Cancer stem cell populations are resistant to 5-aminolevulinic acid-photodynamic therapy (5-ALA-PDT)
Bibliographic record
Abstract
Photodynamic therapy (PDT) is a minimally invasive treatment approved for many types of cancers. PDT involves the administration of photoactive substances called photosensitizers (PS) that selectively accumulate in cancer cells and are subsequently excited/activated by irradiation with light at wavelengths of optimal absorbance. Activated PS leads to the generation of singlet oxygen and other reactive oxygen species (ROS), promoting cancer cell death. 5-aminolevulinic acid (5-ALA) is a naturally occurring PS precursor, which is metabolically converted to the PS, protoporphyrin IX (PPIX). Although 5-ALA-PDT is effective at killing cancer cells, in prior studies conducted by our group we normally observed in in vitro experiments that approximately 5-10% of cells survive 5-ALA-PDT, which served as an impetus for further investigation. Identifying the mechanisms of resistance to 5-ALA-PDT-mediated cell death is important to prevent tumor recurrence following 5-ALA-PDT. Previously, we reported that oncogenic activation of Ras/MEK promotes PPIX efflux and reduces cellular sensitivity to 5-ALA-PDT through increased expression of ABCB1 transporter. As cancer stem cells (CSCs) are known to drive resistance to other cancer treatments and have high efflux of chemotherapeutic agents via ABC-family transporters, we hypothesize that CSCs underlie 5-ALA-PDT resistance. In this study, we determined (1) if CSCs are resistant to 5-ALA-PDT and (2) if CSCs play roles in establishing resistant populations of 5-ALA-PDT. When we compared CSC populations before and after 5-ALA-PDT, we found that CSCs were less susceptible to 5-ALA-PDT. Moreover, we found that the CSC population was enriched in 5-ALA-PDT-resistant cell lines compared to the parental cell line. Our results indicate that CSCs are not sensitive to 5-ALA-PDT, which may contribute to establishment of 5-ALA-PDT resistance.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".