Enhancement of Cancer-Specific Protoporphyrin IX Fluorescence by Targeting Oncogenic Ras/MEK Pathway
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Bibliographic record
Abstract
Protoporphyrin IX (PpIX) is an endogenous fluorescent molecule that selectively accumulates in cancer cells treated with the heme precursor 5-aminolevulinic acid (5-ALA). This cancer-specific accumulation of PpIX is used to distinguish tumor from normal tissues in fluorescence-guided surgery (FGS) and to destroy cancer cells by photodynamic therapy (PDT). In this study, we demonstrate that oncogenic Ras/mitogen-activated protein kinase kinase (MEK) pathway can modulate PpIX accumulation in cancer cells. Methods: To identify Ras downstream elements involved in PpIX accumulation, chemical inhibitors were used. To demonstrate the increase of PpIX accumulation by MEK inhibition, different human normal and cancer cell lines, BALB/c mice bearing mammary 4T1 tumors and athymic nude mice bearing human tumors were used. To identify the mechanisms of PpIX regulation by MEK, biochemical and molecular biological experiments were conducted. Results: Inhibition of one of the Ras downstream elements, MEK, promoted PpIX accumulation in cancer cells treated with 5-ALA, while inhibitors against other Ras downstream elements did not. Increased PpIX accumulation with MEK inhibition was observed in different types of human cancer cell lines, but not in normal cell lines. We identified two independent cellular mechanisms that underlie this effect in cancer cells. MEK inhibition reduced PpIX efflux from cancer cells by decreasing the expression level of ATP binding cassette subfamily B member 1 (ABCB1) transporter. In addition, the activity of ferrochelatase (FECH), the enzyme responsible for converting PpIX to heme, was reduced by MEK inhibition. Finally, we found that in vivo treatment with MEK inhibitors increased PpIX accumulation (2.2to 2.4-fold) within mammary 4T1 tumors in BALB/c mice injected with 5-ALA without any change in normal organs. Similar results were also observed in a human tumor xenograft model.
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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 | 0.001 |
| 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 it