Two antibodies directed at complement activation regulating protein CD59 exhibit efficacy in multiple human cancer models
Bibliographic record
Abstract
4626 CD59 is an inhibitor of complement activation. By blocking the formation of the membrane attack complex (MAC), CD59 terminates the complement cascade that would otherwise lead to destruction of the target cell. It has been postulated that over-expression of complement inhibitory proteins such as CD59 may contribute to enhanced resistance of complement activation that malignant tumors often exhibit. If this is the case, monoclonal antibodies directed against complement inhibitory proteins could overcome this resistance, making the tumor more responsive to treatment. Two antibodies, AR10A304.7 and AR36A36.11.1, have been raised by immunizing mice with colon and prostate cancer cell lines, respectively. Both antibodies target CD59 and have exhibited binding to colon, pancreas, breast, prostate and ovarian cancer cell lines and in vitro cytotoxicity against colon cancer cell lines. AR10A304.7 has shown additional cytotoxicity against pancreas, breast, prostate and ovarian cancer cell lines. Both antibodies have also shown anti-tumor effects in vivo . Treatment with AR10A304.7 and AR36A36.11.1 (20 mg/kg) in a prophylactic MDA-MB-231 breast cancer xenograft model resulted in tumor growth inhibition of 98% (p 3 at the start of treatment and treated with 20 mg/kg. These data demonstrate that antibodies targeting CD59 have anti-tumor effects in various cancer types, including breast, colon and prostate. The in vitro data indicate that the antibodies act on tumor cells directly in the absence of complement, and this effect may be translated into animal models of human cancer.
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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 | 0.000 | 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) | 0.002 | 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".