Cytotoxic properties of radionuclide-conjugated Cetuximab without and in combination with external irradiation in head and neck cancer cells in vitro
Bibliographic record
Abstract
PURPOSE: Epidermal growth factor receptor (EGFR) is critically involved in progression and therapy resistance of squamous cell carcinoma (SCC). Albeit EGFR targeting could improve the effect of radiotherapy on patients' outcome, the clinical results failed to meet expectations from preclinical studies. In this work, we evaluated the potential of the radionuclide Yttrium-90 ((90)Y) bound to Cetuximab ((90)Y-Cetuximab) as novel targeting approach for SCC cells in vitro. MATERIALS AND METHODS: FaDu and A431 cell lines were used. EGFR subcellular localization, clonogenic survival, radiation-induced γH2AX foci and EGFR signaling were examined. Cells were treated with DTPA, DTPA-Cetuximab, (90)Y and (90)Y-Cetuximab alone or in combination with external X-ray irradiation. RESULTS: Dose- and cell line-dependently, (90)Y-Cetuximab mediated a significant reduction in clonogenicity relative to unbound (90)Y. Combined 2-Gy external radiation plus 2-Gy equivalent dose of (90)Y-Cetuximab was more effective than equivalent doses of (90)Y and X-ray radiation. Analogous effects were observed in the number of residual radiation-induced foci. Additionally, EGFR, ERK1/2 and AKT phosphorylation showed alterations upon different treatments. CONCLUSIONS: Our findings show that Cetuximab-conjugated (90)Y has a significant potential to eradicate human SCC cells. A combination of radioimmunotherapeutic compounds and external radiotherapy might be a promising treatment strategy for clinical application.
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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) | 0.001 | 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".