Abstract 896: Unleashing the power within: enhancing cancer treatment with invariant natural killer T cells
Bibliographic record
Abstract
Invariant natural killer T (iNKT) cells are a promising target for adoptive cell therapy (ACT) due to their unique ability to recognize glycolipid antigens presented by the non-polymorphic MHC class I-like CD1d molecule, enabling heterologous application without the risk of alloreactivity. Activated, iNKT cells exhibit potent antitumor activity through cytokine secretion, chemokine release, and cytolysis, making them ideal candidates for off-the-shelf cancer therapies. However, limited knowledge of iNKT cell biology, particularly their functional heterogeneity, has hindered their therapeutic optimization. This study aimed to (a) investigate the functional heterogeneity of iNKT cells, (b) expand iNKT cells from human peripheral blood mononuclear cells (PBMCs), and (c) optimize the generation of cytotoxic iNKT cells by evaluating their phenotypic and functional profiles in response to various cytokine stimulations. PBMCs from 14 healthy donors (7 males and 7 females) were analyzed using spectral flow cytometry to assess the expression of key iNKT cytotoxic markers, along with markers associated with natural killer cells and CD8+ T cells. Phenograph clustering revealed distinct iNKT subpopulations, including one characterized by high expression of cytotoxic markers such as CD57, granzyme B, and granulysin, and another enriched for CD62L, a marker linked to central memory-like phenotypes with the potential to differentiate into cytotoxic subsets with enhanced antitumor activity. To optimize iNKT cell expansion, PBMCs were co-cultured with artificial antigen-presenting cells loaded with the iNKT ligand α-galactosylceramide in the presence of IL-2. iNKT cells were sorted two weeks post-initial stimulation and restimulated every 2-3 weeks using anti-CD3, resulting in the generation of millions of cells. To further enhance cytotoxic potential, iNKT cells were treated with cytokines such as IL-7, IL-15, IL-12, and IL-21. Preliminary findings demonstrated that cytokine stimulation influences the phenotypic profiles of iNKT cells. These findings provide a robust foundation for generating large quantities of cytotoxic iNKT subsets optimized for in vitro and in vivo assays. This work not only enhances the understanding of iNKT cell biology but also represents a significant step toward leveraging iNKT cells as versatile and powerful tools in ACTs. Citation Format: Daniah Alkassab, Carolina de Amat Herbozo, Thierry Mallevaey. Unleashing the power within: enhancing cancer treatment with invariant natural killer T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 896.
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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) | 0.004 | 0.001 |
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".