgical margins of head and neck squamous cell cancer (HNSCC) patients is an independent predictor of recurrence and is functionally activated through the Akt/mammalian target of rapamycin (mTOR) pathway. Although mTOR inhibitors are cytostatic agents, best used in combination therapy, we hypothesize that they can be used as long-term single agents in an HNSCC model of minimal residual disease (MRD). CCI-779, an mTOR inhibitor, arrested growth of a phosphatase and tensin homologue deleted on chromosome 10 (PTEN) abnormal HNSCC cell line FaDu, inhibiting phosphorylation of 4E-binding protein 1, resulting in increased association with eIF4E and inhibition of basic fibroblast growth factor and vascular endothelial growth factor. Fluorescence in situ hybridization detected PTEN abnormalities in 68% of patient tumors and 35% of tumor-free margins. CCI-779 inhibited growth of established tumors in nude mice. However, in the MRD model, there were significant differences in the tumor-free rate between the control (4%) and the treatment group (50%), and the median tumor-free time was 7 versus 18 days, respectively (P < 0.0001). In those animals that formed tumors, CCI-779 caused a significant decrease in the tumor volume. The Kaplan-Meier curve showed that CCI-779 significantly increased survival (P < 0.0001). The mTOR pathway was inhibited in peripheral blood mononuclear cells potential surrogate markers of response to therapy. Stable transfection of FaDu with luciferase allowed us to monitor the effects of CCI-779 with bioluminescence imaging in the MRD model. These results pave the way for a clinical trial using targeted molecular therapy with CCI-779 as a single agent for mTOR-activated residual cells.
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 | 0.001 | 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".