1161 Novel cyclophilin inhibitors could serve as an NK cell-stimulating immunotherapy for triple negative breast cancer
Bibliographic record
Abstract
Background Breast cancer is the most common cancer worldwide and triple negative breast cancer accounts for 15-20% of cases.Triple negative breast cancer has a high recurrence rate and high mortality.Significant levels of tumour-infiltrating lymphocytes within solid tumours make triple negative breast cancer a good candidate for immunotherapy.We have developed small molecule cyclophilin inhibitors, which by binding the natural killer triggering receptor, boost the ability of natural killer cells to kill triple negative breast cancer cells.Methods The NK92 natural killer cell line was co-cultured with the MDA-MB-231 triple negative breast cancer cell line in the presence of 10 mM cyclophilin inhibitor and cultures were imaged over 72 hours.The apoptotic fraction of the target cancer cell population in the presence and absence of cyclophilin inhibitor was then quantified.This cytolysis assay was also carried out with the addition of induced pluripotent stem cell-derived macrophages programmed in vitro to an immune suppressive phenotype.Results Live cell imaging of co-cultures (n=4) demonstrated that the novel cyclophilin inhibitors enhanced NK92-induced apoptosis of MDA-MB-231 cells up to 5-fold (p<0.0001) at 48 hours where peak apoptosis was observed.The inhibitors did not induce significant apoptosis of the cancer cells in the absence of NK92 cells and the efficacy of the inhibitors in enhancing NK92 cytolytic ability reflected the affinity of the inhibitors for the target cyclophilin determined by surface plasmon resonance.Interestingly, one of the inhibitors induced a 3-fold enhancement of NK92-induced killing compared to control while the effect of the S-enantiomer of this inhibitor was insignificant.The inhibitors enhanced NK92-induced apoptosis of target cancer cells even when immune-suppressive macrophages were present.Conclusions Together these data demonstrate that our novel small molecule inhibitors of the natural killer triggering receptor enhance the ability of natural killer cells to kill target triple negative breast cancers cells.This occurs even when immune-suppressive macrophages are present, suggesting these inhibitors could be developed as an immunotherapy and deployed in the neoadjuvant or adjuvant setting.As these molecules act on natural killer cells, they could potentially be combined with other immunotherapies such as checkpoint inhibitors, adoptive immunotherapies and CAR-NK cells for increased efficacy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".