Enhanced killing of SCC17B human head and neck squamous cell carcinoma cells after photodynamic therapy plus fenretinide via the de novo sphingolipid biosynthesis pathway and apoptosis
Bibliographic record
Abstract
Because photodynamic therapy (PDT) alone is not always effective as an anticancer treatment, PDT is combined with other anticancer agents for improved efficacy. The clinically-relevant fenretinide [N-(4-hydroxyphenyl) retinamide; 4HPR], was combined with the silicon phthalocyanine photosensitizer Pc4-mediated PDT to test for their potential to enhance killing of SCC17B cells, a clinically-relevant model of human head and neck squamous cell carcinoma. Because each of these treatments induces apoptosis and regulates the de novo sphingolipid (SL) biosynthesis pathway, the role of ceramide synthase, the pathway-associated enzyme, in PDT+4HPR-induced apoptotic cell death was determined using the ceramide synthase inhibitor fumonisin B1 (FB). PDT+4HPR enhanced loss of clonogenicity. zVAD-fmk, a pan-caspase inhibitor, and FB, protected cells from death post-PDT+4HPR. In contrast, the anti-apoptotic protein Bcl2 inhibitor ABT199 enhanced cell killing after PDT+4HPR. Combining PDT with 4HPR led to FB-sensitive, enhanced Bax associated with mitochondria and cytochrome c redistribution. Mass spectrometry data showed that the accumulation of C16-dihydroceramide, a precursor of ceramide in the de novo SL biosynthesis pathway, was enhanced after PDT+4HPR. Using quantitative confocal microscopy, we found that PDT+4HPR enhanced dihydroceramide/ceramide accumulation in the ER, which was inhibited by FB. The results suggest that SCC17B cells are sensitized to PDT by 4HPR via the de novo SL biosynthesis pathway and apoptosis, and imply potential clinical relevance of the combination for cancer treatment.
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 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".