Enhanced Killing of Primary Ovarian Cancer by Retargeting Autologous Cytokine-Induced Killer Cells with Bispecific Antibodies: A Preclinical Study
Bibliographic record
Abstract
Cytokine-induced killer (CIK) cells are ex vivo activated and expanded CD8+ natural killer T cells that have been shown to have antitumor activity. This is the first study exploring cell killing of primary ovarian carcinoma cells with and without bispecific antibodies. Primary cancer cells and autologous CIK cells were collected from women with epithelial ovarian cancer. Bispecific antibodies against cancer antigen-125 (BSAbxCA125) and Her2 (BSAbxHer2) were developed using chemical heteroconjugation. On fluorescence-activated cell sorting analysis, the expansion of CIK cells resulted in a significant increase of CD3+CD8+ and CD3+CD56+ T cells. With enhancement by bispecific antibodies, the mean percent lysis in a 51Cr release assay of fresh ovarian cancer cells exposed to autologous CIK cells increased from 21.7 +/- 0.3% to 89.4 +/- 2.1% at an E:T ratio of 100:1 (P < 0.001). Anti-NKG2D antibodies attenuated the CIK activity by 56.8% on primary cells (P < 0.001). In a xenograft severe combined immunodeficient mouse model, real-time tumor regression and progression was visualized using a noninvasive in vivo bioluminescence imaging system. Four hours after CIK cell injection, we were able to visualize CD8+NKG2D+ CIK cells infiltrating Her2-expressing cancer cells on fluorescence microscopy. Mice that underwent adoptive transfer of CIK cells redirected with BSAbxCA125 and BSAbxHer2 had significant reduction in tumor burden (P < 0.001 and P < 0.001) and improvement in survival (P = 0.05 and P = 0.006) versus those treated with CIK cells alone. Bispecific antibodies significantly enhanced the cytotoxicity of CIK cells in primary ovarian cancer cells and in our in vivo mouse model. The mechanism of cytolysis seems to be mediated in part by the NKG2D receptor.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".