Ex Vivo-expanded Natural Killer Cells Derived From Long-term Cryopreserved Cord Blood are Cytotoxic Against Primary Breast Cancer Cells
Bibliographic record
Abstract
With over 600,000 units of umbilical cord blood (CB) stored on a global scale, it is important to elucidate the therapeutic abilities of this cryopreserved reservoir. In the advancing field of natural killer (NK) cell cancer immunotherapy, CB has proven to be a promising and noninvasive source of therapeutic NK cells. Although studies have proven the clinical efficacy of using long-term cryopreserved CB in the context of hematopoietic stem cell transplantations, little is known about its use for the ex vivo expansion of effector immune cells. Therefore, our group sought to derive ex vivo-expanded NK cells from long-term cryopreserved CB, using an artificial antigen presenting cell-mediated expansion technique. We compared the expansion potential and antitumor effector function of CB-derived NK (CB-NK) cells expanded from fresh (n=4), short-term cryopreserved (<1-year old, n=5), and long-term cryopreserved (1-10-year old, n=5) CB. Here, we demonstrated it is possible to obtain an exponential amount of expanded CB-NK cells from long-term cryopreserved CB. Ex vivo-expanded CB-NK cells had an increased surface expression of activating markers and showed potent antitumor function by producing robust levels of proinflammatory cytokines, interferon-γ, and tumor necrosis factor-α. Moreover, expanded CB-NK cells (n=3-5) demonstrated cytotoxicity towards primary breast cancer cells (n=2) derived from a triple-negative breast cancer and an estrogen receptor-positive/progesterone receptor-positive breast cancer patient. Long-term cryopreservation had no effect on the expansion potential or effector function of expanded CB-NK cells. Therefore, we propose that long-term cryopreserved CB remains clinically useful for the ex vivo expansion of therapeutic NK cells.
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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 | 0.001 |
| 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".