Internalisation enhances photo-induced cytotoxicity of monoclonal antibody-phthalocyanine conjugates
Bibliographic record
Abstract
Immunophototherapy of cancer combines the specificity of a monoclonal antibody (MAb) to an overexpressed tumor marker with the phototoxic properties of the conjugated dye. To analyze the potential role of internalisation of the dye on photo-induced cytotoxicity, we compared two target antigens, carcinoembryonic antigen (CEA) that does not internalise and ErbB2 that does. Human ovarian carcinoma SKOv3 cells that express a high level of ErbB2 were transfected with the CEA cDNA. Using FACS analysis, the resulting cell line, SKOv3-CEA-1B9, demonstrated comparable levels of expression of the two target antigens. Aluminium tetrasulfophthalocyanine (AlPcS(4)) was covalently coupled to anti-CEA MAb 35A7, anti-ErbB2 MAb FSP77 and a non-specific MAb PX, via a five-carbon sulfonamide spacer chain (A(1)) at molar ratios ranging from 6 to 9 moles of AlPcS(4) per mole of MAb. The 35A7-(AlPcS(4)A(1))(8) conjugate induced 68% growth inhibition of the SKOv3-CEA-1B9 cell line after a 20 h incubation at 2.50 microg/ml (based on AlPcS(4)A(1) content) following light exposure. However, the FSP77-(AlPcS(4)A(1))(6) conjugate gave a 51% growth inhibition for an AlPcS(4)A(1) concentration as low as 0.04 microg/ml after the same incubation time and exposure to the same light dose. At a 1.25 microg/ml AlPcS(4)A(1) concentration, the FSP77-(AlPcS(4)A(1))(6) conjugate gave a 67% growth inhibition after an incubation time as short as 1 h, reaching a 96% inhibition after an 8 h incubation time. Using an unique cell line that expresses two different target antigens, we demonstrated a clear advantage of an internalising over a non-internalising MAb-dye conjugate in terms of phototoxic efficacy. In vivo evaluation of the photodynamic properties of the conjugates is in progress.
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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) | 0.000 | 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".